what is research ethics essay

Introduction: What is Research Ethics?

Research Ethics is defined here to be the ethics of the planning, conduct, and reporting of research. This introduction covers what research ethics is, its ethical distinctions, approaches to teaching research ethics, and other resources on this topic.

What is Research Ethics

Why Teach Research Ethics

Animal Subjects

Biosecurity

Collaboration

Conflicts of Interest

Data Management

Human Subjects

Peer Review

Publication

Research Misconduct

Social Responsibility

Stem Cell Research

Whistleblowing

Descriptions of educational settings , including in the classroom, and in research contexts.

Case Studies

Other Discussion Tools

Information about the history and authors of the Resources for Research Ethics Collection

What is Research Ethics?

Research Ethics is defined here to be the ethics of the planning, conduct, and reporting of research. It is clear that research ethics should include:

Protections of human and animal subjects

However, not all researchers use human or animal subjects, nor are the ethical dimensions of research confined solely to protections for research subjects. Other ethical challenges are rooted in many dimensions of research, including the:

Collection, use, and interpretation of research data
Methods for reporting and reviewing research plans or findings
Relationships among researchers with one another
Relationships between researchers and those that will be affected by their research
Means for responding to misunderstandings, disputes, or misconduct
Options for promoting ethical conduct in research

The domain of research ethics is intended to include nothing less than the fostering of research that protects the interests of the public, the subjects of research, and the researchers themselves.

Ethical Distinctions

In discussing or teaching research ethics, it is important to keep some basic distinctions in mind.

It is important not to confuse moral claims about how people ought to behave with descriptive claims about how they in fact do behave. From the fact that gift authorship or signing off on un-reviewed data may be "common practice" in some contexts, it doesn't follow that they are morally or professionally justified. Nor is morality to be confused with the moral beliefs or ethical codes that a given group or society holds (how some group thinks people should live). A belief in segregation is not morally justified simply because it is widely held by a group of people or given society. Philosophers term this distinction between prescriptive and descriptive claims the 'is-ought distinction.'
A second important distinction is that between morality and the law. The law may or may not conform to the demands of ethics (Kagan, 1998). To take a contemporary example: many believe that the law prohibiting federally funded stem cell research is objectionable on moral (as well as scientific) grounds, i.e., that such research can save lives and prevent much human misery. History is full of examples of bad laws, that is laws now regarded as morally unjustifiable, e.g., the laws of apartheid, laws prohibiting women from voting or inter-racial couples from marrying.
It is also helpful to distinguish between two different levels of discussion (or two different kinds of ethical questions): first-order or "ground-level" questions and second-order questions.
First-order moral questions concern what we should do. Such questions may be very general or quite specific. One might ask whether the tradition of 'senior' authorship should be defended and preserved or, more generally, what are the principles that should go into deciding the issue of 'senior' authorship. Such questions and the substantive proposals regarding how to answer them belong to the domain of what moral philosophers call 'normative ethics.'
Second-order moral questions concern the nature and purpose of morality itself. When someone claims that falsifying data is wrong, what exactly is the standing of this claim? What exactly does the word 'wrong' mean in the conduct of scientific research? And what are we doing when we make claims about right and wrong, scientific integrity and research misconduct? These second-order questions are quite different from the ground-level questions about how to conduct one's private or professional life raised above. They concern the nature of morality rather than its content, i.e., what acts are required, permitted or prohibited. This is the domain of what moral philosophers call 'metaethics' (Kagan, 1998).

Ethical Approaches

Each of these approaches provides moral principles and ways of thinking about the responsibilities, duties and obligations of moral life. Individually and jointly, they can provide practical guidance in ethical decision-making.

One of the most influential and familiar approaches to ethics is deontological ethics, associated with Immanuel Kant (1742-1804). Deontological ethics hold certain acts as right or wrong in themselves, e.g., promise breaking or lying. So, for example, in the context of research, fraud, plagiarism and misrepresentation are regarded as morally wrong in themselves, not simply because they (tend to) have bad consequences. The deontological approach is generally grounded in a single fundamental principle: Act as you would wish others to act towards you OR always treat persons as an end, never as a means to an end.
From such central principles are derived rules or guidelines for what is permitted, required and prohibited. Objections to principle-based or deontological ethics include the difficulty of applying highly general principles to specific cases, e.g.: Does treating persons as ends rule out physician-assisted suicide, or require it? Deontological ethics is generally contrasted to consequentialist ethics (Honderich, 1995).
According to consequentialist approaches, the rightness or wrongness of an action depends solely on its consequences. One should act in such a way as to bring about the best state of affairs, where the best state of affairs may be understood in various ways, e.g., as the greatest happiness for the greatest number of people, maximizing pleasure and minimizing pain or maximizing the satisfaction of preferences. A theory such as Utilitarianism (with its roots in the work of Jeremy Bentham and John Stuart Mill) is generally taken as the paradigm example of consequentialism. Objections to consequentialist ethics tend to focus on its willingness to regard individual rights and values as "negotiable." So, for example, most people would regard murder as wrong independently of the fact that killing one person might allow several others to be saved (the infamous sacrifice of an ailing patient to provide organs for several other needy patients). Similarly, widespread moral opinion holds certain values important (integrity, justice) not only because they generally lead to good outcomes, but in and of themselves.
Virtue ethics focuses on moral character rather than action and behavior considered in isolation. Central to this approach is the question what ought we (as individuals, as scientists, as physicians) to be rather than simply what we ought to do. The emphasis here is on inner states, that is, moral dispositions and habits such as courage or a developed sense of personal integrity. Virtue ethics can be a useful approach in the context of RCR and professional ethics, emphasizing the importance of moral virtues such as compassion, honesty, and respect. This approach has also a great deal to offer in discussions of bioethical issues where a traditional emphasis on rights and abstract principles frequently results in polarized, stalled discussions (e.g., abortion debates contrasting the rights of the mother against the rights of the fetus).
The term 'an ethics of care' grows out of the work of Carol Gilligan, whose empirical work in moral psychology claimed to discover a "different voice," a mode of moral thinking distinct from principle-based moral thinking (e.g., the theories of Kant and Mill). An ethics of care stresses compassion and empathetic understanding, virtues Gilligan associated with traditional care-giving roles, especially those of women.
This approach differs from traditional moral theories in two important ways. First, it assumes that it is the connections between persons, e.g., lab teams, colleagues, parents and children, student and mentor, not merely the rights and obligations of discrete individuals that matter. The moral world, on this view, is best seen not as the interaction of discrete individuals, each with his or her own interests and rights, but as an interrelated web of obligations and commitment. We interact, much of the time, not as private individuals, but as members of families, couples, institutions, research groups, a given profession and so on. Second, these human relationships, including relationships of dependency, play a crucial role on this account in determining what our moral obligations and responsibilities are. So, for example, individuals have special responsibilities to care for their children, students, patients, and research subjects.
An ethics of care is thus particularly useful in discussing human and animal subjects research, issues of informed consent, and the treatment of vulnerable populations such as children, the infirm or the ill.
The case study approach begins from real or hypothetical cases. Its objective is to identify the intuitively plausible principles that should be taken into account in resolving the issues at hand. The case study approach then proceeds to critically evaluate those principles. In discussing whistle-blowing, for example, a good starting point is with recent cases of research misconduct, seeking to identify and evaluate principles such as a commitment to the integrity of science, protecting privacy, or avoiding false or unsubstantiated charges. In the context of RCR instruction, case studies provide one of the most interesting and effective approaches to developing sensitivity to ethical issues and to honing ethical decision-making skills.
Strictly speaking, casuistry is more properly understood as a method for doing ethics rather than as itself an ethical theory. However, casuistry is not wholly unconnected to ethical theory. The need for a basis upon which to evaluate competing principles, e.g., the importance of the well-being of an individual patient vs. a concern for just allocation of scarce medical resources, makes ethical theory relevant even with case study approaches.
Applied ethics is a branch of normative ethics. It deals with practical questions particularly in relation to the professions. Perhaps the best known area of applied ethics is bioethics, which deals with ethical questions arising in medicine and the biological sciences, e.g., questions concerning the application of new areas of technology (stem cells, cloning, genetic screening, nanotechnology, etc.), end of life issues, organ transplants, and just distribution of healthcare. Training in responsible conduct of research or "research ethics" is merely one among various forms of professional ethics that have come to prominence since the 1960s. Worth noting, however, is that concern with professional ethics is not new, as ancient codes such as the Hippocratic Oath and guild standards attest (Singer, 1986).
Adams D, Pimple KD (2005): Research Misconduct and Crime: Lessons from Criminal Science on Preventing Misconduct and Promoting Integrity. Accountability in Research 12(3):225-240.
Anderson MS, Horn AS, Risbey KR, Ronning EA, De Vries R, Martinson BC (2007): What Do Mentoring and Training in the Responsible Conduct of Research Have To Do with Scientists' Misbehavior? Findings from a National Survey of NIH-Funded Scientists . Academic Medicine 82(9):853-860.
Bulger RE, Heitman E (2007): Expanding Responsible Conduct of Research Instruction across the University. Academic Medicine. 82(9):876-878.
Kalichman MW (2006): Ethics and Science: A 0.1% solution. Issues in Science and Technology 23:34-36.
Kalichman MW (2007): Responding to Challenges in Educating for the Responsible Conduct of Research, Academic Medicine. 82(9):870-875.
Kalichman MW, Plemmons DK (2007): Reported Goals for Responsible Conduct of Research Courses. Academic Medicine. 82(9):846-852.
Kalichman MW (2009): Evidence-based research ethics. The American Journal of Bioethics 9(6&7): 85-87.
Pimple KD (2002): Six Domains of Research Ethics: A Heuristic Framework for the Responsible Conduct of Research. Science and Engineering Ethics 8(2):191-205.
Steneck NH (2006): Fostering Integrity in Research: Definitions, Current Knowledge, and Future Directions. Science and Engineering Ethics 12:53-74.
Steneck NH, Bulger RE (2007): The History, Purpose, and Future of Instruction in the Responsible Conduct of Research. Academic Medicine. 82(9):829-834.
Vasgird DR (2007): Prevention over Cure: The Administrative Rationale for Education in the Responsible Conduct of Research. Academic Medicine. 82(9):835-837.
Aristotle. The Nichomachean Ethics.
Beauchamp RL, Childress JF (2001): Principles of Biomedical Ethics, 5th edition, NY: Oxford University Press.
Bentham, J (1781): An Introduction to the Principles of Morals and Legislation.
Gilligan C (1993): In a Different Voice: Psychological Theory and Women's Development. Cambridge: Harvard University Press.
Glover, Jonathan (1977): Penguin Books.
Honderich T, ed. (1995): The Oxford Companion to Philosophy, Oxford and New York: Oxford University Press.
Kagan S (1998): Normative Ethics. Westview Press.
Kant I (1785): Groundwork of the Metaphysics of Morals.
Kant I (1788): Critique of Practical Reason.
Kant I (1797): The Metaphysics of Morals.
Kant I (1797): On a Supposed right to Lie from Benevolent Motives.
Kuhse H, Singer P (1999): Bioethics: An Anthology. Blackwell Publishers.
Mill JS (1861): Utilitarianism.
Rachels J (1999): The Elements of Moral Philosophy, 3rd edition, Boston: McGraw-Hill.
Regan T (1993): Matters of Life and Death: New Introductory Essays in Moral Philosophy, 3rd edition. New York: McGraw-Hill. The history of ethics.
Singer P (1993): Practical Ethics, 2nd ed. Cambridge University Press.

The Resources for Research Ethics Education site was originally developed and maintained by Dr. Michael Kalichman, Director of the Research Ethics Program at the University of California San Diego. The site was transferred to the Online Ethics Center in 2021 with the permission of the author.

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This material is based upon work supported by the National Science Foundation under Award No. 2055332. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Original article
Open access
Published: 13 July 2021

Assisting you to advance with ethics in research: an introduction to ethical governance and application procedures

Shivadas Sivasubramaniam 1 ,
Dita Henek Dlabolová 2 ,
Veronika Kralikova 3 &
Zeenath Reza Khan 3

International Journal for Educational Integrity volume 17 , Article number: 14 ( 2021 ) Cite this article

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Ethics and ethical behaviour are the fundamental pillars of a civilised society. The focus on ethical behaviour is indispensable in certain fields such as medicine, finance, or law. In fact, ethics gets precedence with anything that would include, affect, transform, or influence upon individuals, communities or any living creatures. Many institutions within Europe have set up their own committees to focus on or approve activities that have ethical impact. In contrast, lesser-developed countries (worldwide) are trying to set up these committees to govern their academia and research. As the first European consortium established to assist academic integrity, European Network for Academic Integrity (ENAI), we felt the importance of guiding those institutions and communities that are trying to conduct research with ethical principles. We have established an ethical advisory working group within ENAI with the aim to promote ethics within curriculum, research and institutional policies. We are constantly researching available data on this subject and committed to help the academia to convey and conduct ethical behaviour. Upon preliminary review and discussion, the group found a disparity in understanding, practice and teaching approaches to ethical applications of research projects among peers. Therefore, this short paper preliminarily aims to critically review the available information on ethics, the history behind establishing ethical principles and its international guidelines to govern research.

The paper is based on the workshop conducted in the 5th International conference Plagiarism across Europe and Beyond, in Mykolas Romeris University, Lithuania in 2019. During the workshop, we have detailed a) basic needs of an ethical committee within an institution; b) a typical ethical approval process (with examples from three different universities); and c) the ways to obtain informed consent with some examples. These are summarised in this paper with some example comparisons of ethical approval processes from different universities. We believe this paper will provide guidelines on preparing and training both researchers and research students in appropriately upholding ethical practices through ethical approval processes.

Introduction

Ethics and ethical behaviour (often linked to “responsible practice”) are the fundamental pillars of a civilised society. Ethical behaviour with integrity is important to maintain academic and research activities. It affects everything we do, and gets precedence with anything that would include/affect, transform, or impact upon individuals, communities or any living creatures. In other words, ethics would help us improve our living standards (LaFollette, 2007 ). The focus on ethical behaviour is indispensable in certain fields such as medicine, finance, or law, but is also gaining recognition in all disciplines engaged in research. Therefore, institutions are expected to develop ethical guidelines in research to maintain quality, initiate/own integrity and above all be transparent to be successful by limiting any allegation of misconduct (Flite and Harman, 2013 ). This is especially true for higher education organisations that promote research and scholarly activities. Many European institutions have developed their own regulations for ethics by incorporating international codes (Getz, 1990 ). The lesser developed countries are trying to set up these committees to govern their academia and research. World Health Organization has stated that adhering to “ ethical principles … [is central and important]... in order to protect the dignity, rights and welfare of research participants ” (WHO, 2021 ). Ethical guidelines taught to students can help develop ethical researchers and members of society who uphold values of ethical principles in practice.

As the first European-wide consortium established to assist academic integrity (European Network for Academic Integrity – ENAI), we felt the importance of guiding those institutions and communities that are trying to teach, research, and include ethical principles by providing overarching understanding of ethical guidelines that may influence policy. Therefore, we set up an advisory working group within ENAI in 2018 to support matters related to ethics, ethical committees and assisting on ethics related teaching activities.

Upon preliminary review and discussion, the group found a disparity in understanding, practice and teaching approaches to ethical applications among peers. This became the premise for this research paper. We first carried out a literature survey to review and summarise existing ethical governance (with historical perspectives) and procedures that are already in place to guide researchers in different discipline areas. By doing so, we attempted to consolidate, document and provide important steps in a typical ethical application process with example procedures from different universities. Finally, we attempted to provide insights and findings from practical workshops carried out at the 5th International Conference Plagiarism across Europe and Beyond, in Mykolas Romeris University, Lithuania in 2019, focussing on:

• highlighting the basic needs of an ethical committee within an institution,

• discussing and sharing examples of a typical ethical approval process,

• providing guidelines on the ways to teach research ethics with some examples.

We believe this paper provides guidelines on preparing and training both researchers and research students in appropriately upholding ethical practices through ethical approval processes.

Background literature survey

Responsible research practice (RRP) is scrutinised by the aspects of ethical principles and professional standards (WHO’s Code of Conduct for responsible Research, 2017). The Singapore statement on research integrity (The Singapore Statement on Research integrity, 2010) has provided an internationally acceptable guidance for RRP. The statement is based on maintaining honesty, accountability, professional courtesy in all aspects of research and maintaining fairness during collaborations. In other words, it does not simply focus on the procedural part of the research, instead covers wider aspects of “integrity” beyond the operational aspects (Israel and Drenth, 2016 ).

Institutions should focus on providing ethical guidance based on principles and values reflecting upon all aspects/stages of research (from the funding application/project development stage upto or beyond project closing stage). Figure 1 summarizes the different aspects/stages of a typical research and highlights the needs of RRP in compliance with ethical governance at each stage with examples (the figure is based on Resnik, 2020 ; Žukauskas et al., 2018 ; Anderson, 2011 ; Fouka and Mantzorou, 2011 ).

Summary of the enabling ethical governance at different stages of research. Note that it is imperative for researchers to proactively consider the ethical implications before, during and after the actual research process. The summary shows that RRP should be in line with ethical considerations even long before the ethical approval stage

Individual responsibilities to enhance RRP

As explained in Fig. 1 , a successfully governed research should consider ethics at the planning stages prior to research. Many international guidance are compatible in enforcing/recommending 14 different “responsibilities” that were first highlighted in the Singapore Statement (2010) for researchers to follow and achieve competency in RRP. In order to understand the purpose and the expectation of these ethical guidelines, we have carried out an initial literature survey on expected individual responsibilities. These are summarised in Table 1 .

By following these directives, researchers can carry out accountable research by maximising ethical self-governance whilst minimising misconducts. In our own experiences of working with many researchers, their focus usually revolves around ethical “clearance” rather than behaviour. In other words, they perceive this as a paper exercise rather than trying to “own” ethical behaviour in everything they do. Although the ethical principles and responsibilities are explicitly highlighted in the majority of international guidelines [such as UK’s Research Governance Policy (NICE, 2018 ), Australian Government’s National Statement on Ethical Conduct in Human Research (Difn website a - National Statement on Ethical Conduct in Human Research (NSECHR), 2018 ), the Singapore Statement (2010) etc.]; and the importance of holistic approach has been argued in ethical decision making, many researchers and/or institutions only focus on ethics linked to the procedural aspects.

Studies in the past have also highlighted inconsistencies in institutional guidelines pointing to the fact that these inconsistencies may hinder the predicted research progress (Desmond & Dierickx 2021 ; Alba et al., 2020 ; Dellaportas et al., 2014 ; Speight 2016 ). It may also be possible that these were and still are linked to the institutional perceptions/expectations or the pre-empting contextual conditions that are imposed by individual countries. In fact, it is interesting to note many research organisations and HE institutions establish their own policies based on these directives.

Research governance - origins, expectations and practices

Ethical governance in clinical medicine helps us by providing a structure for analysis and decision-making. By providing workable definitions of benefits and risks as well as the guidance for evaluating/balancing benefits over risks, it supports the researchers to protect the participants and the general population.

According to the definition given by National Institute of Clinical care Excellence, UK (NICE 2018 ), “ research governance can be defined as the broad range of regulations, principles and standards of good practice that ensure high quality research ”. As stated above, our literature-based research survey showed that most of the ethical definitions are basically evolved from the medical field and other disciplines have utilised these principles to develop their own ethical guidance. Interestingly, historical data show that the medical research has been “self-governed” or in other words implicated by the moral behaviour of individual researchers (Fox 2017 ; Shaw et al., 2005 ; Getz, 1990 ). For example, early human vaccination trials conducted in 1700s used the immediate family members as test subjects (Fox, 2017 ). Here the moral justification might have been the fact that the subjects who would have been at risk were either the scientists themselves or their immediate families but those who would reap the benefits from the vaccination were the general public/wider communities. However, according to the current ethical principles, this assumption is entirely not acceptable.

Historically, ambiguous decision-making and resultant incidences of research misconduct have led to the need for ethical research governance in as early as the 1940’s. For instance, the importance of an international governance was realised only after the World War II, when people were astonished to note the unethical research practices carried out by Nazi scientists. As a result of this, in 1947 the Nuremberg code was published. The code mainly focussed on the following:

Informed consent and further insisted the research involving humans should be based on prior animal work,

The anticipated benefits should outweigh the risk,

Research should be carried out only by qualified scientists must conduct research,

Avoiding physical and mental suffering and.

Avoiding human research that would result in which death or disability.

(Weindling, 2001 ).

Unfortunately, it was reported that many researchers in the USA and elsewhere considered the Nuremberg code as a document condemning the Nazi atrocities, rather than a code for ethical governance and therefore ignored these directives (Ghooi, 2011 ). It was only in 1964 that the World Medical Association published the Helsinki Declaration, which set the stage for ethical governance and the implementation of the Institutional Review Board (IRB) process (Shamoo and Irving, 1993 ). This declaration was based on Nuremberg code. In addition, the declaration also paved the way for enforcing research being conducted in accordance with these guidelines.

Incidentally, the focus on research/ethical governance gained its momentum in 1974. As a result of this, a report on ethical principles and guidelines for the protection of human subjects of research was published in 1979 (The Belmont Report, 1979 ). This report paved the way to the current forms of ethical governance in biomedical and behavioural research by providing guidance.

Since 1994, the WHO itself has been providing several guidance to health care policy-makers, researchers and other stakeholders detailing the key concepts in medical ethics. These are specific to applying ethical principles in global public health.

Likewise, World Organization for Animal Health (WOAH), and International Convention for the Protection of Animals (ICPA) provide guidance on animal welfare in research. Due to this continuous guidance, together with accepted practices, there are internationally established ethical guidelines to carry out medical research. Our literature survey further identified freely available guidance from independent organisations such as COPE (Committee of Publication Ethics) and ALLEA (All European Academics) which provide support for maintaining research ethics in other fields such as education, sociology, psychology etc. In reality, ethical governance is practiced differently in different countries. In the UK, there is a clinical excellence research governance, which oversees all NHS related medical research (Mulholland and Bell, 2005 ). Although, the governance in other disciplines is not entirely centralised, many research funding councils and organisations [such as UKRI (UK-Research and Innovation; BBSC (Biotechnology and Biological Sciences Research Council; MRC (Medical Research Council); EPSRC (Economic and Social Research Council)] provide ethical governance and expect institutional adherence and monitoring. They expect local institutional (i.e. university/institutional) research governance for day-to-day monitoring of the research conducted within the organisation and report back to these funding bodies, monthly or annually (Department of Health, 2005). Likewise, there are nationally coordinated/regulated ethics governing bodies such as the US Office for Human Research Protections (US-OHRP), National Institute of Health (NIH) and the Canadian Institutes for Health Research (CIHR) in the USA and Canada respectively (Mulholland and Bell, 2005 ). The OHRP in the USA formally reviews all research activities involving human subjects. On the other hand, in Canada, CIHR works with the Natural Sciences and Engineering Research Council (NSERC), and the Social Sciences and Humanities Research Council (SSHRC). They together have produced a Tri-Council Policy Statement (TCPS) (Stephenson et al., 2020 ) as ethical governance. All Canadian institutions are expected to adhere to this policy for conducting research. As for Australia, the research is governed by the Australian code for the responsible conduct of research (2008). It identifies the responsibilities of institutions and researchers in all areas of research. The code has been jointly developed by the National Health and Medical Research Council (NHMRC), the Australian Research Council (ARC) and Universities Australia (UA). This information is summarized in Table 2 .

Basic structure of an institutional ethical advisory committee (EAC)

The WHO published an article defining the basic concepts of an ethical advisory committee in 2009 (WHO, 2009 - see above). According to this, many countries have established research governance and monitor the ethical practice in research via national and/or regional review committees. The main aims of research ethics committees include reviewing the study proposals, trying to understand the justifications for human/animal use, weighing the merits and demerits of the usage (linking to risks vs. potential benefits) and ensuring the local, ethical guidelines are followed Difn website b - Enago academy Importance of Ethics Committees in Scholarly Research, 2020 ; Guide for Research Ethics - Council of Europe, 2014 ). Once the research has started, the committee needs to carry out periodic surveillance to ensure the institutional ethical norms are followed during and beyond the study. They may also be involved in setting up and/or reviewing the institutional policies.

For these aspects, IRB (or institutional ethical advisory committee - IEAC) is essential for local governance to enhance best practices. The advantage of an IRB/EEAC is that they understand the institutional conditions and can closely monitor the ongoing research, including any changes in research directions. On the other hand, the IRB may be overly supportive to accept applications, influenced by the local agenda for achieving research excellence, disregarding ethical issues (Kotecha et al., 2011 ; Kayser-Jones, 2003 ) or, they may be influenced by the financial interests in attracting external funding. In this respect, regional and national ethics committees are advantageous to ensure ethical practice. Due to their impartiality, they would provide greater consistency and legitimacy to the research (WHO, 2009 ). However, the ethical approval process of regional and national ethics committees would be time consuming, as they do not have the local knowledge.

