purpose of research articles in scientific journals

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1 The Importance of Journal Articles

• Published: March 2008
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This introductory chapter explains how and why journal articles are generally according greater prestige and merit within the scientific community, relative to other forms of disseminating research findings through venues such as books, book chapters, weblogs, and presenting papers at professional conferences. Published journal articles typically have gone through a rigorous screening process known as blind peer review, whereby independent experts provide the author with critical commentary and suggestions to improve their final paper, prior to publication. Most print journals are now widely accessible over the internet and are relatively easy for others to access. Articles submitted to journals usually appear in print sooner than books or book chapters, and continue to be accorded greater influence in promotion and tenure decisions within academia than alterative means of distributing information. Articles published in peer reviewed journals are likely to remain a very important means of distributing research findings for the foreseeable future.

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Reading scientific journals is useful not only for keeping up with the latest scientific discoveries and findings, but also to understand that science is more than the facts we see in textbooks. This blog discusses the history of scientific journals, characteristics of different forms of articles, steps for publishing an article and more!

S cientific journals are publications that circulate and announce discoveries and inventions, gathering known as well as new knowledge in different areas of science. Generally, journal issues are published online and/or offline regularly or ‘periodically’ . In this blog, we discuss the relevance, history, characteristics of various publishing forms of scientific journals and steps for publishing an article. Finally, we put forward some new and engaging scientific journals and magazines disseminating science across languages. The usefulness of scientific journals: Research in all areas of science helps understand the world around us and discover solutions for problems that exist. However, any research carried out can be useful only if it is communicated to other scientists and the world. Now imagine that, through your research, you have learned something new about the world. How will you tell the world about it? By word of mouth or by writing? A written text/document in a global language is a better means of communication. It will serve as a knowledge source or starting point for researchers around the world who are interested in your findings and want to know the “What? Why? How? So what?" of your research. Writing in a language known to most of the world enhances the ease of communication and understanding, removing cultural and language barriers between scientists and helping them interact better, through the language of science. Apart from this, publishing in journals also aids in teamwork or ‘collaboration’ between scientists from different corners of the world. Yesteryears of scientific journals: In the early 16th century, before scientific journals emerged, there were, many other modes of communicating scientific information. Among these modes, the primary position was held by correspondence. While published books remained a major form of communication, the scientific article made its first appearance during the seventeenth century, in the form of 'letters'. These were not personal messages to friends or colleagues, but an essay-like article written in the form of 'letter or correspondence' , reporting the recent experiments and observations. Through letters and correspondences, scientists were able to discuss ideas that were still under the development. Like the modern-day pre-publication, scientists could circulate and share their ideas through letters and obtain critical comments before they finally put them into print. As the pace of discoveries and inventions accelerated, during Renaissance Europe, correspondence played an essential role in establishing disputes about the priority in the conflicting claims made by two or more researchers. For example, although Gottfried Wilhelm Leibniz was the first to publish the books, Isaac Newton laid claim to the invention of the calculus, based on his letters that dated much earlier than the publication of Leibniz. Letters sent to others were shared in many ways. They were read at meetings of societies or social gatherings such as coffee houses & salons. They were copied and forwarded in their entirety or extracts were communicated to other scholars. Correspondence, therefore, held an essential place in the dissemination of scientific information in early modern science. The reason why many scientific periodicals have terms like "letters," "'correspondence," and their cognates in the title is rooted in this history. To disseminate the information in these learned letters more efficiently, some of the scholars in the seventeenth century voluntarily took the job of making copies and sending it to other scholars. John Collins (1625-83) called the "the scientific gazette” of his time and 'intelligencer' for the Royal Society, was one such person. Nicolas Claude Fabri de Peiresc (1580-1637) and Marin Mersenne (1588-1648) are essential names from France and Italy, respectively. Such scholars received letters, made copies and passed them on to other interested scholars until the emergence of 'scientific societies', which then on took the job of "trafficker in intelligence" in a more formalized manner. ‘Philosophical Transactions’ established in 1665 by Henry Oldenburg (1633-77), is touted to be the first 'scientific journal'. Oldenburg collected, edited and published 'letters' and 'correspondences' received from various scholars addressed to him. Thomas Bartholin (1616-80) took a similar step. He published the collection of the letters in Amsterdam in 1654 with the title ‘Epistolarum anatomicorum rariorum’. Later, he also added letters from other scholars to the compilation. These efforts resulted in the publication of the periodical 'Acta Medica et philosophical Hafniensis', which appeared in Copenhagen from 1673 to 1680. The circulation of correspondence resulted in societies becoming a platform for critical appraisal, and the periodical publications for wider dissemination slowly crystallized into agencies. For example, the "Bureau d'Adresse" established by the French physician Theophraste Renaudot (1584-1653), organized a series of seminars and brought out a publication Conferences du Bureau d'Adresse from 1634 to 1642. Soon, Journal des sçavans was started in January 1665 by Denis de Sallo in France with weekly book reviews and news in science, as well as in law and theology. Till today, 'letters' and 'correspondence' form an important means of communicating research. ‘Philosophical Transactions' happens to be the longest-running scientific journal of the world. Starting from the first journal in which the editor had the sole power to decide if the research was suitable for publication, decision-making power shifted slowly into the hands of decision-making committees and has now changed to discipline-based advisory editors.

