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What is Research? – Purpose of Research

• By DiscoverPhDs
• September 10, 2020

The purpose of research is to enhance society by advancing knowledge through the development of scientific theories, concepts and ideas. A research purpose is met through forming hypotheses, collecting data, analysing results, forming conclusions, implementing findings into real-life applications and forming new research questions.

What is Research

Simply put, research is the process of discovering new knowledge. This knowledge can be either the development of new concepts or the advancement of existing knowledge and theories, leading to a new understanding that was not previously known.

As a more formal definition of research, the following has been extracted from the Code of Federal Regulations :

While research can be carried out by anyone and in any field, most research is usually done to broaden knowledge in the physical, biological, and social worlds. This can range from learning why certain materials behave the way they do, to asking why certain people are more resilient than others when faced with the same challenges.

The use of ‘systematic investigation’ in the formal definition represents how research is normally conducted – a hypothesis is formed, appropriate research methods are designed, data is collected and analysed, and research results are summarised into one or more ‘research conclusions’. These research conclusions are then shared with the rest of the scientific community to add to the existing knowledge and serve as evidence to form additional questions that can be investigated. It is this cyclical process that enables scientific research to make continuous progress over the years; the true purpose of research.

What is the Purpose of Research

From weather forecasts to the discovery of antibiotics, researchers are constantly trying to find new ways to understand the world and how things work – with the ultimate goal of improving our lives.

The purpose of research is therefore to find out what is known, what is not and what we can develop further. In this way, scientists can develop new theories, ideas and products that shape our society and our everyday lives.

Although research can take many forms, there are three main purposes of research:

• Exploratory: Exploratory research is the first research to be conducted around a problem that has not yet been clearly defined. Exploration research therefore aims to gain a better understanding of the exact nature of the problem and not to provide a conclusive answer to the problem itself. This enables us to conduct more in-depth research later on.
• Descriptive: Descriptive research expands knowledge of a research problem or phenomenon by describing it according to its characteristics and population. Descriptive research focuses on the ‘how’ and ‘what’, but not on the ‘why’.
• Explanatory: Explanatory research, also referred to as casual research, is conducted to determine how variables interact, i.e. to identify cause-and-effect relationships. Explanatory research deals with the ‘why’ of research questions and is therefore often based on experiments.

Characteristics of Research

There are 8 core characteristics that all research projects should have. These are:

• Empirical  – based on proven scientific methods derived from real-life observations and experiments.
• Logical  – follows sequential procedures based on valid principles.
• Cyclic  – research begins with a question and ends with a question, i.e. research should lead to a new line of questioning.
• Controlled  – vigorous measures put into place to keep all variables constant, except those under investigation.
• Hypothesis-based  – the research design generates data that sufficiently meets the research objectives and can prove or disprove the hypothesis. It makes the research study repeatable and gives credibility to the results.
• Analytical  – data is generated, recorded and analysed using proven techniques to ensure high accuracy and repeatability while minimising potential errors and anomalies.
• Objective  – sound judgement is used by the researcher to ensure that the research findings are valid.
• Statistical treatment  – statistical treatment is used to transform the available data into something more meaningful from which knowledge can be gained.

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Types of Research

Research can be divided into two main types: basic research (also known as pure research) and applied research.

Basic Research

Basic research, also known as pure research, is an original investigation into the reasons behind a process, phenomenon or particular event. It focuses on generating knowledge around existing basic principles.

Basic research is generally considered ‘non-commercial research’ because it does not focus on solving practical problems, and has no immediate benefit or ways it can be applied.

While basic research may not have direct applications, it usually provides new insights that can later be used in applied research.

Applied Research

Applied research investigates well-known theories and principles in order to enhance knowledge around a practical aim. Because of this, applied research focuses on solving real-life problems by deriving knowledge which has an immediate application.

Methods of Research

Research methods for data collection fall into one of two categories: inductive methods or deductive methods.

Inductive research methods focus on the analysis of an observation and are usually associated with qualitative research. Deductive research methods focus on the verification of an observation and are typically associated with quantitative research.

Qualitative Research

Qualitative research is a method that enables non-numerical data collection through open-ended methods such as interviews, case studies and focus groups .

It enables researchers to collect data on personal experiences, feelings or behaviours, as well as the reasons behind them. Because of this, qualitative research is often used in fields such as social science, psychology and philosophy and other areas where it is useful to know the connection between what has occurred and why it has occurred.

Quantitative Research

Quantitative research is a method that collects and analyses numerical data through statistical analysis.

It allows us to quantify variables, uncover relationships, and make generalisations across a larger population. As a result, quantitative research is often used in the natural and physical sciences such as engineering, biology, chemistry, physics, computer science, finance, and medical research, etc.

What does Research Involve?

Research often follows a systematic approach known as a Scientific Method, which is carried out using an hourglass model.

A research project first starts with a problem statement, or rather, the research purpose for engaging in the study. This can take the form of the ‘ scope of the study ’ or ‘ aims and objectives ’ of your research topic.

Subsequently, a literature review is carried out and a hypothesis is formed. The researcher then creates a research methodology and collects the data.

The data is then analysed using various statistical methods and the null hypothesis is either accepted or rejected.

In both cases, the study and its conclusion are officially written up as a report or research paper, and the researcher may also recommend lines of further questioning. The report or research paper is then shared with the wider research community, and the cycle begins all over again.

Although these steps outline the overall research process, keep in mind that research projects are highly dynamic and are therefore considered an iterative process with continued refinements and not a series of fixed stages.

The scope of the study is defined at the start of the study. It is used by researchers to set the boundaries and limitations within which the research study will be performed.

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Airport Passenger-Related Processing Rates Guidebook (2009)

Chapter: chapter 3 - defining the research: purpose, focus, and potential uses.

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

14 Chapter 3 identifies roles, relationships, and responsibilities of stakeholders. It examines principal steps involved in planning an airport passenger-rate data collection effort. It begins with the ques- tion of whether the potential benefits of the proposed effort outweigh the anticipated cost; describes different types of research (i.e., exploratory, descriptive, inferential); summarizes the questions each type addresses; and notes the ends to which the data might be used. 3.1 Roles and Responsibilities When an airport data collection event is first mentioned, it invariably raises numerous ques- tions: Who is asking for the data? How will it be used? What’s the budget? What’s the schedule? What kind of resources can be made available? Without answers to these fundamental questions, the success of your research is in jeopardy. This section will help the researcher establish the role of key stakeholders and their interrelationships within the team. Many entities can sponsor a data collection study, including airports, airlines, manufacturers, and various agencies. Likewise, there are many ways of managing and staffing the event and pro- moting involvement with stakeholders. There are therefore myriad ways of organizing a study. Exhibit 3-1 is an example of how a study could be arranged with the airport as the sponsor. 3.1.1 Client/Sponsor For airports, oversight is guided by a board, commission, or an authority consisting of appointed or elected officials. While these agencies typically provide oversight to airport man- agement and approve long-term plans and large capital expenditures, usually it is the airport director or manager who makes day-to-day decisions. Depending on the size of the airport, there may be several departments, each having its own manager. In such cases, passenger terminal-related studies would typically fall within the purview of the planning and/or engineering department and would be managed by its director. Regardless of the affiliation of the project sponsor(s), it is essential that the following ques- tions be answered clearly and unambiguously as they pertain to the sponsor at the beginning of any project: • Who has primary responsibility for defining the questions the study is intended to address? • What preference does this person or group have regarding ongoing involvement with the project? – What information would they like to receive, in what format, and with what frequency? – Who should be the principal point-of-contact (POC) on the client’s side for questions that might emerge related to the study’s focus, direction, etc.? C H A P T E R 3 Defining the Research: Purpose, Focus, and Potential Uses

Defining the Research: Purpose, Focus, and Potential Uses 15 • Who is the designated project manager, and what information would he or she like to receive, in what format, and with what frequency? • If the person given responsibility for day-to-day issues pertaining to access, authorizations, etc. is different from the project manager, who is that person, and what is the scope of issues he or she is authorized to address? • If problems or obstacles arise in implementing the study, and the project manager is not able or authorized to resolve them, what is the chain of persons through which the issue should be escalated? 3.1.2 Study Team The size of the study team will depend on the team’s depth and organization, and the size, duration, and complexity of the study itself. For a typical medium- to large-scale study, the roles listed in the following sections are the most typical. Multiple roles might be assumed by a single person or distributed across multiple persons. Titles vary as well, but the functions are largely universal. Project Manager The project manager is typically a mid-level to senior person who has the long-term, day-to- day relationship with his or her client counterpart. The need for the passenger-related process- ing rate study may initially originate from discussions between the project manager and those within the airport or airline. Survey Manager The survey manager is usually a mid-level staff person. His/her role on the project would be to oversee the day-to-day management of the data processing rate study, including leading the development of the scope, schedule, and budget; developing the team; and assigning roles and responsibilities. The survey manager would have the responsibility of ensuring the survey goals were adequately defined and met. Decision Maker Survey Manager Admin. Support Staffing Source (e.g., airport personnel, mkt. research firm) Surveyor Surveyor Surveyor Sponsor/Client (Airport) (Large Airport: Dir./Mgr.) Project Manager (Large Airport: Dir. Planning/Eng.) (Small Airport: Apt. Mgr.) Project Manager (Typ. oversees multiple tasks of which survey is but one part) Study Team (Typically, Consultant) Statistical Technical Expert Survey Assistant Data Analyst IT Analyst Other Stakeholders • Airlines • Agencies • Concessionaires Exhibit 3-1. Typical sponsor and study team roles (assuming an airport is the sponsor).

16 Airport Passenger-Related Processing Rates Guidebook Research and Statistical Expert A person(s) with expertise in research methodology and quantitative/statistical analysis should be consulted to develop, or provide comments and recommendations about, the overall methodology, the sampling plan, and so forth. Most of this person’s input would occur at the project’s initiation. A distinction is sometimes drawn in the consulting literature among differ- ent approaches to consulting. One such approach, generally referred to as process consultation might be of particular appeal.1 When acting in this role, the consultant not only provides tech- nical expertise related to the specific project, but also works with the client to develop expertise. This arrangement has the goal of, over time, reducing the reliance on the consultant. Survey Assistant The survey assistant has primary responsibility for assisting the survey project manager and secondarily to assist others on the project team throughout the duration of the study. Typically, this staff person will be at a junior level. The degree of assistance this person can provide is based on his/her level of education and current skill sets. Data Analyst The data analyst should not only be well-versed in technical analysis, but should also have a strong familiarity with the airport terminal environment. This person could be a terminal or air- port planner or aviation architect. The analyst is often largely responsible for documenting results, and responsibilities might extend to presenting findings to the client. Administrative Support Data collection efforts are inherently complex and, as such, often require a significant level of coordination and administration. The staff person serving this function would be responsible for such things as making travel plans, scheduling visits to the airport’s security office, buying supplies, shipping and receiving materials, scheduling meetings, preparing invoices and con- tracts, and editing/proofing the report. Data Collection Staff For small studies (e.g., small airports where only a few functional elements are being observed for a limited time period), airport/airline or consultant staffing may be used. For larger studies, typically examining multiple functional elements of a medium or large airport over a multi-day period, a market-research firm is frequently employed. The data collection staff reports directly to the survey manager. 3.2 Is the Study Needed? While the need for data collection is often justifiable, the benefit of validating the need, and avoiding what might be a costly, and possibly unjustified, effort well exceeds the relatively minor cost of pausing to consider a few basic questions (see Appendix C for more information). Exhibit 3-2 illustrates these questions. 3.3 Research Fundamentals This section summarizes a number of fundamental issues and terms related to the research process. (Additional detail is included in Appendix C.) 1 Schein, E. H. (1999). Process Consultation Revisited: Building the Helping Relationship. NY: Addison Wesley.

Research is a dynamic process with both deductive and inductive dimensions. This differs in some ways from what some present as the “traditional” approach to research, i.e., that theory drives hypothesis testing. Sometimes it does, but sometimes it doesn’t work this way. 3.3.1 Theory, Hypotheses, and Evidence The word “theory” often implies a formal set of laws, propositions, variables, and the like, whose relationships are clearly defined. A related implication is that theory may not be particu- larly germane to the everyday world of work. This view of theory is not incorrect, but neither is it complete. While theory can be abstract and complex in its detail, it does not necessarily have to be abstract, complex, or formal. It can be thought of more broadly and simply as an explanation of “how the world works.” For exam- ple, an organization might develop a mission or a value statement (or both); engrave the words in a medium intended to last millennia; and prominently display the statement in the workplace with the intent of communicating to all its perspective clients on issues pertinent to its view. In Defining the Research: Purpose, Focus, and Potential Uses 17 Question Things to Consider Have relevant data been collected at this airport in the past that might be used rather than collecting new data? Might you be able to get data from another airport similar in key ways to this airport? Are there data available that might help answer the research question? Might access to the data be blocked due to proprietary or security issues? Sometimes the data are perceived to be so sensitive that the “owner” of the data may not give permission to share it. Has the decision already been made, and the data are being collected to legitimize the decision? Is there anything to suggest that the study is an attempt to “prove” something true or false? What role will the results play in the decision being considered? To what extent will the decision makers be persuaded by the results? What will the decision makers accept as credible evidence? Before collecting data, make certain that the research plan will result in data that the sponsors will accept. It is better to learn beforehand, for example, that the proposed sampling plan does not meet the sponsor’s criteria for rigor. What is the cost of the potential investment that the data will help inform? What is the cost of conducting the research? Does the benefit equal or outweigh the cost? Cost should be considered not only in economic terms, but as safety, inconvenience, and so forth. Exhibit 3-2. Considerations to determine need for data collection.