As for membership in the IRBs, most of the guidelines [WHO, NICE, Council of Europe, (2012), European Commission - Facilitating Research Excellence in FP7 ( 2013 ) and OHRP] insist on having a variety of representations including experts in different fields of research, and non-experts with the understanding of local, national/international conflicts of interest. The former would be able to understand/clarify the procedural elements of the research in different fields; whilst the latter would help to make neutral and impartial decisions. These non-experts are usually not affiliated to the institution and consist of individuals representing the broader community (particularly those related to social, legal or cultural considerations). IRBs consisting of these varieties of representation would not only be in a position to understand the study procedures and their potential direct or indirect consequences for participants, but also be able to identify any community, cultural or religious implications of the study.

Understanding the subtle differences between ethics and morals

Interestingly, many ethical guidelines are based on society’s moral “beliefs” in such a way that the words “ethics”‘and “morals” are reciprocally used to define each other. However, there are several subtle differences between them and we have attempted to compare and contrast them herein. In the past, many authors have interchangeably used the words “morals”‘and “ethics”‘(Warwick, 2003 ; Kant, 2018 ; Hazard, GC (Jr)., 1994 , Larry, 1982 ). However, ethics is linked to rules governed by an external source such as codes of conduct in workplaces (Kuyare et al., 2014 ). In contrast, morals refer to an individual’s own principles regarding right and wrong. Quinn ( 2011 ) defines morality as “ rules of conduct describing what people ought and ought not to do in various situations … ” while ethics is “... the philosophical study of morality, a rational examination into people’s moral beliefs and behaviours ”. For instance, in a case of parents demanding that schools overturn a ban on use of corporal punishment of children by schools and teachers (Children’s Rights Alliance for England, 2005 ), the parents believed that teachers should assume the role of parent in schools and use corporal or physical punishment for children who misbehaved. This stemmed from their beliefs and what they felt were motivated by “beliefs of individuals or groups”. For example, recent media highlights about some parents opposing LGBT (Lesbian, Gay, Bisexual, and Transgender) education to their children (BBC News, 2019 ). One parent argued, “Teaching young children about LGBT at a very early stage is ‘morally’ wrong”. She argued “let them learn by themselves as they grow”. This behaviour is linked to and governed by the morals of an ethnic community. Thus, morals are linked to the “beliefs of individuals or group”. However, when it comes to the LGBT rights these are based on ethical principles of that society and governed by law of the land. However, the rights of children to be protected from “inhuman and degrading” treatment is based on the ethical principles of the society and governed by law of the land. Individuals, especially those who are working in medical or judicial professions have to follow an ethical code laid down by their profession, regardless of their own feelings, time or preferences. For instance, a lawyer is expected to follow the professional ethics and represent a defendant, despite the fact that his morals indicate the defendant is guilty.

In fact, we as a group could not find many scholarly articles clearly comparing or contrasting ethics with morals. However, a table presented by Surbhi ( 2015 ) (Difn website c ) tries to differentiate these two terms (see Table 3 ).

Although Table 3 gives some insight on the differences between these two terms, in practice many use these terms as loosely as possible mainly because of their ambiguity. As a group focussed on the application of these principles, we would recommend to use the term “ethics” and avoid “morals” in research and academia.

Based on the literature survey carried out, we were able to identify the following gaps:

there is some disparity in existing literature on the importance of ethical guidelines in research

there is a lack of consensus on what code of conduct should be followed, where it should be derived from and how it should be implemented

The mission of ENAI’s ethical advisory working group

The Ethical Advisory Working Group of ENAI was established in 2018 to promote ethical code of conduct/practice amongst higher educational organisations within Europe and beyond (European Network for Academic Integrity, 2018 ). We aim to provide unbiased advice and consultancy on embedding ethical principles within all types of academic, research and public engagement activities. Our main objective is to promote ethical principles and share good practice in this field. This advisory group aims to standardise ethical norms and to offer strategic support to activities including (but not exclusive to):

● rendering advice and assistance to develop institutional ethical committees and their regulations in member institutions,

● sharing good practice in research and academic ethics,

● acting as a critical guide to institutional review processes, assisting them to maintain/achieve ethical standards,

● collaborating with similar bodies in establishing collegiate partnerships to enhance awareness and practice in this field,

● providing support within and outside ENAI to develop materials to enhance teaching activities in this field,

● organising training for students and early-career researchers about ethical behaviours in form of lectures, seminars, debates and webinars,

● enhancing research and dissemination of the findings in matters and topics related to ethics.

The following sections focus on our suggestions based on collective experiences, review of literature provided in earlier sections and workshop feedback collected:

a) basic needs of an ethical committee within an institution;

b) a typical ethical approval process (with examples from three different universities); and

c) the ways to obtain informed consent with some examples. This would give advice on preparing and training both researchers and research students in appropriately upholding ethical practices through ethical approval processes.

Setting up an institutional ethical committee (ECs)

Institutional Ethical Committees (ECs) are essential to govern every aspect of the activities undertaken by that institute. With regards to higher educational organisations, this is vital to establish ethical behaviour for students and staff to impart research, education and scholarly activities (or everything) they do. These committees should be knowledgeable about international laws relating to different fields of studies (such as science, medicine, business, finance, law, and social sciences). The advantages and disadvantages of institutional, subject specific or common (statutory) ECs are summarised in Fig. 2 . Some institutions have developed individual ECs linked to specific fields (or subject areas) whilst others have one institutional committee that overlooks the entire ethical behaviour and approval process. There is no clear preference between the two as both have their own advantages and disadvantages (see Fig. 2 ). Subject specific ECs are attractive to medical, law and business provisions, as it is perceived the members within respective committees would be able to understand the subject and therefore comprehend the need of the proposed research/activity (Kadam, 2012 ; Schnyder et al., 2018 ). However, others argue, due to this “ specificity ”, the committee would fail to forecast the wider implications of that application. On the other hand, university-wide ECs would look into the wider implications. Yet they find it difficult to understand the purpose and the specific applications of that research. Not everyone understands dynamics of all types of research methodologies, data collection, etc., and therefore there might be a chance of a proposal being rejected merely because the EC could not understand the research applications (Getz, 1990 ).

Summary of advantages and disadvantages of three different forms of ethical committees

[N/B for Fig. 2 : Examples of different types of ethical application procedures and forms used were discussed with the workshop attendees to enhance their understanding of the differences. GDPR = General Data Protection Regulation].

Although we recommend a designated EC with relevant professional, academic and ethical expertise to deal with particular types of applications, the membership (of any EC) should include some non-experts who would represent the wider community (see above). Having some non-experts in EC would not only help the researchers to consider explaining their research in layperson’s terms (by thinking outside the box) but also would ensure efficiency without compromising participants/animal safety. They may even help to address the common ethical issues outside research culture. Some UK universities usually offer this membership to a clergy, councillor or a parliamentarian who does not have any links to the institutions. Most importantly, it is vital for any EC members to undertake further training in addition to previous experience in the relevant field of research ethics.

Another issue that raises concerns is multi-centre research, involving several institutions, where institutionalised ethical approvals are needed from each partner. In some cases, such as clinical research within the UK, a common statutory EC called National Health Services (NHS) Research Ethics Committee (NREC) is in place to cover research ethics involving all partner institutions (NHS, 2018 ). The process of obtaining approval from this type of EC takes time, therefore advanced planning is needed.

Ethics approval forms and process

During the workshop, we discussed some anonymised application forms obtained from open-access sources for qualitative and quantitative research as examples. Considering research ethics, for the purpose of understanding, we arbitrarily divided this in two categories; research based on (a) quantitative and (b) qualitative methodologies. As their name suggests their research approach is extremely different from each other. The discussion elicited how ECs devise different types of ethical application form/questions. As for qualitative research, these are often conducted as “face-to-face” interviews, which would have implications on volunteer anonymity.

Furthermore, discussions posited when the interviews are replaced by on-line surveys, they have to be administered through registered university staff to maintain confidentiality. This becomes difficult when the research is a multi-centre study. These types of issues are also common in medical research regarding participants’ anonymity, confidentially, and above all their right to withdraw consent to be involved in research.

Storing and protecting data collected in the process of the study is also a point of consideration when applying for approval.

Finally, the ethical processes of invasive (involving human/animals) and non-invasive research (questionnaire based) may slightly differ from one another. Following research areas are considered as investigations that need ethical approval:

research that involves human participants (see below)

use of the ‘products’ of human participants (see below)

work that potentially impacts on humans (see below)

research that involves animals

In addition, it is important to provide a disclaimer even if an ethical approval is deemed unnecessary. Following word cloud (Fig. 3 ) shows the important variables that need to be considered at the brainstorming stage before an ethical application. It is worth noting the importance of proactive planning predicting the “unexpected” during different phases of a research project (such as planning, execution, publication, and future directions). Some applications (such as working with vulnerable individuals or children) will require safety protection clearance (such as DBS - Disclosure and Barring Service, commonly obtained from the local police). Please see section on Research involving Humans - Informed consents for further discussions.

Examples of important variables that need to be considered for an ethical approval

It is also imperative to report or re-apply for ethical approval for any minor or major post-approval changes to original proposals made. In case of methodological changes, evidence of risk assessments for changes and/or COSHH (Control of Substances Hazardous to Health Regulations) should also be given. Likewise, any new collaborative partners or removal of researchers should also be notified to the IEAC.

Other findings include:

in case of complete changes in the project, the research must be stopped and new approval should be seeked,

in case of noticing any adverse effects to project participants (human or non-human), these should also be notified to the committee for appropriate clearance to continue the work, and

the completion of the project must also be notified with the indication whether the researchers may restart the project at a later stage.

Research involving humans - informed consents

While discussing research involving humans and based on literature review, findings highlight the human subjects/volunteers must willingly participate in research after being adequately informed about the project. Therefore, research involving humans and animals takes precedence in obtaining ethical clearance and its strict adherence, one of which is providing a participant information sheet/leaflet. This sheet should contain a full explanation about the research that is being carried out and be given out in lay-person’s terms in writing (Manti and Licari 2018 ; Hardicre 2014 ). Measures should also be in place to explain and clarify any doubts from the participants. In addition, there should be a clear statement on how the participants’ anonymity is protected. We provide below some example questions below to help the researchers to write this participant information sheet:

What is the purpose of the study?

Why have they been chosen?

What will happen if they take part?

What do they have to do?

What happens when the research stops?

What if something goes wrong?

What will happen to the results of the research study?

Will taking part be kept confidential?

How to handle “vulnerable” participants?

How to mitigate risks to participants?

Many institutional ethics committees expect the researchers to produce a FAQ (frequently asked questions) in addition to the information about research. Most importantly, the researchers also need to provide an informed consent form, which should be signed by each human participant. The five elements identified that are needed to be considered for an informed consent statement are summarized in Fig. 4 below (slightly modified from the Federal Policy for the Protection of Human Subjects ( 2018 ) - Diffn website c ).

Five basic elements to consider for an informed consent [figure adapted from Diffn website c ]

The informed consent form should always contain a clause for the participant to withdraw their consent at any time. Should this happen all the data from that participant should be eliminated from the study without affecting their anonymity.

Typical research ethics approval process

In this section, we provide an example flow chart explaining how researchers may choose the appropriate application and process, as highlighted in Fig. 5 . However, it is imperative to note here that these are examples only and some institutions may have one unified application with separate sections to demarcate qualitative and quantitative research criteria.

Typical ethical approval processes for quantitative and qualitative research. [N/B for Fig. 5 - This simplified flow chart shows that fundamental process for invasive and non-invasive EC application is same, the routes and the requirements for additional information are slightly different]

Once the ethical application is submitted, the EC should ensure a clear approval procedure with distinctly defined timeline. An example flow chart showing the procedure for an ethical approval was obtained from University of Leicester as open-access. This is presented in Fig. 6 . Further examples of the ethical approval process and governance were discussed in the workshop.

An example ethical approval procedures conducted within University of Leicester (Figure obtained from the University of Leicester research pages - Difn website d - open access)

Strategies for ethics educations for students

Student education on the importance of ethics and ethical behaviour in research and scholarly activities is extremely essential. Literature posits in the area of medical research that many universities are incorporating ethics in post-graduate degrees but when it comes to undergraduate degrees, there is less appetite to deliver modules or even lectures focussing on research ethics (Seymour et al., 2004 ; Willison and O’Regan, 2007 ). This may be due to the fact that undergraduate degree structure does not really focus on research (DePasse et al., 2016 ). However, as Orr ( 2018 ) suggested, institutions should focus more on educating all students about ethics/ethical behaviour and their importance in research, than enforcing punitive measures for unethical behaviour. Therefore, as an advisory committee, and based on our preliminary literature survey and workshop results, we strongly recommend incorporating ethical education within undergraduate curriculum. Looking at those institutions which focus on ethical education for both under-and postgraduate courses, their approaches are either (a) a lecture-based delivery, (b) case study based approach or (c) a combined delivery starting with a lecture on basic principles of ethics followed by generating a debate based discussion using interesting case studies. The combined method seems much more effective than the other two as per our findings as explained next.

As many academics who have been involved in teaching ethics and/or research ethics agree, the underlying principles of ethics is often perceived as a boring subject. Therefore, lecture-based delivery may not be suitable. On the other hand, a debate based approach, though attractive and instantly generates student interest, cannot be effective without students understanding the underlying basic principles. In addition, when selecting case studies, it would be advisable to choose cases addressing all different types of ethical dilemmas. As an advisory group within ENAI, we are in the process of collating supporting materials to help to develop institutional policies, creating advisory documents to help in obtaining ethical approvals, and teaching materials to enhance debate-based lesson plans that can be used by the member and other institutions.

Concluding remarks

In summary, our literature survey and workshop findings highlight that researchers should accept that ethics underpins everything we do, especially in research. Although ethical approval is tedious, it is an imperative process in which proactive thinking is essential to identify ethical issues that might affect the project. Our findings further lead us to state that the ethical approval process differs from institution to institution and we strongly recommend the researchers to follow the institutional guidelines and their underlying ethical principles. The ENAI workshop in Vilnius highlighted the importance of ethical governance by establishing ECs, discussed different types of ECs and procedures with some examples and highlighted the importance of student education to impart ethical culture within research communities, an area that needs further study as future scope.

Declarations

The manuscript was entirely written by the corresponding author with contributions from co-authors who have also taken part in the delivery of the workshop. Authors confirm that the data supporting the findings of this study are available within the article. We can also confirm that there are no potential competing interests with other organisations.

Availability of data and materials

Authors confirm that the data supporting the findings of this study are available within the article.

Abbreviations

ALL European academics

Australian research council

Biotechnology and biological sciences research council

Canadian institutes for health research

Committee of publication ethics

Ethical committee

European network of academic integrity

Economic and social research council

International convention for the protection of animals

institutional ethical advisory committee

Institutional review board

Immaculata university of Pennsylvania

Lesbian, gay, bisexual, and transgender

Medical research council)

National health services

National health services nih national institute of health (NIH)

National institute of clinical care excellence

National health and medical research council

Natural sciences and engineering research council

National research ethics committee

National statement on ethical conduct in human research

Responsible research practice

Social sciences and humanities research council

Tri-council policy statement

World Organization for animal health

Universities Australia

UK-research and innovation

US office for human research protections

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Acknowledgements

Authors wish to thank the organising committee of the 5th international conference named plagiarism across Europe and beyond, in Vilnius, Lithuania for accepting this paper to be presented in the conference.

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The manuscript was entirely written by the corresponding author with contributions from co-authors who have equally contributed to presentation of this paper in the 5th international conference named plagiarism across Europe and beyond, in Vilnius, Lithuania. Authors have equally contributed for the information collection, which were then summarised as narrative explanations by the Corresponding author and Dr. Zeenath Reza Khan. Then checked and verified by Dr. Dlabolova and Ms. Králíková. The author(s) read and approved the final manuscript.

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Sivasubramaniam, S., Dlabolová, D.H., Kralikova, V. et al. Assisting you to advance with ethics in research: an introduction to ethical governance and application procedures. Int J Educ Integr 17 , 14 (2021). https://doi.org/10.1007/s40979-021-00078-6

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Ethics is a system of moral principles or the moral values that influence the proper conduct of an individual or group. The term originated from the Greek word ‘ethos’ meaning habit or character, and it speaks to how we ought to live, that is, how we ought to treat others. Any research which involves human subjects or participants is bound to raise challenging ethical, social, legal and political considerations. Ethics in the context of research is particularly interested in the analysis of ethical issues that arise in research with people as participants. The primary concern of any research project is to protect the participants involved in the study and to ensure that the research is carried out in order to serve the interest of individuals, groups or the society as a whole. Another objective in research ethics is to analyse specific research projects and activities to decipher its ethical soundness. Ethical issues involving the protection of confidentiality, the management of risks, the process of obtaining informed consent, physical or legal harm, deception, the protection of privacy and anonymity should be properly addressed in any research project. A study involving human subjects’ especially vulnerable people as participants raises unique issues in any research context. In light of this, the sensitive nature of my research project which is on “police brutality in Nigeria: a human rights perspective”, raises questions on how ethical issues are to be addressed as it involves victims of police brutality and prisoners as participants in the study. The research seeks to identify the nature and causes of police brutality in Nigeria as well as proffer possible solutions to the problem. Also, through research this study is looking to discover the potential victims of this form of brutality, the human rights issues involved and the extent to which the international community or international human rights groups are aware of police brutality in Nigeria and what steps have or have not been taken to curb it. Furthermore, the methodology of this research project is via a qualitative approach as it acknowledges ethical issues, finds meaning through the eyes of the participants, and it’s ideal to explore and understand people’s experiences, attitudes, behaviour and interactions. The use of focus groups, personal experiences of victims and telephone interviews with international human rights groups like ‘Human Rights watch’ and ‘Amnesty International’ would be pertinent to carry out this research. Reports from credible human rights organisations would also be considered. Ethical issues are bound to arise within this research project considering its sensitivity. The ethical responsibility of the researcher is necessary throughout all the stages of the research process, from recruiting participants to the treatment of participants and to the consequences of their participation. The issue of informed consent is an ethical issue that could arise within this project. According to Miller and Brewer (2003), it is important that clear and accurate information regarding the research is communicated to the participants, including its possible benefits and risk. Information pertaining to the aims and objectives of the research, its methodology and intended outcomes should be given, presented in lay terms to enhance easy understanding. In addressing the issue of consent, the researcher should ensure that the participant is adequately informed and the consent is explicitly and voluntarily given. The researcher should never coerce anyone to participate in a research study and should make participants aware of their rights which include the fact that they could withdraw at anytime without penalty (Endacott, 2004). Confidentiality and anonymity are other ethical issues that could come up in this research project as the process can divulge sensitive and confidential information such as the disclosure of names, addresses, location and occupational details. The researcher should ensure that information shared by the participants is protected from unauthorized observation. It is not enough for the researcher to say he/she will ensure confidentiality, rather the researcher should demonstrate to the participants how. To do this, the researcher should present data publicly only in form of an aggregate e.g. as statistics or percentages (Neuman, 2009). Referring to the research study in question, the researcher should ensure that information concerning the mistreatment and abuse of inmates by police officers should be held in strict confidentiality which cannot be traced to a particular person. Another ethical issue is the protection of participants from harm, although obviously evident in medical research, social research can also cause great psychological or emotional distress. Qualitative interviews on sensitive topics could trigger powerful emotional responses from a participant and as such, the researcher should anticipate risks e.g. screening out high risk participants like people with heart conditions, mental problems or seizures. (Neuman, 2009). Research should not cause the participants harm whether physical or mental. The problem of access, which is how to get hold of participants in any research study, is of immense importance to the success of the study; participants could be in terms of an organisation or individual. To gain access to an institution or organisation, it is important to negotiate with gatekeepers who could deny access to the organisation, ration it or impose certain Conditions (Burnham et al, 2004). Access when denied, restricts the research process. There are certain ethical issues related to access, a research study could be viewed as an invasion of privacy or an intrusion to the institution to be studied as it interrupts routines and schedules causing inconveniences and disturbances; it is highly unethical to invade other people’s privacy and as such gaining access could be a really slow process. Furthermore, the fact that research could disclose the limitations of the activities of an institution or individual could further impede access (Flick, 2009). To gain access within the context of this research project, the researcher should be competent in establishing relationships and gaining the trust of its participants and institutions as much as possible to forge a working alliance in which research becomes possible. Qualitative research in cross- cultural studies is difficult, problematic, challenging and time consuming. Ethical issues in cross-cultural research include issues relating to values and world views which involve the misunderstanding of participants by researchers from a different culture. It is important for the researcher to respect the cultural views and belief systems of the participants and not to impose one’s values in the research process. The researcher should be sensitive to cultural and social differences. Ethical considerations should be in place when representing or in the dissemination of results in a cross-cultural research. According to Marshall and Batten (2003), the researcher should portray findings so that it does not damage the reputation of a community or group of people. Sue & Sue (1990) states that research procedures can be ethically sound by acknowledging and incorporating the cultural practices of participants and their larger communities. In the course of the research, there are ethical guidelines the researcher should adhere to while implementing the project. The researcher must responsibly conduct research morally and legally while conforming to ethical standards, the researcher should be informed and not knowingly contravene the legislation of a country in cross-cultural research. The researcher should not use deception to gain information from participants and should pursue objectivity while upholding their integrity without fear or favour. The researcher should be informative and descriptive rather than rigidly prescriptive or authoritative. The researcher should avoid undue intrusion, obtain informed consent and be confidential. The safety of both the researcher and participants in a study should be ensured and the risk of harm minimised. In conclusion, ethics in research should be concerned with finding a balance between benefits and risk for harm (Boeije, 2010). The results of findings based on data gathered unethically could lead to harm, possible conflicts and enormous dilemmas. As such, it is considered good practice for a research project to fully comply with ethical standards. Bakare Ibironke Helen 09281206 Page 1

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Ethical Issues in Research: Perceptions of Researchers, Research Ethics Board Members and Research Ethics Experts

Marie-josée drolet.

1 Department of Occupational Therapy (OT), Université du Québec à Trois-Rivières (UQTR), Trois-Rivières (Québec), Canada

Eugénie Rose-Derouin

2 Bachelor OT program, Université du Québec à Trois-Rivières (UQTR), Trois-Rivières (Québec), Canada

Julie-Claude Leblanc

Mélanie ruest, bryn williams-jones.

3 Department of Social and Preventive Medicine, School of Public Health, Université de Montréal, Montréal (Québec), Canada

In the context of academic research, a diversity of ethical issues, conditioned by the different roles of members within these institutions, arise. Previous studies on this topic addressed mainly the perceptions of researchers. However, to our knowledge, no studies have explored the transversal ethical issues from a wider spectrum, including other members of academic institutions as the research ethics board (REB) members, and the research ethics experts. The present study used a descriptive phenomenological approach to document the ethical issues experienced by a heterogeneous group of Canadian researchers, REB members, and research ethics experts. Data collection involved socio-demographic questionnaires and individual semi-structured interviews. Following the triangulation of different perspectives (researchers, REB members and ethics experts), emerging ethical issues were synthesized in ten units of meaning: (1) research integrity, (2) conflicts of interest, (3) respect for research participants, (4) lack of supervision and power imbalances, (5) individualism and performance, (6) inadequate ethical guidance, (7) social injustices, (8) distributive injustices, (9) epistemic injustices, and (10) ethical distress. This study highlighted several problematic elements that can support the identification of future solutions to resolve transversal ethical issues in research that affect the heterogeneous members of the academic community.

Introduction

Research includes a set of activities in which researchers use various structured methods to contribute to the development of knowledge, whether this knowledge is theoretical, fundamental, or applied (Drolet & Ruest, accepted ). University research is carried out in a highly competitive environment that is characterized by ever-increasing demands (i.e., on time, productivity), insufficient access to research funds, and within a market economy that values productivity and speed often to the detriment of quality or rigour – this research context creates a perfect recipe for breaches in research ethics, like research misbehaviour or misconduct (i.e., conduct that is ethically questionable or unacceptable because it contravenes the accepted norms of responsible conduct of research or compromises the respect of core ethical values that are widely held by the research community) (Drolet & Girard, 2020 ; Sieber, 2004 ). Problematic ethics and integrity issues – e.g., conflicts of interest, falsification of data, non-respect of participants’ rights, and plagiarism, to name but a few – have the potential to both undermine the credibility of research and lead to negative consequences for many stakeholders, including researchers, research assistants and personnel, research participants, academic institutions, and society as a whole (Drolet & Girard, 2020 ). It is thus evident that the academic community should be able to identify these different ethical issues in order to evaluate the nature of the risks that they pose (and for whom), and then work towards their prevention or management (i.e., education, enhanced policies and procedures, risk mitigation strategies).

In this article, we define an “ethical issue” as any situation that may compromise, in whole or in part, the respect of at least one moral value (Swisher et al., 2005 ) that is considered socially legitimate and should thus be respected. In general, ethical issues occur at three key moments or stages of the research process: (1) research design (i.e., conception, project planning), (2) research conduct (i.e., data collection, data analysis) and (3) knowledge translation or communication (e.g., publications of results, conferences, press releases) (Drolet & Ruest, accepted ). According to Sieber ( 2004 ), ethical issues in research can be classified into five categories, related to: (a) communication with participants and the community, (b) acquisition and use of research data, (c) external influence on research, (d) risks and benefits of the research, and (e) selection and use of research theories and methods. Many of these issues are related to breaches of research ethics norms, misbehaviour or research misconduct. Bruhn et al., ( 2002 ) developed a typology of misbehaviour and misconduct in academia that can be used to judge the seriousness of different cases. This typology takes into consideration two axes of reflection: (a) the origin of the situation (i.e., is it the researcher’s own fault or due to the organizational context?), and (b) the scope and severity (i.e., is this the first instance or a recurrent behaviour? What is the nature of the situation? What are the consequences, for whom, for how many people, and for which organizations?).