Both research articles and reviews are written for a research-specific audience. This means that these articles assume that their readers have some background understanding of research. The language used in these articles is usually filled with many scientific terms (jargon) , that a non-researcher may not have come across before. Added to this, many papers have complex data analysis and representation, which may not be the best way to convey information to a non-scientific audience. Publishing before publishing through pre-prints: The different steps of publication can make it a very long process until the final article is published online. This leads to a delay in sharing of discoveries and results with the scientific community and the world. While scientists can share work through websites/blogs and social media, these do not serve to give them their due credit. Scientists thus use pre-prints. Pre-prints are articles that have not gone through the peer review process but are publicly available online on a server. Since pre-prints have not been evaluated through the peer review process, there is no guarantee that the study has been designed properly and the manuscript written well. However, there are advantages as well. The scientific community benefits, as they get access to new research faster and free of cost, and the scientists get to share their work and get credit for their novel work even before the peer review process is done. Journals and magazines for science engagement: Frontiers For Young Minds is a journal that publishes articles written by scientists for a more general audience, with a focus on children and teens. Scientists write about different topics in science or their research, but in a language that is more accessible to the young audience. This is ensured by allowing young reviewers, children of various age groups, to read the article and give feedback on how readable and accessible the article is before publication, with suggested changes to improve the article. While dedicated journals such as this are few, many scientific journals have started publishing ‘plain-language summaries’ of the research published in their journal. These are meant to describe the research in a more straightforward language and meant for a broad general audience. Several science magazines discuss scientific topics and/or the latest scientific discoveries in simpler words than journals. Some of them include Current Science, Science Reporter and Society for Science released in English; Research Matters in Kannada, Marathi, Assamese, Tamil and Hindi, and English; Sandarbh-Eklavya and Vigyan Pragati in Hindi; Safari in Gujrati; Gyan o Bigyan in Bengali; Science ki Duniya in Urdu. This can be an excellent place to start reading about science. Reading scientific journals is useful for not only keeping up with the latest scientific discoveries and findings, but also to understand that science is more than the facts we see in textbooks. Science is a way of thought, a perspective to critically evaluate the world around us, draw meaningful conclusions from our study of it, and scientific journals are the backbone in this journey. References: 1. 1667, An introduction to this tract Phil. Trans. R. Soc.11–2 http://doi.org/10.1098/rstl.1665.0002 2. https://kids.frontiersin.org/ 3. Sarah, S., 2017. Something for everyone. eLife, 6.

Edited by Ratneshwar Thakur and T. V. Venkateshwaran.

Understanding Scientific Journals and Articles: How to approach reading journal articles

by Anthony Carpi, Ph.D., Anne E. Egger, Ph.D., Natalie H. Kuldell

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Did you know that scientific literature goes all the way back to 600 BCE? Although scientific articles have changed some – for example, Isaac Newton wrote about the fun he had with prisms in a 1672 scientific article – the basics remain the same. This ensures that published research becomes part of the archive of scientific knowledge upon which other scientists can build.

Scientists make their research available to the community by publishing it in scientific journals.

In scientific papers, scientists explain the research that they are building on, their research methods, data and data analysis techniques, and their interpretation of the data.

Understanding how to read scientific papers is a critical skill for scientists and students of science.

We've all read the headlines at the supermarket checkout line: "Aliens Abduct New Jersey School Teacher" or "Quadruplets Born to 99-Year-Old Woman: Exclusive Photos Inside." Journals like the National Enquirer sell copies by publishing sensational headlines, and most readers believe only a fraction of what is printed. A person more interested in news than gossip could buy a publication like Time, Newsweek or Discover . These magazines publish information on current news and events, including recent scientific advances. These are not original reports of scientific research , however. In fact, most of these stories include phrases like, "A group of scientists recently published their findings on..." So where do scientists publish their findings?

Scientists publish their original research in scientific journals, which are fundamentally different from news magazines. The articles in scientific journals are not written by journalists – they are written by scientists. Scientific articles are not sensational stories intended to entertain the reader with an amazing discovery, nor are they news stories intended to summarize recent scientific events, nor even records of every successful and unsuccessful research venture. Instead, scientists write articles to describe their findings to the community in a transparent manner.

• Scientific journals vs. popular media

Within a scientific article, scientists present their research questions, the methods by which the question was approached, and the results they achieved using those methods. In addition, they present their analysis of the data and describe some of the interpretations and implications of their work. Because these articles report new work for the first time, they are called primary literature . In contrast, articles or news stories that review or report on scientific research already published elsewhere are referred to as secondary .

The articles in scientific journals are different from news articles in another way – they must undergo a process called peer review , in which other scientists (the professional peers of the authors) evaluate the quality and merit of research before recommending whether or not it should be published (see our Peer Review module). This is a much lengthier and more rigorous process than the editing and fact-checking that goes on at news organizations. The reason for this thorough evaluation by peers is that a scientific article is more than a snapshot of what is going on at a certain time in a scientist's research. Instead, it is a part of what is collectively called the scientific literature, a global archive of scientific knowledge. When published, each article expands the library of scientific literature available to all scientists and contributes to the overall knowledge base of the discipline of science.

Comprehension Checkpoint

• Scientific journals: Degrees of specialization

Figure 1: Nature : An example of a scientific journal.

There are thousands of scientific journals that publish research articles. These journals are diverse and can be distinguished according to their field of specialization. Among the most broadly targeted and competitive are journals like Cell , the New England Journal of Medicine (NEJM), Nature , and Science that all publish a wide variety of research articles (see Figure 1 for an example). Cell focuses on all areas of biology, NEJM on medicine, and both Science and Nature publish articles in all areas of science. Scientists submit manuscripts for publication in these journals when they feel their work deserves the broadest possible audience.

Just below these journals in terms of their reach are the top-tier disciplinary journals like Analytical Chemistry, Applied Geochemistry, Neuron, Journal of Geophysical Research , and many others. These journals tend to publish broad-based research focused on specific disciplines, such as chemistry, geology, neurology, nuclear physics, etc.

Next in line are highly specialized journals, such as the American Journal of Potato Research, Grass and Forage Science, the Journal of Shellfish Research, Neuropeptides, Paleolimnology , and many more. While the research published in various journals does not differ in terms of the quality or the rigor of the science described, it does differ in its degree of specialization: These journals tend to be more specialized, and thus appeal to a more limited audience.

All of these journals play a critical role in the advancement of science and dissemination of information (see our Utilizing the Scientific Literature module for more information). However, to understand how science is disseminated through these journals, you must first understand how the articles themselves are formatted and what information they contain. While some details about format vary between journals and even between articles in the same journal, there are broad characteristics that all scientific journal articles share.