2008, British Airways announced a new venture: OpenSkies. The “theory” OpenSkies used to define its clients is reflected in its advertising as shown in Exhibit 3-3. So, how does this relate to airport processing rate studies? It relates in the following two ways: 1. The published research literature may well contain formal theories relevant to what data to collect and how to collect it. For example, Appendix B includes a bibliography of recent research articles related to passenger and baggage processing in airports. It is intended to illustrate the scope and diversity of research available on a given topic. Before embarking on an investigation, review the literature to see how it might enhance the quality of the planned research. The Internet provides access to numerous sources for such scholarly documents. 2. Informally, the key decisions about how to go about collecting data are grounded in assump- tions about how things work (i.e., one’s own theory). For example, you might choose to col- lect passenger security screening data between 6:00 a.m. and 8:00 a.m. on a Monday because your experience is that this time period reflects peak checkpoint activity. While this “theory” may be correct in some circumstances, it may also be wrong in others. For example, at many vacation-oriented airports, the peak at the checkpoint occurs in the late morning due to check-out times at hotels. Another common view of research is of the stereotypical scientist, objectively testing hypothe- ses (or an “educated guess”) arising from theory. Exhibit 3-4 reflects this general approach to research. This is certainly one way in which research proceeds, but, similar to theory, it is not the only way. Before considering an “evidence first” approach, we wish to mention a variation on the tra- ditional approach displayed in Exhibit 3-4 that has been gaining dominance in recent years. In particular, this is a confidence interval (CI) approach rather than a hypothesis driven approach. In a hypothesis driven approach, the researcher’s primary interest is in testing a population parameter, and uses a sample drawn from the population. When the researcher takes a CI approach, the intent is to calculate an interval within which the population parameter is likely 18 Airport Passenger-Related Processing Rates Guidebook Exhibit 3-3. OpenSkies advertisement. Question key assumptions, even if they seem to be “common sense,” by checking with informants, look- ing at the literature, etc.

to fall. Hypotheses are stated before data collection; CIs are calculated after data are collected.2 In conducting passenger-processing rate research in airport environments, the CI approach is going to be the most appropriate in most instances. A markedly different approach to those described above is shown in Exhibit 3-5. In contrast to beginning with a theory and then collecting evidence to test the theory or estimate a popula- tion parameter within some CI, this approach begins with evidence for which one seeks poten- tial explanations, or “theories” to explain the evidence. This approach is subsumed under the broad heading of Bayesian Law, so named after the 18th Century English clergyman, Thomas Bayes, credited with developing the approach. Depending on where one begins can result in potentially dramatic conclusions (see Exhibit 3-6). This is important because limiting oneself to a particular perspective of how research should be conducted and how data ought to be gathered may impose unnecessary constraints. What is important is that the research is executed systematically and with rigor. The documented ways in which science proceeds are often idealized: portraying what is inherently a very dynamic and nonlinear process as logical and linear. 3.3.2 Research Questions and Purposes A basic issue in research is specifying the question the research will help answer. Penning a specific question also helps in determining what approach might be best used in seeking an Defining the Research: Purpose, Focus, and Potential Uses 19 Theory Drives questions & hypotheses Hypothesis: Installing n kiosks will reduce the average time of passengers waiting in line by 10% over check-in agents. Leading to a conclusion Drives data collection Followed by analysis Exhibit 3-4. Hypothesis driven approach. Evidence leads to speculation about possible explanations Which may or may not drive more data collection & analysis Theory Exhibit 3-5. Bayesian approach. 2 While these approaches are presented here as mutually exclusive, they might be integrated in practice.

answer. One classic text in research methodology5 suggests that a research question should express a relationship between two or more variables, and it should imply an empirical approach, that is, it should lend itself to being measured using data. A variable is, not surprisingly, some- thing that can vary, or assume different values. In the next section, illustrative questions are given, categorized by the purpose of research with which they are best matched. The five research purposes are presented as the following: 1. Explore, 2. Describe, 3. Test, 4. Evaluate, and 5. Predict. The distinctions among these purposes are not absolute, nor are they necessarily exclusive of one another. A research initiative might be directed at answering questions with multiple pur- poses. Indeed, this is but one of many ways of classifying research. In addition, the reader whose practice lies primarily in the arena of modeling and simulation might note their absence from this list. Although modeling and simulation applications require input data, for example, to gen- erate distributions and parameters for use as stochastic varieties in modeling, the techniques used to collect data are largely independent of specific applications (such as simulation and model- ing). Those issues unique to modeling are beyond the scope of this guidebook. Explore (Exploratory Research) Exploratory research is sometimes defined as “what to do when you don’t know what you don’t know.” Its aim is discovery and to develop an understanding of relevant variables and their interactions in a real (field) environment. Exploratory research, as such, is appropriate when the 20 Airport Passenger-Related Processing Rates Guidebook If your intent is to… And take action based on… Use… Example Test a hypothesis regarding a population parameter Whether you reject or fail to reject the null hypothesis Hypothesis testing approach The proportion of coach passengers checking in more than 60 min prior to scheduled departure is 80% H A : p > .80 3 H 0 : p .804 Estimate a population parameter The confidence interval selected CI approach Plus or minus 5%, what is the average time coach passengers check in prior to scheduled departure? Determine the likelihood of an event given some evidence The calculated probability Bayesian approach What is the probability that a passenger’s carry on- luggage will be subject to secondary security screening given that the passenger is boarding an international flight? Exhibit 3-6. Research approaches. 3 This is the research, or Alternative, hypothesis. It reads: The proportion is greater than 80%. 4 This is the null hypothesis. It is what is tested, and reads: The proportion is less than or equal to 80%. 5 Kerlinger F. & Lee, H. (2000). Foundations of Behavioral Research, 4th ed. NY: Harcourt Brace.

problem is not well defined. For example, passenger complaints about signs within a facility might prompt the following exploratory question: • “Where should signage be located to minimize passenger confusion?” As another example, if a new security checkpoint configuration is proposed, it may be too novel to rely on variables used in other studies. The question, therefore, might then be the following: • “How does a given alternative security checkpoint configuration affect capacity?” This type of research is often qualitative rather than quantitative. That is, it employs verbal descriptors of observations, rather than counts of those observations (see Appendix C for more information). Describe (Descriptive Research) Descriptive research, as the name implies, is intended to describe phenomena. While descrip- tive research might involve collecting qualitative data by asking open-ended questions in an interview, it typically employs quantitative methods resulting in reporting frequencies, calculat- ing averages, and the like. The following two questions illustrate the nature of descriptive research. Each implies that the relevant variables have been identified as well as the conditions under which the data should be collected. • “What is the average number of passengers departing on international flights on weekday evenings in July at a given airport?” • “How many men use a given restroom at a particular location at a given time?” Test (Experimental and Quasi-experimental Research and Modeling) Often, the intent of the research is not simply to describe something, but to test the impact of some intervention. In an airport environment, such research might be initiated to evaluate the relative effectiveness of a security screening technology in accurately detecting contraband. It is similar in approach to research conducted to assess the relative effectiveness of an experimental drug in comparison to a control (placebo) or another drug. Variables are often manipulated and controlled. This research lies largely outside the scope of this guidebook and, as such, will not receive much attention. Examples of questions that might be asked in this type of research include the following: • “What is the impact of posting airline personnel near check-in waiting lines on the average passenger waiting time?” In addition to the classic “experiment,” simulation modeling might be used, employing rep- resentative data to help answer questions such as the following: • “What would be the impact on processing time of a new security measure being considered?” • “How many agents are needed to keep passenger waiting time below an average of 10 min?” Evaluate (Evaluative Research) Sometimes, the intent of the research is to assess performance against some standard or stated requirement. Basically, evaluation research is concerned with seeing how well something is work- ing, with an eye toward improving performance, as illustrated by the following two questions: • “Is the performance of a given piece of equipment in the field consistent with manufacturer’s specifications?” • “On average, what proportion of passengers waits in a security checkpoint line longer than the 10-minute maximum threshold specified by an airline?” Defining the Research: Purpose, Focus, and Potential Uses 21

Predict Finally, research might be initiated to attempt to predict or anticipate potential emerging pat- terns before they occur. This is related to environmental scanning, insofar as it represents a delib- erate attempt to monitor potential trends and their impact. For example, in the early 1970s, one might have posed the following question: • “What would be the impact of an increase in the number of women in the workforce on air- port design?” There are numerous documented approaches to answering questions such as these. While well beyond the scope of this guidebook, here is one as illustrative: scenario planning. This method involves convening persons with relevant expertise to identify those areas that might most impact the industry (e.g., regulation, fuel costs, demographic changes), and then to systemati- cally consider what the best, worst, and might likely scenarios might be. The principal value of such an approach is that it facilitates deliberate consideration of future trends, and in so doing, presumably leaves people better prepared. When the goal of the research is to predict, data from multiple sources might be sought. The scenario planning example relies, to an extent, on the judgments of experts. Probabilities can also be drawn from historical data to help identify patterns and trends. Exhibit 3-7 is a summary of the key characteristics of each research type. 3.4 Developing the Research Plan Large research studies, particularly when funding is being requested, often require the researchers to adhere to a specific set of technical requirements. The Research Team is aware that the ad hoc and short timeline of many airport-planning research efforts makes developing a “for- mal” research plan impracticable. Nonetheless, even though you might not have the “luxury” of 22 Airport Passenger-Related Processing Rates Guidebook Research Purpose Characteristics Explore Primary purpose: to better define or understand a situation. Data will help answer the research question. The benefit of conducting the research justifies the cost. Qualitative data are recorded, using observation. Describe Primary purpose: to provide descriptive information about something. Test Primary purpose: to assess the impact of a proposed change in procedure or policy. Evaluate Primary purpose: to assess performance against requirements. Predict Primary purpose: to consider possible future circumstances with the purpose of being better prepared for emerging trends. Exhibit 3-7. Summary of research types.

developing such a plan, there are benefits to considering the issues described in this section, as well as documenting basic information. The following are the three major elements the Research Team believes worth documenting, regardless of the size of the research endeavor.6 1. Goals or aims. 2. Background and significance. 3. Research design and methods. Each is described in the sections that follow. 3.4.1 Goals or Aims Specify the question the research is intended to help answer or the specific purpose of the research. The experience of having to translate an intended purpose into words can help clarify your intent. In addition, a written statement can serve as a way of ensuring that your understand- ing of the purpose of the research is consistent with that of the sponsor and other stakeholders. Two examples follow: Statement of Purpose—Example 1 The purpose of this study is to aid decision makers in determining if extending the dwell time of the airport’s automated guideway transit system (AGTS) vehicles from 30 sec to 35 sec at the Concourse C station might improve overall system capacity by providing more boarding time for passengers. Statement of Purpose—Example 2 The goal of this study is to provide airport management with recent data showing the percent- age of arriving flights whose first checked bag reaches the claim device within the airport’s goal of 15 min. 3.4.2 Background and Significance Document what is already known, and specify how the proposed research initiative will add to this knowledge. Consider a “devil’s advocate” perspective by asking what the consequences of not doing the research might be. 3.4.3 Research Design and Methods In this section, describe how you will go about collecting and analyzing data. Additional infor- mation about these issues, including sampling strategies and sample size, is presented in Chapter 5 and in Appendix C. The research plan does not need be lengthy. It should, however, capture key information that, were it not documented and those familiar with the research were not available, would be diffi- cult to ascertain. Defining the Research: Purpose, Focus, and Potential Uses 23 6 This section is partly based on guidelines published by the Agency for Healthcare Research and Quality, Department of Health and Human Services. http://www.ahrq.gov/fund/esstplan.htm.

TRB’s Airport Cooperative Research Program (ACRP) Report 23: Airport Passenger-Related Processing Rates Guidebook provides guidance on how to collect accurate passenger-related processing data for evaluating facility requirements to promote efficient and cost-effective airport terminal design.

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Purpose Statement Overview

Best practices for writing your purpose statement, writing your purpose statement, sample purpose statements.

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The purpose statement succinctly explains (on no more than 1 page) the objectives of the research study. These objectives must directly address the problem and help close the stated gap. Expressed as a formula:

Good purpose statements:

• Flow from the problem statement and actually address the proposed problem
• Are concise and clear
• Answer the question ‘Why are you doing this research?’
• Match the methodology (similar to research questions)
• Have a ‘hook’ to get the reader’s attention
• Set the stage by clearly stating, “The purpose of this (qualitative or quantitative) study is to ...

In PhD studies, the purpose usually involves applying a theory to solve the problem. In other words, the purpose tells the reader what the goal of the study is, and what your study will accomplish, through which theoretical lens. The purpose statement also includes brief information about direction, scope, and where the data will come from.

A problem and gap in combination can lead to different research objectives, and hence, different purpose statements. In the example from above where the problem was severe underrepresentation of female CEOs in Fortune 500 companies and the identified gap related to lack of research of male-dominated boards; one purpose might be to explore implicit biases in male-dominated boards through the lens of feminist theory. Another purpose may be to determine how board members rated female and male candidates on scales of competency, professionalism, and experience to predict which candidate will be selected for the CEO position. The first purpose may involve a qualitative ethnographic study in which the researcher observes board meetings and hiring interviews; the second may involve a quantitative regression analysis. The outcomes will be very different, so it’s important that you find out exactly how you want to address a problem and help close a gap!

The purpose of the study must not only align with the problem and address a gap; it must also align with the chosen research method. In fact, the DP/DM template requires you to name the  research method at the very beginning of the purpose statement. The research verb must match the chosen method. In general, quantitative studies involve “closed-ended” research verbs such as determine , measure , correlate , explain , compare , validate , identify , or examine ; whereas qualitative studies involve “open-ended” research verbs such as explore , understand , narrate , articulate [meanings], discover , or develop .

A qualitative purpose statement following the color-coded problem statement (assumed here to be low well-being among financial sector employees) + gap (lack of research on followers of mid-level managers), might start like this:

In response to declining levels of employee well-being, the purpose of the qualitative phenomenology was to explore and understand the lived experiences related to the well-being of the followers of novice mid-level managers in the financial services industry. The levels of follower well-being have been shown to correlate to employee morale, turnover intention, and customer orientation (Eren et al., 2013). A combined framework of Leader-Member Exchange (LMX) Theory and the employee well-being concept informed the research questions and supported the inquiry, analysis, and interpretation of the experiences of followers of novice managers in the financial services industry.

A quantitative purpose statement for the same problem and gap might start like this:

In response to declining levels of employee well-being, the purpose of the quantitative correlational study was to determine which leadership factors predict employee well-being of the followers of novice mid-level managers in the financial services industry. Leadership factors were measured by the Leader-Member Exchange (LMX) assessment framework  by Mantlekow (2015), and employee well-being was conceptualized as a compound variable consisting of self-reported turnover-intent and psychological test scores from the Mental Health Survey (MHS) developed by Johns Hopkins University researchers.

Both of these purpose statements reflect viable research strategies and both align with the problem and gap so it’s up to the researcher to design a study in a manner that reflects personal preferences and desired study outcomes. Note that the quantitative research purpose incorporates operationalized concepts  or variables ; that reflect the way the researcher intends to measure the key concepts under study; whereas the qualitative purpose statement isn’t about translating the concepts under study as variables but instead aim to explore and understand the core research phenomenon.  

Always keep in mind that the dissertation process is iterative, and your writing, over time, will be refined as clarity is gradually achieved. Most of the time, greater clarity for the purpose statement and other components of the Dissertation is the result of a growing understanding of the literature in the field. As you increasingly master the literature you will also increasingly clarify the purpose of your study.

The purpose statement should flow directly from the problem statement. There should be clear and obvious alignment between the two and that alignment will get tighter and more pronounced as your work progresses.

The purpose statement should specifically address the reason for conducting the study, with emphasis on the word specifically. There should not be any doubt in your readers’ minds as to the purpose of your study. To achieve this level of clarity you will need to also insure there is no doubt in your mind as to the purpose of your study.

Many researchers benefit from stopping your work during the research process when insight strikes you and write about it while it is still fresh in your mind. This can help you clarify all aspects of a dissertation, including clarifying its purpose.

Your Chair and your committee members can help you to clarify your study’s purpose so carefully attend to any feedback they offer.

The purpose statement should reflect the research questions and vice versa. The chain of alignment that began with the research problem description and continues on to the research purpose, research questions, and methodology must be respected at all times during dissertation development. You are to succinctly describe the overarching goal of the study that reflects the research questions. Each research question narrows and focuses the purpose statement. Conversely, the purpose statement encompasses all of the research questions.

Identify in the purpose statement the research method as quantitative, qualitative or mixed (i.e., “The purpose of this [qualitative/quantitative/mixed] study is to ...)

Avoid the use of the phrase “research study” since the two words together are redundant.