A previous detailed review of the international literature on ethical issues in research revealed several interesting findings (Beauchemin et al., 2021 ). Indeed, the current literature is dominated by descriptive ethics, i.e., the sharing by researchers from various disciplines of the ethical issues they have personally experienced. While such anecdotal documentation is relevant, it is insufficient because it does not provide a global view of the situation. Among the reviewed literature, empirical studies were in the minority (Table 1 ) – only about one fifth of the sample (n = 19) presented empirical research findings on ethical issues in research. The first of these studies was conducted almost 50 years ago (Hunt et al., 1984 ), with the remainder conducted in the 1990s. Eight studies were conducted in the United States (n = 8), five in Canada (n = 5), three in England (n = 3), two in Sweden (n = 2) and one in Ghana (n = 1).

Summary of Empirical Studies on Ethical Issues in Research by the year of publication

Further, the majority of studies in our sample (n = 12) collected the perceptions of a homogeneous group of participants, usually researchers (n = 14) and sometimes health professionals (n = 6). A minority of studies (n = 7) triangulated the perceptions of diverse research stakeholders (i.e., researchers and research participants, or students). To our knowledge, only one study has examined perceptions of ethical issues in research by research ethics board members (REB; Institutional Review Boards [IRB] in the USA), and none to date have documented the perceptions of research ethics experts. Finally, nine studies (n = 9) adopted a qualitative design, seven studies (n = 7) a quantitative design, and three (n = 3) a mixed-methods design.

More studies using empirical research methods are needed to better identify broader trends, to enrich discussions on the values that should govern responsible conduct of research in the academic community, and to evaluate the means by which these values can be supported in practice (Bahn, 2012 ; Beauchemin et al., 2021 ; Bruhn et al., 2002 ; Henderson et al., 2013 ; Resnik & Elliot, 2016; Sieber 2004 ). To this end, we conducted an empirical qualitative study to document the perceptions and experiences of a heterogeneous group of Canadian researchers, REB members, and research ethics experts, to answer the following broad question: What are the ethical issues in research?

Research Methods

Research design.

A qualitative research approach involving individual semi-structured interviews was used to systematically document ethical issues (De Poy & Gitlin, 2010 ; Hammell et al., 2000 ). Specifically, a descriptive phenomenological approach inspired by the philosophy of Husserl was used (Husserl, 1970 , 1999 ), as it is recommended for documenting the perceptions of ethical issues raised by various practices (Hunt & Carnavale, 2011 ).

Ethical considerations

The principal investigator obtained ethics approval for this project from the Research Ethics Board of the Université du Québec à Trois-Rivières (UQTR). All members of the research team signed a confidentiality agreement, and research participants signed the consent form after reading an information letter explaining the nature of the research project.

Sampling and recruitment

As indicated above, three types of participants were sought: (1) researchers from different academic disciplines conducting research (i.e., theoretical, fundamental or empirical) in Canadian universities; (2) REB members working in Canadian organizations responsible for the ethical review, oversight or regulation of research; and (3) research ethics experts, i.e., academics or ethicists who teach research ethics, conduct research in research ethics, or are scholars who have acquired a specialization in research ethics. To be included in the study, participants had to work in Canada, speak and understand English or French, and be willing to participate in the study. Following Thomas and Polio’s (2002) recommendation to recruit between six and twelve participants (for a homogeneous sample) to ensure data saturation, for our heterogeneous sample, we aimed to recruit approximately twelve participants in order to obtain data saturation. Having used this method several times in related projects in professional ethics, data saturation is usually achieved with 10 to 15 participants (Drolet & Goulet, 2018 ; Drolet & Girard, 2020 ; Drolet et al., 2020 ). From experience, larger samples only serve to increase the degree of data saturation, especially in heterogeneous samples (Drolet et al., 2017 , 2019 ; Drolet & Maclure, 2016 ).

Purposive sampling facilitated the identification of participants relevant to documenting the phenomenon in question (Fortin, 2010 ). To ensure a rich and most complete representation of perceptions, we sought participants with varied and complementary characteristics with regards to the social roles they occupy in research practice (Drolet & Girard, 2020 ). A triangulation of sources was used for the recruitment (Bogdan & Biklen, 2006 ). The websites of Canadian universities and Canadian health institution REBs, as well as those of major Canadian granting agencies (i.e., the Canadian Institutes of Health Research, the Natural Sciences and Engineering Research Council of Canada, and the Social Sciences and Humanities Research Council of Canada, Fonds de recherche du Quebec), were searched to identify individuals who might be interested in participating in the study. Further, people known by the research team for their knowledge and sensitivity to ethical issues in research were asked to participate. Research participants were also asked to suggest other individuals who met the study criteria.

Data Collection

Two tools were used for data collecton: (a) a socio-demographic questionnaire, and (b) a semi-structured individual interview guide. English and French versions of these two documents were used and made available, depending on participant preferences. In addition, although the interview guide contained the same questions, they were adapted to participants’ specific roles (i.e., researcher, REB member, research ethics expert). When contacted by email by the research assistant, participants were asked to confirm under which role they wished to participate (because some participants might have multiple, overlapping responsibilities) and they were sent the appropriate interview guide.

The interview guides each had two parts: an introduction and a section on ethical issues. The introduction consisted of general questions to put the participant at ease (i.e., “Tell me what a typical day at work is like for you”). The section on ethical issues was designed to capture the participant’s perceptions through questions such as: “Tell me three stories you have experienced at work that involve an ethical issue?” and “Do you feel that your organization is doing enough to address, manage, and resolve ethical issues in your work?”. Although some interviews were conducted in person, the majority were conducted by videoconference to promote accessibility and because of the COVID-19 pandemic. Interviews were digitally recorded so that the verbatim could be transcribed in full, and varied between 40 and 120 min in duration, with an average of 90 min. Research assistants conducted the interviews and transcribed the verbatim.

Data Analysis

The socio-demographic questionnaires were subjected to simple descriptive statistical analyses (i.e., means and totals), and the semi-structured interviews were subjected to qualitative analysis. The steps proposed by Giorgi ( 1997 ) for a Husserlian phenomenological reduction of the data were used. After collecting, recording, and transcribing the interviews, all verbatim were analyzed by at least two analysts: a research assistant (2nd author of this article) and the principal investigator (1st author) or a postdoctoral fellow (3rd author). The repeated reading of the verbatim allowed the first analyst to write a synopsis, i.e., an initial extraction of units of meaning. The second analyst then read the synopses, which were commented and improved if necessary. Agreement between analysts allowed the final drafting of the interview synopses, which were then analyzed by three analysts to generate and organize the units of meaning that emerged from the qualitative data.

Participants

Sixteen individuals (n = 16) participated in the study, of whom nine (9) identified as female and seven (7) as male (Table 2 ). Participants ranged in age from 22 to 72 years, with a mean age of 47.5 years. Participants had between one (1) and 26 years of experience in the research setting, with an average of 14.3 years of experience. Participants held a variety of roles, including: REB members (n = 11), researchers (n = 10), research ethics experts (n = 4), and research assistant (n = 1). As mentioned previously, seven (7) participants held more than one role, i.e., REB member, research ethics expert, and researcher. The majority (87.5%) of participants were working in Quebec, with the remaining working in other Canadian provinces. Although all participants considered themselves to be francophone, one quarter (n = 4) identified themselves as belonging to a cultural minority group.

Description of Participants

With respect to their academic background, most participants (n = 9) had a PhD, three (3) had a post-doctorate, two (2) had a master’s degree, and two (2) had a bachelor’s degree. Participants came from a variety of disciplines: nine (9) had a specialty in the humanities or social sciences, four (4) in the health sciences and three (3) in the natural sciences. In terms of their knowledge of ethics, five (5) participants reported having taken one university course entirely dedicated to ethics, four (4) reported having taken several university courses entirely dedicated to ethics, three (3) had a university degree dedicated to ethics, while two (2) only had a few hours or days of training in ethics and two (2) reported having no knowledge of ethics.

Ethical issues

As Fig. 1 illustrates, ten units of meaning emerge from the data analysis, namely: (1) research integrity, (2) conflicts of interest, (3) respect for research participants, (4) lack of supervision and power imbalances, (5) individualism and performance, (6) inadequate ethical guidance, (7) social injustices, (8) distributive injustices, (9) epistemic injustices, and (10) ethical distress. To illustrate the results, excerpts from verbatim interviews are presented in the following sub-sections. Most of the excerpts have been translated into English as the majority of interviews were conducted with French-speaking participants.

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Ethical issues in research according to the participants

Research Integrity

The research environment is highly competitive and performance-based. Several participants, in particular researchers and research ethics experts, felt that this environment can lead both researchers and research teams to engage in unethical behaviour that reflects a lack of research integrity. For example, as some participants indicated, competition for grants and scientific publications is sometimes so intense that researchers falsify research results or plagiarize from colleagues to achieve their goals.

Some people will lie or exaggerate their research findings in order to get funding. Then, you see it afterwards, you realize: “ah well, it didn’t work, but they exaggerated what they found and what they did” (participant 14). Another problem in research is the identification of authors when there is a publication. Very often, there are authors who don’t even know what the publication is about and that their name is on it. (…) The time that it surprised me the most was just a few months ago when I saw someone I knew who applied for a teaching position. He got it I was super happy for him. Then I looked at his publications and … there was one that caught my attention much more than the others, because I was in it and I didn’t know what that publication was. I was the second author of a publication that I had never read (participant 14). I saw a colleague who had plagiarized another colleague. [When the colleague] found out about it, he complained. So, plagiarism is a serious [ethical breach]. I would also say that there is a certain amount of competition in the university faculties, especially for grants (…). There are people who want to win at all costs or get as much as possible. They are not necessarily going to consider their colleagues. They don’t have much of a collegial spirit (participant 10).

These examples of research misbehaviour or misconduct are sometimes due to or associated with situations of conflicts of interest, which may be poorly managed by certain researchers or research teams, as noted by many participants.

Conflict of interest

The actors and institutions involved in research have diverse interests, like all humans and institutions. As noted in Chap. 7 of the Canadian Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS2, 2018),

“researchers and research students hold trust relationships, either directly or indirectly, with participants, research sponsors, institutions, their professional bodies and society. These trust relationships can be put at risk by conflicts of interest that may compromise independence, objectivity or ethical duties of loyalty. Although the potential for such conflicts has always existed, pressures on researchers (i.e., to delay or withhold dissemination of research outcomes or to use inappropriate recruitment strategies) heighten concerns that conflicts of interest may affect ethical behaviour” (p. 92).

The sources of these conflicts are varied and can include interpersonal conflicts, financial partnerships, third-party pressures, academic or economic interests, a researcher holding multiple roles within an institution, or any other incentive that may compromise a researcher’s independence, integrity, and neutrality (TCPS2, 2018). While it is not possible to eliminate all conflicts of interest, it is important to manage them properly and to avoid temptations to behave unethically.

Ethical temptations correspond to situations in which people are tempted to prioritize their own interests to the detriment of the ethical goods that should, in their own context, govern their actions (Swisher et al., 2005 ). In the case of researchers, this refers to situations that undermine independence, integrity, neutrality, or even the set of principles that govern research ethics (TCPS2, 2018) or the responsible conduct of research. According to study participants, these types of ethical issues frequently occur in research. Many participants, especially researchers and REB members, reported that conflicts of interest can arise when members of an organization make decisions to obtain large financial rewards or to increase their academic profile, often at the expense of the interests of members of their research team, research participants, or even the populations affected by their research.

A company that puts money into making its drug work wants its drug to work. So, homeopathy is a good example, because there are not really any consequences of homeopathy, there are not very many side effects, because there are no effects at all. So, it’s not dangerous, but it’s not a good treatment either. But some people will want to make it work. And that’s a big issue when you’re sitting at a table and there are eight researchers, and there are two or three who are like that, and then there are four others who are neutral, and I say to myself, this is not science. I think that this is a very big ethical issue (participant 14). There are also times in some research where there will be more links with pharmaceutical companies. Obviously, there are then large amounts of money that will be very interesting for the health-care institutions because they still receive money for clinical trials. They’re still getting some compensation because its time consuming for the people involved and all that. The pharmaceutical companies have money, so they will compensate, and that is sometimes interesting for the institutions, and since we are a bit caught up in this, in the sense that we have no choice but to accept it. (…) It may not be the best research in the world, there may be a lot of side effects due to the drugs, but it’s good to accept it, we’re going to be part of the clinical trial (participant 3). It is integrity, what we believe should be done or said. Often by the pressure of the environment, integrity is in tension with the pressures of the environment, so it takes resistance, it takes courage in research. (…) There were all the debates there about the problems of research that was funded and then the companies kept control over what was written. That was really troubling for a lot of researchers (participant 5).

Further, these situations sometimes have negative consequences for research participants as reported by some participants.

Respect for research participants

Many research projects, whether they are psychosocial or biomedical in nature, involve human participants. Relationships between the members of research teams and their research participants raise ethical issues that can be complex. Research projects must always be designed to respect the rights and interests of research participants, and not just those of researchers. However, participants in our study – i.e., REB members, researchers, and research ethics experts – noted that some research teams seem to put their own interests ahead of those of research participants. They also emphasized the importance of ensuring the respect, well-being, and safety of research participants. The ethical issues related to this unit of meaning are: respect for free, informed and ongoing consent of research participants; respect for and the well-being of participants; data protection and confidentiality; over-solicitation of participants; ownership of the data collected on participants; the sometimes high cost of scientific innovations and their accessibility; balance between the social benefits of research and the risks to participants (particularly in terms of safety); balance between collective well-being (development of knowledge) and the individual rights of participants; exploitation of participants; paternalism when working with populations in vulnerable situations; and the social acceptability of certain types of research. The following excerpts present some of these issues.

Where it disturbs me ethically is in the medical field – because it’s more in the medical field that we’re going to see this – when consent forms are presented to patients to solicit them as participants, and then [these forms] have an average of 40 pages. That annoys me. When they say that it has to be easy to understand and all that, adapted to the language, and then the hyper-technical language plus there are 40 pages to read, I don’t understand how you’re going to get informed consent after reading 40 pages. (…) For me, it doesn’t work. I read them to evaluate them and I have a certain level of education and experience in ethics, and there are times when I don’t understand anything (participant 2). There is a lot of pressure from researchers who want to recruit research participants (…). The idea that when you enter a health care institution, you become a potential research participant, when you say “yes to a research, you check yes to all research”, then everyone can ask you. I think that researchers really have this fantasy of saying to themselves: “as soon as people walk through the door of our institution, they become potential participants with whom we can communicate and get them involved in all projects”. There’s a kind of idea that, yes, it can be done, but it has to be somewhat supervised to avoid over-solicitation (…). Researchers are very interested in facilitating recruitment and making it more fluid, but perhaps to the detriment of confidentiality, privacy, and respect; sometimes that’s what it is, to think about what type of data you’re going to have in your bank of potential participants? Is it just name and phone number or are you getting into more sensitive information? (participant 9).

In addition, one participant reported that their university does not provide the resources required to respect the confidentiality of research participants.

The issue is as follows: researchers, of course, commit to protecting data with passwords and all that, but we realize that in practice, it is more difficult. It is not always as protected as one might think, because professor-researchers will run out of space. Will the universities make rooms available to researchers, places where they can store these things, especially when they have paper documentation, and is there indeed a guarantee of confidentiality? Some researchers have told me: “Listen; there are even filing cabinets in the corridors”. So, that certainly poses a concrete challenge. How do we go about challenging the administrative authorities? Tell them it’s all very well to have an ethics committee, but you have to help us, you also have to make sure that the necessary infrastructures are in place so that what we are proposing is really put into practice (participant 4).

If the relationships with research participants are likely to raise ethical issues, so too are the relationships with students, notably research assistants. On this topic, several participants discussed the lack of supervision or recognition offered to research assistants by researchers as well as the power imbalances between members of the research team.

Lack of Supervision and Power Imbalances

Many research teams are composed not only of researchers, but also of students who work as research assistants. The relationship between research assistants and other members of research teams can sometimes be problematic and raise ethical issues, particularly because of the inevitable power asymmetries. In the context of this study, several participants – including a research assistant, REB members, and researchers – discussed the lack of supervision or recognition of the work carried out by students, psychological pressure, and the more or less well-founded promises that are sometimes made to students. Participants also mentioned the exploitation of students by certain research teams, which manifest when students are inadequately paid, i.e., not reflective of the number of hours actually worked, not a fair wage, or even a wage at all.

[As a research assistant], it was more of a feeling of distress that I felt then because I didn’t know what to do. (…) I was supposed to get coaching or be supported, but I didn’t get anything in the end. It was like, “fix it by yourself”. (…) All research assistants were supposed to be supervised, but in practice they were not (participant 1). Very often, we have a master’s or doctoral student that we put on a subject and we consider that the project will be well done, while the student is learning. So, it happens that the student will do a lot of work and then we realize that the work is poorly done, and it is not necessarily the student’s fault. He wasn’t necessarily well supervised. There are directors who have 25 students, and they just don’t supervise them (participant 14). I think it’s really the power relationship. I thought to myself, how I saw my doctorate, the beginning of my research career, I really wanted to be in that laboratory, but they are the ones who are going to accept me or not, so what do I do to be accepted? I finally accept their conditions [which was to work for free]. If these are the conditions that are required to enter this lab, I want to go there. So, what do I do, well I accepted. It doesn’t make sense, but I tell myself that I’m still privileged, because I don’t have so many financial worries, one more reason to work for free, even though it doesn’t make sense (participant 1). In research, we have research assistants. (…). The fact of using people… so that’s it, you have to take into account where they are, respect them, but at the same time they have to show that they are there for the research. In English, we say “carry” or take care of people. With research assistants, this is often a problem that I have observed: for grant machines, the person is the last to be found there. Researchers, who will take, use student data, without giving them the recognition for it (participant 5). The problem at our university is that they reserve funding for Canadian students. The doctoral clientele in my field is mostly foreign students. So, our students are poorly funded. I saw one student end up in the shelter, in a situation of poverty. It ended very badly for him because he lacked financial resources. Once you get into that dynamic, it’s very hard to get out. I was made aware of it because the director at the time had taken him under her wing and wanted to try to find a way to get him out of it. So, most of my students didn’t get funded (participant 16). There I wrote “manipulation”, but it’s kind of all promises all the time. I, for example, was promised a lot of advancement, like when I got into the lab as a graduate student, it was said that I had an interest in [this particular area of research]. I think there are a lot of graduate students who must have gone through that, but it is like, “Well, your CV has to be really good, if you want to do a lot of things and big things. If you do this, if you do this research contract, the next year you could be the coordinator of this part of the lab and supervise this person, get more contracts, be paid more. Let’s say: you’ll be invited to go to this conference, this big event”. They were always dangling something, but you have to do that first to get there. But now, when you’ve done that, you have to do this business. It’s like a bit of manipulation, I think. That was very hard to know who is telling the truth and who is not (participant 1).

These ethical issues have significant negative consequences for students. Indeed, they sometimes find themselves at the mercy of researchers, for whom they work, struggling to be recognized and included as authors of an article, for example, or to receive the salary that they are due. For their part, researchers also sometimes find themselves trapped in research structures that can negatively affect their well-being. As many participants reported, researchers work in organizations that set very high productivity standards and in highly competitive contexts, all within a general culture characterized by individualism.

Individualism and performance

Participants, especially researchers, discussed the culture of individualism and performance that characterizes the academic environment. In glorifying excellence, some universities value performance and productivity, often at the expense of psychological well-being and work-life balance (i.e., work overload and burnout). Participants noted that there are ethical silences in their organizations on this issue, and that the culture of individualism and performance is not challenged for fear of retribution or simply to survive, i.e., to perform as expected. Participants felt that this culture can have a significant negative impact on the quality of the research conducted, as research teams try to maximize the quantity of their work (instead of quality) in a highly competitive context, which is then exacerbated by a lack of resources and support, and where everything must be done too quickly.

The work-life balance with the professional ethics related to work in a context where you have too much and you have to do a lot, it is difficult to balance all that and there is a lot of pressure to perform. If you don’t produce enough, that’s it; after that, you can’t get any more funds, so that puts pressure on you to do more and more and more (participant 3). There is a culture, I don’t know where it comes from, and that is extremely bureaucratic. If you dare to raise something, you’re going to have many, many problems. They’re going to make you understand it. So, I don’t talk. It is better: your life will be easier. I think there are times when you have to talk (…) because there are going to be irreparable consequences. (…) I’m not talking about a climate of terror, because that’s exaggerated, it’s not true, people are not afraid. But people close their office door and say nothing because it’s going to make their work impossible and they’re not going to lose their job, they’re not going to lose money, but researchers need time to be focused, so they close their office door and say nothing (participant 16).

Researchers must produce more and more, and they feel little support in terms of how to do such production, ethically, and how much exactly they are expected to produce. As this participant reports, the expectation is an unspoken rule: more is always better.

It’s sometimes the lack of a clear line on what the expectations are as a researcher, like, “ah, we don’t have any specific expectations, but produce, produce, produce, produce.” So, in that context, it’s hard to be able to put the line precisely: “have I done enough for my work?” (participant 3).

Inadequate ethical Guidance

While the productivity expectation is not clear, some participants – including researchers, research ethics experts, and REB members – also felt that the ethical expectations of some REBs were unclear. The issue of the inadequate ethical guidance of research includes the administrative mechanisms to ensure that research projects respect the principles of research ethics. According to those participants, the forms required for both researchers and REB members are increasingly long and numerous, and one participant noted that the standards to be met are sometimes outdated and disconnected from the reality of the field. Multicentre ethics review (by several REBs) was also critiqued by a participant as an inefficient method that encumbers the processes for reviewing research projects. Bureaucratization imposes an ever-increasing number of forms and ethics guidelines that actually hinder researchers’ ethical reflection on the issues at stake, leading the ethics review process to be perceived as purely bureaucratic in nature.

The ethical dimension and the ethical review of projects have become increasingly bureaucratized. (…) When I first started working (…) it was less bureaucratic, less strict then. I would say [there are now] tons of forms to fill out. Of course, we can’t do without it, it’s one of the ways of marking out ethics and ensuring that there are ethical considerations in research, but I wonder if it hasn’t become too bureaucratized, so that it’s become a kind of technical reflex to fill out these forms, and I don’t know if people really do ethical reflection as such anymore (participant 10). The fundamental structural issue, I would say, is the mismatch between the normative requirements and the real risks posed by the research, i.e., we have many, many requirements to meet; we have very long forms to fill out but the research projects we evaluate often pose few risks (participant 8). People [in vulnerable situations] were previously unable to participate because of overly strict research ethics rules that were to protect them, but in the end [these rules] did not protect them. There was a perverse effect, because in the end there was very little research done with these people and that’s why we have very few results, very little evidence [to support practices with these populations] so it didn’t improve the quality of services. (…) We all understand that we have to be careful with that, but when the research is not too risky, we say to ourselves that it would be good because for once a researcher who is interested in that population, because it is not a very popular population, it would be interesting to have results, but often we are blocked by the norms, and then we can’t accept [the project] (participant 2).

Moreover, as one participant noted, accessing ethics training can be a challenge.

There is no course on research ethics. […] Then, I find that it’s boring because you go through university and you come to do your research and you know how to do quantitative and qualitative research, but all the research ethics, where do you get this? I don’t really know (participant 13).

Yet, such training could provide relevant tools to resolve, to some extent, the ethical issues that commonly arise in research. That said, and as noted by many participants, many ethical issues in research are related to social injustices over which research actors have little influence.

Social Injustices

For many participants, notably researchers, the issues that concern social injustices are those related to power asymmetries, stigma, or issues of equity, diversity, and inclusion, i.e., social injustices related to people’s identities (Blais & Drolet, 2022 ). Participants reported experiencing or witnessing discrimination from peers, administration, or lab managers. Such oppression is sometimes cross-sectional and related to a person’s age, cultural background, gender or social status.

I have my African colleague who was quite successful when he arrived but had a backlash from colleagues in the department. I think it’s unconscious, nobody is overtly racist. But I have a young person right now who is the same, who has the same success, who got exactly the same early career award and I don’t see the same backlash. He’s just as happy with what he’s doing. It’s normal, they’re young and they have a lot of success starting out. So, I think there is discrimination. Is it because he is African? Is it because he is black? I think it’s on a subconscious level (participant 16).

Social injustices were experienced or reported by many participants, and included issues related to difficulties in obtaining grants or disseminating research results in one’s native language (i.e., even when there is official bilingualism) or being considered credible and fundable in research when one researcher is a woman.

If you do international research, there are things you can’t talk about (…). It is really a barrier to research to not be able to (…) address this question [i.e. the question of inequalities between men and women]. Women’s inequality is going to be addressed [but not within the country where the research takes place as if this inequality exists elsewhere but not here]. There are a lot of women working on inequality issues, doing work and it’s funny because I was talking to a young woman who works at Cairo University and she said to me: “Listen, I saw what you had written, you’re right. I’m willing to work on this but guarantee me a position at your university with a ticket to go”. So yes, there are still many barriers [for women in research] (participant 16).