• The standard format of journal articles

In June of 2005, the journal Science published a research report on a sighting of the ivory-billed woodpecker, a bird long considered extinct in North America (Fitzpatrick et al., 2005). The work was of such significance and broad interest that it was displayed prominently on the cover (Figure 2) and highlighted by an editorial at the front of the journal (Kennedy, 2005). The authors were aware that their findings were likely to be controversial, and they worked especially hard to make their writing clear. Although the article has no headings within the text, it can easily be divided into sections:

Figure 2: A picture of the cover of Science from June 3, 2005.

Title and authors: The title of a scientific article should concisely and accurately summarize the research . Here, the title used is "Ivory-billed Woodpecker ( Campephilus principalis ) Persists in North America." While it is meant to capture attention, journals avoid using misleading or overly sensational titles (you can imagine that a tabloid might use the headline "Long-dead Giant Bird Attacks Canoeists!"). The names of all scientific contributors are listed as authors immediately after the title. You may be used to seeing one or maybe two authors for a book or newspaper article, but this article has seventeen authors! It's unlikely that all seventeen of those authors sat down in a room and wrote the manuscript together. Instead, the authorship reflects the distribution of the workload and responsibility for the research, in addition to the writing. By convention, the scientist who performed most of the work described in the article is listed first, and it is likely that the first author did most of the writing. Other authors had different contributions; for example, Gene Sparling is the person who originally spotted the bird in Arkansas and was subsequently contacted by the scientists at the Cornell Laboratory of Ornithology. In some cases, but not in the woodpecker article, the last author listed is the senior researcher on the project, or the scientist from whose lab the project originated. Increasingly, journals are requesting that authors detail their exact contributions to the research and writing associated with a particular study.

Abstract: The abstract is the first part of the article that appears right after the listing of authors in an article. In it, the authors briefly describe the research question, the general methods , and the major findings and implications of the work. Providing a summary like this at the beginning of an article serves two purposes: First, it gives readers a way to decide whether the article in question discusses research that interests them, and second, it is entered into literature databases as a means of providing more information to people doing scientific literature searches. For both purposes, it is important to have a short version of the full story. In this case, all of the critical information about the timing of the study, the type of data collected, and the potential interpretations of the findings is captured in four straightforward sentences as seen below:

The ivory-billed woodpecker ( Campephilus principalis ), long suspected to be extinct, has been rediscovered in the Big Woods region of eastern Arkansas. Visual encounters during 2004 and 2005, and analysis of a video clip from April 2004, confirm the existence of at least one male. Acoustic signatures consistent with Campephilus display drums also have been heard from the region. Extensive efforts to find birds away from the primary encounter site remain unsuccessful, but potential habitat for a thinly distributed source population is vast (over 220,000 hectares).

Introduction: The central research question and important background information are presented in the introduction. Because science is a process that builds on previous findings, relevant and established scientific knowledge is cited in this section and then listed in the References section at the end of the article. In many articles, a heading is used to set this and subsequent sections apart, but in the woodpecker article the introduction consists of the first three paragraphs, in which the history of the decline of the woodpecker and previous studies are cited. The introduction is intended to lead the reader to understand the authors' hypothesis and means of testing it. In addition, the introduction provides an opportunity for the authors to show that they are aware of the work that scientists have done before them and how their results fit in, explicitly building on existing knowledge.

Materials and methods: In this section, the authors describe the research methods they used (see The Practice of Science module for more information on these methods). All procedures, equipment, measurement parameters , etc. are described in detail sufficient for another researcher to evaluate and/or reproduce the research. In addition, authors explain the sources of error and procedures employed to reduce and measure the uncertainty in their data (see our Uncertainty, Error, and Confidence module). The detail given here allows other scientists to evaluate the quality of the data collected. This section varies dramatically depending on the type of research done. In an experimental study, the experimental set-up and procedure would be described in detail, including the variables , controls , and treatment . The woodpecker study used a descriptive research approach, and the materials and methods section is quite short, including the means by which the bird was initially spotted (on a kayaking trip) and later photographed and videotaped.

Results: The data collected during the research are presented in this section, both in written form and using tables, graphs, and figures (see our Using Graphs and Visual Data module). In addition, all statistical and data analysis techniques used are presented (see our Statistics in Science module). Importantly, the data should be presented separately from any interpretation by the authors. This separation of data from interpretation serves two purposes: First, it gives other scientists the opportunity to evaluate the quality of the actual data, and second, it allows others to develop their own interpretations of the findings based on their background knowledge and experience. In the woodpecker article, the data consist largely of photographs and videos (see Figure 3 for an example). The authors include both the raw data (the photograph) and their analysis (the measurement of the tree trunk and inferred length of the bird perched on the trunk). The sketch of the bird on the right-hand side of the photograph is also a form of analysis, in which the authors have simplified the photograph to highlight the features of interest. Keeping the raw data (in the form of a photograph) facilitated reanalysis by other scientists: In early 2006, a team of researchers led by the American ornithologist David Sibley reanalyzed the photograph in Figure 3 and came to the conclusion that the bird was not an ivory-billed woodpecker after all (Sibley et al, 2006).

Figure 3: An example of the data presented in the Ivory-billed woodpecker article (Fitzpatrick et al ., 2005, Figure 1).

Discussion and conclusions: In this section, authors present their interpretation of the data , often including a model or idea they feel best explains their results. They also present the strengths and significance of their work. Naturally, this is the most subjective section of a scientific research article as it presents interpretation as opposed to strictly methods and data, but it is not speculation by the authors. Instead, this is where the authors combine their experience, background knowledge, and creativity to explain the data and use the data as evidence in their interpretation (see our Data Analysis and Interpretation module). Often, the discussion section includes several possible explanations or interpretations of the data; the authors may then describe why they support one particular interpretation over the others. This is not just a process of hedging their bets – this how scientists say to their peers that they have done their homework and that there is more than one possible explanation. In the woodpecker article, for example, the authors go to great lengths to describe why they believe the bird they saw is an ivory-billed woodpecker rather than a variant of the more common pileated woodpecker, knowing that this is a likely potential rebuttal to their initial findings. A final component of the conclusions involves placing the current work back into a larger context by discussing the implications of the work. The authors of the woodpecker article do so by discussing the nature of the woodpecker habitat and how it might be better preserved.