Follow the initial declaration of purpose with a brief overview of how, with what instruments/data, with whom and where (as applicable) the study will be conducted. Identify variables/constructs and/or phenomenon/concept/idea. Since this section is to be a concise paragraph, emphasis must be placed on the word brief. However, adding these details will give your readers a very clear picture of the purpose of your research.

Developing the purpose section of your dissertation is usually not achieved in a single flash of insight. The process involves a great deal of reading to find out what other scholars have done to address the research topic and problem you have identified. The purpose section of your dissertation could well be the most important paragraph you write during your academic career, and every word should be carefully selected. Think of it as the DNA of your dissertation. Everything else you write should emerge directly and clearly from your purpose statement. In turn, your purpose statement should emerge directly and clearly from your research problem description. It is good practice to print out your problem statement and purpose statement and keep them in front of you as you work on each part of your dissertation in order to insure alignment.

It is helpful to collect several dissertations similar to the one you envision creating. Extract the problem descriptions and purpose statements of other dissertation authors and compare them in order to sharpen your thinking about your own work.  Comparing how other dissertation authors have handled the many challenges you are facing can be an invaluable exercise. Keep in mind that individual universities use their own tailored protocols for presenting key components of the dissertation so your review of these purpose statements should focus on content rather than form.

Once your purpose statement is set it must be consistently presented throughout the dissertation. This may require some recursive editing because the way you articulate your purpose may evolve as you work on various aspects of your dissertation. Whenever you make an adjustment to your purpose statement you should carefully follow up on the editing and conceptual ramifications throughout the entire document.

In establishing your purpose you should NOT advocate for a particular outcome. Research should be done to answer questions not prove a point. As a researcher, you are to inquire with an open mind, and even when you come to the work with clear assumptions, your job is to prove the validity of the conclusions reached. For example, you would not say the purpose of your research project is to demonstrate that there is a relationship between two variables. Such a statement presupposes you know the answer before your research is conducted and promotes or supports (advocates on behalf of) a particular outcome. A more appropriate purpose statement would be to examine or explore the relationship between two variables.

Your purpose statement should not imply that you are going to prove something. You may be surprised to learn that we cannot prove anything in scholarly research for two reasons. First, in quantitative analyses, statistical tests calculate the probability that something is true rather than establishing it as true. Second, in qualitative research, the study can only purport to describe what is occurring from the perspective of the participants. Whether or not the phenomenon they are describing is true in a larger context is not knowable. We cannot observe the phenomenon in all settings and in all circumstances.

It is important to distinguish in your mind the differences between the Problem Statement and Purpose Statement.

The Problem Statement is why I am doing the research

The Purpose Statement is what type of research I am doing to fit or address the problem

The Purpose Statement includes:

• Method of Study
• Specific Population

Remember, as you are contemplating what to include in your purpose statement and then when you are writing it, the purpose statement is a concise paragraph that describes the intent of the study, and it should flow directly from the problem statement.  It should specifically address the reason for conducting the study, and reflect the research questions.  Further, it should identify the research method as qualitative, quantitative, or mixed.  Then provide a brief overview of how the study will be conducted, with what instruments/data collection methods, and with whom (subjects) and where (as applicable). Finally, you should identify variables/constructs and/or phenomenon/concept/idea.

Qualitative Purpose Statement

Creswell (2002) suggested for writing purpose statements in qualitative research include using deliberate phrasing to alert the reader to the purpose statement. Verbs that indicate what will take place in the research and the use of non-directional language that do not suggest an outcome are key. A purpose statement should focus on a single idea or concept, with a broad definition of the idea or concept. How the concept was investigated should also be included, as well as participants in the study and locations for the research to give the reader a sense of with whom and where the study took place. 

Creswell (2003) advised the following script for purpose statements in qualitative research:

“The purpose of this qualitative_________________ (strategy of inquiry, such as ethnography, case study, or other type) study is (was? will be?) to ________________ (understand? describe? develop? discover?) the _________________(central phenomenon being studied) for ______________ (the participants, such as the individual, groups, organization) at __________(research site). At this stage in the research, the __________ (central phenomenon being studied) will be generally defined as ___________________ (provide a general definition)” (pg. 90).

Quantitative Purpose Statement

Creswell (2003) offers vast differences between the purpose statements written for qualitative research and those written for quantitative research, particularly with respect to language and the inclusion of variables. The comparison of variables is often a focus of quantitative research, with the variables distinguishable by either the temporal order or how they are measured. As with qualitative research purpose statements, Creswell (2003) recommends the use of deliberate language to alert the reader to the purpose of the study, but quantitative purpose statements also include the theory or conceptual framework guiding the study and the variables that are being studied and how they are related. 

Creswell (2003) suggests the following script for drafting purpose statements in quantitative research:

“The purpose of this _____________________ (experiment? survey?) study is (was? will be?) to test the theory of _________________that _________________ (compares? relates?) the ___________(independent variable) to _________________________(dependent variable), controlling for _______________________ (control variables) for ___________________ (participants) at _________________________ (the research site). The independent variable(s) _____________________ will be generally defined as _______________________ (provide a general definition). The dependent variable(s) will be generally defined as _____________________ (provide a general definition), and the control and intervening variables(s), _________________ (identify the control and intervening variables) will be statistically controlled in this study” (pg. 97).

• The purpose of this qualitative study was to determine how participation in service-learning in an alternative school impacted students academically, civically, and personally.  There is ample evidence demonstrating the failure of schools for students at-risk; however, there is still a need to demonstrate why these students are successful in non-traditional educational programs like the service-learning model used at TDS.  This study was unique in that it examined one alternative school’s approach to service-learning in a setting where students not only serve, but faculty serve as volunteer teachers.  The use of a constructivist approach in service-learning in an alternative school setting was examined in an effort to determine whether service-learning participation contributes positively to academic, personal, and civic gain for students, and to examine student and teacher views regarding the overall outcomes of service-learning.  This study was completed using an ethnographic approach that included observations, content analysis, and interviews with teachers at The David School.
• The purpose of this quantitative non-experimental cross-sectional linear multiple regression design was to investigate the relationship among early childhood teachers’ self-reported assessment of multicultural awareness as measured by responses from the Teacher Multicultural Attitude Survey (TMAS) and supervisors’ observed assessment of teachers’ multicultural competency skills as measured by the Multicultural Teaching Competency Scale (MTCS) survey. Demographic data such as number of multicultural training hours, years teaching in Dubai, curriculum program at current school, and age were also examined and their relationship to multicultural teaching competency. The study took place in the emirate of Dubai where there were 14,333 expatriate teachers employed in private schools (KHDA, 2013b).
• The purpose of this quantitative, non-experimental study is to examine the degree to which stages of change, gender, acculturation level and trauma types predicts the reluctance of Arab refugees, aged 18 and over, in the Dearborn, MI area, to seek professional help for their mental health needs. This study will utilize four instruments to measure these variables: University of Rhode Island Change Assessment (URICA: DiClemente & Hughes, 1990); Cumulative Trauma Scale (Kira, 2012); Acculturation Rating Scale for Arabic Americans-II Arabic and English (ARSAA-IIA, ARSAA-IIE: Jadalla & Lee, 2013), and a demographic survey. This study will examine 1) the relationship between stages of change, gender, acculturation levels, and trauma types and Arab refugees’ help-seeking behavior, 2) the degree to which any of these variables can predict Arab refugee help-seeking behavior.  Additionally, the outcome of this study could provide researchers and clinicians with a stage-based model, TTM, for measuring Arab refugees’ help-seeking behavior and lay a foundation for how TTM can help target the clinical needs of Arab refugees. Lastly, this attempt to apply the TTM model to Arab refugees’ condition could lay the foundation for future research to investigate the application of TTM to clinical work among refugee populations.
• The purpose of this qualitative, phenomenological study is to describe the lived experiences of LLM for 10 EFL learners in rural Guatemala and to utilize that data to determine how it conforms to, or possibly challenges, current theoretical conceptions of LLM. In accordance with Morse’s (1994) suggestion that a phenomenological study should utilize at least six participants, this study utilized semi-structured interviews with 10 EFL learners to explore why and how they have experienced the motivation to learn English throughout their lives. The methodology of horizontalization was used to break the interview protocols into individual units of meaning before analyzing these units to extract the overarching themes (Moustakas, 1994). These themes were then interpreted into a detailed description of LLM as experienced by EFL students in this context. Finally, the resulting description was analyzed to discover how these learners’ lived experiences with LLM conformed with and/or diverged from current theories of LLM.
• The purpose of this qualitative, embedded, multiple case study was to examine how both parent-child attachment relationships are impacted by the quality of the paternal and maternal caregiver-child interactions that occur throughout a maternal deployment, within the context of dual-military couples. In order to examine this phenomenon, an embedded, multiple case study was conducted, utilizing an attachment systems metatheory perspective. The study included four dual-military couples who experienced a maternal deployment to Operation Iraqi Freedom (OIF) or Operation Enduring Freedom (OEF) when they had at least one child between 8 weeks-old to 5 years-old.  Each member of the couple participated in an individual, semi-structured interview with the researcher and completed the Parenting Relationship Questionnaire (PRQ). “The PRQ is designed to capture a parent’s perspective on the parent-child relationship” (Pearson, 2012, para. 1) and was used within the proposed study for this purpose. The PRQ was utilized to triangulate the data (Bekhet & Zauszniewski, 2012) as well as to provide some additional information on the parents’ perspective of the quality of the parent-child attachment relationship in regards to communication, discipline, parenting confidence, relationship satisfaction, and time spent together (Pearson, 2012). The researcher utilized the semi-structured interview to collect information regarding the parents' perspectives of the quality of their parental caregiver behaviors during the deployment cycle, the mother's parent-child interactions while deployed, the behavior of the child or children at time of reunification, and the strategies or behaviors the parents believe may have contributed to their child's behavior at the time of reunification. The results of this study may be utilized by the military, and by civilian providers, to develop proactive and preventive measures that both providers and parents can implement, to address any potential adverse effects on the parent-child attachment relationship, identified through the proposed study. The results of this study may also be utilized to further refine and understand the integration of attachment theory and systems theory, in both clinical and research settings, within the field of marriage and family therapy.

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Home Market Research

What is Research: Definition, Methods, Types & Examples

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

• Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

• Identify potential and new customers
• Understand existing customers
• Set pragmatic goals
• Develop productive market strategies
• Address business challenges
• Put together a business expansion plan
• Identify new business opportunities
• Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
• The analysis is based on logical reasoning and involves both inductive and deductive methods.
• Real-time data and knowledge is derived from actual observations in natural settings.
• There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
• It creates a path for generating new questions. Existing data helps create more research opportunities.
• It is analytical and uses all the available data so that there is no ambiguity in inference.
• Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

• Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

• Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

• Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

• One-to-one Interview
• Focus Groups
• Ethnographic studies
• Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

• Survey research
• Descriptive research
• Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

• Valid – founded, logical, rigorous, and impartial.
• Accurate – free of errors and including required details.
• Reliable – other people who investigate in the same way can produce similar results.
• Timely – current and collected within an appropriate time frame.
• Complete – includes all the data you need to support your business decisions.

Gather insights

• Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
• Keep track of the frequency with which each of the main findings appears.
• Make a list of your findings from the most common to the least common.
• Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
• Prepare conclusions and recommendations about your study.
• Act on your strategies
• Look for gaps in the information, and consider doing additional inquiry if necessary
• Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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Home » Scientific Research – Types, Purpose and Guide

Scientific Research – Types, Purpose and Guide

Table of Contents

Scientific Research

Definition:

Scientific research is the systematic and empirical investigation of phenomena, theories, or hypotheses, using various methods and techniques in order to acquire new knowledge or to validate existing knowledge.

It involves the collection, analysis, interpretation, and presentation of data, as well as the formulation and testing of hypotheses. Scientific research can be conducted in various fields, such as natural sciences, social sciences, and engineering, and may involve experiments, observations, surveys, or other forms of data collection. The goal of scientific research is to advance knowledge, improve understanding, and contribute to the development of solutions to practical problems.

Types of Scientific Research

There are different types of scientific research, which can be classified based on their purpose, method, and application. In this response, we will discuss the four main types of scientific research.

Descriptive Research

Descriptive research aims to describe or document a particular phenomenon or situation, without altering it in any way. This type of research is usually done through observation, surveys, or case studies. Descriptive research is useful in generating ideas, understanding complex phenomena, and providing a foundation for future research. However, it does not provide explanations or causal relationships between variables.

Exploratory Research

Exploratory research aims to explore a new area of inquiry or develop initial ideas for future research. This type of research is usually conducted through observation, interviews, or focus groups. Exploratory research is useful in generating hypotheses, identifying research questions, and determining the feasibility of a larger study. However, it does not provide conclusive evidence or establish cause-and-effect relationships.

Experimental Research

Experimental research aims to test cause-and-effect relationships between variables by manipulating one variable and observing the effects on another variable. This type of research involves the use of an experimental group, which receives a treatment, and a control group, which does not receive the treatment. Experimental research is useful in establishing causal relationships, replicating results, and controlling extraneous variables. However, it may not be feasible or ethical to manipulate certain variables in some contexts.

Correlational Research

Correlational research aims to examine the relationship between two or more variables without manipulating them. This type of research involves the use of statistical techniques to determine the strength and direction of the relationship between variables. Correlational research is useful in identifying patterns, predicting outcomes, and testing theories. However, it does not establish causation or control for confounding variables.

Scientific Research Methods

Scientific research methods are used in scientific research to investigate phenomena, acquire knowledge, and answer questions using empirical evidence. Here are some commonly used scientific research methods:

Observational Studies

This method involves observing and recording phenomena as they occur in their natural setting. It can be done through direct observation or by using tools such as cameras, microscopes, or sensors.

Experimental Studies

This method involves manipulating one or more variables to determine the effect on the outcome. This type of study is often used to establish cause-and-effect relationships.

Survey Research

This method involves collecting data from a large number of people by asking them a set of standardized questions. Surveys can be conducted in person, over the phone, or online.

Case Studies

This method involves in-depth analysis of a single individual, group, or organization. Case studies are often used to gain insights into complex or unusual phenomena.

Meta-analysis

This method involves combining data from multiple studies to arrive at a more reliable conclusion. This technique can be used to identify patterns and trends across a large number of studies.

Qualitative Research

This method involves collecting and analyzing non-numerical data, such as interviews, focus groups, or observations. This type of research is often used to explore complex phenomena and to gain an understanding of people’s experiences and perspectives.

Quantitative Research

This method involves collecting and analyzing numerical data using statistical techniques. This type of research is often used to test hypotheses and to establish cause-and-effect relationships.

Longitudinal Studies

This method involves following a group of individuals over a period of time to observe changes and to identify patterns and trends. This type of study can be used to investigate the long-term effects of a particular intervention or exposure.

Data Analysis Methods

There are many different data analysis methods used in scientific research, and the choice of method depends on the type of data being collected and the research question. Here are some commonly used data analysis methods:

• Descriptive statistics: This involves using summary statistics such as mean, median, mode, standard deviation, and range to describe the basic features of the data.
• Inferential statistics: This involves using statistical tests to make inferences about a population based on a sample of data. Examples of inferential statistics include t-tests, ANOVA, and regression analysis.
• Qualitative analysis: This involves analyzing non-numerical data such as interviews, focus groups, and observations. Qualitative analysis may involve identifying themes, patterns, or categories in the data.
• Content analysis: This involves analyzing the content of written or visual materials such as articles, speeches, or images. Content analysis may involve identifying themes, patterns, or categories in the content.
• Data mining: This involves using automated methods to analyze large datasets to identify patterns, trends, or relationships in the data.
• Machine learning: This involves using algorithms to analyze data and make predictions or classifications based on the patterns identified in the data.