Because of the varied contextual characteristics that intervene in their occurrence, these social injustices are also related to distributive injustices, as discussed by many participants.

Distributive Injustices

Although there are several views of distributive justice, a classical definition such as that of Aristotle ( 2012 ), describes distributive justice as consisting in distributing honours, wealth, and other social resources or benefits among the members of a community in proportion to their alleged merit. Justice, then, is about determining an equitable distribution of common goods. Contemporary theories of distributive justice are numerous and varied. Indeed, many authors (e.g., Fraser 2011 ; Mills, 2017 ; Sen, 2011 ; Young, 2011 ) have, since Rawls ( 1971 ), proposed different visions of how social burdens and benefits should be shared within a community to ensure equal respect, fairness, and distribution. In our study, what emerges from participants’ narratives is a definite concern for this type of justice. Women researchers, francophone researchers, early career researchers or researchers belonging to racialized groups all discussed inequities in the distribution of research grants and awards, and the extra work they need to do to somehow prove their worth. These inequities are related to how granting agencies determine which projects will be funded.

These situations make me work 2–3 times harder to prove myself and to show people in power that I have a place as a woman in research (participant 12). Number one: it’s conservative thinking. The older ones control what comes in. So, the younger people have to adapt or they don’t get funded (participant 14).

Whether it is discrimination against stigmatized or marginalized populations or interest in certain hot topics, granting agencies judge research projects according to criteria that are sometimes questionable, according to those participants. Faced with difficulties in obtaining funding for their projects, several strategies – some of which are unethical – are used by researchers in order to cope with these situations.

Sometimes there are subjects that everyone goes to, such as nanotechnology (…), artificial intelligence or (…) the therapeutic use of cannabis, which are very fashionable, and this is sometimes to the detriment of other research that is just as relevant, but which is (…), less sexy, less in the spirit of the time. (…) Sometimes this can lead to inequities in the funding of certain research sectors (participant 9). When we use our funds, we get them given to us, we pretty much say what we think we’re going to do with them, but things change… So, when these things change, sometimes it’s an ethical decision, but by force of circumstances I’m obliged to change the project a little bit (…). Is it ethical to make these changes or should I just let the money go because I couldn’t use it the way I said I would? (participant 3).

Moreover, these distributional injustices are not only linked to social injustices, but also epistemic injustices. Indeed, the way in which research honours and grants are distributed within the academic community depends on the epistemic authority of the researchers, which seems to vary notably according to their language of use, their age or their gender, but also to the research design used (inductive versus deductive), their decision to use (or not use) animals in research, or to conduct activist research.

Epistemic injustices

The philosopher Fricker ( 2007 ) conceptualized the notions of epistemic justice and injustice. Epistemic injustice refers to a form of social inequality that manifests itself in the access, recognition, and production of knowledge as well as the various forms of ignorance that arise (Godrie & Dos Santos, 2017 ). Addressing epistemic injustice necessitates acknowledging the iniquitous wrongs suffered by certain groups of socially stigmatized individuals who have been excluded from knowledge, thus limiting their abilities to interpret, understand, or be heard and account for their experiences. In this study, epistemic injustices were experienced or reported by some participants, notably those related to difficulties in obtaining grants or disseminating research results in one’s native language (i.e., even when there is official bilingualism) or being considered credible and fundable in research when a researcher is a woman or an early career researcher.

I have never sent a grant application to the federal government in English. I have always done it in French, even though I know that when you receive the review, you can see that reviewers didn’t understand anything because they are English-speaking. I didn’t want to get in the boat. It’s not my job to translate, because let’s be honest, I’m not as good in English as I am in French. So, I do them in my first language, which is the language I’m most used to. Then, technically at the administrative level, they are supposed to be able to do it, but they are not good in French. (…) Then, it’s a very big Canadian ethical issue, because basically there are technically two official languages, but Canada is not a bilingual country, it’s a country with two languages, either one or the other. (…) So I was not funded (participant 14).

Researchers who use inductive (or qualitative) methods observed that their projects are sometimes less well reviewed or understood, while research that adopts a hypothetical-deductive (or quantitative) or mixed methods design is better perceived, considered more credible and therefore more easily funded. Of course, regardless of whether a research project adopts an inductive, deductive or mixed-methods scientific design, or whether it deals with qualitative or quantitative data, it must respect a set of scientific criteria. A research project should achieve its objectives by using proven methods that, in the case of inductive research, are credible, reliable, and transferable or, in the case of deductive research, generalizable, objective, representative, and valid (Drolet & Ruest, accepted ). Participants discussing these issues noted that researchers who adopt a qualitative design or those who question the relevance of animal experimentation or are not militant have sometimes been unfairly devalued in their epistemic authority.

There is a mini war between quantitative versus qualitative methods, which I think is silly because science is a method. If you apply the method well, it doesn’t matter what the field is, it’s done well and it’s perfect ” (participant 14). There is also the issue of the place of animals in our lives, because for me, ethics is human ethics, but also animal ethics. Then, there is a great evolution in society on the role of the animal… with the new law that came out in Quebec on the fact that animals are sensitive beings. Then, with the rise of the vegan movement, [we must ask ourselves]: “Do animals still have a place in research?” That’s a big question and it also means that there are practices that need to evolve, but sometimes there’s a disconnection between what’s expected by research ethics boards versus what’s expected in the field (participant 15). In research today, we have more and more research that is militant from an ideological point of view. And so, we have researchers, because they defend values that seem important to them, we’ll talk for example about the fight for equality and social justice. They have pressure to defend a form of moral truth and have the impression that everyone thinks like them or should do so, because they are defending a moral truth. This is something that we see more and more, namely the lack of distance between ideology and science (participant 8).

The combination or intersectionality of these inequities, which seems to be characterized by a lack of ethical support and guidance, is experienced in the highly competitive and individualistic context of research; it provides therefore the perfect recipe for researchers to experience ethical distress.

Ethical distress

The concept of “ethical distress” refers to situations in which people know what they should do to act ethically, but encounter barriers, generally of an organizational or systemic nature, limiting their power to act according to their moral or ethical values (Drolet & Ruest, 2021 ; Jameton, 1984 ; Swisher et al., 2005 ). People then run the risk of finding themselves in a situation where they do not act as their ethical conscience dictates, which in the long term has the potential for exhaustion and distress. The examples reported by participants in this study point to the fact that researchers in particular may be experiencing significant ethical distress. This distress takes place in a context of extreme competition, constant injunctions to perform, and where administrative demands are increasingly numerous and complex to complete, while paradoxically, they lack the time to accomplish all their tasks and responsibilities. Added to these demands are a lack of resources (human, ethical, and financial), a lack of support and recognition, and interpersonal conflicts.

We are in an environment, an elite one, you are part of it, you know what it is: “publish or perish” is the motto. Grants, there is a high level of performance required, to do a lot, to publish, to supervise students, to supervise them well, so yes, it is clear that we are in an environment that is conducive to distress. (…). Overwork, definitely, can lead to distress and eventually to exhaustion. When you know that you should take the time to read the projects before sharing them, but you don’t have the time to do that because you have eight that came in the same day, and then you have others waiting… Then someone rings a bell and says: “ah but there, the protocol is a bit incomplete”. Oh yes, look at that, you’re right. You make up for it, but at the same time it’s a bit because we’re in a hurry, we don’t necessarily have the resources or are able to take the time to do things well from the start, we have to make up for it later. So yes, it can cause distress (participant 9). My organization wanted me to apply in English, and I said no, and everyone in the administration wanted me to apply in English, and I always said no. Some people said: “Listen, I give you the choice”, then some people said: “Listen, I agree with you, but if you’re not [submitting] in English, you won’t be funded”. Then the fact that I am young too, because very often they will look at the CV, they will not look at the project: “ah, his CV is not impressive, we will not finance him”. This is complete nonsense. The person is capable of doing the project, the project is fabulous: we fund the project. So, that happened, organizational barriers: that happened a lot. I was not eligible for Quebec research funds (…). I had big organizational barriers unfortunately (participant 14). At the time of my promotion, some colleagues were not happy with the type of research I was conducting. I learned – you learn this over time when you become friends with people after you enter the university – that someone was against me. He had another candidate in mind, and he was angry about the selection. I was under pressure for the first three years until my contract was renewed. I almost quit at one point, but another colleague told me, “No, stay, nothing will happen”. Nothing happened, but these issues kept me awake at night (participant 16).

This difficult context for many researchers affects not only the conduct of their own research, but also their participation in research. We faced this problem in our study, despite the use of multiple recruitment methods, including more than 200 emails – of which 191 were individual solicitations – sent to potential participants by the two research assistants. REB members and organizations overseeing or supporting research (n = 17) were also approached to see if some of their employees would consider participating. While it was relatively easy to recruit REB members and research ethics experts, our team received a high number of non-responses to emails (n = 175) and some refusals (n = 5), especially by researchers. The reasons given by those who replied were threefold: (a) fear of being easily identified should they take part in the research, (b) being overloaded and lacking time, and (c) the intrusive aspect of certain questions (i.e., “Have you experienced a burnout episode? If so, have you been followed up medically or psychologically?”). In light of these difficulties and concerns, some questions in the socio-demographic questionnaire were removed or modified. Talking about burnout in research remains a taboo for many researchers, which paradoxically can only contribute to the unresolved problem of unhealthy research environments.

Returning to the research question and objective

The question that prompted this research was: What are the ethical issues in research? The purpose of the study was to describe these issues from the perspective of researchers (from different disciplines), research ethics board (REB) members, and research ethics experts. The previous section provided a detailed portrait of the ethical issues experienced by different research stakeholders: these issues are numerous, diverse and were recounted by a range of stakeholders.

The results of the study are generally consistent with the literature. For example, as in our study, the literature discusses the lack of research integrity on the part of some researchers (Al-Hidabi et al., 2018 ; Swazey et al., 1993 ), the numerous conflicts of interest experienced in research (Williams-Jones et al., 2013 ), the issues of recruiting and obtaining the free and informed consent of research participants (Provencher et al., 2014 ; Keogh & Daly, 2009 ), the sometimes difficult relations between researchers and REBs (Drolet & Girard, 2020 ), the epistemological issues experienced in research (Drolet & Ruest, accepted; Sieber 2004 ), as well as the harmful academic context in which researchers evolve, insofar as this is linked to a culture of performance, an overload of work in a context of accountability (Berg & Seeber, 2016 ; FQPPU; 2019 ) that is conducive to ethical distress and even burnout.

If the results of the study are generally in line with those of previous publications on the subject, our findings also bring new elements to the discussion while complementing those already documented. In particular, our results highlight the role of systemic injustices – be they social, distributive or epistemic – within the environments in which research is carried out, at least in Canada. To summarize, the results of our study point to the fact that the relationships between researchers and research participants are likely still to raise worrying ethical issues, despite widely accepted research ethics norms and institutionalized review processes. Further, the context in which research is carried out is not only conducive to breaches of ethical norms and instances of misbehaviour or misconduct, but also likely to be significantly detrimental to the health and well-being of researchers, as well as research assistants. Another element that our research also highlighted is the instrumentalization and even exploitation of students and research assistants, which is another important and worrying social injustice given the inevitable power imbalances between students and researchers.

Moreover, in a context in which ethical issues are often discussed from a micro perspective, our study helps shed light on both the micro- and macro-level ethical dimensions of research (Bronfenbrenner, 1979 ; Glaser 1994 ). However, given that ethical issues in research are not only diverse, but also and above all complex, a broader perspective that encompasses the interplay between the micro and macro dimensions can enable a better understanding of these issues and thereby support the identification of the multiple factors that may be at their origin. Triangulating the perspectives of researchers with those of REB members and research ethics experts enabled us to bring these elements to light, and thus to step back from and critique the way that research is currently conducted. To this end, attention to socio-political elements such as the performance culture in academia or how research funds are distributed, and according to what explicit and implicit criteria, can contribute to identifying the sources of the ethical issues described above.

Contemporary culture characterized by the social acceleration

The German sociologist and philosopher Rosa (2010) argues that late modernity – that is, the period between the 1980s and today – is characterized by a phenomenon of social acceleration that causes various forms of alienation in our relationship to time, space, actions, things, others and ourselves. Rosa distinguishes three types of acceleration: technical acceleration , the acceleration of social changes and the acceleration of the rhythm of life . According to Rosa, social acceleration is the main problem of late modernity, in that the invisible social norm of doing more and faster to supposedly save time operates unchallenged at all levels of individual and collective life, as well as organizational and social life. Although we all, researchers and non-researchers alike, perceive this unspoken pressure to be ever more productive, the process of social acceleration as a new invisible social norm is our blind spot, a kind of tyrant over which we have little control. This conceptualization of the contemporary culture can help us to understand the context in which research is conducted (like other professional practices). To this end, Berg & Seeber ( 2016 ) invite faculty researchers to slow down in order to better reflect and, in the process, take care of their health and their relationships with their colleagues and students. Many women professors encourage their fellow researchers, especially young women researchers, to learn to “say No” in order to protect their mental and physical health and to remain in their academic careers (Allaire & Descheneux, 2022 ). These authors also remind us of the relevance of Kahneman’s ( 2012 ) work which demonstrates that it takes time to think analytically, thoroughly, and logically. Conversely, thinking quickly exposes humans to cognitive and implicit biases that then lead to errors in thinking (e.g., in the analysis of one’s own research data or in the evaluation of grant applications or student curriculum vitae). The phenomenon of social acceleration, which pushes the researcher to think faster and faster, is likely to lead to unethical bad science that can potentially harm humankind. In sum, Rosa’s invitation to contemporary critical theorists to seriously consider the problem of social acceleration is particularly insightful to better understand the ethical issues of research. It provides a lens through which to view the toxic context in which research is conducted today, and one that was shared by the participants in our study.

Clark & Sousa ( 2022 ) note, it is important that other criteria than the volume of researchers’ contributions be valued in research, notably quality. Ultimately, it is the value of the knowledge produced and its influence on the concrete lives of humans and other living beings that matters, not the quantity of publications. An interesting articulation of this view in research governance is seen in a change in practice by Australia’s national health research funder: they now restrict researchers to listing on their curriculum vitae only the top ten publications from the past ten years (rather than all of their publications), in order to evaluate the quality of contributions rather than their quantity. To create environments conducive to the development of quality research, it is important to challenge the phenomenon of social acceleration, which insidiously imposes a quantitative normativity that is both alienating and detrimental to the quality and ethical conduct of research. Based on our experience, we observe that the social norm of acceleration actively disfavours the conduct of empirical research on ethics in research. The fact is that researchers are so busy that it is almost impossible for them to find time to participate in such studies. Further, operating in highly competitive environments, while trying to respect the values and ethical principles of research, creates ethical paradoxes for members of the research community. According to Malherbe ( 1999 ), an ethical paradox is a situation where an individual is confronted by contradictory injunctions (i.e., do more, faster, and better). And eventually, ethical paradoxes lead individuals to situations of distress and burnout, or even to ethical failures (i.e., misbehaviour or misconduct) in the face of the impossibility of responding to contradictory injunctions.

Strengths and Limitations of the study

The triangulation of perceptions and experiences of different actors involved in research is a strength of our study. While there are many studies on the experiences of researchers, rarely are members of REBs and experts in research ethics given the space to discuss their views of what are ethical issues. Giving each of these stakeholders a voice and comparing their different points of view helped shed a different and complementary light on the ethical issues that occur in research. That said, it would have been helpful to also give more space to issues experienced by students or research assistants, as the relationships between researchers and research assistants are at times very worrying, as noted by a participant, and much work still needs to be done to eliminate the exploitative situations that seem to prevail in certain research settings. In addition, no Indigenous or gender diverse researchers participated in the study. Given the ethical issues and systemic injustices that many people from these groups face in Canada (Drolet & Goulet, 2018 ; Nicole & Drolet, in press ), research that gives voice to these researchers would be relevant and contribute to knowledge development, and hopefully also to change in research culture.

Further, although most of the ethical issues discussed in this article may be transferable to the realities experienced by researchers in other countries, the epistemic injustice reported by Francophone researchers who persist in doing research in French in Canada – which is an officially bilingual country but in practice is predominantly English – is likely specific to the Canadian reality. In addition, and as mentioned above, recruitment proved exceedingly difficult, particularly amongst researchers. Despite this difficulty, we obtained data saturation for all but two themes – i.e., exploitation of students and ethical issues of research that uses animals. It follows that further empirical research is needed to improve our understanding of these specific issues, as they may diverge to some extent from those documented here and will likely vary across countries and academic research contexts.

Conclusions

This study, which gave voice to researchers, REB members, and ethics experts, reveals that the ethical issues in research are related to several problematic elements as power imbalances and authority relations. Researchers and research assistants are subject to external pressures that give rise to integrity issues, among others ethical issues. Moreover, the current context of social acceleration influences the definition of the performance indicators valued in academic institutions and has led their members to face several ethical issues, including social, distributive, and epistemic injustices, at different steps of the research process. In this study, ten categories of ethical issues were identified, described and illustrated: (1) research integrity, (2) conflicts of interest, (3) respect for research participants, (4) lack of supervision and power imbalances, (5) individualism and performance, (6) inadequate ethical guidance, (7) social injustices, (8) distributive injustices, (9) epistemic injustices, and (10) ethical distress. The triangulation of the perspectives of different members (i.e., researchers from different disciplines, REB members, research ethics experts, and one research assistant) involved in the research process made it possible to lift the veil on some of these ethical issues. Further, it enabled the identification of additional ethical issues, especially systemic injustices experienced in research. To our knowledge, this is the first time that these injustices (social, distributive, and epistemic injustices) have been clearly identified.

Finally, this study brought to the fore several problematic elements that are important to address if the research community is to develop and implement the solutions needed to resolve the diverse and transversal ethical issues that arise in research institutions. A good starting point is the rejection of the corollary norms of “publish or perish” and “do more, faster, and better” and their replacement with “publish quality instead of quantity”, which necessarily entails “do less, slower, and better”. It is also important to pay more attention to the systemic injustices within which researchers work, because these have the potential to significantly harm the academic careers of many researchers, including women researchers, early career researchers, and those belonging to racialized groups as well as the health, well-being, and respect of students and research participants.

Acknowledgements

The team warmly thanks the participants who took part in the research and who made this study possible. Marie-Josée Drolet thanks the five research assistants who participated in the data collection and analysis: Julie-Claude Leblanc, Élie Beauchemin, Pénéloppe Bernier, Louis-Pierre Côté, and Eugénie Rose-Derouin, all students at the Université du Québec à Trois-Rivières (UQTR), two of whom were active in the writing of this article. MJ Drolet and Bryn Williams-Jones also acknowledge the financial contribution of the Social Sciences and Humanities Research Council of Canada (SSHRC), which supported this research through a grant. We would also like to thank the reviewers of this article who helped us improve it, especially by clarifying and refining our ideas.

Competing Interests and Funding

As noted in the Acknowledgements, this research was supported financially by the Social Sciences and Humanities Research Council of Canada (SSHRC).

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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How to Write an Ethics Paper: Guide & Ethical Essay Examples

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An ethics essay is a type of academic writing that explores ethical issues and dilemmas. Students should evaluates them in terms of moral principles and values. The purpose of an ethics essay is to examine the moral implications of a particular issue, and provide a reasoned argument in support of an ethical perspective.

Writing an essay about ethics is a tough task for most students. The process involves creating an outline to guide your arguments about a topic and planning your ideas to convince the reader of your feelings about a difficult issue. If you still need assistance putting together your thoughts in composing a good paper, you have come to the right place. We have provided a series of steps and tips to show how you can achieve success in writing. This guide will tell you how to write an ethics paper using ethical essay examples to understand every step it takes to be proficient. In case you don’t have time for writing, get in touch with our professional essay writers for hire . Our experts work hard to supply students with excellent essays.

What Is an Ethics Essay?

An ethics essay uses moral theories to build arguments on an issue. You describe a controversial problem and examine it to determine how it affects individuals or society. Ethics papers analyze arguments on both sides of a possible dilemma, focusing on right and wrong. The analysis gained can be used to solve real-life cases. Before embarking on writing an ethical essay, keep in mind that most individuals follow moral principles. From a social context perspective, these rules define how a human behaves or acts towards another. Therefore, your theme essay on ethics needs to demonstrate how a person feels about these moral principles. More specifically, your task is to show how significant that issue is and discuss if you value or discredit it.

Purpose of an Essay on Ethics

The primary purpose of an ethics essay is to initiate an argument on a moral issue using reasoning and critical evidence. Instead of providing general information about a problem, you present solid arguments about how you view the moral concern and how it affects you or society. When writing an ethical paper, you demonstrate philosophical competence, using appropriate moral perspectives and principles.

Things to Write an Essay About Ethics On

Before you start to write ethics essays, consider a topic you can easily address. In most cases, an ethical issues essay analyzes right and wrong. This includes discussing ethics and morals and how they contribute to the right behaviors. You can also talk about work ethic, code of conduct, and how employees promote or disregard the need for change. However, you can explore other areas by asking yourself what ethics mean to you. Think about how a recent game you watched with friends started a controversial argument. Or maybe a newspaper that highlighted a story you felt was misunderstood or blown out of proportion. This way, you can come up with an excellent topic that resonates with your personal ethics and beliefs.

Ethics Paper Outline

Sometimes, you will be asked to submit an outline before writing an ethics paper. Creating an outline for an ethics paper is an essential step in creating a good essay. You can use it to arrange your points and supporting evidence before writing. It also helps organize your thoughts, enabling you to fill any gaps in your ideas. The outline for an essay should contain short and numbered sentences to cover the format and outline. Each section is structured to enable you to plan your work and include all sources in writing an ethics paper. An ethics essay outline is as follows:

Background information
Thesis statement
Restate thesis statement
Summarize key points
Final thoughts on the topic

Using this outline will improve clarity and focus throughout your writing process.

Ethical Essay Structure

Ethics essays are similar to other essays based on their format, outline, and structure. An ethical essay should have a well-defined introduction, body, and conclusion section as its structure. When planning your ideas, make sure that the introduction and conclusion are around 20 percent of the paper, leaving the rest to the body. We will take a detailed look at what each part entails and give examples that are going to help you understand them better. Refer to our essay structure examples to find a fitting way of organizing your writing.

Ethics Paper Introduction

An ethics essay introduction gives a synopsis of your main argument. One step on how to write an introduction for an ethics paper is telling about the topic and describing its background information. This paragraph should be brief and straight to the point. It informs readers what your position is on that issue. Start with an essay hook to generate interest from your audience. It can be a question you will address or a misunderstanding that leads up to your main argument. You can also add more perspectives to be discussed; this will inform readers on what to expect in the paper.

Ethics Essay Introduction Example

You can find many ethics essay introduction examples on the internet. In this guide, we have written an excellent extract to demonstrate how it should be structured. As you read, examine how it begins with a hook and then provides background information on an issue.

Imagine living in a world where people only lie, and honesty is becoming a scarce commodity. Indeed, modern society is facing this reality as truth and deception can no longer be separated. Technology has facilitated a quick transmission of voluminous information, whereas it's hard separating facts from opinions.

In this example, the first sentence of the introduction makes a claim or uses a question to hook the reader.

Ethics Essay Thesis Statement

An ethics paper must contain a thesis statement in the first paragraph. Learning how to write a thesis statement for an ethics paper is necessary as readers often look at it to gauge whether the essay is worth their time.

When you deviate away from the thesis, your whole paper loses meaning. In ethics essays, your thesis statement is a roadmap in writing, stressing your position on the problem and giving reasons for taking that stance. It should focus on a specific element of the issue being discussed. When writing a thesis statement, ensure that you can easily make arguments for or against its stance.

Ethical Paper Thesis Example

Look at this example of an ethics paper thesis statement and examine how well it has been written to state a position and provide reasons for doing so:

The moral implications of dishonesty are far-reaching as they undermine trust, integrity, and other foundations of society, damaging personal and professional relationships.

The above thesis statement example is clear and concise, indicating that this paper will highlight the effects of dishonesty in society. Moreover, it focuses on aspects of personal and professional relationships.

Ethics Essay Body

The body section is the heart of an ethics paper as it presents the author's main points. In an ethical essay, each body paragraph has several elements that should explain your main idea. These include:

A topic sentence that is precise and reiterates your stance on the issue.
Evidence supporting it.
Examples that illustrate your argument.
A thorough analysis showing how the evidence and examples relate to that issue.
A transition sentence that connects one paragraph to another with the help of essay transitions .

When you write an ethics essay, adding relevant examples strengthens your main point and makes it easy for others to understand and comprehend your argument.

Body Paragraph for Ethics Paper Example

A good body paragraph must have a well-defined topic sentence that makes a claim and includes evidence and examples to support it. Look at part of an example of ethics essay body paragraph below and see how its idea has been developed:

Honesty is an essential component of professional integrity. In many fields, trust and credibility are crucial for professionals to build relationships and success. For example, a doctor who is dishonest about a potential side effect of a medication is not only acting unethically but also putting the health and well-being of their patients at risk. Similarly, a dishonest businessman could achieve short-term benefits but will lose their client’s trust.