In many articles, the results and discussion sections are combined, but regardless, the data are initially presented without interpretation .

References: Scientific progress requires building on existing knowledge, and previous findings are recognized by directly citing them in any new work. The citations are collected in one list, commonly called "References," although the precise format for each journal varies considerably. The reference list may seem like something you don't actually read, but in fact it can provide a wealth of information about whether the authors are citing the most recent work in their field or whether they are biased in their citations towards certain institutions or authors. In addition, the reference section provides readers of the article with more information about the particular research topic discussed. The reference list for the woodpecker article includes a wide variety of sources that includes books, other journal articles, and personal accounts of bird sightings.

Supporting material: Increasingly, journals make supporting material that does not fit into the article itself – like extensive data tables, detailed descriptions of methods , figures, and animations – available online. In this case, the video footage shot by the authors is available online, along with several other resources.

• Reading the primary literature

The format of a scientific article may seem overly structured compared to many other things you read, but it serves a purpose by providing an archive of scientific research in the primary literature that we can build on. Though isolated examples of that archive go as far back as 600 BCE (see the Babylonian tablets in our Description in Scientific Research module), the first consistently published scientific journal was the Philosophical Transactions of the Royal Society of London , edited by Henry Oldenburg for the Royal Society beginning in 1666 (see our Scientific Institutions and Societies module). These early scientific writings include all of the components listed above, but the writing style is surprisingly different than a modern journal article. For example, Isaac Newton opened his 1672 article "New Theory About Light and Colours" with the following:

I shall without further ceremony acquaint you, that in the beginning of the Year 1666...I procured me a Triangular glass-Prisme, to try therewith the celebrated Phenomena of Colours . And in order thereto having darkened my chamber, and made a small hole in my window-shuts, to let in a convenient quantity of the Suns light, I placed my Prisme at his entrance, that it might be thereby refracted to the opposite wall. It was at first a very pleasing divertissement, to view the vivid and intense colours produced thereby; but after a while applying my self to consider them more circumspectly, I became surprised to see them in an oblong form; which, according to the received laws of Refraction, I expected should have been circular . (Newton, 1672)

Figure 4: Isaac Newton described the rainbow produced by a prism as a "pleasing divertissement."

Newton describes his materials and methods in the first few sentences ("... a small hole in my window-shuts"), describes his results ("an oblong form"), refers to the work that has come before him ("the received laws of Refraction"), and highlights how his results differ from his expectations. Today, however, Newton 's statement that the "colours" produced were a "very pleasing divertissement" would be out of place in a scientific article (Figure 4). Much more typically, modern scientific articles are written in an objective tone, typically without statements of personal opinion to avoid any appearance of bias in the interpretation of their results. Unfortunately, this tone often results in overuse of the passive voice, with statements like "a Triangular glass-Prisme was procured" instead of the wording Newton chose: "I procured me a Triangular glass-Prisme." The removal of the first person entirely from the articles reinforces the misconception that science is impersonal, boring, and void of creativity, lacking the enjoyment and surprise described by Newton. The tone can sometimes be misleading if the study involves many authors, making it unclear who did what work. The best scientific writers are able to both present their work in an objective tone and make their own contributions clear.

The scholarly vocabulary in scientific articles can be another obstacle to reading the primary literature. Materials and Methods sections often are highly technical in nature and can be confusing if you are not intimately familiar with the type of research being conducted. There is a reason for all of this vocabulary, however: An explicit, technical description of materials and methods provides a means for other scientists to evaluate the quality of the data presented and can often provide insight to scientists on how to replicate or extend the research described.

The tone and specialized vocabulary of the modern scientific article can make it hard to read, but understanding the purpose and requirements for each section can help you decipher the primary literature. Learning to read scientific articles is a skill, and like any other skill, it requires practice and experience to master. It is not, however, an impossible task.

Strange as it seems, the most efficient way to tackle a new article may be through a piecemeal approach, reading some but not all the sections and not necessarily in their order of appearance. For example, the abstract of an article will summarize its key points, but this section can often be dense and difficult to understand. Sometimes the end of the article may be a better place to start reading. In many cases, authors present a model that fits their data in this last section of the article. The discussion section may emphasize some themes or ideas that tie the story together, giving the reader some foundation for reading the article from the beginning. Even experienced scientists read articles this way – skimming the figures first, perhaps, or reading the discussion and then going back to the results. Often, it takes a scientist multiple readings to truly understand the authors' work and incorporate it into their personal knowledge base in order to build on that knowledge.

• Building knowledge and facilitating discussion

The process of science does not stop with the publication of the results of research in a scientific article. In fact, in some ways, publication is just the beginning. Scientific journals also provide a means for other scientists to respond to the work they publish; like many newspapers and magazines, most scientific journals publish letters from their readers.

Unlike the common "Letters to the Editor" of a newspaper, however, the letters in scientific journals are usually critical responses to the authors of a research study in which alternative interpretations are outlined. When such a letter is received by a journal editor, it is typically given to the original authors so that they can respond, and both the letter and response are published together. Nine months after the original publication of the woodpecker article, Science published a letter (called a "Comment") from David Sibley and three of his colleagues, who reinterpreted the Fitzpatrick team's data and concluded that the bird in question was a more common pileated woodpecker, not an ivory-billed woodpecker (Sibley et al., 2006). The team from the Cornell lab wrote a response supporting their initial conclusions, and Sibley's team followed that up with a response of their own in 2007 (Fitzpatrick et al., 2006; Sibley at al., 2007). As expected, the research has generated significant scientific controversy and, in addition, has captured the attention of the public, spreading the story of the controversy into the popular media.

For more information about this story see The Case of the Ivory-Billed Woodpecker module.

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Peer Review in Scientific Publications: Benefits, Critiques, & A Survival Guide

Affiliations.