Application of Scientific Research

Scientific research has numerous applications in many fields, including:

• Medicine and healthcare: Scientific research is used to develop new drugs, medical treatments, and vaccines. It is also used to understand the causes and risk factors of diseases, as well as to develop new diagnostic tools and medical devices.
• Agriculture : Scientific research is used to develop new crop varieties, to improve crop yields, and to develop more sustainable farming practices.
• Technology and engineering : Scientific research is used to develop new technologies and engineering solutions, such as renewable energy systems, new materials, and advanced manufacturing techniques.
• Environmental science : Scientific research is used to understand the impacts of human activity on the environment and to develop solutions for mitigating those impacts. It is also used to monitor and manage natural resources, such as water and air quality.
• Education : Scientific research is used to develop new teaching methods and educational materials, as well as to understand how people learn and develop.
• Business and economics: Scientific research is used to understand consumer behavior, to develop new products and services, and to analyze economic trends and policies.
• Social sciences : Scientific research is used to understand human behavior, attitudes, and social dynamics. It is also used to develop interventions to improve social welfare and to inform public policy.

How to Conduct Scientific Research

Conducting scientific research involves several steps, including:

• Identify a research question: Start by identifying a question or problem that you want to investigate. This question should be clear, specific, and relevant to your field of study.
• Conduct a literature review: Before starting your research, conduct a thorough review of existing research in your field. This will help you identify gaps in knowledge and develop hypotheses or research questions.
• Develop a research plan: Once you have a research question, develop a plan for how you will collect and analyze data to answer that question. This plan should include a detailed methodology, a timeline, and a budget.
• Collect data: Depending on your research question and methodology, you may collect data through surveys, experiments, observations, or other methods.
• Analyze data: Once you have collected your data, analyze it using appropriate statistical or qualitative methods. This will help you draw conclusions about your research question.
• Interpret results: Based on your analysis, interpret your results and draw conclusions about your research question. Discuss any limitations or implications of your findings.
• Communicate results: Finally, communicate your findings to others in your field through presentations, publications, or other means.

Purpose of Scientific Research

The purpose of scientific research is to systematically investigate phenomena, acquire new knowledge, and advance our understanding of the world around us. Scientific research has several key goals, including:

• Exploring the unknown: Scientific research is often driven by curiosity and the desire to explore uncharted territory. Scientists investigate phenomena that are not well understood, in order to discover new insights and develop new theories.
• Testing hypotheses: Scientific research involves developing hypotheses or research questions, and then testing them through observation and experimentation. This allows scientists to evaluate the validity of their ideas and refine their understanding of the phenomena they are studying.
• Solving problems: Scientific research is often motivated by the desire to solve practical problems or address real-world challenges. For example, researchers may investigate the causes of a disease in order to develop new treatments, or explore ways to make renewable energy more affordable and accessible.
• Advancing knowledge: Scientific research is a collective effort to advance our understanding of the world around us. By building on existing knowledge and developing new insights, scientists contribute to a growing body of knowledge that can be used to inform decision-making, solve problems, and improve our lives.

Examples of Scientific Research

Here are some examples of scientific research that are currently ongoing or have recently been completed:

• Clinical trials for new treatments: Scientific research in the medical field often involves clinical trials to test new treatments for diseases and conditions. For example, clinical trials may be conducted to evaluate the safety and efficacy of new drugs or medical devices.
• Genomics research: Scientists are conducting research to better understand the human genome and its role in health and disease. This includes research on genetic mutations that can cause diseases such as cancer, as well as the development of personalized medicine based on an individual’s genetic makeup.
• Climate change: Scientific research is being conducted to understand the causes and impacts of climate change, as well as to develop solutions for mitigating its effects. This includes research on renewable energy technologies, carbon capture and storage, and sustainable land use practices.
• Neuroscience : Scientists are conducting research to understand the workings of the brain and the nervous system, with the goal of developing new treatments for neurological disorders such as Alzheimer’s disease and Parkinson’s disease.
• Artificial intelligence: Researchers are working to develop new algorithms and technologies to improve the capabilities of artificial intelligence systems. This includes research on machine learning, computer vision, and natural language processing.
• Space exploration: Scientific research is being conducted to explore the cosmos and learn more about the origins of the universe. This includes research on exoplanets, black holes, and the search for extraterrestrial life.

When to use Scientific Research

Some specific situations where scientific research may be particularly useful include:

• Solving problems: Scientific research can be used to investigate practical problems or address real-world challenges. For example, scientists may investigate the causes of a disease in order to develop new treatments, or explore ways to make renewable energy more affordable and accessible.
• Decision-making: Scientific research can provide evidence-based information to inform decision-making. For example, policymakers may use scientific research to evaluate the effectiveness of different policy options or to make decisions about public health and safety.
• Innovation : Scientific research can be used to develop new technologies, products, and processes. For example, research on materials science can lead to the development of new materials with unique properties that can be used in a range of applications.
• Knowledge creation : Scientific research is an important way of generating new knowledge and advancing our understanding of the world around us. This can lead to new theories, insights, and discoveries that can benefit society.

Advantages of Scientific Research

There are many advantages of scientific research, including:

• Improved understanding : Scientific research allows us to gain a deeper understanding of the world around us, from the smallest subatomic particles to the largest celestial bodies.
• Evidence-based decision making: Scientific research provides evidence-based information that can inform decision-making in many fields, from public policy to medicine.
• Technological advancements: Scientific research drives technological advancements in fields such as medicine, engineering, and materials science. These advancements can improve quality of life, increase efficiency, and reduce costs.
• New discoveries: Scientific research can lead to new discoveries and breakthroughs that can advance our knowledge in many fields. These discoveries can lead to new theories, technologies, and products.
• Economic benefits : Scientific research can stimulate economic growth by creating new industries and jobs, and by generating new technologies and products.
• Improved health outcomes: Scientific research can lead to the development of new medical treatments and technologies that can improve health outcomes and quality of life for people around the world.
• Increased innovation: Scientific research encourages innovation by promoting collaboration, creativity, and curiosity. This can lead to new and unexpected discoveries that can benefit society.

Limitations of Scientific Research

Scientific research has some limitations that researchers should be aware of. These limitations can include:

• Research design limitations : The design of a research study can impact the reliability and validity of the results. Poorly designed studies can lead to inaccurate or inconclusive results. Researchers must carefully consider the study design to ensure that it is appropriate for the research question and the population being studied.
• Sample size limitations: The size of the sample being studied can impact the generalizability of the results. Small sample sizes may not be representative of the larger population, and may lead to incorrect conclusions.
• Time and resource limitations: Scientific research can be costly and time-consuming. Researchers may not have the resources necessary to conduct a large-scale study, or may not have sufficient time to complete a study with appropriate controls and analysis.
• Ethical limitations : Certain types of research may raise ethical concerns, such as studies involving human or animal subjects. Ethical concerns may limit the scope of the research that can be conducted, or require additional protocols and procedures to ensure the safety and well-being of participants.
• Limitations of technology: Technology may limit the types of research that can be conducted, or the accuracy of the data collected. For example, certain types of research may require advanced technology that is not yet available, or may be limited by the accuracy of current measurement tools.
• Limitations of existing knowledge: Existing knowledge may limit the types of research that can be conducted. For example, if there is limited knowledge in a particular field, it may be difficult to design a study that can provide meaningful results.

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Researcher, Academic Writer, Web developer

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Doing Research in Education: Theory and Practice

Student resources, 1. the purpose of research: why do we do it.

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Brace, M., Herriotts, P., Mccullagh, A. and Nzegwu, F. (2007) ‘Why research — what research should be done?: Report of a collaborative workshop in the UK to discuss social research priorities on visual impairment’, British Journal of Visual Impairment , 25(2): 178–189.

Hannah, D.R. and Lautsch, B.A. (2010) ‘Counting in Qualitative Research: Why to Conduct it, When to Avoid it, and When to Closet it’, in Journal of Management Inquiry , 20(1): 14–22.

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Study designs: Part 1 – An overview and classification

Priya ranganathan.

Department of Anaesthesiology, Tata Memorial Centre, Mumbai, Maharashtra, India

Rakesh Aggarwal

1 Department of Gastroenterology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India

There are several types of research study designs, each with its inherent strengths and flaws. The study design used to answer a particular research question depends on the nature of the question and the availability of resources. In this article, which is the first part of a series on “study designs,” we provide an overview of research study designs and their classification. The subsequent articles will focus on individual designs.

INTRODUCTION

Research study design is a framework, or the set of methods and procedures used to collect and analyze data on variables specified in a particular research problem.

Research study designs are of many types, each with its advantages and limitations. The type of study design used to answer a particular research question is determined by the nature of question, the goal of research, and the availability of resources. Since the design of a study can affect the validity of its results, it is important to understand the different types of study designs and their strengths and limitations.

There are some terms that are used frequently while classifying study designs which are described in the following sections.

A variable represents a measurable attribute that varies across study units, for example, individual participants in a study, or at times even when measured in an individual person over time. Some examples of variables include age, sex, weight, height, health status, alive/dead, diseased/healthy, annual income, smoking yes/no, and treated/untreated.

Exposure (or intervention) and outcome variables

A large proportion of research studies assess the relationship between two variables. Here, the question is whether one variable is associated with or responsible for change in the value of the other variable. Exposure (or intervention) refers to the risk factor whose effect is being studied. It is also referred to as the independent or the predictor variable. The outcome (or predicted or dependent) variable develops as a consequence of the exposure (or intervention). Typically, the term “exposure” is used when the “causative” variable is naturally determined (as in observational studies – examples include age, sex, smoking, and educational status), and the term “intervention” is preferred where the researcher assigns some or all participants to receive a particular treatment for the purpose of the study (experimental studies – e.g., administration of a drug). If a drug had been started in some individuals but not in the others, before the study started, this counts as exposure, and not as intervention – since the drug was not started specifically for the study.

Observational versus interventional (or experimental) studies

Observational studies are those where the researcher is documenting a naturally occurring relationship between the exposure and the outcome that he/she is studying. The researcher does not do any active intervention in any individual, and the exposure has already been decided naturally or by some other factor. For example, looking at the incidence of lung cancer in smokers versus nonsmokers, or comparing the antenatal dietary habits of mothers with normal and low-birth babies. In these studies, the investigator did not play any role in determining the smoking or dietary habit in individuals.

For an exposure to determine the outcome, it must precede the latter. Any variable that occurs simultaneously with or following the outcome cannot be causative, and hence is not considered as an “exposure.”

Observational studies can be either descriptive (nonanalytical) or analytical (inferential) – this is discussed later in this article.

Interventional studies are experiments where the researcher actively performs an intervention in some or all members of a group of participants. This intervention could take many forms – for example, administration of a drug or vaccine, performance of a diagnostic or therapeutic procedure, and introduction of an educational tool. For example, a study could randomly assign persons to receive aspirin or placebo for a specific duration and assess the effect on the risk of developing cerebrovascular events.

Descriptive versus analytical studies

Descriptive (or nonanalytical) studies, as the name suggests, merely try to describe the data on one or more characteristics of a group of individuals. These do not try to answer questions or establish relationships between variables. Examples of descriptive studies include case reports, case series, and cross-sectional surveys (please note that cross-sectional surveys may be analytical studies as well – this will be discussed in the next article in this series). Examples of descriptive studies include a survey of dietary habits among pregnant women or a case series of patients with an unusual reaction to a drug.

Analytical studies attempt to test a hypothesis and establish causal relationships between variables. In these studies, the researcher assesses the effect of an exposure (or intervention) on an outcome. As described earlier, analytical studies can be observational (if the exposure is naturally determined) or interventional (if the researcher actively administers the intervention).

Directionality of study designs

Based on the direction of inquiry, study designs may be classified as forward-direction or backward-direction. In forward-direction studies, the researcher starts with determining the exposure to a risk factor and then assesses whether the outcome occurs at a future time point. This design is known as a cohort study. For example, a researcher can follow a group of smokers and a group of nonsmokers to determine the incidence of lung cancer in each. In backward-direction studies, the researcher begins by determining whether the outcome is present (cases vs. noncases [also called controls]) and then traces the presence of prior exposure to a risk factor. These are known as case–control studies. For example, a researcher identifies a group of normal-weight babies and a group of low-birth weight babies and then asks the mothers about their dietary habits during the index pregnancy.

Prospective versus retrospective study designs

The terms “prospective” and “retrospective” refer to the timing of the research in relation to the development of the outcome. In retrospective studies, the outcome of interest has already occurred (or not occurred – e.g., in controls) in each individual by the time s/he is enrolled, and the data are collected either from records or by asking participants to recall exposures. There is no follow-up of participants. By contrast, in prospective studies, the outcome (and sometimes even the exposure or intervention) has not occurred when the study starts and participants are followed up over a period of time to determine the occurrence of outcomes. Typically, most cohort studies are prospective studies (though there may be retrospective cohorts), whereas case–control studies are retrospective studies. An interventional study has to be, by definition, a prospective study since the investigator determines the exposure for each study participant and then follows them to observe outcomes.

The terms “prospective” versus “retrospective” studies can be confusing. Let us think of an investigator who starts a case–control study. To him/her, the process of enrolling cases and controls over a period of several months appears prospective. Hence, the use of these terms is best avoided. Or, at the very least, one must be clear that the terms relate to work flow for each individual study participant, and not to the study as a whole.

Classification of study designs

Figure 1 depicts a simple classification of research study designs. The Centre for Evidence-based Medicine has put forward a useful three-point algorithm which can help determine the design of a research study from its methods section:[ 1 ]

Classification of research study designs

• Does the study describe the characteristics of a sample or does it attempt to analyze (or draw inferences about) the relationship between two variables? – If no, then it is a descriptive study, and if yes, it is an analytical (inferential) study
• If analytical, did the investigator determine the exposure? – If no, it is an observational study, and if yes, it is an experimental study
• If observational, when was the outcome determined? – at the start of the study (case–control study), at the end of a period of follow-up (cohort study), or simultaneously (cross sectional).

In the next few pieces in the series, we will discuss various study designs in greater detail.

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educational research techniques

Research techniques and education.

Research Purpose, Hypotheses, and Questions

Four key components to a research project are the purpose statement, research questions, hypotheses, and research objectives. In this post, we will define each of these.

Definitions

The purpose of this study is to examine the relationship between college completion and organizational commitment of undergraduate students in Thailand. 

Here is an example of a qualitative purpose statement.

The purpose of this study is to explore student experiences at a university in Thailand about completing their tertiary degree.

Both of these examples are short one-sentence responses to what the study will attempt to do. This is a critical first step in shaping the study.

Research Question

The research question(s) in a quantitative or qualitative study narrows the purpose down to a specific question(s) for the researcher to find answers. Below are examples from both the quantitative and qualitative perspective. We are continuing the research themes from the previous section on the purpose statement.