Ethics Essay Conclusion

A concluding paragraph shares the summary and overview of the author's main arguments. Many students need clarification on what should be included in the essay conclusion and how best to get a reader's attention. When writing an ethics paper conclusion, consider the following:

Restate the thesis statement to emphasize your position.
Summarize its main points and evidence.
Final thoughts on the issue and any other considerations.

You can also reflect on the topic or acknowledge any possible challenges or questions that have not been answered. A closing statement should present a call to action on the problem based on your position.

Sample Ethics Paper Conclusion

The conclusion paragraph restates the thesis statement and summarizes the arguments presented in that paper. The sample conclusion for an ethical essay example below demonstrates how you should write a concluding statement.

In conclusion, the implications of dishonesty and the importance of honesty in our lives cannot be overstated. Honesty builds solid relationships, effective communication, and better decision-making. This essay has explored how dishonesty impacts people and that we should value honesty. We hope this essay will help readers assess their behavior and work towards being more honest in their lives.

In the above extract, the writer gives final thoughts on the topic, urging readers to adopt honest behavior.

How to Write an Ethics Paper?

As you learn how to write an ethics essay, it is not advised to immediately choose a topic and begin writing. When you follow this method, you will get stuck or fail to present concrete ideas. A good writer understands the importance of planning. As a fact, you should organize your work and ensure it captures key elements that shed more light on your arguments. Hence, following the essay structure and creating an outline to guide your writing process is the best approach. In the following segment, we have highlighted step-by-step techniques on how to write a good ethics paper.

1. Pick a Topic

Before writing ethical papers, brainstorm to find ideal topics that can be easily debated. For starters, make a list, then select a title that presents a moral issue that may be explained and addressed from opposing sides. Make sure you choose one that interests you. Here are a few ideas to help you search for topics:

Review current trends affecting people.
Think about your personal experiences.
Study different moral theories and principles.
Examine classical moral dilemmas.

Once you find a suitable topic and are ready, start to write your ethics essay, conduct preliminary research, and ascertain that there are enough sources to support it.

2. Conduct In-Depth Research

Once you choose a topic for your essay, the next step is gathering sufficient information about it. Conducting in-depth research entails looking through scholarly journals to find credible material. Ensure you note down all sources you found helpful to assist you on how to write your ethics paper. Use the following steps to help you conduct your research:

Clearly state and define a problem you want to discuss.
This will guide your research process.
Develop keywords that match the topic.
Begin searching from a wide perspective. This will allow you to collect more information, then narrow it down by using the identified words above.

3. Develop an Ethics Essay Outline

An outline will ease up your writing process when developing an ethic essay. As you develop a paper on ethics, jot down factual ideas that will build your paragraphs for each section. Include the following steps in your process:

Review the topic and information gathered to write a thesis statement.
Identify the main arguments you want to discuss and include their evidence.
Group them into sections, each presenting a new idea that supports the thesis.
Write an outline.
Review and refine it.

Examples can also be included to support your main arguments. The structure should be sequential, coherent, and with a good flow from beginning to end. When you follow all steps, you can create an engaging and organized outline that will help you write a good essay.

4. Write an Ethics Essay

Once you have selected a topic, conducted research, and outlined your main points, you can begin writing an essay . Ensure you adhere to the ethics paper format you have chosen. Start an ethics paper with an overview of your topic to capture the readers' attention. Build upon your paper by avoiding ambiguous arguments and using the outline to help you write your essay on ethics. Finish the introduction paragraph with a thesis statement that explains your main position. Expand on your thesis statement in all essay paragraphs. Each paragraph should start with a topic sentence and provide evidence plus an example to solidify your argument, strengthen the main point, and let readers see the reasoning behind your stance. Finally, conclude the essay by restating your thesis statement and summarizing all key ideas. Your conclusion should engage the reader, posing questions or urging them to reflect on the issue and how it will impact them.

5. Proofread Your Ethics Essay

Proofreading your essay is the last step as you countercheck any grammatical or structural errors in your essay. When writing your ethic paper, typical mistakes you could encounter include the following:

Spelling errors: e.g., there, they’re, their.
Homophone words: such as new vs. knew.
Inconsistencies: like mixing British and American words, e.g., color vs. color.
Formatting issues: e.g., double spacing, different font types.

While proofreading your ethical issue essay, read it aloud to detect lexical errors or ambiguous phrases that distort its meaning. Verify your information and ensure it is relevant and up-to-date. You can ask your fellow student to read the essay and give feedback on its structure and quality.

Ethics Essay Examples

Writing an essay is challenging without the right steps. There are so many ethics paper examples on the internet, however, we have provided a list of free ethics essay examples below that are well-structured and have a solid argument to help you write your paper. Click on them and see how each writing step has been integrated. Ethics essay example 1

Ethics essay example 2

Ethics essay example 3

Ethics essay example 4

College ethics essay example 5

Ethics Essay Writing Tips

When writing papers on ethics, here are several tips to help you complete an excellent essay:

Choose a narrow topic and avoid broad subjects, as it is easy to cover the topic in detail.
Ensure you have background information. A good understanding of a topic can make it easy to apply all necessary moral theories and principles in writing your paper.
State your position clearly. It is important to be sure about your stance as it will allow you to draft your arguments accordingly.
When writing ethics essays, be mindful of your audience. Provide arguments that they can understand.
Integrate solid examples into your essay. Morality can be hard to understand; therefore, using them will help a reader grasp these concepts.

Bottom Line on Writing an Ethics Paper

Creating this essay is a common exercise in academics that allows students to build critical skills. When you begin writing, state your stance on an issue and provide arguments to support your position. This guide gives information on how to write an ethics essay as well as examples of ethics papers. Remember to follow these points in your writing:

Create an outline highlighting your main points.
Write an effective introduction and provide background information on an issue.
Include a thesis statement.
Develop concrete arguments and their counterarguments, and use examples.
Sum up all your key points in your conclusion and restate your thesis statement.

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Ethical Considerations – Types, Examples and Writing Guide

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Ethical Considerations

Ethical considerations in research refer to the principles and guidelines that researchers must follow to ensure that their studies are conducted in an ethical and responsible manner. These considerations are designed to protect the rights, safety, and well-being of research participants, as well as the integrity and credibility of the research itself

Some of the key ethical considerations in research include:

Informed consent: Researchers must obtain informed consent from study participants, which means they must inform participants about the study’s purpose, procedures, risks, benefits, and their right to withdraw at any time.
Privacy and confidentiality : Researchers must ensure that participants’ privacy and confidentiality are protected. This means that personal information should be kept confidential and not shared without the participant’s consent.
Harm reduction : Researchers must ensure that the study does not harm the participants physically or psychologically. They must take steps to minimize the risks associated with the study.
Fairness and equity : Researchers must ensure that the study does not discriminate against any particular group or individual. They should treat all participants equally and fairly.
Use of deception: Researchers must use deception only if it is necessary to achieve the study’s objectives. They must inform participants of the deception as soon as possible.
Use of vulnerable populations : Researchers must be especially cautious when working with vulnerable populations, such as children, pregnant women, prisoners, and individuals with cognitive or intellectual disabilities.
Conflict of interest : Researchers must disclose any potential conflicts of interest that may affect the study’s integrity. This includes financial or personal relationships that could influence the study’s results.
Data manipulation: Researchers must not manipulate data to support a particular hypothesis or agenda. They should report the results of the study objectively, even if the findings are not consistent with their expectations.
Intellectual property: Researchers must respect intellectual property rights and give credit to previous studies and research.
Cultural sensitivity : Researchers must be sensitive to the cultural norms and beliefs of the participants. They should avoid imposing their values and beliefs on the participants and should be respectful of their cultural practices.

Types of Ethical Considerations

Types of Ethical Considerations are as follows:

Research Ethics:

This includes ethical principles and guidelines that govern research involving human or animal subjects, ensuring that the research is conducted in an ethical and responsible manner.

Business Ethics :

This refers to ethical principles and standards that guide business practices and decision-making, such as transparency, honesty, fairness, and social responsibility.

Medical Ethics :

This refers to ethical principles and standards that govern the practice of medicine, including the duty to protect patient autonomy, informed consent, confidentiality, and non-maleficence.

Environmental Ethics :

This involves ethical principles and values that guide our interactions with the natural world, including the obligation to protect the environment, minimize harm, and promote sustainability.

Legal Ethics

This involves ethical principles and standards that guide the conduct of legal professionals, including issues such as confidentiality, conflicts of interest, and professional competence.

Social Ethics

This involves ethical principles and values that guide our interactions with other individuals and society as a whole, including issues such as justice, fairness, and human rights.

Information Ethics

This involves ethical principles and values that govern the use and dissemination of information, including issues such as privacy, accuracy, and intellectual property.

Cultural Ethics

This involves ethical principles and values that govern the relationship between different cultures and communities, including issues such as respect for diversity, cultural sensitivity, and inclusivity.

Technological Ethics

This refers to ethical principles and guidelines that govern the development, use, and impact of technology, including issues such as privacy, security, and social responsibility.

Journalism Ethics

This involves ethical principles and standards that guide the practice of journalism, including issues such as accuracy, fairness, and the public interest.

Educational Ethics

This refers to ethical principles and standards that guide the practice of education, including issues such as academic integrity, fairness, and respect for diversity.

Political Ethics

This involves ethical principles and values that guide political decision-making and behavior, including issues such as accountability, transparency, and the protection of civil liberties.

Professional Ethics

This refers to ethical principles and standards that guide the conduct of professionals in various fields, including issues such as honesty, integrity, and competence.

Personal Ethics

This involves ethical principles and values that guide individual behavior and decision-making, including issues such as personal responsibility, honesty, and respect for others.

Global Ethics

This involves ethical principles and values that guide our interactions with other nations and the global community, including issues such as human rights, environmental protection, and social justice.

Applications of Ethical Considerations

Ethical considerations are important in many areas of society, including medicine, business, law, and technology. Here are some specific applications of ethical considerations:

Medical research : Ethical considerations are crucial in medical research, particularly when human subjects are involved. Researchers must ensure that their studies are conducted in a way that does not harm participants and that participants give informed consent before participating.
Business practices: Ethical considerations are also important in business, where companies must make decisions that are socially responsible and avoid activities that are harmful to society. For example, companies must ensure that their products are safe for consumers and that they do not engage in exploitative labor practices.
Environmental protection: Ethical considerations play a crucial role in environmental protection, as companies and governments must weigh the benefits of economic development against the potential harm to the environment. Decisions about land use, resource allocation, and pollution must be made in an ethical manner that takes into account the long-term consequences for the planet and future generations.
Technology development : As technology continues to advance rapidly, ethical considerations become increasingly important in areas such as artificial intelligence, robotics, and genetic engineering. Developers must ensure that their creations do not harm humans or the environment and that they are developed in a way that is fair and equitable.
Legal system : The legal system relies on ethical considerations to ensure that justice is served and that individuals are treated fairly. Lawyers and judges must abide by ethical standards to maintain the integrity of the legal system and to protect the rights of all individuals involved.

Examples of Ethical Considerations

Here are a few examples of ethical considerations in different contexts:

In healthcare : A doctor must ensure that they provide the best possible care to their patients and avoid causing them harm. They must respect the autonomy of their patients, and obtain informed consent before administering any treatment or procedure. They must also ensure that they maintain patient confidentiality and avoid any conflicts of interest.
In the workplace: An employer must ensure that they treat their employees fairly and with respect, provide them with a safe working environment, and pay them a fair wage. They must also avoid any discrimination based on race, gender, religion, or any other characteristic protected by law.
In the media : Journalists must ensure that they report the news accurately and without bias. They must respect the privacy of individuals and avoid causing harm or distress. They must also be transparent about their sources and avoid any conflicts of interest.
In research: Researchers must ensure that they conduct their studies ethically and with integrity. They must obtain informed consent from participants, protect their privacy, and avoid any harm or discomfort. They must also ensure that their findings are reported accurately and without bias.
In personal relationships : People must ensure that they treat others with respect and kindness, and avoid causing harm or distress. They must respect the autonomy of others and avoid any actions that would be considered unethical, such as lying or cheating. They must also respect the confidentiality of others and maintain their privacy.

How to Write Ethical Considerations

When writing about research involving human subjects or animals, it is essential to include ethical considerations to ensure that the study is conducted in a manner that is morally responsible and in accordance with professional standards. Here are some steps to help you write ethical considerations:

Describe the ethical principles: Start by explaining the ethical principles that will guide the research. These could include principles such as respect for persons, beneficence, and justice.
Discuss informed consent : Informed consent is a critical ethical consideration when conducting research. Explain how you will obtain informed consent from participants, including how you will explain the purpose of the study, potential risks and benefits, and how you will protect their privacy.
Address confidentiality : Describe how you will protect the confidentiality of the participants’ personal information and data, including any measures you will take to ensure that the data is kept secure and confidential.
Consider potential risks and benefits : Describe any potential risks or harms to participants that could result from the study and how you will minimize those risks. Also, discuss the potential benefits of the study, both to the participants and to society.
Discuss the use of animals : If the research involves the use of animals, address the ethical considerations related to animal welfare. Explain how you will minimize any potential harm to the animals and ensure that they are treated ethically.
Mention the ethical approval : Finally, it’s essential to acknowledge that the research has received ethical approval from the relevant institutional review board or ethics committee. State the name of the committee, the date of approval, and any specific conditions or requirements that were imposed.

When to Write Ethical Considerations

Ethical considerations should be written whenever research involves human subjects or has the potential to impact human beings, animals, or the environment in some way. Ethical considerations are also important when research involves sensitive topics, such as mental health, sexuality, or religion.

In general, ethical considerations should be an integral part of any research project, regardless of the field or subject matter. This means that they should be considered at every stage of the research process, from the initial planning and design phase to data collection, analysis, and dissemination.

Ethical considerations should also be written in accordance with the guidelines and standards set by the relevant regulatory bodies and professional associations. These guidelines may vary depending on the discipline, so it is important to be familiar with the specific requirements of your field.

Purpose of Ethical Considerations

Ethical considerations are an essential aspect of many areas of life, including business, healthcare, research, and social interactions. The primary purposes of ethical considerations are:

Protection of human rights: Ethical considerations help ensure that people’s rights are respected and protected. This includes respecting their autonomy, ensuring their privacy is respected, and ensuring that they are not subjected to harm or exploitation.
Promoting fairness and justice: Ethical considerations help ensure that people are treated fairly and justly, without discrimination or bias. This includes ensuring that everyone has equal access to resources and opportunities, and that decisions are made based on merit rather than personal biases or prejudices.
Promoting honesty and transparency : Ethical considerations help ensure that people are truthful and transparent in their actions and decisions. This includes being open and honest about conflicts of interest, disclosing potential risks, and communicating clearly with others.
Maintaining public trust: Ethical considerations help maintain public trust in institutions and individuals. This is important for building and maintaining relationships with customers, patients, colleagues, and other stakeholders.
Ensuring responsible conduct: Ethical considerations help ensure that people act responsibly and are accountable for their actions. This includes adhering to professional standards and codes of conduct, following laws and regulations, and avoiding behaviors that could harm others or damage the environment.

Advantages of Ethical Considerations

Here are some of the advantages of ethical considerations:

Builds Trust : When individuals or organizations follow ethical considerations, it creates a sense of trust among stakeholders, including customers, clients, and employees. This trust can lead to stronger relationships and long-term loyalty.
Reputation and Brand Image : Ethical considerations are often linked to a company’s brand image and reputation. By following ethical practices, a company can establish a positive image and reputation that can enhance its brand value.
Avoids Legal Issues: Ethical considerations can help individuals and organizations avoid legal issues and penalties. By adhering to ethical principles, companies can reduce the risk of facing lawsuits, regulatory investigations, and fines.
Increases Employee Retention and Motivation: Employees tend to be more satisfied and motivated when they work for an organization that values ethics. Companies that prioritize ethical considerations tend to have higher employee retention rates, leading to lower recruitment costs.
Enhances Decision-making: Ethical considerations help individuals and organizations make better decisions. By considering the ethical implications of their actions, decision-makers can evaluate the potential consequences and choose the best course of action.
Positive Impact on Society: Ethical considerations have a positive impact on society as a whole. By following ethical practices, companies can contribute to social and environmental causes, leading to a more sustainable and equitable society.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Frequently asked questions

Why do research ethics matter.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe.

Frequently asked questions: Methodology

Attrition refers to participants leaving a study. It always happens to some extent—for example, in randomized controlled trials for medical research.

Differential attrition occurs when attrition or dropout rates differ systematically between the intervention and the control group . As a result, the characteristics of the participants who drop out differ from the characteristics of those who stay in the study. Because of this, study results may be biased .

Action research is conducted in order to solve a particular issue immediately, while case studies are often conducted over a longer period of time and focus more on observing and analyzing a particular ongoing phenomenon.

Action research is focused on solving a problem or informing individual and community-based knowledge in a way that impacts teaching, learning, and other related processes. It is less focused on contributing theoretical input, instead producing actionable input.

Action research is particularly popular with educators as a form of systematic inquiry because it prioritizes reflection and bridges the gap between theory and practice. Educators are able to simultaneously investigate an issue as they solve it, and the method is very iterative and flexible.

A cycle of inquiry is another name for action research . It is usually visualized in a spiral shape following a series of steps, such as “planning → acting → observing → reflecting.”

To make quantitative observations , you need to use instruments that are capable of measuring the quantity you want to observe. For example, you might use a ruler to measure the length of an object or a thermometer to measure its temperature.

Criterion validity and construct validity are both types of measurement validity . In other words, they both show you how accurately a method measures something.

While construct validity is the degree to which a test or other measurement method measures what it claims to measure, criterion validity is the degree to which a test can predictively (in the future) or concurrently (in the present) measure something.

Construct validity is often considered the overarching type of measurement validity . You need to have face validity , content validity , and criterion validity in order to achieve construct validity.

Convergent validity and discriminant validity are both subtypes of construct validity . Together, they help you evaluate whether a test measures the concept it was designed to measure.

Convergent validity indicates whether a test that is designed to measure a particular construct correlates with other tests that assess the same or similar construct.
Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related. This type of validity is also called divergent validity .

You need to assess both in order to demonstrate construct validity. Neither one alone is sufficient for establishing construct validity.

Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related

Content validity shows you how accurately a test or other measurement method taps into the various aspects of the specific construct you are researching.

In other words, it helps you answer the question: “does the test measure all aspects of the construct I want to measure?” If it does, then the test has high content validity.

The higher the content validity, the more accurate the measurement of the construct.

If the test fails to include parts of the construct, or irrelevant parts are included, the validity of the instrument is threatened, which brings your results into question.

Face validity and content validity are similar in that they both evaluate how suitable the content of a test is. The difference is that face validity is subjective, and assesses content at surface level.

When a test has strong face validity, anyone would agree that the test’s questions appear to measure what they are intended to measure.

For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity (i.e., it looks like a math test).

On the other hand, content validity evaluates how well a test represents all the aspects of a topic. Assessing content validity is more systematic and relies on expert evaluation. of each question, analyzing whether each one covers the aspects that the test was designed to cover.

A 4th grade math test would have high content validity if it covered all the skills taught in that grade. Experts(in this case, math teachers), would have to evaluate the content validity by comparing the test to the learning objectives.

Snowball sampling is a non-probability sampling method . Unlike probability sampling (which involves some form of random selection ), the initial individuals selected to be studied are the ones who recruit new participants.

Because not every member of the target population has an equal chance of being recruited into the sample, selection in snowball sampling is non-random.

Snowball sampling is a non-probability sampling method , where there is not an equal chance for every member of the population to be included in the sample .

This means that you cannot use inferential statistics and make generalizations —often the goal of quantitative research . As such, a snowball sample is not representative of the target population and is usually a better fit for qualitative research .

Snowball sampling relies on the use of referrals. Here, the researcher recruits one or more initial participants, who then recruit the next ones.

Participants share similar characteristics and/or know each other. Because of this, not every member of the population has an equal chance of being included in the sample, giving rise to sampling bias .

Snowball sampling is best used in the following cases:

If there is no sampling frame available (e.g., people with a rare disease)
If the population of interest is hard to access or locate (e.g., people experiencing homelessness)
If the research focuses on a sensitive topic (e.g., extramarital affairs)

The reproducibility and replicability of a study can be ensured by writing a transparent, detailed method section and using clear, unambiguous language.

Reproducibility and replicability are related terms.

Reproducing research entails reanalyzing the existing data in the same manner.
Replicating (or repeating ) the research entails reconducting the entire analysis, including the collection of new data .
A successful reproduction shows that the data analyses were conducted in a fair and honest manner.
A successful replication shows that the reliability of the results is high.

Stratified sampling and quota sampling both involve dividing the population into subgroups and selecting units from each subgroup. The purpose in both cases is to select a representative sample and/or to allow comparisons between subgroups.

The main difference is that in stratified sampling, you draw a random sample from each subgroup ( probability sampling ). In quota sampling you select a predetermined number or proportion of units, in a non-random manner ( non-probability sampling ).

Purposive and convenience sampling are both sampling methods that are typically used in qualitative data collection.

A convenience sample is drawn from a source that is conveniently accessible to the researcher. Convenience sampling does not distinguish characteristics among the participants. On the other hand, purposive sampling focuses on selecting participants possessing characteristics associated with the research study.

The findings of studies based on either convenience or purposive sampling can only be generalized to the (sub)population from which the sample is drawn, and not to the entire population.

Random sampling or probability sampling is based on random selection. This means that each unit has an equal chance (i.e., equal probability) of being included in the sample.

On the other hand, convenience sampling involves stopping people at random, which means that not everyone has an equal chance of being selected depending on the place, time, or day you are collecting your data.

Convenience sampling and quota sampling are both non-probability sampling methods. They both use non-random criteria like availability, geographical proximity, or expert knowledge to recruit study participants.

However, in convenience sampling, you continue to sample units or cases until you reach the required sample size.

In quota sampling, you first need to divide your population of interest into subgroups (strata) and estimate their proportions (quota) in the population. Then you can start your data collection, using convenience sampling to recruit participants, until the proportions in each subgroup coincide with the estimated proportions in the population.

A sampling frame is a list of every member in the entire population . It is important that the sampling frame is as complete as possible, so that your sample accurately reflects your population.

Stratified and cluster sampling may look similar, but bear in mind that groups created in cluster sampling are heterogeneous , so the individual characteristics in the cluster vary. In contrast, groups created in stratified sampling are homogeneous , as units share characteristics.

Relatedly, in cluster sampling you randomly select entire groups and include all units of each group in your sample. However, in stratified sampling, you select some units of all groups and include them in your sample. In this way, both methods can ensure that your sample is representative of the target population .

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment .

An observational study is a great choice for you if your research question is based purely on observations. If there are ethical, logistical, or practical concerns that prevent you from conducting a traditional experiment , an observational study may be a good choice. In an observational study, there is no interference or manipulation of the research subjects, as well as no control or treatment groups .

It’s often best to ask a variety of people to review your measurements. You can ask experts, such as other researchers, or laypeople, such as potential participants, to judge the face validity of tests.

While experts have a deep understanding of research methods , the people you’re studying can provide you with valuable insights you may have missed otherwise.

Face validity is important because it’s a simple first step to measuring the overall validity of a test or technique. It’s a relatively intuitive, quick, and easy way to start checking whether a new measure seems useful at first glance.

Good face validity means that anyone who reviews your measure says that it seems to be measuring what it’s supposed to. With poor face validity, someone reviewing your measure may be left confused about what you’re measuring and why you’re using this method.

Face validity is about whether a test appears to measure what it’s supposed to measure. This type of validity is concerned with whether a measure seems relevant and appropriate for what it’s assessing only on the surface.

Statistical analyses are often applied to test validity with data from your measures. You test convergent validity and discriminant validity with correlations to see if results from your test are positively or negatively related to those of other established tests.

You can also use regression analyses to assess whether your measure is actually predictive of outcomes that you expect it to predict theoretically. A regression analysis that supports your expectations strengthens your claim of construct validity .

When designing or evaluating a measure, construct validity helps you ensure you’re actually measuring the construct you’re interested in. If you don’t have construct validity, you may inadvertently measure unrelated or distinct constructs and lose precision in your research.

Construct validity is often considered the overarching type of measurement validity , because it covers all of the other types. You need to have face validity , content validity , and criterion validity to achieve construct validity.

Construct validity is about how well a test measures the concept it was designed to evaluate. It’s one of four types of measurement validity , which includes construct validity, face validity , and criterion validity.

There are two subtypes of construct validity.

Convergent validity : The extent to which your measure corresponds to measures of related constructs
Discriminant validity : The extent to which your measure is unrelated or negatively related to measures of distinct constructs

Naturalistic observation is a valuable tool because of its flexibility, external validity , and suitability for topics that can’t be studied in a lab setting.

The downsides of naturalistic observation include its lack of scientific control , ethical considerations , and potential for bias from observers and subjects.

Naturalistic observation is a qualitative research method where you record the behaviors of your research subjects in real world settings. You avoid interfering or influencing anything in a naturalistic observation.

You can think of naturalistic observation as “people watching” with a purpose.

A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it “depends” on your independent variable.

In statistics, dependent variables are also called:

Response variables (they respond to a change in another variable)
Outcome variables (they represent the outcome you want to measure)
Left-hand-side variables (they appear on the left-hand side of a regression equation)

An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.