• 1 Clinical Biochemistry, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, University of Toronto , Toronto, Ontario, Canada.
• 2 Clinical Biochemistry, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada; Chair, Communications and Publications Division (CPD), International Federation for Sick Clinical Chemistry (IFCC), Milan, Italy.
• PMID: 27683470
• PMCID: PMC4975196

Peer review has been defined as a process of subjecting an author's scholarly work, research or ideas to the scrutiny of others who are experts in the same field. It functions to encourage authors to meet the accepted high standards of their discipline and to control the dissemination of research data to ensure that unwarranted claims, unacceptable interpretations or personal views are not published without prior expert review. Despite its wide-spread use by most journals, the peer review process has also been widely criticised due to the slowness of the process to publish new findings and due to perceived bias by the editors and/or reviewers. Within the scientific community, peer review has become an essential component of the academic writing process. It helps ensure that papers published in scientific journals answer meaningful research questions and draw accurate conclusions based on professionally executed experimentation. Submission of low quality manuscripts has become increasingly prevalent, and peer review acts as a filter to prevent this work from reaching the scientific community. The major advantage of a peer review process is that peer-reviewed articles provide a trusted form of scientific communication. Since scientific knowledge is cumulative and builds on itself, this trust is particularly important. Despite the positive impacts of peer review, critics argue that the peer review process stifles innovation in experimentation, and acts as a poor screen against plagiarism. Despite its downfalls, there has not yet been a foolproof system developed to take the place of peer review, however, researchers have been looking into electronic means of improving the peer review process. Unfortunately, the recent explosion in online only/electronic journals has led to mass publication of a large number of scientific articles with little or no peer review. This poses significant risk to advances in scientific knowledge and its future potential. The current article summarizes the peer review process, highlights the pros and cons associated with different types of peer review, and describes new methods for improving peer review.

Keywords: journal; manuscript; open access; peer review; publication.

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Understanding Peer Review in Science

Peer review is an essential element of the scientific publishing process that helps ensure that research articles are evaluated, critiqued, and improved before release into the academic community. Take a look at the significance of peer review in scientific publications, the typical steps of the process, and and how to approach peer review if you are asked to assess a manuscript.

What Is Peer Review?

Peer review is the evaluation of work by peers, who are people with comparable experience and competency. Peers assess each others’ work in educational settings, in professional settings, and in the publishing world. The goal of peer review is improving quality, defining and maintaining standards, and helping people learn from one another.

In the context of scientific publication, peer review helps editors determine which submissions merit publication and improves the quality of manuscripts prior to their final release.

Types of Peer Review for Manuscripts

There are three main types of peer review:

• Single-blind review: The reviewers know the identities of the authors, but the authors do not know the identities of the reviewers.
• Double-blind review: Both the authors and reviewers remain anonymous to each other.
• Open peer review: The identities of both the authors and reviewers are disclosed, promoting transparency and collaboration.

There are advantages and disadvantages of each method. Anonymous reviews reduce bias but reduce collaboration, while open reviews are more transparent, but increase bias.

Key Elements of Peer Review

Proper selection of a peer group improves the outcome of the process:

• Expertise : Reviewers should possess adequate knowledge and experience in the relevant field to provide constructive feedback.
• Objectivity : Reviewers assess the manuscript impartially and without personal bias.
• Confidentiality : The peer review process maintains confidentiality to protect intellectual property and encourage honest feedback.
• Timeliness : Reviewers provide feedback within a reasonable timeframe to ensure timely publication.

Steps of the Peer Review Process

The typical peer review process for scientific publications involves the following steps:

• Submission : Authors submit their manuscript to a journal that aligns with their research topic.
• Editorial assessment : The journal editor examines the manuscript and determines whether or not it is suitable for publication. If it is not, the manuscript is rejected.
• Peer review : If it is suitable, the editor sends the article to peer reviewers who are experts in the relevant field.
• Reviewer feedback : Reviewers provide feedback, critique, and suggestions for improvement.
• Revision and resubmission : Authors address the feedback and make necessary revisions before resubmitting the manuscript.
• Final decision : The editor makes a final decision on whether to accept or reject the manuscript based on the revised version and reviewer comments.
• Publication : If accepted, the manuscript undergoes copyediting and formatting before being published in the journal.

Pros and Cons

While the goal of peer review is improving the quality of published research, the process isn’t without its drawbacks.

• Quality assurance : Peer review helps ensure the quality and reliability of published research.
• Error detection : The process identifies errors and flaws that the authors may have overlooked.
• Credibility : The scientific community generally considers peer-reviewed articles to be more credible.
• Professional development : Reviewers can learn from the work of others and enhance their own knowledge and understanding.
• Time-consuming : The peer review process can be lengthy, delaying the publication of potentially valuable research.
• Bias : Personal biases of reviews impact their evaluation of the manuscript.
• Inconsistency : Different reviewers may provide conflicting feedback, making it challenging for authors to address all concerns.
• Limited effectiveness : Peer review does not always detect significant errors or misconduct.
• Poaching : Some reviewers take an idea from a submission and gain publication before the authors of the original research.

Steps for Conducting Peer Review of an Article

Generally, an editor provides guidance when you are asked to provide peer review of a manuscript. Here are typical steps of the process.