Quantitative

Does organizational commitment affect college completion of students?

Qualitative

What kinds of experiences have students had while completing their degree?

On closer examination, you may have noticed that the research questions sound a lot like the purpose statement. Research questions often split a part a long complex purpose statement into several questions. This is why questions sound so redundant when compared to the purpose statement. Despite this apparent problem, this thought process helps researchers to organize their thinking and proceed in a manner that is much more efficient.

The next two components only relate to quantitative research and they are the hypotheses and research objective(s). For this reason our illustration of qualitative concepts will stop at this point.

Hypotheses are statements a researcher makes about the potential outcome(s) of a study based on the examination of literature. Below is an example from the same theme as before.

Students who have a higher perception of organizational commitment will also have a higher likelihood of completing college.

Again, the wording of the research questions, hypotheses and purpose statement are similarly. The difference is only slightly and is due to context. Seeing these similarities quickly will help you to move faster in finishing a study. The difference between these elements is a matter of perspective rather than a strong difference, as they do sound awfully similar.

Research Objectives

Research objectives are the goals a researcher has for a study. This component is not always included in a study. Below is an example.

To examine the correlation between organizational commitment and the rate of college completion

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10 thoughts on “ research purpose, hypotheses, and questions ”.

This is the wrong use of the word, it should be “their” not “there”.

The purpose of this study is to explore student experiences at a university in Thailand about completing there tertiary degree.

Whoops, thanks for catching that

Thank you for this, very helpful 🙂

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This was helpful. Thank you

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This was helpful.

Glad to be of service

As an emerging researcher, my worry is that I have six objectives but five research questions and hypotheses. Am I correct or they must all be the same in times of numbers? Thank you

Thank you, this information helped me so much.

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11.1 The Purpose of Research Writing

Learning objectives.

• Identify reasons to research writing projects.
• Outline the steps of the research writing process.

Why was the Great Wall of China built? What have scientists learned about the possibility of life on Mars? What roles did women play in the American Revolution? How does the human brain create, store, and retrieve memories? Who invented the game of football, and how has it changed over the years?

You may know the answers to these questions off the top of your head. If you are like most people, however, you find answers to tough questions like these by searching the Internet, visiting the library, or asking others for information. To put it simply, you perform research.

Whether you are a scientist, an artist, a paralegal, or a parent, you probably perform research in your everyday life. When your boss, your instructor, or a family member asks you a question that you do not know the answer to, you locate relevant information, analyze your findings, and share your results. Locating, analyzing, and sharing information are key steps in the research process, and in this chapter, you will learn more about each step. By developing your research writing skills, you will prepare yourself to answer any question no matter how challenging.

Reasons for Research

When you perform research, you are essentially trying to solve a mystery—you want to know how something works or why something happened. In other words, you want to answer a question that you (and other people) have about the world. This is one of the most basic reasons for performing research.

But the research process does not end when you have solved your mystery. Imagine what would happen if a detective collected enough evidence to solve a criminal case, but she never shared her solution with the authorities. Presenting what you have learned from research can be just as important as performing the research. Research results can be presented in a variety of ways, but one of the most popular—and effective—presentation forms is the research paper . A research paper presents an original thesis, or purpose statement, about a topic and develops that thesis with information gathered from a variety of sources.

If you are curious about the possibility of life on Mars, for example, you might choose to research the topic. What will you do, though, when your research is complete? You will need a way to put your thoughts together in a logical, coherent manner. You may want to use the facts you have learned to create a narrative or to support an argument. And you may want to show the results of your research to your friends, your teachers, or even the editors of magazines and journals. Writing a research paper is an ideal way to organize thoughts, craft narratives or make arguments based on research, and share your newfound knowledge with the world.

Write a paragraph about a time when you used research in your everyday life. Did you look for the cheapest way to travel from Houston to Denver? Did you search for a way to remove gum from the bottom of your shoe? In your paragraph, explain what you wanted to research, how you performed the research, and what you learned as a result.

Research Writing and the Academic Paper

No matter what field of study you are interested in, you will most likely be asked to write a research paper during your academic career. For example, a student in an art history course might write a research paper about an artist’s work. Similarly, a student in a psychology course might write a research paper about current findings in childhood development.

Having to write a research paper may feel intimidating at first. After all, researching and writing a long paper requires a lot of time, effort, and organization. However, writing a research paper can also be a great opportunity to explore a topic that is particularly interesting to you. The research process allows you to gain expertise on a topic of your choice, and the writing process helps you remember what you have learned and understand it on a deeper level.

Research Writing at Work

Knowing how to write a good research paper is a valuable skill that will serve you well throughout your career. Whether you are developing a new product, studying the best way to perform a procedure, or learning about challenges and opportunities in your field of employment, you will use research techniques to guide your exploration. You may even need to create a written report of your findings. And because effective communication is essential to any company, employers seek to hire people who can write clearly and professionally.

Writing at Work

Take a few minutes to think about each of the following careers. How might each of these professionals use researching and research writing skills on the job?

• Medical laboratory technician
• Small business owner
• Information technology professional
• Freelance magazine writer

A medical laboratory technician or information technology professional might do research to learn about the latest technological developments in either of these fields. A small business owner might conduct research to learn about the latest trends in his or her industry. A freelance magazine writer may need to research a given topic to write an informed, up-to-date article.

Think about the job of your dreams. How might you use research writing skills to perform that job? Create a list of ways in which strong researching, organizing, writing, and critical thinking skills could help you succeed at your dream job. How might these skills help you obtain that job?

Steps of the Research Writing Process

How does a research paper grow from a folder of brainstormed notes to a polished final draft? No two projects are identical, but most projects follow a series of six basic steps.

These are the steps in the research writing process:

• Choose a topic.
• Plan and schedule time to research and write.
• Conduct research.
• Organize research and ideas.
• Draft your paper.
• Revise and edit your paper.

Each of these steps will be discussed in more detail later in this chapter. For now, though, we will take a brief look at what each step involves.

Step 1: Choosing a Topic

As you may recall from Chapter 8 “The Writing Process: How Do I Begin?” , to narrow the focus of your topic, you may try freewriting exercises, such as brainstorming. You may also need to ask a specific research question —a broad, open-ended question that will guide your research—as well as propose a possible answer, or a working thesis . You may use your research question and your working thesis to create a research proposal . In a research proposal, you present your main research question, any related subquestions you plan to explore, and your working thesis.

Step 2: Planning and Scheduling

Before you start researching your topic, take time to plan your researching and writing schedule. Research projects can take days, weeks, or even months to complete. Creating a schedule is a good way to ensure that you do not end up being overwhelmed by all the work you have to do as the deadline approaches.

During this step of the process, it is also a good idea to plan the resources and organizational tools you will use to keep yourself on track throughout the project. Flowcharts, calendars, and checklists can all help you stick to your schedule. See Chapter 11 “Writing from Research: What Will I Learn?” , Section 11.2 “Steps in Developing a Research Proposal” for an example of a research schedule.

Step 3: Conducting Research

When going about your research, you will likely use a variety of sources—anything from books and periodicals to video presentations and in-person interviews.

Your sources will include both primary sources and secondary sources . Primary sources provide firsthand information or raw data. For example, surveys, in-person interviews, and historical documents are primary sources. Secondary sources, such as biographies, literary reviews, or magazine articles, include some analysis or interpretation of the information presented. As you conduct research, you will take detailed, careful notes about your discoveries. You will also evaluate the reliability of each source you find.

Step 4: Organizing Research and the Writer’s Ideas

When your research is complete, you will organize your findings and decide which sources to cite in your paper. You will also have an opportunity to evaluate the evidence you have collected and determine whether it supports your thesis, or the focus of your paper. You may decide to adjust your thesis or conduct additional research to ensure that your thesis is well supported.

Remember, your working thesis is not set in stone. You can and should change your working thesis throughout the research writing process if the evidence you find does not support your original thesis. Never try to force evidence to fit your argument. For example, your working thesis is “Mars cannot support life-forms.” Yet, a week into researching your topic, you find an article in the New York Times detailing new findings of bacteria under the Martian surface. Instead of trying to argue that bacteria are not life forms, you might instead alter your thesis to “Mars cannot support complex life-forms.”

Step 5: Drafting Your Paper

Now you are ready to combine your research findings with your critical analysis of the results in a rough draft. You will incorporate source materials into your paper and discuss each source thoughtfully in relation to your thesis or purpose statement.

When you cite your reference sources, it is important to pay close attention to standard conventions for citing sources in order to avoid plagiarism , or the practice of using someone else’s words without acknowledging the source. Later in this chapter, you will learn how to incorporate sources in your paper and avoid some of the most common pitfalls of attributing information.

Step 6: Revising and Editing Your Paper

In the final step of the research writing process, you will revise and polish your paper. You might reorganize your paper’s structure or revise for unity and cohesion, ensuring that each element in your paper flows into the next logically and naturally. You will also make sure that your paper uses an appropriate and consistent tone.

Once you feel confident in the strength of your writing, you will edit your paper for proper spelling, grammar, punctuation, mechanics, and formatting. When you complete this final step, you will have transformed a simple idea or question into a thoroughly researched and well-written paper you can be proud of!

Review the steps of the research writing process. Then answer the questions on your own sheet of paper.

• In which steps of the research writing process are you allowed to change your thesis?
• In step 2, which types of information should you include in your project schedule?
• What might happen if you eliminated step 4 from the research writing process?

Key Takeaways

• People undertake research projects throughout their academic and professional careers in order to answer specific questions, share their findings with others, increase their understanding of challenging topics, and strengthen their researching, writing, and analytical skills.
• The research writing process generally comprises six steps: choosing a topic, scheduling and planning time for research and writing, conducting research, organizing research and ideas, drafting a paper, and revising and editing the paper.

Writing for Success Copyright © 2015 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

2.1 Why Is Research Important?

Learning objectives.

By the end of this section, you will be able to:

• Explain how scientific research addresses questions about behavior
• Discuss how scientific research guides public policy
• Appreciate how scientific research can be important in making personal decisions

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession ( Figure 2.2 ). It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This chapter explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

Use of Research Information

Trying to determine which theories are and are not accepted by the scientific community can be difficult, especially in an area of research as broad as psychology. More than ever before, we have an incredible amount of information at our fingertips, and a simple internet search on any given research topic might result in a number of contradictory studies. In these cases, we are witnessing the scientific community going through the process of reaching a consensus, and it could be quite some time before a consensus emerges. For example, the explosion in our use of technology has led researchers to question whether this ultimately helps or hinders us. The use and implementation of technology in educational settings has become widespread over the last few decades. Researchers are coming to different conclusions regarding the use of technology. To illustrate this point, a study investigating a smartphone app targeting surgery residents (graduate students in surgery training) found that the use of this app can increase student engagement and raise test scores (Shaw & Tan, 2015). Conversely, another study found that the use of technology in undergraduate student populations had negative impacts on sleep, communication, and time management skills (Massimini & Peterson, 2009). Until sufficient amounts of research have been conducted, there will be no clear consensus on the effects that technology has on a student's acquisition of knowledge, study skills, and mental health.

In the meantime, we should strive to think critically about the information we encounter by exercising a degree of healthy skepticism. When someone makes a claim, we should examine the claim from a number of different perspectives: what is the expertise of the person making the claim, what might they gain if the claim is valid, does the claim seem justified given the evidence, and what do other researchers think of the claim? This is especially important when we consider how much information in advertising campaigns and on the internet claims to be based on “scientific evidence” when in actuality it is a belief or perspective of just a few individuals trying to sell a product or draw attention to their perspectives.

We should be informed consumers of the information made available to us because decisions based on this information have significant consequences. One such consequence can be seen in politics and public policy. Imagine that you have been elected as the governor of your state. One of your responsibilities is to manage the state budget and determine how to best spend your constituents’ tax dollars. As the new governor, you need to decide whether to continue funding early intervention programs. These programs are designed to help children who come from low-income backgrounds, have special needs, or face other disadvantages. These programs may involve providing a wide variety of services to maximize the children's development and position them for optimal levels of success in school and later in life (Blann, 2005). While such programs sound appealing, you would want to be sure that they also proved effective before investing additional money in these programs. Fortunately, psychologists and other scientists have conducted vast amounts of research on such programs and, in general, the programs are found to be effective (Neil & Christensen, 2009; Peters-Scheffer, Didden, Korzilius, & Sturmey, 2011). While not all programs are equally effective, and the short-term effects of many such programs are more pronounced, there is reason to believe that many of these programs produce long-term benefits for participants (Barnett, 2011). If you are committed to being a good steward of taxpayer money, you would want to look at research. Which programs are most effective? What characteristics of these programs make them effective? Which programs promote the best outcomes? After examining the research, you would be best equipped to make decisions about which programs to fund.

Link to Learning

Watch this video about early childhood program effectiveness to learn how scientists evaluate effectiveness and how best to invest money into programs that are most effective.

Ultimately, it is not just politicians who can benefit from using research in guiding their decisions. We all might look to research from time to time when making decisions in our lives. Imagine that your sister, Maria, expresses concern about her two-year-old child, Umberto. Umberto does not speak as much or as clearly as the other children in his daycare or others in the family. Umberto's pediatrician undertakes some screening and recommends an evaluation by a speech pathologist, but does not refer Maria to any other specialists. Maria is concerned that Umberto's speech delays are signs of a developmental disorder, but Umberto's pediatrician does not; she sees indications of differences in Umberto's jaw and facial muscles. Hearing this, you do some internet searches, but you are overwhelmed by the breadth of information and the wide array of sources. You see blog posts, top-ten lists, advertisements from healthcare providers, and recommendations from several advocacy organizations. Why are there so many sites? Which are based in research, and which are not?

In the end, research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

NOTABLE RESEARCHERS

Psychological research has a long history involving important figures from diverse backgrounds. While the introductory chapter discussed several researchers who made significant contributions to the discipline, there are many more individuals who deserve attention in considering how psychology has advanced as a science through their work ( Figure 2.3 ). For instance, Margaret Floy Washburn (1871–1939) was the first woman to earn a PhD in psychology. Her research focused on animal behavior and cognition (Margaret Floy Washburn, PhD, n.d.). Mary Whiton Calkins (1863–1930) was a preeminent first-generation American psychologist who opposed the behaviorist movement, conducted significant research into memory, and established one of the earliest experimental psychology labs in the United States (Mary Whiton Calkins, n.d.).

Francis Sumner (1895–1954) was the first African American to receive a PhD in psychology in 1920. His dissertation focused on issues related to psychoanalysis. Sumner also had research interests in racial bias and educational justice. Sumner was one of the founders of Howard University’s department of psychology, and because of his accomplishments, he is sometimes referred to as the “Father of Black Psychology.” Thirteen years later, Inez Beverly Prosser (1895–1934) became the first African American woman to receive a PhD in psychology. Prosser’s research highlighted issues related to education in segregated versus integrated schools, and ultimately, her work was very influential in the hallmark Brown v. Board of Education Supreme Court ruling that segregation of public schools was unconstitutional (Ethnicity and Health in America Series: Featured Psychologists, n.d.).