Independent variables are also called:

Explanatory variables (they explain an event or outcome)
Predictor variables (they can be used to predict the value of a dependent variable)
Right-hand-side variables (they appear on the right-hand side of a regression equation).

As a rule of thumb, questions related to thoughts, beliefs, and feelings work well in focus groups. Take your time formulating strong questions, paying special attention to phrasing. Be careful to avoid leading questions , which can bias your responses.

Overall, your focus group questions should be:

Open-ended and flexible
Impossible to answer with “yes” or “no” (questions that start with “why” or “how” are often best)
Unambiguous, getting straight to the point while still stimulating discussion
Unbiased and neutral

A structured interview is a data collection method that relies on asking questions in a set order to collect data on a topic. They are often quantitative in nature. Structured interviews are best used when:

You already have a very clear understanding of your topic. Perhaps significant research has already been conducted, or you have done some prior research yourself, but you already possess a baseline for designing strong structured questions.
You are constrained in terms of time or resources and need to analyze your data quickly and efficiently.
Your research question depends on strong parity between participants, with environmental conditions held constant.

More flexible interview options include semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias is the tendency for interview participants to give responses that will be viewed favorably by the interviewer or other participants. It occurs in all types of interviews and surveys , but is most common in semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias can be mitigated by ensuring participants feel at ease and comfortable sharing their views. Make sure to pay attention to your own body language and any physical or verbal cues, such as nodding or widening your eyes.

This type of bias can also occur in observations if the participants know they’re being observed. They might alter their behavior accordingly.

The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.

There is a risk of an interviewer effect in all types of interviews , but it can be mitigated by writing really high-quality interview questions.

A semi-structured interview is a blend of structured and unstructured types of interviews. Semi-structured interviews are best used when:

You have prior interview experience. Spontaneous questions are deceptively challenging, and it’s easy to accidentally ask a leading question or make a participant uncomfortable.
Your research question is exploratory in nature. Participant answers can guide future research questions and help you develop a more robust knowledge base for future research.

An unstructured interview is the most flexible type of interview, but it is not always the best fit for your research topic.

Unstructured interviews are best used when:

You are an experienced interviewer and have a very strong background in your research topic, since it is challenging to ask spontaneous, colloquial questions.
Your research question is exploratory in nature. While you may have developed hypotheses, you are open to discovering new or shifting viewpoints through the interview process.
You are seeking descriptive data, and are ready to ask questions that will deepen and contextualize your initial thoughts and hypotheses.
Your research depends on forming connections with your participants and making them feel comfortable revealing deeper emotions, lived experiences, or thoughts.

The four most common types of interviews are:

Structured interviews : The questions are predetermined in both topic and order.
Semi-structured interviews : A few questions are predetermined, but other questions aren’t planned.
Unstructured interviews : None of the questions are predetermined.
Focus group interviews : The questions are presented to a group instead of one individual.

Deductive reasoning is commonly used in scientific research, and it’s especially associated with quantitative research .

In research, you might have come across something called the hypothetico-deductive method . It’s the scientific method of testing hypotheses to check whether your predictions are substantiated by real-world data.

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning , where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic.

There are many different types of inductive reasoning that people use formally or informally.

Here are a few common types:

Inductive generalization : You use observations about a sample to come to a conclusion about the population it came from.
Statistical generalization: You use specific numbers about samples to make statements about populations.
Causal reasoning: You make cause-and-effect links between different things.
Sign reasoning: You make a conclusion about a correlational relationship between different things.
Analogical reasoning: You make a conclusion about something based on its similarities to something else.

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

In inductive research , you start by making observations or gathering data. Then, you take a broad scan of your data and search for patterns. Finally, you make general conclusions that you might incorporate into theories.

Inductive reasoning is a method of drawing conclusions by going from the specific to the general. It’s usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions.

Inductive reasoning is also called inductive logic or bottom-up reasoning.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Triangulation can help:

Reduce research bias that comes from using a single method, theory, or investigator
Enhance validity by approaching the same topic with different tools
Establish credibility by giving you a complete picture of the research problem

But triangulation can also pose problems:

It’s time-consuming and labor-intensive, often involving an interdisciplinary team.
Your results may be inconsistent or even contradictory.

There are four main types of triangulation :

Data triangulation : Using data from different times, spaces, and people
Investigator triangulation : Involving multiple researchers in collecting or analyzing data
Theory triangulation : Using varying theoretical perspectives in your research
Methodological triangulation : Using different methodologies to approach the same topic

Many academic fields use peer review , largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the published manuscript.

However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure.

Peer assessment is often used in the classroom as a pedagogical tool. Both receiving feedback and providing it are thought to enhance the learning process, helping students think critically and collaboratively.

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. It also represents an excellent opportunity to get feedback from renowned experts in your field. It acts as a first defense, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process.

Peer-reviewed articles are considered a highly credible source due to this stringent process they go through before publication.

In general, the peer review process follows the following steps:

First, the author submits the manuscript to the editor.
Reject the manuscript and send it back to author, or
Send it onward to the selected peer reviewer(s)
Next, the peer review process occurs. The reviewer provides feedback, addressing any major or minor issues with the manuscript, and gives their advice regarding what edits should be made.
Lastly, the edited manuscript is sent back to the author. They input the edits, and resubmit it to the editor for publication.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

Explanatory research is used to investigate how or why a phenomenon occurs. Therefore, this type of research is often one of the first stages in the research process , serving as a jumping-off point for future research.

Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.

Explanatory research is a research method used to investigate how or why something occurs when only a small amount of information is available pertaining to that topic. It can help you increase your understanding of a given topic.

Clean data are valid, accurate, complete, consistent, unique, and uniform. Dirty data include inconsistencies and errors.

Dirty data can come from any part of the research process, including poor research design , inappropriate measurement materials, or flawed data entry.

Data cleaning takes place between data collection and data analyses. But you can use some methods even before collecting data.

For clean data, you should start by designing measures that collect valid data. Data validation at the time of data entry or collection helps you minimize the amount of data cleaning you’ll need to do.

After data collection, you can use data standardization and data transformation to clean your data. You’ll also deal with any missing values, outliers, and duplicate values.

Every dataset requires different techniques to clean dirty data , but you need to address these issues in a systematic way. You focus on finding and resolving data points that don’t agree or fit with the rest of your dataset.

These data might be missing values, outliers, duplicate values, incorrectly formatted, or irrelevant. You’ll start with screening and diagnosing your data. Then, you’ll often standardize and accept or remove data to make your dataset consistent and valid.

Data cleaning is necessary for valid and appropriate analyses. Dirty data contain inconsistencies or errors , but cleaning your data helps you minimize or resolve these.

Without data cleaning, you could end up with a Type I or II error in your conclusion. These types of erroneous conclusions can be practically significant with important consequences, because they lead to misplaced investments or missed opportunities.

Data cleaning involves spotting and resolving potential data inconsistencies or errors to improve your data quality. An error is any value (e.g., recorded weight) that doesn’t reflect the true value (e.g., actual weight) of something that’s being measured.

In this process, you review, analyze, detect, modify, or remove “dirty” data to make your dataset “clean.” Data cleaning is also called data cleansing or data scrubbing.

Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. It’s a form of academic fraud.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.

Anonymity means you don’t know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. Both are important ethical considerations .

You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.

You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.

Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.

Scientists and researchers must always adhere to a certain code of conduct when collecting data from others .

These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.

In multistage sampling , you can use probability or non-probability sampling methods .

For a probability sample, you have to conduct probability sampling at every stage.

You can mix it up by using simple random sampling , systematic sampling , or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study.

Multistage sampling can simplify data collection when you have large, geographically spread samples, and you can obtain a probability sample without a complete sampling frame.

But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples .

These are four of the most common mixed methods designs :

Convergent parallel: Quantitative and qualitative data are collected at the same time and analyzed separately. After both analyses are complete, compare your results to draw overall conclusions.
Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.
Explanatory sequential: Quantitative data is collected and analyzed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualize your quantitative findings.
Exploratory sequential: Qualitative data is collected and analyzed first, followed by quantitative data. You can use this design if you think the quantitative data will confirm or validate your qualitative findings.

Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.

Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.

In multistage sampling , or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.

This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings (e.g., from state to city to neighborhood) to create a sample that’s less expensive and time-consuming to collect data from.

No, the steepness or slope of the line isn’t related to the correlation coefficient value. The correlation coefficient only tells you how closely your data fit on a line, so two datasets with the same correlation coefficient can have very different slopes.

To find the slope of the line, you’ll need to perform a regression analysis .

Correlation coefficients always range between -1 and 1.

The sign of the coefficient tells you the direction of the relationship: a positive value means the variables change together in the same direction, while a negative value means they change together in opposite directions.

The absolute value of a number is equal to the number without its sign. The absolute value of a correlation coefficient tells you the magnitude of the correlation: the greater the absolute value, the stronger the correlation.

These are the assumptions your data must meet if you want to use Pearson’s r :

Both variables are on an interval or ratio level of measurement
Data from both variables follow normal distributions
Your data have no outliers
Your data is from a random or representative sample
You expect a linear relationship between the two variables

Quantitative research designs can be divided into two main categories:

Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

The priorities of a research design can vary depending on the field, but you usually have to specify:

Your research questions and/or hypotheses
Your overall approach (e.g., qualitative or quantitative )
The type of design you’re using (e.g., a survey , experiment , or case study )
Your sampling methods or criteria for selecting subjects
Your data collection methods (e.g., questionnaires , observations)
Your data collection procedures (e.g., operationalization , timing and data management)
Your data analysis methods (e.g., statistical tests or thematic analysis )

A research design is a strategy for answering your research question . It defines your overall approach and determines how you will collect and analyze data.

Questionnaires can be self-administered or researcher-administered.

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or through mail. All questions are standardized so that all respondents receive the same questions with identical wording.

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

You can organize the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomization can minimize the bias from order effects.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.

The third variable and directionality problems are two main reasons why correlation isn’t causation .

The third variable problem means that a confounding variable affects both variables to make them seem causally related when they are not.

The directionality problem is when two variables correlate and might actually have a causal relationship, but it’s impossible to conclude which variable causes changes in the other.

Correlation describes an association between variables : when one variable changes, so does the other. A correlation is a statistical indicator of the relationship between variables.

Causation means that changes in one variable brings about changes in the other (i.e., there is a cause-and-effect relationship between variables). The two variables are correlated with each other, and there’s also a causal link between them.

While causation and correlation can exist simultaneously, correlation does not imply causation. In other words, correlation is simply a relationship where A relates to B—but A doesn’t necessarily cause B to happen (or vice versa). Mistaking correlation for causation is a common error and can lead to false cause fallacy .

Controlled experiments establish causality, whereas correlational studies only show associations between variables.

In an experimental design , you manipulate an independent variable and measure its effect on a dependent variable. Other variables are controlled so they can’t impact the results.
In a correlational design , you measure variables without manipulating any of them. You can test whether your variables change together, but you can’t be sure that one variable caused a change in another.

In general, correlational research is high in external validity while experimental research is high in internal validity .

A correlation is usually tested for two variables at a time, but you can test correlations between three or more variables.

A correlation coefficient is a single number that describes the strength and direction of the relationship between your variables.

Different types of correlation coefficients might be appropriate for your data based on their levels of measurement and distributions . The Pearson product-moment correlation coefficient (Pearson’s r ) is commonly used to assess a linear relationship between two quantitative variables.

A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. It’s a non-experimental type of quantitative research .

A correlation reflects the strength and/or direction of the association between two or more variables.

A positive correlation means that both variables change in the same direction.
A negative correlation means that the variables change in opposite directions.
A zero correlation means there’s no relationship between the variables.

Random error is almost always present in scientific studies, even in highly controlled settings. While you can’t eradicate it completely, you can reduce random error by taking repeated measurements, using a large sample, and controlling extraneous variables .

You can avoid systematic error through careful design of your sampling , data collection , and analysis procedures. For example, use triangulation to measure your variables using multiple methods; regularly calibrate instruments or procedures; use random sampling and random assignment ; and apply masking (blinding) where possible.

Systematic error is generally a bigger problem in research.

With random error, multiple measurements will tend to cluster around the true value. When you’re collecting data from a large sample , the errors in different directions will cancel each other out.

Systematic errors are much more problematic because they can skew your data away from the true value. This can lead you to false conclusions ( Type I and II errors ) about the relationship between the variables you’re studying.

Random and systematic error are two types of measurement error.

Random error is a chance difference between the observed and true values of something (e.g., a researcher misreading a weighing scale records an incorrect measurement).

Systematic error is a consistent or proportional difference between the observed and true values of something (e.g., a miscalibrated scale consistently records weights as higher than they actually are).

On graphs, the explanatory variable is conventionally placed on the x-axis, while the response variable is placed on the y-axis.

If you have quantitative variables , use a scatterplot or a line graph.
If your response variable is categorical, use a scatterplot or a line graph.
If your explanatory variable is categorical, use a bar graph.

The term “ explanatory variable ” is sometimes preferred over “ independent variable ” because, in real world contexts, independent variables are often influenced by other variables. This means they aren’t totally independent.

Multiple independent variables may also be correlated with each other, so “explanatory variables” is a more appropriate term.

The difference between explanatory and response variables is simple:

An explanatory variable is the expected cause, and it explains the results.
A response variable is the expected effect, and it responds to other variables.

In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

A control group that receives a standard treatment, a fake treatment, or no treatment.
Random assignment of participants to ensure the groups are equivalent.

Depending on your study topic, there are various other methods of controlling variables .

There are 4 main types of extraneous variables :

Demand characteristics : environmental cues that encourage participants to conform to researchers’ expectations.
Experimenter effects : unintentional actions by researchers that influence study outcomes.
Situational variables : environmental variables that alter participants’ behaviors.
Participant variables : any characteristic or aspect of a participant’s background that could affect study results.

An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study.

A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.

In a factorial design, multiple independent variables are tested.

If you test two variables, each level of one independent variable is combined with each level of the other independent variable to create different conditions.

Within-subjects designs have many potential threats to internal validity , but they are also very statistically powerful .

Advantages:

Only requires small samples
Statistically powerful
Removes the effects of individual differences on the outcomes

Disadvantages:

Internal validity threats reduce the likelihood of establishing a direct relationship between variables
Time-related effects, such as growth, can influence the outcomes
Carryover effects mean that the specific order of different treatments affect the outcomes

While a between-subjects design has fewer threats to internal validity , it also requires more participants for high statistical power than a within-subjects design .

Prevents carryover effects of learning and fatigue.
Shorter study duration.
Needs larger samples for high power.
Uses more resources to recruit participants, administer sessions, cover costs, etc.
Individual differences may be an alternative explanation for results.

Yes. Between-subjects and within-subjects designs can be combined in a single study when you have two or more independent variables (a factorial design). In a mixed factorial design, one variable is altered between subjects and another is altered within subjects.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word “between” means that you’re comparing different conditions between groups, while the word “within” means you’re comparing different conditions within the same group.

Random assignment is used in experiments with a between-groups or independent measures design. In this research design, there’s usually a control group and one or more experimental groups. Random assignment helps ensure that the groups are comparable.

In general, you should always use random assignment in this type of experimental design when it is ethically possible and makes sense for your study topic.

To implement random assignment , assign a unique number to every member of your study’s sample .

Then, you can use a random number generator or a lottery method to randomly assign each number to a control or experimental group. You can also do so manually, by flipping a coin or rolling a dice to randomly assign participants to groups.

Random selection, or random sampling , is a way of selecting members of a population for your study’s sample.

In contrast, random assignment is a way of sorting the sample into control and experimental groups.

Random sampling enhances the external validity or generalizability of your results, while random assignment improves the internal validity of your study.

In experimental research, random assignment is a way of placing participants from your sample into different groups using randomization. With this method, every member of the sample has a known or equal chance of being placed in a control group or an experimental group.

“Controlling for a variable” means measuring extraneous variables and accounting for them statistically to remove their effects on other variables.

Researchers often model control variable data along with independent and dependent variable data in regression analyses and ANCOVAs . That way, you can isolate the control variable’s effects from the relationship between the variables of interest.

Control variables help you establish a correlational or causal relationship between variables by enhancing internal validity .

If you don’t control relevant extraneous variables , they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable .

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

Including mediators and moderators in your research helps you go beyond studying a simple relationship between two variables for a fuller picture of the real world. They are important to consider when studying complex correlational or causal relationships.

Mediators are part of the causal pathway of an effect, and they tell you how or why an effect takes place. Moderators usually help you judge the external validity of your study by identifying the limitations of when the relationship between variables holds.

If something is a mediating variable :

It’s caused by the independent variable .
It influences the dependent variable
When it’s taken into account, the statistical correlation between the independent and dependent variables is higher than when it isn’t considered.

A confounder is a third variable that affects variables of interest and makes them seem related when they are not. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

There are three key steps in systematic sampling :

Define and list your population , ensuring that it is not ordered in a cyclical or periodic order.
Decide on your sample size and calculate your interval, k , by dividing your population by your target sample size.
Choose every k th member of the population as your sample.

Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval – for example, by selecting every 15th person on a list of the population. If the population is in a random order, this can imitate the benefits of simple random sampling .

Yes, you can create a stratified sample using multiple characteristics, but you must ensure that every participant in your study belongs to one and only one subgroup. In this case, you multiply the numbers of subgroups for each characteristic to get the total number of groups.

For example, if you were stratifying by location with three subgroups (urban, rural, or suburban) and marital status with five subgroups (single, divorced, widowed, married, or partnered), you would have 3 x 5 = 15 subgroups.

You should use stratified sampling when your sample can be divided into mutually exclusive and exhaustive subgroups that you believe will take on different mean values for the variable that you’re studying.

Using stratified sampling will allow you to obtain more precise (with lower variance ) statistical estimates of whatever you are trying to measure.

For example, say you want to investigate how income differs based on educational attainment, but you know that this relationship can vary based on race. Using stratified sampling, you can ensure you obtain a large enough sample from each racial group, allowing you to draw more precise conclusions.

In stratified sampling , researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment).

Once divided, each subgroup is randomly sampled using another probability sampling method.

Cluster sampling is more time- and cost-efficient than other probability sampling methods , particularly when it comes to large samples spread across a wide geographical area.

However, it provides less statistical certainty than other methods, such as simple random sampling , because it is difficult to ensure that your clusters properly represent the population as a whole.

There are three types of cluster sampling : single-stage, double-stage and multi-stage clustering. In all three types, you first divide the population into clusters, then randomly select clusters for use in your sample.

In single-stage sampling , you collect data from every unit within the selected clusters.
In double-stage sampling , you select a random sample of units from within the clusters.
In multi-stage sampling , you repeat the procedure of randomly sampling elements from within the clusters until you have reached a manageable sample.

Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.

The clusters should ideally each be mini-representations of the population as a whole.

If properly implemented, simple random sampling is usually the best sampling method for ensuring both internal and external validity . However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied,

If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.

The American Community Survey is an example of simple random sampling . In order to collect detailed data on the population of the US, the Census Bureau officials randomly select 3.5 million households per year and use a variety of methods to convince them to fill out the survey.

Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population . Each member of the population has an equal chance of being selected. Data is then collected from as large a percentage as possible of this random subset.

Quasi-experimental design is most useful in situations where it would be unethical or impractical to run a true experiment .

Quasi-experiments have lower internal validity than true experiments, but they often have higher external validity as they can use real-world interventions instead of artificial laboratory settings.

A quasi-experiment is a type of research design that attempts to establish a cause-and-effect relationship. The main difference with a true experiment is that the groups are not randomly assigned.

Blinding is important to reduce research bias (e.g., observer bias , demand characteristics ) and ensure a study’s internal validity .

If participants know whether they are in a control or treatment group , they may adjust their behavior in ways that affect the outcome that researchers are trying to measure. If the people administering the treatment are aware of group assignment, they may treat participants differently and thus directly or indirectly influence the final results.

In a single-blind study , only the participants are blinded.
In a double-blind study , both participants and experimenters are blinded.
In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analyzing the data.

Blinding means hiding who is assigned to the treatment group and who is assigned to the control group in an experiment .

A true experiment (a.k.a. a controlled experiment) always includes at least one control group that doesn’t receive the experimental treatment.

However, some experiments use a within-subjects design to test treatments without a control group. In these designs, you usually compare one group’s outcomes before and after a treatment (instead of comparing outcomes between different groups).

For strong internal validity , it’s usually best to include a control group if possible. Without a control group, it’s harder to be certain that the outcome was caused by the experimental treatment and not by other variables.

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyze your data.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with 5 or 7 possible responses, to capture their degree of agreement.

In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports).

The process of turning abstract concepts into measurable variables and indicators is called operationalization .

There are various approaches to qualitative data analysis , but they all share five steps in common:

Prepare and organize your data.
Review and explore your data.
Develop a data coding system.
Assign codes to the data.
Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

There are five common approaches to qualitative research :

Grounded theory involves collecting data in order to develop new theories.
Ethnography involves immersing yourself in a group or organization to understand its culture.
Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
Phenomenological research involves investigating phenomena through people’s lived experiences.
Action research links theory and practice in several cycles to drive innovative changes.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

When conducting research, collecting original data has significant advantages:

You can tailor data collection to your specific research aims (e.g. understanding the needs of your consumers or user testing your website)
You can control and standardize the process for high reliability and validity (e.g. choosing appropriate measurements and sampling methods )

However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomization , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

To ensure the internal validity of your research, you must consider the impact of confounding variables. If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variables , or even find a causal relationship where none exists.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both!

You want to find out how blood sugar levels are affected by drinking diet soda and regular soda, so you conduct an experiment .

The type of soda – diet or regular – is the independent variable .
The level of blood sugar that you measure is the dependent variable – it changes depending on the type of soda.

Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

In non-probability sampling , the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.

Common non-probability sampling methods include convenience sampling , voluntary response sampling, purposive sampling , snowball sampling, and quota sampling .

Probability sampling means that every member of the target population has a known chance of being included in the sample.

Probability sampling methods include simple random sampling , systematic sampling , stratified sampling , and cluster sampling .

Using careful research design and sampling procedures can help you avoid sampling bias . Oversampling can be used to correct undercoverage bias .

Some common types of sampling bias include self-selection bias , nonresponse bias , undercoverage bias , survivorship bias , pre-screening or advertising bias, and healthy user bias.

Sampling bias is a threat to external validity – it limits the generalizability of your findings to a broader group of people.

A sampling error is the difference between a population parameter and a sample statistic .

A statistic refers to measures about the sample , while a parameter refers to measures about the population .

Populations are used when a research question requires data from every member of the population. This is usually only feasible when the population is small and easily accessible.

Samples are used to make inferences about populations . Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable.

There are seven threats to external validity : selection bias , history, experimenter effect, Hawthorne effect , testing effect, aptitude-treatment and situation effect.

The two types of external validity are population validity (whether you can generalize to other groups of people) and ecological validity (whether you can generalize to other situations and settings).

The external validity of a study is the extent to which you can generalize your findings to different groups of people, situations, and measures.

Cross-sectional studies cannot establish a cause-and-effect relationship or analyze behavior over a period of time. To investigate cause and effect, you need to do a longitudinal study or an experimental study .

Cross-sectional studies are less expensive and time-consuming than many other types of study. They can provide useful insights into a population’s characteristics and identify correlations for further research.

Sometimes only cross-sectional data is available for analysis; other times your research question may only require a cross-sectional study to answer it.

Longitudinal studies can last anywhere from weeks to decades, although they tend to be at least a year long.

The 1970 British Cohort Study , which has collected data on the lives of 17,000 Brits since their births in 1970, is one well-known example of a longitudinal study .

Longitudinal studies are better to establish the correct sequence of events, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies.

Longitudinal studies and cross-sectional studies are two different types of research design . In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time.

There are eight threats to internal validity : history, maturation, instrumentation, testing, selection bias , regression to the mean, social interaction and attrition .

Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

Discrete and continuous variables are two types of quantitative variables :

Discrete variables represent counts (e.g. the number of objects in a collection).
Continuous variables represent measurable amounts (e.g. water volume or weight).

Quantitative variables are any variables where the data represent amounts (e.g. height, weight, or age).

Categorical variables are any variables where the data represent groups. This includes rankings (e.g. finishing places in a race), classifications (e.g. brands of cereal), and binary outcomes (e.g. coin flips).

You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results .

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause , while a dependent variable is the effect .

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

The independent variable is the amount of nutrients added to the crop field.
The dependent variable is the biomass of the crops at harvest time.

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design .

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

A testable hypothesis
At least one independent variable that can be precisely manipulated
At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

How you will manipulate the variable(s)
How you will control for any potential confounding variables
How many subjects or samples will be included in the study
How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

I nternal validity is the degree of confidence that the causal relationship you are testing is not influenced by other factors or variables .

External validity is the extent to which your results can be generalized to other contexts.

The validity of your experiment depends on your experimental design .

Reliability and validity are both about how well a method measures something:

Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions).
Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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SOC101: Introduction to Sociology (2020.A.01)

What is ethics in research and why is it important.

Read the article on the importance of ethics in research.

The ideas and opinions expressed in this essay are the author's own and do not necessarily represent those of the NIH, NIEHS, or US government.