• Accept the right assignment: Accept invitations to review articles that align with your area of expertise to ensure you can provide well-informed feedback.
• Manage your time: Allocate sufficient time to thoroughly read and evaluate the manuscript, while adhering to the journal’s deadline for providing feedback.
• Read the manuscript multiple times: First, read the manuscript for an overall understanding of the research. Then, read it more closely to assess the details, methodology, results, and conclusions.
• Evaluate the structure and organization: Check if the manuscript follows the journal’s guidelines and is structured logically, with clear headings, subheadings, and a coherent flow of information.
• Assess the quality of the research: Evaluate the research question, study design, methodology, data collection, analysis, and interpretation. Consider whether the methods are appropriate, the results are valid, and the conclusions are supported by the data.
• Examine the originality and relevance: Determine if the research offers new insights, builds on existing knowledge, and is relevant to the field.
• Check for clarity and consistency: Review the manuscript for clarity of writing, consistent terminology, and proper formatting of figures, tables, and references.
• Identify ethical issues: Look for potential ethical concerns, such as plagiarism, data fabrication, or conflicts of interest.
• Provide constructive feedback: Offer specific, actionable, and objective suggestions for improvement, highlighting both the strengths and weaknesses of the manuscript. Don’t be mean.
• Organize your review: Structure your review with an overview of your evaluation, followed by detailed comments and suggestions organized by section (e.g., introduction, methods, results, discussion, and conclusion).
• Be professional and respectful: Maintain a respectful tone in your feedback, avoiding personal criticism or derogatory language.
• Proofread your review: Before submitting your review, proofread it for typos, grammar, and clarity.
• Couzin-Frankel J (September 2013). “Biomedical publishing. Secretive and subjective, peer review proves resistant to study”. Science . 341 (6152): 1331. doi: 10.1126/science.341.6152.1331
• Lee, Carole J.; Sugimoto, Cassidy R.; Zhang, Guo; Cronin, Blaise (2013). “Bias in peer review”. Journal of the American Society for Information Science and Technology. 64 (1): 2–17. doi: 10.1002/asi.22784
• Slavov, Nikolai (2015). “Making the most of peer review”. eLife . 4: e12708. doi: 10.7554/eLife.12708
• Spier, Ray (2002). “The history of the peer-review process”. Trends in Biotechnology . 20 (8): 357–8. doi: 10.1016/S0167-7799(02)01985-6
• Squazzoni, Flaminio; Brezis, Elise; Marušić, Ana (2017). “Scientometrics of peer review”. Scientometrics . 113 (1): 501–502. doi: 10.1007/s11192-017-2518-4

Related Posts

What Is Research, and Why Do People Do It?

• Open Access
• First Online: 03 December 2022

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• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  

Part of the book series: Research in Mathematics Education ((RME))

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Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

You have full access to this open access chapter,  Download chapter PDF

Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1

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• Published: 17 September 2024

Evidence for widespread human exposure to food contact chemicals

• Birgit Geueke   ORCID: orcid.org/0000-0002-0749-3982 1 ,
• Lindsey V. Parkinson   ORCID: orcid.org/0000-0002-6219-0546 1 ,
• Ksenia J. Groh   ORCID: orcid.org/0000-0002-3778-4721 2 ,
• Christopher D. Kassotis   ORCID: orcid.org/0000-0002-0990-2428 3 ,
• Maricel V. Maffini   ORCID: orcid.org/0000-0002-3853-9461 4 ,
• Olwenn V. Martin   ORCID: orcid.org/0000-0003-2724-7882 5 ,
• Lisa Zimmermann   ORCID: orcid.org/0000-0001-6801-6859 1 ,
• Martin Scheringer   ORCID: orcid.org/0000-0002-0809-7826 6 , 7 &
• Jane Muncke   ORCID: orcid.org/0000-0002-6942-0594 1  

Journal of Exposure Science & Environmental Epidemiology ( 2024 ) Cite this article

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Over 1800 food contact chemicals (FCCs) are known to migrate from food contact articles used to store, process, package, and serve foodstuffs. Many of these FCCs have hazard properties of concern, and still others have never been tested for toxicity. Humans are known to be exposed to FCCs via foods, but the full extent of human exposure to all FCCs is unknown.

To close this important knowledge gap, we conducted a systematic overview of FCCs that have been monitored and detected in human biomonitoring studies according to a previously published protocol.

We first compared the more than 14,000 known FCCs to five biomonitoring programs and three metabolome/exposome databases. In a second step, we prioritized FCCs that have been frequently detected in food contact materials and systematically mapped the available evidence for their presence in humans.

For 25% of the known FCCs (3601), we found evidence for their presence in humans. This includes 194 FCCs from human biomonitoring programs, with 80 of these having hazard properties of high concern. Of the 3528 FCCs included in metabolome/exposome databases, most are from the Blood Exposome Database. We found evidence for the presence in humans for 63 of the 175 prioritized FCCs included in the systematic evidence map, and 59 of the prioritized FCCs lack hazard data.

Significance

Notwithstanding that there are also other sources of exposure for many FCCs, these data will help to prioritize FCCs of concern by linking information on migration and biomonitoring. Our results on FCCs monitored in humans are available as an interactive dashboard (FCChumon) to enable policymakers, public health researchers, and food industry decision-makers to make food contact materials and articles safer, reduce human exposure to hazardous FCCs and improve public health.

Impact statement

We present systematically compiled evidence on human exposure to 3601 food contact chemicals (FCCs) and highlight FCCs that are of concern because of their known hazard properties. Further, we identify relevant data gaps for FCCs found in food contact materials and foods. This article improves the understanding of food contact materials’ contribution to chemical exposure for the human population and highlights opportunities for improving public health.

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Introduction.

Humans are exposed to synthetic chemicals from food, drugs, household and personal care products, and environmental pollutants. Some of these chemicals have been associated with the increasing prevalence of non-communicable diseases [ 1 , 2 , 3 ]. Food packaging and other food contact articles (FCAs), such as tableware and food processing equipment, contribute to the human chemical burden via oral exposure, because food contact chemicals (FCCs) migrate from different food contact materials (FCMs) into foodstuffs and are then ingested [ 4 , 5 , 6 , 7 , 8 ].

For individual FCCs, such as bisphenol A (BPA) and several phthalates, the contribution of chemical migration from FCMs to human exposure has been studied in detail, taking into account that other exposure sources exist [ 9 , 10 , 11 , 12 ]. BPA is banned in some food contact applications, such as baby bottles, in many parts of the world, but is still regularly measured in FCMs (e.g [ 13 , 14 , 15 ].). Currently, a complete ban on BPA in FCMs is proposed by the European Commission [ 16 ]. However, hundreds of FCCs have been shown to migrate from FCMs into foods, and thousands of FCCs have been extracted from FCMs [ 5 ]. In total, over 12,000 FCCs could be intentionally used during the manufacturing of different types of FCMs [ 17 ] and even more chemicals could be present in FCMs as non-intentionally added substances (NIAS) that are introduced or formed during manufacture or use [ 5 , 18 , 19 ].