Although the establishment of psychology’s scientific roots occurred first in Europe and the United States, it did not take much time until researchers from around the world began to establish their own laboratories and research programs. For example, some of the first experimental psychology laboratories in South America were founded by Horatio Piñero (1869–1919) at two institutions in Buenos Aires, Argentina (Godoy & Brussino, 2010). In India, Gunamudian David Boaz (1908–1965) and Narendra Nath Sen Gupta (1889–1944) established the first independent departments of psychology at the University of Madras and the University of Calcutta, respectively. These developments provided an opportunity for Indian researchers to make important contributions to the field (Gunamudian David Boaz, n.d.; Narendra Nath Sen Gupta, n.d.).

When the American Psychological Association (APA) was first founded in 1892, all of the members were White males (Women and Minorities in Psychology, n.d.). However, by 1905, Mary Whiton Calkins was elected as the first female president of the APA, and by 1946, nearly one-quarter of American psychologists were female. Psychology became a popular degree option for students enrolled in the nation’s historically Black higher education institutions, increasing the number of Black Americans who went on to become psychologists. Given demographic shifts occurring in the United States and increased access to higher educational opportunities among historically underrepresented populations, there is reason to hope that the diversity of the field will increasingly match the larger population, and that the research contributions made by the psychologists of the future will better serve people of all backgrounds (Women and Minorities in Psychology, n.d.).

The Process of Scientific Research

Scientific knowledge is advanced through a process known as the scientific method . Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on. In this sense, the scientific process is circular. The types of reasoning within the circle are called deductive and inductive. In deductive reasoning , ideas are tested in the real world; in inductive reasoning , real-world observations lead to new ideas ( Figure 2.4 ). These processes are inseparable, like inhaling and exhaling, but different research approaches place different emphasis on the deductive and inductive aspects.

In the scientific context, deductive reasoning begins with a generalization—one hypothesis—that is then used to reach logical conclusions about the real world. If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct. A deductive reasoning argument might go something like this: All living things require energy to survive (this would be your hypothesis). Ducks are living things. Therefore, ducks require energy to survive (logical conclusion). In this example, the hypothesis is correct; therefore, the conclusion is correct as well. Sometimes, however, an incorrect hypothesis may lead to a logical but incorrect conclusion. Consider this argument: all ducks are born with the ability to see. Quackers is a duck. Therefore, Quackers was born with the ability to see. Scientists use deductive reasoning to empirically test their hypotheses. Returning to the example of the ducks, researchers might design a study to test the hypothesis that if all living things require energy to survive, then ducks will be found to require energy to survive.

Deductive reasoning starts with a generalization that is tested against real-world observations; however, inductive reasoning moves in the opposite direction. Inductive reasoning uses empirical observations to construct broad generalizations. Unlike deductive reasoning, conclusions drawn from inductive reasoning may or may not be correct, regardless of the observations on which they are based. For instance, you may notice that your favorite fruits—apples, bananas, and oranges—all grow on trees; therefore, you assume that all fruit must grow on trees. This would be an example of inductive reasoning, and, clearly, the existence of strawberries, blueberries, and kiwi demonstrate that this generalization is not correct despite it being based on a number of direct observations. Scientists use inductive reasoning to formulate theories, which in turn generate hypotheses that are tested with deductive reasoning. In the end, science involves both deductive and inductive processes.

For example, case studies, which you will read about in the next section, are heavily weighted on the side of empirical observations. Thus, case studies are closely associated with inductive processes as researchers gather massive amounts of observations and seek interesting patterns (new ideas) in the data. Experimental research, on the other hand, puts great emphasis on deductive reasoning.

We’ve stated that theories and hypotheses are ideas, but what sort of ideas are they, exactly? A theory is a well-developed set of ideas that propose an explanation for observed phenomena. Theories are repeatedly checked against the world, but they tend to be too complex to be tested all at once; instead, researchers create hypotheses to test specific aspects of a theory.

A hypothesis is a testable prediction about how the world will behave if our idea is correct, and it is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests Figure 2.5 .

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later chapter, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

A scientific hypothesis is also falsifiable , or capable of being shown to be incorrect. Recall from the introductory chapter that Sigmund Freud had lots of interesting ideas to explain various human behaviors ( Figure 2.6 ). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Scientific research’s dependence on falsifiability allows for great confidence in the information that it produces. Typically, by the time information is accepted by the scientific community, it has been tested repeatedly.

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The purpose of qualitative research

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• Janice M. Morse 3 &
• Peggy Anne Field 4  

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Research fills a vital and important role in society: it is the means by which discoveries are made, ideas are confirmed or refuted, events controlled or predicted and theory developed or refined. All of these functions contribute to the development of knowledge. However, no single research approach fulfills all of these functions, and the contribution of qualitative research is both vital and unique to the goals of research in general. Qualitative research enables us to make sense of reality, to describe and explain the social world and to develop explanatory models and theories. It is the primary means by which the theoretical foundations of social sciences may be constructed or re-examined.

Research is to see what everybody has seen and to think what nobody has thought. (Albert Szent-Gyorgy)

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Further Reading

Atkinson, P. (1994) Some perils of paradigms. Qualitative Health Research , 5 (1).

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Gilbert, N. (ed.) (1993) Researching Social Life , Sage, London.

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Hammersley, M. (ed) (1993) Social Research: Philosophy, Politics and Practice , Sage, London.

Morse, J.M. (ed.) (1992) Part I: The characteristics of qualitative research, in Qualitative Health Research , Sage, Newbury Park, CA, pp. 69–90.

Morse, J.M., Bottorff, J.L., Neander, W. et al. (1991/1992) Comparative analysis of conceptualizations and theories of caring, in Qualitative Health Research , (ed. J.M. Morse), Sage, Newbury Park, CA, pp. 69–90.

Noblit, G.W. and Engel, J.D. (1991/1992) The holistic injunction: an ideal and a moral imperative for qualitative research, in Qualitative Health Research , (ed. J.M. Morse), Sage, Newbury Park, CA, pp. 43–63.

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Smith, R.B. and Manning, P.K. (eds) (1982) A Handbook of Social Science Methods , Ballinger, Cambridge, MA.

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Purpose of the Study: Common Errors in Writing Your Purpose Statement

The Purpose of the Study is perhaps the single most important sentence in your dissertation. In conjunction with the Problem Statement, it guides the focus of your research. Your research questions, methodology, and data analysis are all guided by the purpose of the study.

The “Purpose of the Study” section consists of a few short paragraphs describing, aptly, the purpose of your study. Within this section is the “Purpose Statement,” which is a single sentence.

It’s the distillation of your study’s purpose, and that particular sentence will show up again and again in your paper. It generally includes (a) the research paradigm, (b) the intent of the study (such as describe, develop, explore, etc.), and (c) the phenomenon of interest.

It’s also a sentence that many students struggle with, and find themselves revising multiple times before it’s finally accepted. My goal here is to give you all the information you need to create a stellar purpose statement the first time around.

Purpose of the Study in a Single Sentence

Your purpose statement distills the purpose of your study into a single sentence. It indicates the study’s method and overarching goal. This sentence is contained in the “Purpose of the Study” section. It should be a logical, explicit research response to the stated problem (more on that later). 

Elements of the Purpose Statement: 

Include the following elements in your purpose statement:

• Identify the research method (qualitative, quantitative, or mixed-method. Usually this is as simple as saying, “the purpose of this qualitative study is…”).
• The stated purpose reflects the research questions (make sure to identify variables/constructs and the central phenomenon/concept/idea).
• Clearly state the research design.
• Ensure the purpose (as well as the method/design) is aligned with the problem statement.  
• Identify participants or other data sources. 
• Identify the geographic location of study (when relevant).

Purpose of the Study Template

For Qualitative Studies

The purpose of this quantitative study is to ___[describe, compare, explore, or develop] ____ [describe the study goal that directly reflects and encompasses the research questions] in [describe the population or data source and geographic location]. [Brief overview of how, with what instruments/data, with whom, and where]

For Quantitative Studies:

The purpose of this quantitative study is to ___[describe, compare, correlate, explore, or develop] ____ [describe the study goal that directly reflects and encompasses the research questions] in [describe the population or data source and geographic location]. [State the independent, dependent, and covariate variables]. [Brief overview of how, with what instruments/data, with whom, and where]

How Long Should the Purpose of the Study Section Be?

Speaking with a Dissertation Chair about the Purpose of the Study section, he said simply, “Don’t make it too long. State the purpose and go onto something else.” That’s good advice. 

Treat dissertation sections like testifying in court (anything you say can and will be used against you by your committee). If you’re asked, “Do you know what time it is?” the correct answer is “yes” or “no,” not “Oh yes, it’s 11:30 and I have a meeting with Charlie in half an hour.” 

Similarly, in the Statement of the Purpose section, just give the purpose, whatever is required by your university’s template, and not much else. This can be accomplished within a few pages at most.

Aligning the Purpose of the Study With the Rest of Your Paper

Keeping your paper in alignment is an extraordinarily important part of writing your dissertation. What this means is that your Problem Statement, Purpose Statement, and Research Questions all say essentially the same thing (just with different wording).

Aligning the Purpose Statement with the Problem Statement

Your problem statement should have two parts–a General Problem and a Specific Problem. The general problem is an overarching view of the problem you’re looking to address–this is what you would tell a curious person asking what you’re studying. The Specific Problem is always a gap in research. “The specific problem is that ___ is not known.”

The language that you use to fill in the blank is the same language you should use for the purpose statement. 

Problem : “The problem is that x isn’t known”

Purpose : “The purpose is to find x out”

• The problem is that we don’t know what factors influence parent involvement in schools.
• The purpose is to determine the factors that determine parent involvement in schools.
• The problem is that we don’t know the impact of Covid-19 unemployment on stock prices.
• The purpose is to determine the impact of Covid-19 unemployment on stock prices.

The professor I interviewed said, “Your committee wants to see you being consistent. ‘My problem is x. My purpose is to explore the problem.’ Period. Don’t have more than one purpose, and don’t stray from your problem statement.”

Aligning the Purpose Statement with the Research Questions

The research questions should arise directly from the purpose statement. For example:

What factors do parents report impact their involvement in schools?

To what degree is there a significant relationship between Covid-19 unemployment and stock prices?

There could be additional research questions for each of these studies, but you get the idea: ensure that your research question arises from the purpose statement and the purpose statement arises from the problem statement.  These steps create the foundation of your study, and doing it this way will ensure there is alignment.

Mistakes People Make When Writing Their Purpose Statement

• Writing the purpose statement apart from their problem statement, so the purpose doesn’t directly relate to the problem.
• Trying to take on too much in one study — too big a problem to study while you’re paying tuition. (Save those larger studies for when you’re being paid.)
• Trying to be creative with wording and thereby veering away from the problem statement.
• Creating multiple purpose statements. 

In short, you’re trying to find information that will help your field better understand a problem that’s important to you. Your job in your dissertation is to address the problem, and your purpose statement will tell us that.

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Nicholas Tippins is the Founder & Executive Director of My Dissertation Editor. He has edited more dissertations than he can count. When not managing his business, he can be found playing the guitar or wandering around in the woods.

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A scoping review of continuous quality improvement in healthcare system: conceptualization, models and tools, barriers and facilitators, and impact

• Aklilu Endalamaw 1 , 2 ,
• Resham B Khatri 1 , 3 ,
• Tesfaye Setegn Mengistu 1 , 2 ,
• Daniel Erku 1 , 4 , 5 ,
• Eskinder Wolka 6 ,
• Anteneh Zewdie 6 &
• Yibeltal Assefa 1  

BMC Health Services Research volume  24 , Article number:  487 ( 2024 ) Cite this article

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The growing adoption of continuous quality improvement (CQI) initiatives in healthcare has generated a surge in research interest to gain a deeper understanding of CQI. However, comprehensive evidence regarding the diverse facets of CQI in healthcare has been limited. Our review sought to comprehensively grasp the conceptualization and principles of CQI, explore existing models and tools, analyze barriers and facilitators, and investigate its overall impacts.

This qualitative scoping review was conducted using Arksey and O’Malley’s methodological framework. We searched articles in PubMed, Web of Science, Scopus, and EMBASE databases. In addition, we accessed articles from Google Scholar. We used mixed-method analysis, including qualitative content analysis and quantitative descriptive for quantitative findings to summarize findings and PRISMA extension for scoping reviews (PRISMA-ScR) framework to report the overall works.

A total of 87 articles, which covered 14 CQI models, were included in the review. While 19 tools were used for CQI models and initiatives, Plan-Do-Study/Check-Act cycle was the commonly employed model to understand the CQI implementation process. The main reported purposes of using CQI, as its positive impact, are to improve the structure of the health system (e.g., leadership, health workforce, health technology use, supplies, and costs), enhance healthcare delivery processes and outputs (e.g., care coordination and linkages, satisfaction, accessibility, continuity of care, safety, and efficiency), and improve treatment outcome (reduce morbidity and mortality). The implementation of CQI is not without challenges. There are cultural (i.e., resistance/reluctance to quality-focused culture and fear of blame or punishment), technical, structural (related to organizational structure, processes, and systems), and strategic (inadequate planning and inappropriate goals) related barriers that were commonly reported during the implementation of CQI.

Conclusions

Implementing CQI initiatives necessitates thoroughly comprehending key principles such as teamwork and timeline. To effectively address challenges, it’s crucial to identify obstacles and implement optimal interventions proactively. Healthcare professionals and leaders need to be mentally equipped and cognizant of the significant role CQI initiatives play in achieving purposes for quality of care.

Peer Review reports

Continuous quality improvement (CQI) initiative is a crucial initiative aimed at enhancing quality in the health system that has gradually been adopted in the healthcare industry. In the early 20th century, Shewhart laid the foundation for quality improvement by describing three essential steps for process improvement: specification, production, and inspection [ 1 , 2 ]. Then, Deming expanded Shewhart’s three-step model into ‘plan, do, study/check, and act’ (PDSA or PDCA) cycle, which was applied to management practices in Japan in the 1950s [ 3 ] and was gradually translated into the health system. In 1991, Kuperman applied a CQI approach to healthcare, comprising selecting a process to be improved, assembling a team of expert clinicians that understands the process and the outcomes, determining key steps in the process and expected outcomes, collecting data that measure the key process steps and outcomes, and providing data feedback to the practitioners [ 4 ]. These philosophies have served as the baseline for the foundation of principles for continuous improvement [ 5 ].

Continuous quality improvement fosters a culture of continuous learning, innovation, and improvement. It encourages proactive identification and resolution of problems, promotes employee engagement and empowerment, encourages trust and respect, and aims for better quality of care [ 6 , 7 ]. These characteristics drive the interaction of CQI with other quality improvement projects, such as quality assurance and total quality management [ 8 ]. Quality assurance primarily focuses on identifying deviations or errors through inspections, audits, and formal reviews, often settling for what is considered ‘good enough’, rather than pursuing the highest possible standards [ 9 , 10 ], while total quality management is implemented as the management philosophy and system to improve all aspects of an organization continuously [ 11 ].