When most people think of ethics (or morals), they think of rules for distinguishing between right and wrong, such as the Golden Rule ("Do unto others as you would have them do unto you"), a code of professional conduct like the Hippocratic Oath ("First of all, do no harm"), a religious creed like the Ten Commandments ("Thou Shalt not kill..."), or a wise aphorisms like the sayings of Confucius. This is the most common way of defining "ethics": norms for conduct that distinguish between acceptable and unacceptable behavior. Most people learn ethical norms at home, at school, in church, or in other social settings. Although most people acquire their sense of right and wrong during childhood, moral development occurs throughout life and human beings pass through different stages of growth as they mature. Ethical norms are so ubiquitous that one might be tempted to regard them as simple commonsense. On the other hand, if morality were nothing more than commonsense, then why are there so many ethical disputes and issues in our society? One plausible explanation of these disagreements is that all people recognize some common ethical norms but interpret, apply, and balance them in different ways in light of their own values and life experiences. For example, two people could agree that murder is wrong but disagree about the morality of abortion because they have different understandings of what it means to be a human being. Most societies also have legal rules that govern behavior, but ethical norms tend to be broader and more informal than laws. Although most societies use laws to enforce widely accepted moral standards and ethical and legal rules use similar concepts, ethics and law are not the same. An action may be legal but unethical or illegal but ethical. We can also use ethical concepts and principles to criticize, evaluate, propose, or interpret laws. Indeed, in the last century, many social reformers have urged citizens to disobey laws they regarded as immoral or unjust laws. Peaceful civil disobedience is an ethical way of protesting laws or expressing political viewpoints. Another way of defining 'ethics' focuses on the disciplines that study standards of conduct, such as philosophy, theology, law, psychology, or sociology. For example, a "medical ethicist" is someone who studies ethical standards in medicine. One may also define ethics as a method, procedure, or perspective for deciding how to act and for analyzing complex problems and issues. For instance, in considering a complex issue like global warming, one may take an economic, ecological, political, or ethical perspective on the problem. While an economist might examine the cost and benefits of various policies related to global warming, an environmental ethicist could examine the ethical values and principles at stake. Many different disciplines, institutions, and professions have standards for behavior that suit their particular aims and goals. These standards also help members of the discipline to coordinate their actions or activities and to establish the public's trust of the discipline. For instance, ethical standards govern conduct in medicine, law, engineering, and business. Ethical norms also serve the aims or goals of research and apply to people who conduct scientific research or other scholarly or creative activities. There is even a specialized discipline, research ethics, which studies these norms. See Glossary of Commonly Used Terms in Research Ethics. There are several reasons why it is important to adhere to ethical norms in research. First, norms promote the aims of research, such as knowledge, truth, and avoidance of error. For example, prohibitions against fabricating, falsifying, or misrepresenting research data promote the truth and minimize error. Second, since research often involves a great deal of cooperation and coordination among many different people in different disciplines and institutions, ethical standards promote the values that are essential to collaborative work , such as trust, accountability, mutual respect, and fairness. For example, many ethical norms in research, such as guidelines for authorship, copyright and patenting policies, data sharing policies, and confidentiality rules in peer review, are designed to protect intellectual property interests while encouraging collaboration. Most researchers want to receive credit for their contributions and do not want to have their ideas stolen or disclosed prematurely. Third, many of the ethical norms help to ensure that researchers can be held accountable to the public . For instance, federal policies on research misconduct, conflicts of interest, the human subjects protections, and animal care and use are necessary in order to make sure that researchers who are funded by public money can be held accountable to the public. Fourth, ethical norms in research also help to build public support for research. People are more likely to fund a research project if they can trust the quality and integrity of research. Finally, many of the norms of research promote a variety of other important moral and social values , such as social responsibility, human rights, animal welfare, compliance with the law, and public health and safety. Ethical lapses in research can significantly harm human and animal subjects, students, and the public. For example, a researcher who fabricates data in a clinical trial may harm or even kill patients, and a researcher who fails to abide by regulations and guidelines relating to radiation or biological safety may jeopardize his health and safety or the health and safety of staff and students.

Codes and Policies for Research Ethics

Given the importance of ethics for the conduct of research, it should come as no surprise that many different professional associations, government agencies, and universities have adopted specific codes, rules, and policies relating to research ethics. Many government agencies have ethics rules for funded researchers.

National Institutes of Health (NIH)
National Science Foundation (NSF)
Food and Drug Administration (FDA)
Environmental Protection Agency (EPA)
US Department of Agriculture (USDA)
Singapore Statement on Research Integrity
American Chemical Society, The Chemist Professional's Code of Conduct
Code of Ethics (American Society for Clinical Laboratory Science)
American Psychological Association, Ethical Principles of Psychologists and Code of Conduct
Statement on Professional Ethics (American Association of University Professors)
Nuremberg Code
World Medical Association's Declaration of Helsinki

Ethical Principles

The following is a rough and general summary of some ethical principles that various codes address*:

Strive for honesty in all scientific communications. Honestly report data, results, methods and procedures, and publication status. Do not fabricate, falsify, or misrepresent data. Do not deceive colleagues, research sponsors, or the public.

Objectivity

Strive to avoid bias in experimental design, data analysis, data interpretation, peer review, personnel decisions, grant writing, expert testimony, and other aspects of research where objectivity is expected or required. Avoid or minimize bias or self-deception. Disclose personal or financial interests that may affect research.

Keep your promises and agreements; act with sincerity; strive for consistency of thought and action.

Carefulness

Avoid careless errors and negligence; carefully and critically examine your own work and the work of your peers. Keep good records of research activities, such as data collection, research design, and correspondence with agencies or journals.

Share data, results, ideas, tools, resources. Be open to criticism and new ideas.

Transparency

Disclose methods, materials, assumptions, analyses, and other information needed to evaluate your research.

Accountability

Take responsibility for your part in research and be prepared to give an account (i.e. an explanation or justification) of what you did on a research project and why.

Intellectual Property

Honor patents, copyrights, and other forms of intellectual property. Do not use unpublished data, methods, or results without permission. Give proper acknowledgement or credit for all contributions to research. Never plagiarize.

Confidentiality

Protect confidential communications, such as papers or grants submitted for publication, personnel records, trade or military secrets, and patient records.

Responsible Publication

Publish in order to advance research and scholarship, not to advance just your own career. Avoid wasteful and duplicative publication.

Responsible Mentoring

Help to educate, mentor, and advise students. Promote their welfare and allow them to make their own decisions.

Respect for Colleagues

Respect your colleagues and treat them fairly.

Social Responsibility

Strive to promote social good and prevent or mitigate social harms through research, public education, and advocacy.

Non-Discrimination

Avoid discrimination against colleagues or students on the basis of sex, race, ethnicity, or other factors not related to scientific competence and integrity.

Maintain and improve your own professional competence and expertise through lifelong education and learning; take steps to promote competence in science as a whole.

Know and obey relevant laws and institutional and governmental policies.

Animal Care

Show proper respect and care for animals when using them in research. Do not conduct unnecessary or poorly designed animal experiments.

Human Subjects protection

When conducting research on human subjects, minimize harms and risks and maximize benefits; respect human dignity, privacy, and autonomy; take special precautions with vulnerable populations; and strive to distribute the benefits and burdens of research fairly.

Ethical Decision Making in Research

Although codes, policies, and principles are very important and useful, like any set of rules, they do not cover every situation, they often conflict, and they require considerable interpretation. It is therefore important for researchers to learn how to interpret, assess, and apply various research rules and how to make decisions and to act ethically in various situations. The vast majority of decisions involve the straightforward application of ethical rules. For example, consider the following case,

The research protocol for a study of a drug on hypertension requires the administration of the drug at different doses to 50 laboratory mice, with chemical and behavioral tests to determine toxic effects. Tom has almost finished the experiment for Dr. Q. He has only 5 mice left to test. However, he really wants to finish his work in time to go to Florida on spring break with his friends, who are leaving tonight. He has injected the drug in all 50 mice but has not completed all of the tests. He therefore decides to extrapolate from the 45 completed results to produce the 5 additional results. Many different research ethics policies would hold that Tom has acted unethically by fabricating data. If this study were sponsored by a federal agency, such as the NIH, his actions would constitute a form of research misconduct, which the government defines as "fabrication, falsification, or plagiarism" (or FFP). Actions that nearly all researchers classify as unethical are viewed as misconduct. It is important to remember, however, that misconduct occurs only when researchers intend to deceive : honest errors related to sloppiness, poor record keeping, miscalculations, bias, self-deception, and even negligence do not constitute misconduct. Also, reasonable disagreements about research methods, procedures, and interpretations do not constitute research misconduct. Consider the following case:

Dr. T has just discovered a mathematical error in his paper that has been accepted for publication in a journal. The error does not affect the overall results of his research, but it is potentially misleading. The journal has just gone to press, so it is too late to catch the error before it appears in print. In order to avoid embarrassment, Dr. T decides to ignore the error. Dr. T's error is not misconduct nor is his decision to take no action to correct the error. Most researchers, as well as many different policies and codes would say that Dr. T should tell the journal (and any coauthors) about the error and consider publishing a correction or errata. Failing to publish a correction would be unethical because it would violate norms relating to honesty and objectivity in research. There are many other activities that the government does not define as "misconduct" but which are still regarded by most researchers as unethical. These are sometimes referred to as "other deviations" from acceptable research practices and include:

Publishing the same paper in two different journals without telling the editors
Submitting the same paper to different journals without telling the editors
Not informing a collaborator of your intent to file a patent in order to make sure that you are the sole inventor
Including a colleague as an author on a paper in return for a favor even though the colleague did not make a serious contribution to the paper
Discussing with your colleagues confidential data from a paper that you are reviewing for a journal
Using data, ideas, or methods you learn about while reviewing a grant or a papers without permission
Trimming outliers from a data set without discussing your reasons in paper
Using an inappropriate statistical technique in order to enhance the significance of your research
Bypassing the peer review process and announcing your results through a press conference without giving peers adequate information to review your work
Conducting a review of the literature that fails to acknowledge the contributions of other people in the field or relevant prior work
Stretching the truth on a grant application in order to convince reviewers that your project will make a significant contribution to the field
Stretching the truth on a job application or curriculum vita
Giving the same research project to two graduate students in order to see who can do it the fastest
Overworking, neglecting, or exploiting graduate or post-doctoral students
Failing to keep good research records
Failing to maintain research data for a reasonable period of time
Making derogatory comments and personal attacks in your review of author's submission
Promising a student a better grade for sexual favors
Using a racist epithet in the laboratory
Making significant deviations from the research protocol approved by your institution's Animal Care and Use Committee or Institutional Review Board for Human Subjects Research without telling the committee or the board
Not reporting an adverse event in a human research experiment
Wasting animals in research
Exposing students and staff to biological risks in violation of your institution's biosafety rules
Sabotaging someone's work
Stealing supplies, books, or data
Rigging an experiment so you know how it will turn out
Making unauthorized copies of data, papers, or computer programs
Owning over $10,000 in stock in a company that sponsors your research and not disclosing this financial interest
Deliberately overestimating the clinical significance of a new drug in order to obtain economic benefits

These actions would be regarded as unethical by most scientists and some might even be illegal in some cases. Most of these would also violate different professional ethics codes or institutional policies. However, they do not fall into the narrow category of actions that the government classifies as research misconduct. Indeed, there has been considerable debate about the definition of "research misconduct" and many researchers and policy makers are not satisfied with the government's narrow definition that focuses on FFP. However, given the huge list of potential offenses that might fall into the category "other serious deviations," and the practical problems with defining and policing these other deviations, it is understandable why government officials have chosen to limit their focus. Finally, situations frequently arise in research in which different people disagree about the proper course of action and there is no broad consensus about what should be done. In these situations, there may be good arguments on both sides of the issue and different ethical principles may conflict. These situations create difficult decisions for research known as ethical or moral dilemmas. Consider the following case:

Dr. Wexford is the principal investigator of a large, epidemiological study on the health of 10,000 agricultural workers. She has an impressive dataset that includes information on demographics, environmental exposures, diet, genetics, and various disease outcomes such as cancer, Parkinson's disease (PD), and ALS. She has just published a paper on the relationship between pesticide exposure and PD in a prestigious journal. She is planning to publish many other papers from her dataset. She receives a request from another research team that wants access to her complete dataset. They are interested in examining the relationship between pesticide exposures and skin cancer. Dr. Wexford was planning to conduct a study on this topic. Dr. Wexford faces a difficult choice. On the one hand, the ethical norm of openness obliges her to share data with the other research team. Her funding agency may also have rules that obligate her to share data. On the other hand, if she shares data with the other team, they may publish results that she was planning to publish, thus depriving her (and her team) of recognition and priority. It seems that there are good arguments on both sides of this issue and Dr. Wexford needs to take some time to think about what she should do. One possible option is to share data, provided that the investigators sign a data use agreement. The agreement could define allowable uses of the data, publication plans, authorship, etc. Another option would be to offer to collaborate with the researchers. The following are some step that researchers, such as Dr. Wexford, can take to deal with ethical dilemmas in research:

What is the problem or issue? It is always important to get a clear statement of the problem. In this case, the issue is whether to share information with the other research team.

What is the relevant information? Many bad decisions are made as a result of poor information. To know what to do, Dr. Wexford needs to have more information concerning such matters as university or funding agency or journal policies that may apply to this situation, the team's intellectual property interests, the possibility of negotiating some kind of agreement with the other team, whether the other team also has some information it is willing to share, the impact of the potential publications, etc.

What are the different options? People may fail to see different options due to a limited imagination, bias, ignorance, or fear. In this case, there may be other choices besides 'share' or 'don't share,' such as 'negotiate an agreement' or 'offer to collaborate with the researchers.' How do ethical codes or policies as well as legal rules apply to these different options? The university or funding agency may have policies on data management that apply to this case. Broader ethical rules, such as openness and respect for credit and intellectual property, may also apply to this case. Laws relating to intellectual property may be relevant.

Are there any people who can offer ethical advice? It may be useful to seek advice from a colleague, a senior researcher, your department chair, an ethics or compliance officer, or anyone else you can trust. In the case, Dr. Wexford might want to talk to her supervisor and research team before making a decision. After considering these questions, a person facing an ethical dilemma may decide to ask more questions, gather more information, explore different options, or consider other ethical rules. However, at some point he or she will have to make a decision and then take action. Ideally, a person who makes a decision in an ethical dilemma should be able to justify his or her decision to himself or herself, as well as colleagues, administrators, and other people who might be affected by the decision. He or she should be able to articulate reasons for his or her conduct and should consider the following questions in order to explain how he or she arrived at his or her decision: .

Which choice will probably have the best overall consequences for science and society?
Which choice could stand up to further publicity and scrutiny?
Which choice could you not live with?
Think of the wisest person you know. What would he or she do in this situation?
Which choice would be the most just, fair, or responsible?

After considering all of these questions, one still might find it difficult to decide what to do. If this is the case, then it may be appropriate to consider others ways of making the decision, such as going with a gut feeling or intuition, seeking guidance through prayer or meditation, or even flipping a coin. Endorsing these methods in this context need not imply that ethical decisions are irrational, however. The main point is that human reasoning plays a pivotal role in ethical decision-making but there are limits to its ability to solve all ethical dilemmas in a finite amount of time.

Promoting Ethical Conduct in Science

Most academic institutions in the US require undergraduate, graduate, or postgraduate students to have some education in the responsible conduct of research (RCR). The NIH and NSF have both mandated training in research ethics for students and trainees. Many academic institutions outside of the US have also developed educational curricula in research ethics Those of you who are taking or have taken courses in research ethics may be wondering why you are required to have education in research ethics. You may believe that you are highly ethical and know the difference between right and wrong. You would never fabricate or falsify data or plagiarize. Indeed, you also may believe that most of your colleagues are highly ethical and that there is no ethics problem in research.. If you feel this way, relax. No one is accusing you of acting unethically. Indeed, the evidence produced so far shows that misconduct is a very rare occurrence in research, although there is considerable variation among various estimates. The rate of misconduct has been estimated to be as low as 0.01% of researchers per year (based on confirmed cases of misconduct in federally funded research) to as high as 1% of researchers per year (based on self-reports of misconduct on anonymous surveys).

Clearly, it would be useful to have more data on this topic, but so far there is no evidence that science has become ethically corrupt, despite some highly publicized scandals. Even if misconduct is only a rare occurrence, it can still have a tremendous impact on science and society because it can compromise the integrity of research, erode the public's trust in science, and waste time and resources. Will education in research ethics help reduce the rate of misconduct in science? It is too early to tell. The answer to this question depends, in part, on how one understands the causes of misconduct. There are two main theories about why researchers commit misconduct. According to the "bad apple" theory, most scientists are highly ethical. Only researchers who are morally corrupt, economically desperate, or psychologically disturbed commit misconduct. Moreover, only a fool would commit misconduct because science's peer review system and self-correcting mechanisms will eventually catch those who try to cheat the system. In any case, a course in research ethics will have little impact on "bad apples," one might argue. According to the "stressful" or "imperfect" environment theory, misconduct occurs because various institutional pressures, incentives, and constraints encourage people to commit misconduct, such as pressures to publish or obtain grants or contracts, career ambitions, the pursuit of profit or fame, poor supervision of students and trainees, and poor oversight of researchers. Moreover, defenders of the stressful environment theory point out that science's peer review system is far from perfect and that it is relatively easy to cheat the system. Erroneous or fraudulent research often enters the public record without being detected for years. Misconduct probably results from environmental and individual causes, i.e. when people who are morally weak, ignorant, or insensitive are placed in stressful or imperfect environments. In any case, a course in research ethics can be useful in helping to prevent deviations from norms even if it does not prevent misconduct. Education in research ethics is can help people get a better understanding of ethical standards, policies, and issues and improve ethical judgment and decision making. Many of the deviations that occur in research may occur because researchers simply do not know or have never thought seriously about some of the ethical norms of research. For example, some unethical authorship practices probably reflect traditions and practices that have not been questioned seriously until recently. If the director of a lab is named as an author on every paper that comes from his lab, even if he does not make a significant contribution, what could be wrong with that? That's just the way it's done, one might argue. Another example where there may be some ignorance or mistaken traditions is conflicts of interest in research. A researcher may think that a "normal" or "traditional" financial relationship, such as accepting stock or a consulting fee from a drug company that sponsors her research, raises no serious ethical issues. Or perhaps a university administrator sees no ethical problem in taking a large gift with strings attached from a pharmaceutical company. Maybe a physician thinks that it is perfectly appropriate to receive a $300 finder's fee for referring patients into a clinical trial. If "deviations" from ethical conduct occur in research as a result of ignorance or a failure to reflect critically on problematic traditions, then a course in research ethics may help reduce the rate of serious deviations by improving the researcher's understanding of ethics and by sensitizing him or her to the issues. Finally, education in research ethics should be able to help researchers grapple with the ethical dilemmas they are likely to encounter by introducing them to important concepts, tools, principles, and methods that can be useful in resolving these dilemmas. Scientists must deal with a number of different controversial topics, such as human embryonic stem cell research, cloning, genetic engineering, and research involving animal or human subjects, which require ethical reflection and deliberation.

Practical Ethics

Oxford Uehiro Prize in Practical Ethics: The Moral Importance of Low Welfare Species

March 26, 2024 March 26, 2024

This essay was the winner of the Graduate category of the 10th National Oxford Uehiro Prize in Practical Ethics 2024. Written by Jakob Lohmar.

Many people believe that we sometimes ought to produce one larger benefit rather than any number of smaller benefits. For example, many believe that in a choice between saving a human life and alleviating headaches, one always ought to prioritize the life, no matter the number of headaches. [1] Call the benefits that (no matter their number) cannot outweigh the saving of one human life “minor benefits” and the wellbeing differences that minor benefits amount to “minor wellbeing differences”. Now consider a hypothetical species with a wellbeing (or “welfare”) range that is as large as such a minor wellbeing difference. That is, the difference between the maximum and minimum level of wellbeing that members of that species can (under any realistic circumstances) achieve equals a minor wellbeing difference. [2] Call species with such minor welfare ranges “low welfare species”. The question that I will discuss in this essay is whether benefits for low welfare species can in principle outweigh even the most significant benefits for humans. Using the saving of a human life as a proxy for the most significant benefit for humans, we can state this question more precisely as follows: Is there any number N and benefit B such that one ought to confer benefit B to N members of a low welfare species rather than save one human life?

The question is not just of theoretical interest. There are many actual species that presumably have welfare ranges that correspond to what we tend to think of as minor wellbeing differences (in the stipulated sense). If they have any welfare at all, invertebrates, small mammals, and many fish, reptiles and birds may well be low welfare species. [3] An answer to my question would accordingly tell us whether benefits for many actual species could in principle outweigh even the largest benefits for humans. This would not be practically relevant if we could help humans more effectively than animals anyway, so that even if benefits for low welfare species could in principle outweigh all benefits for humans, we should prioritize humans under the actual circumstances. But it seems that we can in fact help animals very effectively. That goes in particular for animals in factory farms whose living conditions we could greatly improve. But also the unmeasurable suffering of wild animals provides an opportunity for us to potentially do a lot of good. [4] If benefits for low welfare species could in principle outweigh all benefits for humans, it may well be, therefore, that they (sometimes) actually do outweigh the largest benefits for humans.

Here is a straightforward argument for a negative answer to my question. The welfare range of an individual’s species restricts by how much individuals of that species could be benefited: increasing their wellbeing from the minimum to the maximum wellbeing level of that species is the most that could be done for them. The welfare range of a low welfare species is, by definition, as large as the wellbeing difference that a minor benefit amounts to. Hence, the most significant benefit to individuals of a low welfare species is no larger than a minor benefit. By definition, no number of minor benefits can outweigh one human life. If no number of a certain benefit can outweigh one human life, no number of an equally (or less) large benefit can outweigh a human life either. Thus, no number of even the most significant benefit to members of low welfare species can outweigh one human life.

One way of resisting the argument is to reject the implicit assumption that there are any minor benefits in the stipulated sense: perhaps all benefits can, if numerous enough, outweigh a human life. [5] This is a possibility that should be taken seriously. However, as alluded to in the beginning, such unrestricted aggregation has counterintuitive implications that many find unacceptable. Let us therefore assume, for the sake of the argument, that there are indeed minor benefits no number of which can outweigh one human life. Is the argument sound under that assumption? I think that it is not. We should reject the premise that if no number of a certain benefit can outweigh one human life, no number of an equally (or less) large benefit can outweigh a human life either. The more general principle that motivates this premise is that the comparative magnitudes of benefits determine whether they can be traded off against each other: the smaller benefit can outweigh the larger benefit iff its magnitude is sufficiently close to the magnitude of the larger benefit. This principle, which I will refer to as “Compare Absolute Magnitudes”, has some plausibility. It can explain why headaches can outweigh slightly stronger headaches but not human lives, and why human lives can be outweighed by cases of constant paralysis. However, while the principle gives us the right results in common intra-species comparisons, it fails in cases of inter-species comparisons.

To see this, consider a hypothetical “high welfare species” with a welfare range that is much larger than the welfare range of humans. Perhaps individuals of that species live much longer or are able to experience much more intensely than humans, for example. Assume that we could increase the wellbeing of one individual of that species from a neutral level to the maximum wellbeing level of that species by saving that individual’s life. This seems to be a morally weighty consideration, but it also seems that the greatest goods for humans are still an important moral factor that can be morally decisive. According to Compare Absolute Magnitudes, however, there is no number of any benefits for humans such that one ought to prioritize them, given that the maximum wellbeing level of the high welfare species is high enough. This seems to be the wrong result. Surely, for example, there is some number of human lives such that we should save them rather than the one individual of the high welfare species.

Compare Absolute Magnitudes should be rejected, then. But perhaps there are other (related) principles that don’t share this problem but equally suggest that we ought to prioritize a single human life over any number of any benefits for individuals of low welfare species? In what follows, I will present two arguments that we should reject all such principles. These arguments will also illuminate why it seems wrong to prioritize some benefits for members of high welfare species over any number of any benefits to humans.

The first argument is based on the value of fairness . As far as this value is concerned, it seems plausible that we should give the welfare of members of low welfare species special consideration to compensate for their low natural capacity for welfare. At the least, we should give their welfare considerable weight. There are different reasonable explications of what considerable weight amounts to here. On no reasonable explication, however, would we give their welfare considerable weight if we followed a principle according to which no number of even the largest benefits attainable to them can outweigh a single instance of some human goods, such as one human life. In a world like ours in which we could virtually always use our resources to save human lives with statistical certainty (e.g. by donating to effective charities), this would mean that we should never prioritize them, even if we could help them incredibly effectively. This would be an extreme form of discrimination that is incompatible with any plausible notion of fairness. [6]

The second argument can be considered an argument from empathy . Unlike the argument from fairness, this argument is not based on an inter-species welfare comparison but focuses on the perspective of members of the species with the smaller welfare range. [7] The point is that from their perspective the largest goods attainable to them are significant even if they are much smaller than the goods that are attainable to us. Perhaps, for example, the joy that they can experience is much less intense or much shorter than the joy that we are able to experience. Still, if that is the most joy that they can experience, experiencing it would constitute a highlight in their lives that is worth aspiring to. Or take their lives: from our perspective they may seem insignificant because they have, for example, only a tiny fraction of the length of our lives. But for them, their lives are all that they have, and preventing their lives from being cut short is a worthy goal. None of that is to say that their capacity for welfare is not in fact much lower than our capacity for welfare, or that this difference is morally irrelevant. However, this change in perspective is supposed to show that the goods to low welfare species can have a significance that makes it inappropriate to consider them irrelevant whenever important goods for us are at stake. It would be arrogant and perhaps disrespectful not to count their largest goods at all whenever our largest goods are at stake.