Many FCCs are of concern for human health because they have hazard properties such as carcinogenicity, mutagenicity, and reprotoxicity (CMR), endocrine disrupting properties, bioaccumulation potential, and/or persistence [ 17 , 20 , 21 ]. In addition, toxicity data are often incomplete or missing, which means that safe use cannot be assessed [ 17 , 22 , 23 ]. Therefore, reducing exposure to known hazardous FCCs and assessing untested FCCs can contribute to the prevention of non-communicable diseases that are associated with chemical exposures [ 24 , 25 ].

The challenges in regulating FCMs and managing the health risks associated with FCCs are diverse and legislation often does not keep up with the latest scientific understanding [ 26 , 27 ]. Publicly available evidence on intentionally used FCCs and their known hazards is available in our earlier work where we compiled the Food Contact Chemicals Database (FCCdb) [ 17 ]. The FCCdb gives an overview of all chemicals that are known to be used in the manufacture of FCMs. Further, we systematically mapped data on migrating and extractable FCCs, and our Database on Migrating and Extractable Food Contact Chemicals (FCCmigex) provides evidence for FCCs that have been detected in extracts of FCMs and/or their migrates into food and food simulants, indicating the potential for human exposure [ 5 ]. Only 30% of the chemicals present in FCMs are listed in the FCCdb, based on information from the most recent update of the FCCmigex database [ 28 ]. This indicates that the non-listed FCCs are either NIAS or have been intentionally used although they are not recorded in any of the FCCdb’s sources. Even though it is well-established that chemicals migrating from FCMs contribute to human exposure, the presence of FCCs in human samples has not yet been systematically assessed.

Here, we provide a systematic overview of FCCs that have been monitored and detected in humans by including information from biomonitoring programs, metabolome and exposome databases, and the primary scientific literature. We detailed our approach in a previously published protocol [ 29 ]. The resulting Database on Food Contact Chemicals Monitored in Humans (FCChumon) is a publicly available tool integrating empirical data on FCCs in human samples, and it complements the FCCdb and FCCmigex databases. Our goal is to provide scientific evidence that supports advancing global FCM regulations and the safety assessments of FCCs.

Overview of the two-step approach

The evidence for FCCs that have been monitored and detected in human samples was compiled according to a protocol initially registered on Zenodo in September 2022 and updated in April 2023 [ 29 ]. We followed the structure of a Population-Outcome (PO) question:

Question: Which known FCCs have been monitored in the human body?

Population (P): Human samples, such as blood, urine, hair, and breast milk, from people of any age, gender, or ethnicity

Outcome (O): Any result describing the monitoring/detection of a known FCC or its metabolite

As detailed in the protocol and further specified below, we applied a stepwise approach and referred to biomonitoring programs, databases on the human exposome and metabolome, and the primary scientific literature to map the evidence for FCCs’ presence in humans. Briefly, in step 1, FCCs included in the FCCdb and the FCCmigex databases were matched to the chemicals listed in biomonitoring programs and metabolome and exposome databases (Fig.  1 ). During protocol development, we found that thousands of FCCs were neither included in the selected metabolome/exposome databases nor in biomonitoring programs, while the primary scientific literature reported the monitoring of some of these FCCs in human samples. In step 2, we therefore applied the methodology of a systematic evidence map to obtain relevant information from the scientific literature. FCCs not found in any of the sources consulted in step 1 were prioritized based on their presence in FCMs, according to evidence from FCCmigex. These prioritized FCCs were included in the systematic evidence mapping performed in step 2 to understand their presence in human samples.

We compared known FCCs to biomonitoring programs and metabolome/exposome databases (step 1) and systematically mapped the evidence for presence of additional, priority FCCs in humans (step 2). The results of steps 1 and step 2 (red boxes) comprise the Database of Food Contact Chemicals Monitored in Humans (FCChumon).

Information sources for chemical comparisons

Together, the FCCdb and the FCCmigex databases presently consist of 14,402 known FCCs with assigned CAS Registry Numbers (Fig.  1 ). The FCCdb is an inventory for FCCs that are potentially used in the manufacture of FCMs and FCAs [ 17 ]. It currently contains 12,285 distinct FCCs of which 11,593 have a CAS Registry Number. The FCCmigex database systematically maps scientific evidence of FCCs that have been measured in FCMs and FCAs [ 5 , 28 ]. The most recent version of the FCCmigex database contains 4262 chemicals with a CAS Registry Number, of which 3995 FCCs have been detected at least once in an FCM migrate or extract. Each FCCmigex database entry is linked to the reference from which it was generated and provides information about the FCC, what type of FCA and which FCM(s) were tested, details about the experimental set-up, and whether the FCC was detected or not. Chemicals that have been targeted but never detected in FCMs, and that are not in the FCCdb, are not included in this study.

In the first step, we consulted five biomonitoring programs that encompass different ranges of chemicals and provide wide geographic coverage, namely the National Health and Nutrition Examination Survey (NHANES) of the US [ 30 ], the Canadian Health Measures Survey (CHMS) [ 31 ], the Human Biomonitoring for Europe project (HBM4EU) [ 32 , 33 ], the Korean National Environmental Health Survey (KoNEHS) [ 34 ], and Biomonitoring California [ 35 ]. Further, three metabolome/exposome databases were used to identify FCCs that have been monitored in humans: the Human Metabolome Database (HMDB) [ 36 , 37 ]; the Blood Exposome Database [ 38 , 39 ], and the Exposome Explorer [ 40 , 41 ]. In addition to these sources, in the second step we systematically searched the primary scientific literature for human biomonitoring data on specific FCCs, using bibliographic databases (PubMed, Web of Science Core Collection (WoS), ScienceDirect, and CAS SciFinder n ).