Continuous quality improvement has been implemented to provide quality care. However, providing effective healthcare is a complicated and complex task in achieving the desired health outcomes and the overall well-being of individuals and populations. It necessitates tackling issues, including access, patient safety, medical advances, care coordination, patient-centered care, and quality monitoring [ 12 , 13 ], rooted long ago. It is assumed that the history of quality improvement in healthcare started in 1854 when Florence Nightingale introduced quality improvement documentation [ 14 ]. Over the passing decades, Donabedian introduced structure, processes, and outcomes as quality of care components in 1966 [ 15 ]. More comprehensively, the Institute of Medicine in the United States of America (USA) has identified effectiveness, efficiency, equity, patient-centredness, safety, and timeliness as the components of quality of care [ 16 ]. Moreover, quality of care has recently been considered an integral part of universal health coverage (UHC) [ 17 ], which requires initiatives to mobilise essential inputs [ 18 ].

While the overall objective of CQI in health system is to enhance the quality of care, it is important to note that the purposes and principles of CQI can vary across different contexts [ 19 , 20 ]. This variation has sparked growing research interest. For instance, a review of CQI approaches for capacity building addressed its role in health workforce development [ 21 ]. Another systematic review, based on random-controlled design studies, assessed the effectiveness of CQI using training as an intervention and the PDSA model [ 22 ]. As a research gap, the former review was not directly related to the comprehensive elements of quality of care, while the latter focused solely on the impact of training using the PDSA model, among other potential models. Additionally, a review conducted in 2015 aimed to identify barriers and facilitators of CQI in Canadian contexts [ 23 ]. However, all these reviews presented different perspectives and investigated distinct outcomes. This suggests that there is still much to explore in terms of comprehensively understanding the various aspects of CQI initiatives in healthcare.

As a result, we conducted a scoping review to address several aspects of CQI. Scoping reviews serve as a valuable tool for systematically mapping the existing literature on a specific topic. They are instrumental when dealing with heterogeneous or complex bodies of research. Scoping reviews provide a comprehensive overview by summarizing and disseminating findings across multiple studies, even when evidence varies significantly [ 24 ]. In our specific scoping review, we included various types of literature, including systematic reviews, to enhance our understanding of CQI.

This scoping review examined how CQI is conceptualized and measured and investigated models and tools for its application while identifying implementation challenges and facilitators. It also analyzed the purposes and impact of CQI on the health systems, providing valuable insights for enhancing healthcare quality.

Protocol registration and results reporting

Protocol registration for this scoping review was not conducted. Arksey and O’Malley’s methodological framework was utilized to conduct this scoping review [ 25 ]. The scoping review procedures start by defining the research questions, identifying relevant literature, selecting articles, extracting data, and summarizing the results. The review findings are reported using the PRISMA extension for a scoping review (PRISMA-ScR) [ 26 ]. McGowan and colleagues also advised researchers to report findings from scoping reviews using PRISMA-ScR [ 27 ].

Defining the research problems

This review aims to comprehensively explore the conceptualization, models, tools, barriers, facilitators, and impacts of CQI within the healthcare system worldwide. Specifically, we address the following research questions: (1) How has CQI been defined across various contexts? (2) What are the diverse approaches to implementing CQI in healthcare settings? (3) Which tools are commonly employed for CQI implementation ? (4) What barriers hinder and facilitators support successful CQI initiatives? and (5) What effects CQI initiatives have on the overall care quality?

Information source and search strategy

We conducted the search in PubMed, Web of Science, Scopus, and EMBASE databases, and the Google Scholar search engine. The search terms were selected based on three main distinct concepts. One group was CQI-related terms. The second group included terms related to the purpose for which CQI has been implemented, and the third group included processes and impact. These terms were selected based on the Donabedian framework of structure, process, and outcome [ 28 ]. Additionally, the detailed keywords were recruited from the primary health framework, which has described lists of dimensions under process, output, outcome, and health system goals of any intervention for health [ 29 ]. The detailed search strategy is presented in the Supplementary file 1 (Search strategy). The search for articles was initiated on August 12, 2023, and the last search was conducted on September 01, 2023.

Eligibility criteria and article selection

Based on the scoping review’s population, concept, and context frameworks [ 30 ], the population included any patients or clients. Additionally, the concepts explored in the review encompassed definitions, implementation, models, tools, barriers, facilitators, and impacts of CQI. Furthermore, the review considered contexts at any level of health systems. We included articles if they reported results of qualitative or quantitative empirical study, case studies, analytic or descriptive synthesis, any review, and other written documents, were published in peer-reviewed journals, and were designed to address at least one of the identified research questions or one of the identified implementation outcomes or their synonymous taxonomy as described in the search strategy. Based on additional contexts, we included articles published in English without geographic and time limitations. We excluded articles with abstracts only, conference abstracts, letters to editors, commentators, and corrections.

We exported all citations to EndNote x20 to remove duplicates and screen relevant articles. The article selection process includes automatic duplicate removal by using EndNote x20, unmatched title and abstract removal, citation and abstract-only materials removal, and full-text assessment. The article selection process was mainly conducted by the first author (AE) and reported to the team during the weekly meetings. The first author encountered papers that caused confusion regarding whether to include or exclude them and discussed them with the last author (YA). Then, decisions were ultimately made. Whenever disagreements happened, they were resolved by discussion and reconsideration of the review questions in relation to the written documents of the article. Further statistical analysis, such as calculating Kappa, was not performed to determine article inclusion or exclusion.

Data extraction and data items

We extracted first author, publication year, country, settings, health problem, the purpose of the study, study design, types of intervention if applicable, CQI approaches/steps if applicable, CQI tools and procedures if applicable, and main findings using a customized Microsoft Excel form.

Summarizing and reporting the results

The main findings were summarized and described based on the main themes, including concepts under conceptualizing, principles, teams, timelines, models, tools, barriers, facilitators, and impacts of CQI. Results-based convergent synthesis, achieved through mixed-method analysis, involved content analysis to identify the thematic presentation of findings. Additionally, a narrative description was used for quantitative findings, aligning them with the appropriate theme. The authors meticulously reviewed the primary findings from each included material and contextualized these findings concerning the main themes1. This approach provides a comprehensive understanding of complex interventions and health systems, acknowledging quantitative and qualitative evidence.

Search results

A total of 11,251 documents were identified from various databases: SCOPUS ( n  = 4,339), PubMed ( n  = 2,893), Web of Science ( n  = 225), EMBASE ( n  = 3,651), and Google Scholar ( n  = 143). After removing duplicates ( n  = 5,061), 6,190 articles were evaluated by title and abstract. Subsequently, 208 articles were assessed for full-text eligibility. Following the eligibility criteria, 121 articles were excluded, leaving 87 included in the current review (Fig.  1 ).

Article selection process

Operationalizing continuous quality improvement

Continuous Quality Improvement (CQI) is operationalized as a cyclic process that requires commitment to implementation, teamwork, time allocation, and celebrating successes and failures.

CQI is a cyclic ongoing process that is followed reflexive, analytical and iterative steps, including identifying gaps, generating data, developing and implementing action plans, evaluating performance, providing feedback to implementers and leaders, and proposing necessary adjustments [ 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 ].

CQI requires committing to the philosophy, involving continuous improvement [ 19 , 38 ], establishing a mission statement [ 37 ], and understanding quality definition [ 19 ].

CQI involves a wide range of patient-oriented measures and performance indicators, specifically satisfying internal and external customers, developing quality assurance, adopting common quality measures, and selecting process measures [ 8 , 19 , 35 , 36 , 37 , 39 , 40 ].

CQI requires celebrating success and failure without personalization, leading each team member to develop error-free attitudes [ 19 ]. Success and failure are related to underlying organizational processes and systems as causes of failure rather than blaming individuals [ 8 ] because CQI is process-focused based on collaborative, data-driven, responsive, rigorous and problem-solving statistical analysis [ 8 , 19 , 38 ]. Furthermore, a gap or failure opens another opportunity for establishing a data-driven learning organization [ 41 ].

CQI cannot be implemented without a CQI team [ 8 , 19 , 37 , 39 , 42 , 43 , 44 , 45 , 46 ]. A CQI team comprises individuals from various disciplines, often comprising a team leader, a subject matter expert (physician or other healthcare provider), a data analyst, a facilitator, frontline staff, and stakeholders [ 39 , 43 , 47 , 48 , 49 ]. It is also important to note that inviting stakeholders or partners as part of the CQI support intervention is crucial [ 19 , 38 , 48 ].

The timeline is another distinct feature of CQI because the results of CQI vary based on the implementation duration of each cycle [ 35 ]. There is no specific time limit for CQI implementation, although there is a general consensus that a cycle of CQI should be relatively short [ 35 ]. For instance, a CQI implementation took 2 months [ 42 ], 4 months [ 50 ], 9 months [ 51 , 52 ], 12 months [ 53 , 54 , 55 ], and one year and 5 months [ 49 ] duration to achieve the desired positive outcome, while bi-weekly [ 47 ] and monthly data reviews and analyses [ 44 , 48 , 56 ], and activities over 3 months [ 57 ] have also resulted in a positive outcome.

Continuous quality improvement models and tools

There have been several models are utilized. The Plan-Do-Study/Check-Act cycle is a stepwise process involving project initiation, situation analysis, root cause identification, solution generation and selection, implementation, result evaluation, standardization, and future planning [ 7 , 36 , 37 , 45 , 47 , 48 , 49 , 50 , 51 , 53 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 ]. The FOCUS-PDCA cycle enhances the PDCA process by adding steps to find and improve a process (F), organize a knowledgeable team (O), clarify the process (C), understand variations (U), and select improvements (S) [ 55 , 71 , 72 , 73 ]. The FADE cycle involves identifying a problem (Focus), understanding it through data analysis (Analyze), devising solutions (Develop), and implementing the plan (Execute) [ 74 ]. The Logic Framework involves brainstorming to identify improvement areas, conducting root cause analysis to develop a problem tree, logically reasoning to create an objective tree, formulating the framework, and executing improvement projects [ 75 ]. Breakthrough series approach requires CQI teams to meet in quarterly collaborative learning sessions, share learning experiences, and continue discussion by telephone and cross-site visits to strengthen learning and idea exchange [ 47 ]. Another CQI model is the Lean approach, which has been conducted with Kaizen principles [ 52 ], 5 S principles, and the Six Sigma model. The 5 S (Sort, Set/Straighten, Shine, Standardize, Sustain) systematically organises and improves the workplace, focusing on sorting, setting order, shining, standardizing, and sustaining the improvement [ 54 , 76 ]. Kaizen principles guide CQI by advocating for continuous improvement, valuing all ideas, solving problems, focusing on practical, low-cost improvements, using data to drive change, acknowledging process defects, reducing variability and waste, recognizing every interaction as a customer-supplier relationship, empowering workers, responding to all ideas, and maintaining a disciplined workplace [ 77 ]. Lean Six Sigma, a CQI model, applies the DMAIC methodology, which involves defining (D) and measuring the problem (M), analyzing root causes (A), improving by finding solutions (I), and controlling by assessing process stability (C) [ 78 , 79 ]. The 5 C-cyclic model (consultation, collection, consideration, collaboration, and celebration), the first CQI framework for volunteer dental services in Aboriginal communities, ensures quality care based on community needs [ 80 ]. One study used meetings involving activities such as reviewing objectives, assigning roles, discussing the agenda, completing tasks, retaining key outputs, planning future steps, and evaluating the meeting’s effectiveness [ 81 ].

Various tools are involved in the implementation or evaluation of CQI initiatives: checklists [ 53 , 82 ], flowcharts [ 81 , 82 , 83 ], cause-and-effect diagrams (fishbone or Ishikawa diagrams) [ 60 , 62 , 79 , 81 , 82 ], fuzzy Pareto diagram [ 82 ], process maps [ 60 ], time series charts [ 48 ], why-why analysis [ 79 ], affinity diagrams and multivoting [ 81 ], and run chart [ 47 , 48 , 51 , 60 , 84 ], and others mentioned in the table (Table  1 ).

Barriers and facilitators of continuous quality improvement implementation

Implementing CQI initiatives is determined by various barriers and facilitators, which can be thematized into four dimensions. These dimensions are cultural, technical, structural, and strategic dimensions.

Continuous quality improvement initiatives face various cultural, strategic, technical, and structural barriers. Cultural dimension barriers involve resistance to change (e.g., not accepting online technology), lack of quality-focused culture, staff reporting apprehensiveness, and fear of blame or punishment [ 36 , 41 , 85 , 86 ]. The technical dimension barriers of CQI can include various factors that hinder the effective implementation and execution of CQI processes [ 36 , 86 , 87 , 88 , 89 ]. Structural dimension barriers of CQI arise from the organization structure, process, and systems that can impede the effective implementation and sustainability of CQI [ 36 , 85 , 86 , 87 , 88 ]. Strategic dimension barriers are, for example, the inability to select proper CQI goals and failure to integrate CQI into organizational planning and goals [ 36 , 85 , 86 , 87 , 88 , 90 ].

Facilitators are also grouped to cultural, structural, technical, and strategic dimensions to provide solutions to CQI barriers. Cultural challenges were addressed by developing a group culture to CQI and other rewards [ 39 , 41 , 80 , 85 , 86 , 87 , 90 , 91 , 92 ]. Technical facilitators are pivotal to improving technical barriers [ 39 , 42 , 53 , 69 , 86 , 90 , 91 ]. Structural-related facilitators are related to improving communication, infrastructure, and systems [ 86 , 92 , 93 ]. Strategic dimension facilitators include strengthening leadership and improving decision-making skills [ 43 , 53 , 67 , 86 , 87 , 92 , 94 , 95 ] (Table  2 ).

Impact of continuous quality improvement

Continuous quality improvement initiatives can significantly impact the quality of healthcare in a wide range of health areas, focusing on improving structure, the health service delivery process and improving client wellbeing and reducing mortality.

Structure components

These are health leadership, financing, workforce, technology, and equipment and supplies. CQI has improved planning, monitoring and evaluation [ 48 , 53 ], and leadership and planning [ 48 ], indicating improvement in leadership perspectives. Implementing CQI in primary health care (PHC) settings has shown potential for maintaining or reducing operation costs [ 67 ]. Findings from another study indicate that the costs associated with implementing CQI interventions per facility ranged from approximately $2,000 to $10,500 per year, with an average cost of approximately $10 to $60 per admitted client [ 57 ]. However, based on model predictions, the average cost savings after implementing CQI were estimated to be $5430 [ 31 ]. CQI can also be applied to health workforce development [ 32 ]. CQI in the institutional system improved medical education [ 66 , 96 , 97 ], human resources management [ 53 ], motivated staffs [ 76 ], and increased staff health awareness [ 69 ], while concerns raised about CQI impartiality, independence, and public accountability [ 96 ]. Regarding health technology, CQI also improved registration and documentation [ 48 , 53 , 98 ]. Furthermore, the CQI initiatives increased cleanliness [ 54 ] and improved logistics, supplies, and equipment [ 48 , 53 , 68 ].

Process and output components

The process component focuses on the activities and actions involved in delivering healthcare services.

Service delivery

CQI interventions improved service delivery [ 53 , 56 , 99 ], particularly a significant 18% increase in the overall quality of service performance [ 48 ], improved patient counselling, adherence to appropriate procedures, and infection prevention [ 48 , 68 ], and optimised workflow [ 52 ].

Coordination and collaboration

CQI initiatives improved coordination and collaboration through collecting and analysing data, onsite technical support, training, supportive supervision [ 53 ] and facilitating linkages between work processes and a quality control group [ 65 ].