I have argued that we should reject any principle that asks us to prioritize a single human life over any number of any benefits to members of low welfare species. How should we decide, then, in which cases some number of benefits of one kind can outweigh benefits of another kind? Establishing such a principle is beyond the scope of this paper, but I will (tentatively) argue for some features of an acceptable principle that the previous arguments suggest. It seems that instead of comparing the absolute magnitudes of benefits we should compare, at least among others, the magnitudes of benefits relative to some factor that correlates with the welfare range of the respective species. Which factor? The most obvious choice is the species’ welfare range itself. However, I think it is clear that species’ welfare ranges only derivatively matter. At least, they matter only insofar as they correlate with the individual’s welfare range. This correlation is usually strong, but an individual’s welfare range can also significantly come apart from the welfare range of its species, as in the case of some chronic diseases. Benefits to such individuals should not be considered irrelevant merely because they are small relative to the species’ welfare range. It could be suggested, furthermore, that individuals’ welfare ranges only matter insofar as they correlate with the individual’s actual welfare. [8] Whether this suggestion is correct is unobvious to me. It is plausible that the actual welfare of an individual matters, but questionable if an individual’s capacity for welfare (as represented by its welfare range) does not also matter independently.

Whatever the exact factor is relative to which the magnitude of benefits should be measured, I think that a principle on which we should compare such relative magnitudes is promising. Such a principle (“Compare Relative Magnitudes”) would give us the same plausible results as Compare Absolute Magnitudes for common intra-species comparisons since the relational factor has in these cases (per common assumption) the same value for all benefits and therefore cancels out. At the same time, Compare Relative Magnitudes can avoid the problems discussed above for Compare Absolute Magnitudes arising in inter-species comparisons. By comparing relative magnitudes of benefits, it does not discriminate against species with small welfare ranges and does justice to the perspective of members of low welfare species. Most importantly, Compare Relative Magnitudes can explain why the largest attainable benefits for a species, whether for humans or a low welfare species, are always relevant: these benefits have the largest possible relative magnitude.

Since principles that prioritize a single human life over any number of any benefits for members of low welfare species face severe problems, and there is a promising (type of) principle that can explain why some benefits for members of low welfare species are relevant even when human lives are at stake, I conclude that some benefits for low welfare species can in principle outweigh even the most significant benefits for humans.

Dorsey, Dale (2009), “Headaches, Lives and Value”, Utilitas , 21(1): 36-58.

Horta, Oscar & Dayron Teran (2023), “Reducing Wild Animal Suffering Effectively”, Ethics, Policy and Environment 26(2): 217-230.

Horton, Joe (2018), “Always aggregate”, Philosophy & Public Affairs 46.2: 160-174.

Kamm, Francis (2013), “Nonconsequentialism”, In H. LaFollette (Ed.), The Blackwell guide to ethical theory . Oxford: Blackwell Publishing.

Kamm, Francis (2015), “Cost effectiveness analysis and fairness”, Journal of Practical Ethics 3 (1).

Norcross, Alastair (1997), “Comparing Harms: Headaches and Human Lives”, Philosophy & Public Affairs , 26(2): 135-67.

Fischer, Bob (2023), „Rethink Priorities’ Welfare Range Estimates”, URL: https://rethinkpriorities.org/publications/welfare-range-estimates.

Scanlon, T. M. (1998), What We Owe to Each Other , Cambridge, MA: Belknap Press of Harvard University Press.

Voorhoeve, Alex (2014), “How Should We Aggregate Competing Claims?” Ethics , 125(1): 64-87.

[1] This case, which is known as “lives for headaches”, is often used to motivate restrictions on aggregation (e.g. Dorsey 2009). If benefits of one kind cannot be aggregated, no number of them can outweigh a more significant benefit. Advocates of restricted (or “partial”) aggregation include, for example, Kamm (2013), Scanlon (1998), and Voorhoeve (2014).

[2] Which circumstances count as “realistic”? This is hard to specify. Surely not all metaphysically possible circumstances, but perhaps also not quite all nomologically possible circumstances. For an approximation, we can think of the minimum wellbeing level as the wellbeing level resulting from a life full of the suffering that the species is capable of, and the maximum wellbeing level as the wellbeing level resulting from a life in full health with (virtually) no unsatisfied needs or desires.

[3] See Rethink Priorities’ pioneering research on the welfare ranges of other species, in particular Fischer (2023). Note that on their definition, welfare ranges measure the momentary welfare rather than the total welfare of species.

[4] See Horta & Teran (2023) for different promising ways of benefitting wild animals effectively.

[5] See, for example, Horton (2018) and Norcross (1997) for arguments that aggregation should not be restricted at all.

[6] Compare this with Kamm’s (2015) concern that a utilitarian approach to global health might have the unfair result that we should save the life of a healthy person rather than the life of a disabled person. This is a valid concern, but there seem to be reasonable notions of fairness that are compatible with the utilitarian verdict. By contrast, it is clearly unfair to prioritize one healthy life over any number of disabled lives. Analogously, it is unfair to prioritize one human life over any number of lives of low welfare species.

[7] This does not need to be their actual perspective. We can consider this perspective a hypothetical one which it would be appropriate to have given the welfare structure of members of a low welfare species. My argument therefore does not require that individuals of low welfare species have the cognitive capacities to contemplate the significance of their goods.

[8] This would make the principle similar to how contractualists usually test the relevance of claims (e.g. Voorhoeve 2014). A contractualist framework might therefore have similar results if, against contractualist orthodoxy, all animals are assigned claims as well.

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What Is Research Ethics & Why Is It Important?

What Is Research Ethics?

Research Ethics refers to the set of principles and standards that govern the conduct of research involving human or animal subjects. It involves ensuring that research is conducted in an ethical manner. The rights and well-being of research participants are protected.

Research ethics includes several key principles, such as:

Informed consent: researchers must obtain informed consent from participants before involving them in a study. This means that participants must be provided with all the necessary information about the study. Including its purpose, procedures, risks, and benefits, and must be given the opportunity to ask questions. Make an informed decision about whether to participate.
Respect for autonomy: participants have the right to make their own decisions and to be treated with respect and dignity. Researchers must ensure that participants are not coerced or pressured into participating in a study. And that they are free to withdraw from the study at any time.
Beneficence: researchers must take steps to minimize the risks and maximize the benefits of the research for participants. This includes ensuring that the research is designed in a way. Is likely to produce valid and useful results. That any risks are minimized and justified by the potential benefits.
Non-maleficence: researchers must ensure that the research does not cause harm to participants. This includes both physical harm (such as injury or illness) and psychological harm (such as stress, anxiety, or embarrassment).
Confidentiality: researchers must take steps to protect the confidentiality of participants and their data. This includes ensuring that participants’ personal information is kept private. Any data collected is used only for the purposes of the research.

Overall, research ethics is an essential component of conducting responsible and ethical research. Is important to ensure that research is conducted in a way. That respects the rights and well-being of research participants.

Why Is It Important?

Research ethics is important for several reasons:

Protecting human and animal subjects: Research ethics helps to ensure that research is conducted in a way. That respects the rights and well-being of human and animal subjects. This includes minimizing the risks of harm and ensuring that participants provide informed consent before participating in a study.
Ensuring the validity of research: Research ethics also helps to ensure the validity of research findings by ensuring. That research is conducted in a rigorous and unbiased manner. This includes avoiding conflicts of interest and ensuring that the research design and methodology are appropriate for the research question.
Building trust in research: Research ethics is important for building trust in research and ensuring. The research is seen as a valuable and credible source of information. This is important for both researchers and the wider public. As it helps to ensure that research findings are taken seriously and used to inform policy and practice.
Protecting the reputation of researchers and institutions: Research ethics helps to protect the reputation of researchers. Institutions by ensuring that research is conducted in an ethical and responsible manner. This is important for maintaining public trust in research and ensuring that researchers. And institutions are seen as credible and trustworthy.

Overall, research ethics is essential for ensuring that research is conducted responsibly. Ethical manner, and for protecting the rights and well-being of research participants. It is important for building trust in research and ensuring. Research findings are taken seriously and used to inform policy and practice.

Codes and Policies for Research Ethics

There are various codes and policies for research ethics that guide researchers in their conduct of research. Here are some examples:

The Belmont Report: This report outlines the ethical principles and guidelines for research involving human subjects. It identifies three key ethical principles: respect for persons, beneficence, and justice.
The Declaration of Helsinki: This is a set of ethical principles for medical research involving human subjects. It provides guidelines for researchers on issues such as informed consent, risk-benefit assessment, and confidentiality.
The Nuremberg Code: This is a set of ethical principles for research involving human subjects, developed in response to the unethical medical experiments conducted by Nazi doctors during World War II. It emphasizes the importance of informed consent, voluntary participation, and minimizing harm to participants.
The Animal Welfare Act: This is a federal law in the United States that provides guidelines for the ethical treatment of animals used in research.
Institutional Review Boards (IRBs): These are committees that review research proposals to ensure. That they meet ethical guidelines and their rights. The welfare of human subjects is protected.
Good Clinical Practice (GCP): This is an international standard for the design, conduct, and reporting of clinical trials. It provides guidelines for researchers on issues such as informed consent, data collection and management, and monitoring of the study.

Overall, these codes and policies provide guidance for researchers on ethical issues related to research involving human and animal subjects. By following these guidelines, researchers can ensure that their research is conducted in a responsible and ethical manner. The rights and well-being of research participants are protected.

Principles of Research Ethics

There are several principles of research ethics that guide the conduct of research involving human or animal subjects. These principles are as follows:

Respect for persons: This principle emphasizes the importance of respecting the autonomy of research participants and treating them with dignity and respect. It requires researchers to obtain informed consent from participants before involving them in a study and to ensure that participants are free to make their own decisions and to withdraw from the study at any time.
Beneficence: This principle requires researchers to minimize risks to participants and maximize the potential benefits of the research. It involves designing the study in a way that is likely to produce valid and useful results. Ensuring that any risks are minimized and justified by the potential benefits.
Non-maleficence: This principle requires researchers to ensure that the research does not cause harm to participants. It involves taking steps to protect participants from physical harm (such as injury or illness) and psychological harm (such as stress, anxiety, or embarrassment).

More here…

Justice: This principle requires that the benefits and burdens of research be distributed fairly. It involves ensuring that participants are selected fairly. They are not unfairly excluded from participating in the study. It also involves ensuring that the benefits of the research are distributed fairly among all participants.
Respect for law and public interest: This principle requires researchers to comply with applicable laws and regulations, and to ensure that their research serves the public interest. It involves conducting research in a way that is transparent and accountable, and that respects the rights and interests of all stakeholders.

Overall, these principles provide guidance for researchers on ethical issues related to research involving human or animal subjects. By following these principles, researchers can ensure that their research is conducted in a responsible and ethical manner. The rights and well-being of research participants are protected.

In conclusion, research ethics is a critical component of responsible and ethical research. It involves adhering to principles and guidelines that ensure that the rights. And the well-being of human and animal subjects is protected. That research is conducted in a rigorous and unbiased manner. Research findings are credible and trustworthy.

The codes, policies, and principles of research ethics provide guidance to researchers on how to conduct research in a responsible and ethical manner. By following these guidelines, researchers can ensure that their research is conducted with integrity. That the benefits of the research are distributed fairly and serve the public interest.

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Essay on Ethics for Students and Children

500+ words essay on ethics.

Essay on Ethics – Ethics refers to the concepts of right and wrong conduct. Furthermore, ethics is basically a branch of philosophy dealing with the issue of morality. Moreover, ethics consist of the rules of behavior. It certainly defines how a person should behave in specific situations. The origin of ethics is old and it started from the Stone Age . Most noteworthy, over the centuries many religions and philosophers have made contributions to ethics.

Branches of Ethics

First of all, comes the descriptive branch of ethics. Descriptive ethics involve what people actually believe to be right or wrong. On the basis of this, the law decides whether certain human actions are acceptable or not. Most noteworthy, the moral principles of society keep changing from time to time. Therefore, descriptive ethics are also known as comparative ethics. This is because; it compares the ethics of past and present as well as ethics of one society and another.

Normative ethics is another important branch of ethics. Moreover, Normative ethics deals with certain norms or set of considerations. Furthermore, these norms or set of considerations dictate how one should act. Therefore, normative ethics sets out the rightness or wrongness of actions or behaviours. Another name for normative ethics is prescriptive ethics. This is because; it has principles which determine whether an action is right or wrong.

Meta-ethics consists of the origin of the ethical concepts themselves. Meta-ethics is not concerned whether an action is good or evil. Rather, meta-ethics questions what morality itself is. Therefore, meta-ethics questions the very essence of goodness or rightness. Most noteworthy, it is a highly abstract way of analyzing ethics.

Applied ethics involves philosophical examination or certain private and public life issues. Furthermore, this examination of issues takes place from a moral standpoint. Moreover, this branch of ethics is very essential for professionals. Also, these professionals belong to different walks of life and include doctors , teachers , administrators, rulers.

Get the huge list of more than 500 Essay Topics and Ideas

Applications of Ethics

Bioethicists deal with the ethical questions that arise in the relationships among life sciences, biotechnology, medicine, politics, and philosophy. Furthermore, Bioethics refers to the study of controversial ethics brought about by advances in biology and medicine .

Ethics also have a significant application in business. Moreover, business ethics examines ethical principles in relation to a business environment.

Military ethics involve the questions regarding the application of ethos of the soldier. Furthermore, military ethics involves the laws of war. Moreover, it also includes the question of justification of initiating military force.

Public sector ethics deals with a set of principles that guide public officials in their service. Furthermore, the public sector involves the morality of decision making. Most noteworthy, it consists of the question of what best serves the public’s interests.

In conclusion, ethics is certainly one of the most important requirements of humanity. Furthermore, without ethics, the world would have been an evil and chaotic place. Also, the advancement of humanity is not possible without ethics. There must be widespread awareness of ethics among the youth of society.

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Professional experience, peer-to-peer relationships, scientific papers: what matters most

EDITOR’S CORNER
Published: 26 March 2024

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Giampiero Campanelli 1

Avoid common mistakes on your manuscript.

For a number of years now, we have been witnessing a progressive change in interpersonal relationships, be it in the family setting (where this change is most commonly experienced), the workplace or in interpersonal relationships generally.

The pandemic has played a more than decisive role in this phenomenon.

There is no doubt that while the now vast wealth of opportunities for remote interaction has, in some ways, simplified relationships, it has also distanced us from real feelings. The fact is, it is only when two people are able to meet and see each other face to face that they are likely to develop that special “feeling” or understanding that they need to have in order to really get to know each other.

In science, the daily work of a surgeon can remain an end in itself and gratify the individual concerned, even when, overwhelmed by commitments, routine and life generally, they fail to communicate their results. When this happens, what scientific value can these results possibly have? The opportunity for visibility is wasted and the profession as a whole loses out.

There is only one way to prevent this from happening, and that is by “comparing notes” with peers. In other words, it is only by comparing our own techniques, results and problems with the ones used, obtained or encountered by other professionals that we can obtain progress. As well as an honest evaluation of our work.

And if this process of “comparing notes” brings to light real results, in other words, good scientific work that can benefit the global surgical community, then we really have no choice but to try and ensure that it gets published in a serious and recognised journal.

Producing good scientific work is complex, laborious and difficult, but it is also a source of great satisfaction, not only in terms of impact and citations, but also, and perhaps above all, because it allows us to indicate alternative avenues, share useful experiences, and generate those close peer-to-peer relationships that are essential for everyone’s professional growth.

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Guest Essay

The Best Way to Find Out if We Can Cool the Planet

An illustration of five people standing and looking down at a large glowing orb. The background is the black night sky.

By Jeremy Freeman

Dr. Freeman is the executive director of CarbonPlan, a climate research nonprofit.

A few years ago, the idea of deliberately blocking the sun to combat climate change was taboo for scientists. But a lot can change in a short time .

As the disastrous effects of climate change mount, Congress has asked federal scientists for a research plan , private money is flowing and rogue start-ups are attempting experiments — all signs that momentum around solar geoengineering is building fast. The most discussed approach involves spraying tiny particles into the stratosphere to reflect sunlight and cool the planet. Other proposals include injecting sea salt into clouds to increase their reflectivity or using giant space parasols to block the sun .

It might all sound like dystopian science fiction, but some techno-futurists, like OpenAI’s chief executive, Sam Altman, are already normalizing it: “We’re going to have to do something dramatic with climate like geoengineering as a Band-Aid, as a stopgap,” he said in January at the World Economic Forum in Davos.

No one fully understands the risks of these technologies — which could include calamitous disruptions in weather — or how significant the benefits could be. I’m increasingly convinced that we should do more research on solar geoengineering . But such high-stakes science requires extraordinary levels of transparency and accountability to the global public. The alternative is clandestine research controlled by corporations or autocratic regimes, lurching toward deployment without knowing — or knowing and not sharing — the true risks.

The potential risks of solar geoengineering are serious. Spraying reflective particles in one place, for example, could significantly change rainfall patterns elsewhere. What’s more, once anyone starts solar geoengineering at a larger scale, suddenly stopping it could lead to “ termination shock ” — global temperatures rapidly readjusting to where they would have been without geoengineering. With such terrifying points of no return, every accelerating step of research requires global public participation and deliberation.

Most research so far has been tentative and contained to computer simulations . But to know what will happen in the real world, we also need outdoor experiments. By launching an instrument-laden balloon into the stratosphere, for example, researchers could release a tiny amount of particles and measure how they interact with the atmosphere, with minimal environmental risk.

But already we’ve seen a backlash to these kinds of experiments: Harvard geoengineering researchers planned a dry run of their instruments in Sweden in 2021 only to be shut down after the Indigenous Saami Council and local environmental groups protested the tests. A key concern was how such research could redirect attention and investment from more pressing efforts to reduce emissions, thereby becoming a moral hazard . More recently, Mexico banned geoengineering experiments after discovering an American tech entrepreneur had launched a balloon test without permission. And a startup out of Israel has now raised millions of dollars and is planning experiments with little to no transparency. Some assessments suggest that more experiments, and even larger deployments, are increasingly likely. It would be far better if they happened in the open, as in Sweden, rather than in secret.

Even in places where no experiments have been planned, the public is wary. Most people haven’t heard of geoengineering in the United States, but of those who have, 72 percent reported being very concerned we’ll use it before understanding its impact. More broadly, while there’s evidence of support for research , that support is reluctant and conditional. Without transparency and trust, public debate on geoengineering could devolve into conspiracy theories and partisan ideology.

A reluctance to trust scientists is understandable. Science as a profession has for too long pursued prestige at the expense of integrity, and public scientific institutions have been increasingly privatized with minimal accountability. With a long, troubled history that includes eugenics and weapons of war, we cannot pretend that science is either pure or infallible.

But science is fallible precisely because it is a practice , a cooperative human activity. And as the moral philosopher Alasdair MacIntyre reminds us, engaging in a practice well requires exercising its virtues — which for science include transparency, honesty, humility, skepticism and collaboration. For geoengineering, that means disclosing all funding and effectively managing potential conflicts of interests, ensuring the participation of stakeholders from around the world in decision making , avoiding groupthink, sharing early-stage results and data to accelerate research and engaging in radically open science .

Transparency on its own may not lead to the widespread adoption of a new technology. A study on Covid-19 vaccine communication showed that increased transparency, especially about negative outcomes, led to lower vaccine acceptance — but it did increase trust in public health. A potential lesson for solar geoengineering is that transparency is important even when or perhaps especially when it doesn’t result in an outcome scientists initially imagine.

We should be especially wary of ceding control over geoengineering research to the tech industry. Often under the guise of virtue, techno-futurists capitalize on the power that comes from scientific knowledge while exploiting people and the environment, a pattern The Atlantic’s Adrienne LaFrance diagnoses as techno-authoritarianism. We cannot allow private for-profit entities to steer, or covertly fund, solar geoengineering research.

Instead, any research must be done by institutions acting in the public’s interest. If private funding is the only option, scientists will need to choose carefully where they work and defend their integrity against external pressures. They must clearly communicate research findings, positive and negative, and educate the public about what’s possible and what’s at stake. That way the public can in turn hold policymakers, regulators and scientists to account, with everyone working together in pursuit of a common good.

When confronted with the prospect of solar geoengineering, we may wish it had never come to this point. But we can still decide how to move forward responsibly, with and for the public.

Jeremy Freeman is the executive director of CarbonPlan, a climate research nonprofit. Much of CarbonPlan’s work has focused on carbon dioxide removal, another controversial climate technology.

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27 March 2024

Tweeting your research paper boosts engagement but not citations

Bianca Nogrady

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Even before recent complaints about X's declining quality, posting a paper on the social media platform did not translate to a boost in citations. Credit: Matt Cardy/Getty

Posting about a research paper on social media platform X (formerly known as Twitter) doesn’t translate into a bump in citations, according to a study that looked at 550 papers.

The finding comes as scientists are moving away from the platform in the wake of changes after its 2022 purchase by entrepreneur Elon Musk.

An international group of 11 researchers, who by the end of the experiment between them had nearly 230,000 followers on X, examined whether there was evidence that posting about a paper would increase its citation rate.

“There certainly is a correlation, and that’s been found in a lot of papers. But very few people have ever looked to see whether there’s any experimental causation,” says Trevor Branch, a marine ecologist at the University of Washington in Seattle and lead author on the paper, published in PLoS ONE last week 1 .

Every month for ten months, each researcher was allocated a randomly selected primary research article or review from a journal of their choice to post about on their personal account. Four randomly chosen articles from the same edition of the journal served as controls, which the researchers did not post about. They conducted the experiment in the period before Elon Musk took ownership of what was then known as Twitter and complaints of its declining quality increased.

‘Nail in the coffin’

Three years after the initial posts, the team compared the citation rates for the 110 posted articles with those of the 440 control articles, and found no significant difference. The researchers did acknowledge that their followers may not have have been numerous enough to detect a statistically significant effect on citations.

The rate of daily downloads for the posted papers was nearly fourfold higher on the day that they were shared, compared with controls. Shared papers also had significantly higher accumulated Altmetric scores both 30 days and three years after the initial post. Calculated by London-based technology company Digital Science, an Altmetric score, says Branch, is a measure of how many people have looked at a paper and are talking about it, but it’s not a reliable indicator of a paper’s scientific worth. “It’s thoroughly biased by how many people with large followings tweet about it,” he says.

The findings echo those of information scientist Stefanie Haustein at the University of Ottawa, whose 2013 study 2 found a low correlation between posts and citations.

Haustein says the problem with using posts as a metric is that, even a decade ago, there was a lot of noise in the signal.

“We actually showed that a lot of the counts on Twitter you would get were bots, it wasn’t even humans,” says Haustein, who wasn’t involved in the new study.

She says the more recent departure of scientists from the platform has been the final nail in the coffin of the idea that posting could increase citations.

doi: https://doi.org/10.1038/d41586-024-00922-y

Branch, T. A. et al. PLoS ONE 19 , e0292201 (2024).

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Haustein, S., Peters, I., Sugimoto, C. R., Thelwall, M. & Larivière, V. J. Assoc. Inf. Sci. Technol. 65, 656–669 (2014).

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Introduction: What is Research Ethics?

What is Research Ethics?

Ethical Distinctions

Ethical Approaches

Related Resources

Assisting you to advance with ethics in research: an introduction to ethical governance and application procedures

Introduction

Background literature survey

Individual responsibilities to enhance RRP

Research governance - origins, expectations and practices

Basic structure of an institutional ethical advisory committee (EAC)

Understanding the subtle differences between ethics and morals

The mission of ENAI’s ethical advisory working group

Setting up an institutional ethical committee (ECs)

Ethics approval forms and process

Research involving humans - informed consents

Typical research ethics approval process

Strategies for ethics educations for students

Concluding remarks

Declarations

Availability of data and materials

Abbreviations

Acknowledgements

Author information

Contributions

Corresponding author

Ethics declarations

Additional information

Rights and permissions

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International Journal for Educational Integrity

Essay: Research ethics

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Essay Categories:

Ethical Issues in Research: Perceptions of Researchers, Research Ethics Board Members and Research Ethics Experts

Eugénie Rose-Derouin

Julie-Claude Leblanc

Introduction

Research Methods

Ethical considerations

Sampling and recruitment

Data Collection

Data Analysis

Participants

Ethical issues

Research Integrity

Conflict of interest

Respect for research participants

Lack of Supervision and Power Imbalances

Individualism and performance

Inadequate ethical Guidance

Social Injustices

Distributive Injustices

Epistemic injustices

Ethical distress

Returning to the research question and objective

Contemporary culture characterized by the social acceleration

Strengths and Limitations of the study

Conclusions

Acknowledgements

Competing Interests and Funding

How to Write an Ethics Paper: Guide & Ethical Essay Examples

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