Patient satisfaction

The CQI initiatives increased patient satisfaction and improved quality of life by optimizing care quality management, improving the quality of clinical nursing, reducing nursing defects and enhancing the wellbeing of clients [ 54 , 76 , 100 ], although CQI was not associated with changes in adolescent and young adults’ satisfaction [ 51 ].

CQI initiatives reduced medication error reports from 16 to 6 [ 101 ], and it significantly reduced the administration of inappropriate prophylactic antibiotics [ 44 ], decreased errors in inpatient care [ 52 ], decreased the overall episiotomy rate from 44.5 to 33.3% [ 83 ], reduced the overall incidence of unplanned endotracheal extubation [ 102 ], improving appropriate use of computed tomography angiography [ 103 ], and appropriate diagnosis and treatment selection [ 47 ].

Continuity of care

CQI initiatives effectively improve continuity of care by improving client and physician interaction. For instance, provider continuity levels showed a 64% increase [ 55 ]. Modifying electronic medical record templates, scheduling, staff and parental education, standardization of work processes, and birth to 1-year age-specific incentives in post-natal follow-up care increased continuity of care to 74% in 2018 compared to baseline 13% in 2012 [ 84 ].

The CQI initiative yielded enhanced efficiency in the cardiac catheterization laboratory, as evidenced by improved punctuality in procedure starts and increased efficiency in manual sheath-pulls inside [ 78 ].

Accessibility

CQI initiatives were effective in improving accessibility in terms of increasing service coverage and utilization rate. For instance, screening for cigarettes, nutrition counselling, folate prescription, maternal care, immunization coverage [ 53 , 81 , 104 , 105 ], reducing the percentage of non-attending patients to surgery to 0.9% from the baseline 3.9% [ 43 ], increasing Chlamydia screening rates from 29 to 60% [ 45 ], increasing HIV care continuum coverage [ 51 , 59 , 60 ], increasing in the uptake of postpartum long-acting reversible contraceptive use from 6.9% at the baseline to 25.4% [ 42 ], increasing post-caesarean section prophylaxis from 36 to 89% [ 62 ], a 31% increase of kangaroo care practice [ 50 ], and increased follow-up [ 65 ]. Similarly, the QI intervention increased the quality of antenatal care by 29.3%, correct partograph use by 51.7%, and correct active third-stage labour management, a 19.6% improvement from the baseline, but not significantly associated with improvement in contraceptive service uptake [ 61 ].

Timely access

CQI interventions improved the time care provision [ 52 ], and reduced waiting time [ 62 , 74 , 76 , 106 ]. For instance, the discharge process waiting time in the emergency department decreased from 76 min to 22 min [ 79 ]. It also reduced mean postprocedural length of stay from 2.8 days to 2.0 days [ 31 ].

Acceptability

Acceptability of CQI by healthcare providers was satisfactory. For instance, 88% of the faculty, 64% of the residents, and 82% of the staff believed CQI to be useful in the healthcare clinic [ 107 ].

Outcome components

Morbidity and mortality.

CQI efforts have demonstrated better management outcomes among diabetic patients [ 40 ], patients with oral mucositis [ 71 ], and anaemic patients [ 72 ]. It has also reduced infection rate in post-caesarean Sect. [ 62 ], reduced post-peritoneal dialysis peritonitis [ 49 , 108 ], and prevented pressure ulcers [ 70 ]. It is explained by peritonitis incidence from once every 40.1 patient months at baseline to once every 70.8 patient months after CQI [ 49 ] and a 63% reduction in pressure ulcer prevalence within 2 years from 2008 to 2010 [ 70 ]. Furthermore, CQI initiatives significantly reduced in-hospital deaths [ 31 ] and increased patient survival rates [ 108 ]. Figure  2 displays the overall process of the CQI implementations.

The overall mechanisms of continuous quality improvement implementation

In this review, we examined the fundamental concepts and principles underlying CQI, the factors that either hinder or assist in its successful application and implementation, and the purpose of CQI in enhancing quality of care across various health issues.

Our findings have brought attention to the application and implementation of CQI, emphasizing its underlying concepts and principles, as evident in the existing literature [ 31 , 32 , 33 , 34 , 35 , 36 , 39 , 40 , 43 , 45 , 46 ]. Continuous quality improvement has shared with the principles of continuous improvement, such as a customer-driven focus, effective leadership, active participation of individuals, a process-oriented approach, systematic implementation, emphasis on design improvement and prevention, evidence-based decision-making, and fostering partnership [ 5 ]. Moreover, Deming’s 14 principles laid the foundation for CQI principles [ 109 ]. These principles have been adapted and put into practice in various ways: ten [ 19 ] and five [ 38 ] principles in hospitals, five principles for capacity building [ 38 ], and two principles for medication error prevention [ 41 ]. As a principle, the application of CQI can be process-focused [ 8 , 19 ] or impact-focused [ 38 ]. Impact-focused CQI focuses on achieving specific outcomes or impacts, whereas process-focused CQI prioritizes and improves the underlying processes and systems. These principles complement each other and can be utilized based on the objectives of quality improvement initiatives in healthcare settings. Overall, CQI is an ongoing educational process that requires top management’s involvement, demands coordination across departments, encourages the incorporation of views beyond clinical area, and provides non-judgemental evidence based on objective data [ 110 ].

The current review recognized that it was not easy to implement CQI. It requires reasonable utilization of various models and tools. The application of each tool can be varied based on the studied health problem and the purpose of CQI initiative [ 111 ], varied in context, content, structure, and usability [ 112 ]. Additionally, overcoming the cultural, technical, structural, and strategic-related barriers. These barriers have emerged from clinical staff, managers, and health systems perspectives. Of the cultural obstacles, staff non-involvement, resistance to change, and reluctance to report error were staff-related. In contrast, others, such as the absence of celebration for success and hierarchical and rational culture, may require staff and manager involvement. Staff members may exhibit reluctance in reporting errors due to various cultural factors, including lack of trust, hierarchical structures, fear of retribution, and a blame-oriented culture. These challenges pose obstacles to implementing standardized CQI practices, as observed, for instance, in community pharmacy settings [ 85 ]. The hierarchical culture, characterized by clearly defined levels of power, authority, and decision-making, posed challenges to implementing CQI initiatives in public health [ 41 , 86 ]. Although rational culture, a type of organizational culture, emphasizes logical thinking and rational decision-making, it can also create challenges for CQI implementation [ 41 , 86 ] because hierarchical and rational cultures, which emphasize bureaucratic norms and narrow definitions of achievement, were found to act as barriers to the implementation of CQI [ 86 ]. These could be solved by developing a shared mindset and collective commitment, establishing a shared purpose, developing group norms, and cultivating psychological preparedness among staff, managers, and clients to implement and sustain CQI initiatives. Furthermore, reversing cultural-related barriers necessitates cultural-related solutions: development of a culture and group culture to CQI [ 41 , 86 ], positive comprehensive perception [ 91 ], commitment [ 85 ], involving patients, families, leaders, and staff [ 39 , 92 ], collaborating for a common goal [ 80 , 86 ], effective teamwork [ 86 , 87 ], and rewarding and celebrating successes [ 80 , 90 ].

The technical dimension barriers of CQI can include inadequate capitalization of a project and insufficient support for CQI facilitators and data entry managers [ 36 ], immature electronic medical records or poor information systems [ 36 , 86 ], and the lack of training and skills [ 86 , 87 , 88 ]. These challenges may cause the CQI team to rely on outdated information and technologies. The presence of barriers on the technical dimension may challenge the solid foundation of CQI expertise among staff, the ability to recognize opportunities for improvement, a comprehensive understanding of how services are produced and delivered, and routine use of expertise in daily work. Addressing these technical barriers requires knowledge creation activities (training, seminar, and education) [ 39 , 42 , 53 , 69 , 86 , 90 , 91 ], availability of quality data [ 86 ], reliable information [ 92 ], and a manual-online hybrid reporting system [ 85 ].

Structural dimension barriers of CQI include inadequate communication channels and lack of standardized process, specifically weak physician-to-physician synergies [ 36 ], lack of mechanisms for disseminating knowledge and limited use of communication mechanisms [ 86 ]. Lack of communication mechanism endangers sharing ideas and feedback among CQI teams, leading to misunderstandings, limited participation and misinterpretations, and a lack of learning [ 113 ]. Knowledge translation facilitates the co-production of research, subsequent diffusion of knowledge, and the developing stakeholder’s capacity and skills [ 114 ]. Thus, the absence of a knowledge translation mechanism may cause missed opportunities for learning, inefficient problem-solving, and limited creativity. To overcome these challenges, organizations should establish effective communication and information systems [ 86 , 93 ] and learning systems [ 92 ]. Though CQI and knowledge translation have interacted with each other, it is essential to recognize that they are distinct. CQI focuses on process improvement within health care systems, aiming to optimize existing processes, reduce errors, and enhance efficiency.

In contrast, knowledge translation bridges the gap between research evidence and clinical practice, translating research findings into actionable knowledge for practitioners. While both CQI and knowledge translation aim to enhance health care quality and patient outcomes, they employ different strategies: CQI utilizes tools like Plan-Do-Study-Act cycles and statistical process control, while knowledge translation involves knowledge synthesis and dissemination. Additionally, knowledge translation can also serve as a strategy to enhance CQI. Both concepts share the same principle: continuous improvement is essential for both. Therefore, effective strategies on the structural dimension may build efficient and effective steering councils, information systems, and structures to diffuse learning throughout the organization.

Strategic factors, such as goals, planning, funds, and resources, determine the overall purpose of CQI initiatives. Specific barriers were improper goals and poor planning [ 36 , 86 , 88 ], fragmentation of quality assurance policies [ 87 ], inadequate reinforcement to staff [ 36 , 90 ], time constraints [ 85 , 86 ], resource inadequacy [ 86 ], and work overload [ 86 ]. These barriers can be addressed through strengthening leadership [ 86 , 87 ], CQI-based mentoring [ 94 ], periodic monitoring, supportive supervision and coaching [ 43 , 53 , 87 , 92 , 95 ], participation, empowerment, and accountability [ 67 ], involving all stakeholders in decision-making [ 86 , 87 ], a provider-payer partnership [ 64 ], and compensating staff for after-hours meetings on CQI [ 85 ]. The strategic dimension, characterized by a strategic plan and integrated CQI efforts, is devoted to processes that are central to achieving strategic priorities. Roles and responsibilities are defined in terms of integrated strategic and quality-related goals [ 115 ].

The utmost goal of CQI has been to improve the quality of care, which is usually revealed by structure, process, and outcome. After resolving challenges and effectively using tools and running models, the goal of CQI reflects the ultimate reason and purpose of its implementation. First, effectively implemented CQI initiatives can improve leadership, health financing, health workforce development, health information technology, and availability of supplies as the building blocks of a health system [ 31 , 48 , 53 , 68 , 98 ]. Second, effectively implemented CQI initiatives improved care delivery process (counselling, adherence with standards, coordination, collaboration, and linkages) [ 48 , 53 , 65 , 68 ]. Third, the CQI can improve outputs of healthcare delivery, such as satisfaction, accessibility (timely access, utilization), continuity of care, safety, efficiency, and acceptability [ 52 , 54 , 55 , 76 , 78 ]. Finally, the effectiveness of the CQI initiatives has been tested in enhancing responses related to key aspects of the HIV response, maternal and child health, non-communicable disease control, and others (e.g., surgery and peritonitis). However, it is worth noting that CQI initiative has not always been effective. For instance, CQI using a two- to nine-times audit cycle model through systems assessment tools did not bring significant change to increase syphilis testing performance [ 116 ]. This study was conducted within the context of Aboriginal and Torres Strait Islander people’s primary health care settings. Notably, ‘the clinics may not have consistently prioritized syphilis testing performance in their improvement strategies, as facilitated by the CQI program’ [ 116 ]. Additionally, by applying CQI-based mentoring, uptake of facility-based interventions was not significantly improved, though it was effective in increasing community health worker visits during pregnancy and the postnatal period, knowledge about maternal and child health and exclusive breastfeeding practice, and HIV disclosure status [ 117 ]. The study conducted in South Africa revealed no significant association between the coverage of facility-based interventions and Continuous Quality Improvement (CQI) implementation. This lack of association was attributed to the already high antenatal and postnatal attendance rates in both control and intervention groups at baseline, leaving little room for improvement. Additionally, the coverage of HIV interventions remained consistently high throughout the study period [ 117 ].

Regarding health care and policy implications, CQI has played a vital role in advancing PHC and fostering the realization of UHC goals worldwide. The indicators found in Donabedian’s framework that are positively influenced by CQI efforts are comparable to those included in the PHC performance initiative’s conceptual framework [ 29 , 118 , 119 ]. It is clearly explained that PHC serves as the roadmap to realizing the vision of UHC [ 120 , 121 ]. Given these circumstances, implementing CQI can contribute to the achievement of PHC principles and the objectives of UHC. For instance, by implementing CQI methods, countries have enhanced the accessibility, affordability, and quality of PHC services, leading to better health outcomes for their populations. CQI has facilitated identifying and resolving healthcare gaps and inefficiencies, enabling countries to optimize resource allocation and deliver more effective and patient-centered care. However, it is crucial to recognize that the successful implementation of Continuous Quality Improvement (CQI) necessitates optimizing the duration of each cycle, understanding challenges and barriers that extend beyond the health system and settings, and acknowledging that its effectiveness may be compromised if these challenges are not adequately addressed.

Despite abundant literature, there are still gaps regarding the relationship between CQI and other dimensions within the healthcare system. No studies have examined the impact of CQI initiatives on catastrophic health expenditure, effective service coverage, patient-centredness, comprehensiveness, equity, health security, and responsiveness.

Limitations

In conducting this review, it has some limitations to consider. Firstly, only articles published in English were included, which may introduce the exclusion of relevant non-English articles. Additionally, as this review follows a scoping methodology, the focus is on synthesising available evidence rather than critically evaluating or scoring the quality of the included articles.

Continuous quality improvement is investigated as a continuous and ongoing intervention, where the implementation time can vary across different cycles. The CQI team and implementation timelines were critical elements of CQI in different models. Among the commonly used approaches, the PDSA or PDCA is frequently employed. In most CQI models, a wide range of tools, nineteen tools, are commonly utilized to support the improvement process. Cultural, technical, structural, and strategic barriers and facilitators are significant in implementing CQI initiatives. Implementing the CQI initiative aims to improve health system blocks, enhance health service delivery process and output, and ultimately prevent morbidity and reduce mortality. For future researchers, considering that CQI is context-dependent approach, conducting scale-up implementation research about catastrophic health expenditure, effective service coverage, patient-centredness, comprehensiveness, equity, health security, and responsiveness across various settings and health issues would be valuable.

Availability of data and materials

The data used and/or analyzed during the current study are available in this manuscript and/or the supplementary file.

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Endalamaw, A., Khatri, R.B., Mengistu, T.S. et al. A scoping review of continuous quality improvement in healthcare system: conceptualization, models and tools, barriers and facilitators, and impact. BMC Health Serv Res 24 , 487 (2024). https://doi.org/10.1186/s12913-024-10828-0

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