Data processing and comparisons (step 1)

All known FCCs with CAS Registry Numbers were included in the comparisons of step 1, regardless of whether the CAS Registry Number indicates a specific structure or a chemical mixture. If available, additional chemical identifiers, such as INChI Keys and SMILES, were retrieved from the collections of FCCs associated with lists S77 and S112 from the NORMAN Suspect List Exchange [ 42 , 43 , 44 ].

In step 1A, information on chemicals that are part of any of the biomonitoring programs was downloaded from the respective sources. We also collected information on whether a chemical has been ‘monitored but never detected’ or ‘monitored and detected’. If it was stated in the biomonitoring programs that the analyte was a metabolite of a specific parent compound, we paired the metabolite and the parent compound for comparison with the known FCCs. For example, the analyte mono-ethyl phthalate (CAS 863029-89-4) is listed as a metabolite of di-ethyl phthalate (CAS 84-66-2) in NHANES, and we used both CAS Registry Numbers in the comparisons to the known FCCs. In this way, we ensured that FCCs were identified in the biomonitoring programs regardless of whether detection in human samples was reported for parent compounds or their metabolites. We manually added CAS Registry Numbers to chemicals missing these identifiers in the biomonitoring lists to enable their comparisons to the FCCs.

In step 1B, the data set ‘biomarkers’ was downloaded from the Exposome Explorer, and the full content of the Blood Exposome Database was retrieved. From the HMDB, all chemicals were included that were labeled by metabolite status as ‘detected and quantified’, ‘detected but not quantified’, and ‘expected but not quantified’. The metabolome/exposome databases do not systematically report links between parent compounds and metabolites. We used these chemical lists from the metabolome/exposome databases without any further editing.

Based on their CAS Registry Numbers, InChI Keys, or SMILES identifiers, FCCs were then compared to the chemical lists retrieved from the biomonitoring programs and metabolome/exposome databases. These comparisons were performed by means of Python (v3.10.8) pandas package (v1.5.3).

Systematic evidence mapping (step 2)

Prioritization and grouping of fccs.

In step 2, we focused on the FCCs that were not found in any of the sources of step 1, i.e., all FCCs, or their metabolites, that have never been included in a biomonitoring program (regardless of whether they have been detected or not) and all FCCs that did not generate any match in the metabolome/exposome databases. These FCCs not monitored in any of the sources of step 1 were candidates for the systematic evidence mapping in step 2. For this step, we prioritized FCCs that have at least five database entries in the FCCmigex, reporting their detection in migrates and/or extracts of FCMs. To verify the absence of any prioritized chemicals in step 1, we also searched the HMDB for the chemical names that are used in the FCCmigex database and in Norman SLE.

For further data analysis and interpretation, prioritized FCCs were assigned to chemical groups based on functional categories and/or chemical structures. During grouping, we referred to the primary literature included in this systematic evidence map and in the FCCmigex database to understand the function and/or chemical features of an FCC. Additionally, we used the tool Classyfire [ 45 ], the Plastics Additives Handbook [ 46 ], and expert knowledge to group FCCs based on their applications in FCMs and/or chemical features, such as functional groups and structural properties.

Literature searches and screening

For each of the prioritized FCCs, individual literature searches were performed. For PubMed, WoS, and ScienceDirect, search strategies included the chemical name as used in the FCCdb or the FCCmigex, and generic search terms related to human biomonitoring (e.g., human, blood, urine, biomonitoring) that were connected by the Boolean operator OR. Searches in CAS SciFinder n used CAS Registry Numbers instead of chemical names. Search strings and settings were slightly adapted depending on the requirements of each database. The searches were not restricted by publication date or language and included all literature published by February 2023. Full details on search strings, applied filters, and settings have been published previously [ 29 ].

Individual literature searches were stored in separate Endnote files, from which duplicates were removed. All individual libraries were uploaded into the online evidence synthesis tool Cadima [ 47 ], where further duplicates were deleted. The references were then screened in a two-level process, beginning with title-and-abstract screening and followed by full-text screening. During the screening, the eligibility criteria specified in the protocol were applied to all prioritized FCCs that were analyzed in the respective reference [ 29 ]. In brief, studies were considered eligible and included in the systematic evidence map if the analyzed sample originated from a human specimen (e.g., urine, blood, and breast milk) and at least one prioritized FCC was analyzed. Ten percent of the references were independently screened by two reviewers in parallel at title-and-abstract and full-text levels, and disagreements were resolved bilaterally. Reasons for exclusion were recorded during full-text screening.

Data extraction

Eligible studies were used to collect information on whether FCCs have been monitored in human samples and if they have been detected. Details on the sample type and analytical approaches were part of the data extraction process (see Supplementary Information). The process was based on the data extraction software tool SciExtract [ 5 ] which allowed us to use precoded options to systematically compile the data. SciExtract was also used to organize and manage the workflow and to store the extracted data.

Hazard mapping

For FCCs included in the biomonitoring programs (step 1A) and those prioritized in step 2, we compiled the hazard properties according to human-health-related criteria described in the EU’s Chemicals Strategy for Sustainability (CSS) [ 48 ]. The CSS seeks to ban the most harmful chemicals from consumer products, including FCMs, and defines chemicals as ‘most harmful’ to human health if they are carcinogenic, mutagenic or toxic to reproduction (CMR) or exhibit specific target organ toxicity (STOT). Hazards associated with endocrine-disrupting properties, persistence, bioaccumulation, and mobility of a chemical are also mentioned in the CSS but were not included in this analysis. We consulted the European Chemicals Agency’s (ECHA) Classification and Labelling Inventory aligned with the Globally Harmonized System (GHS) for chemical classification and labeling [ 49 ] and referred to GHS-aligned classifications by the Japanese Government [ 50 ] for identifying human health-related hazards. Following the GHS criteria for classification and labeling, we identified chemicals as ‘high concern’ if they exhibit CMR properties belonging to categories 1A and 1B (known and presumed CMR, respectively) and/or have been classified as STOT category 1 after repeated exposure (RE) (Fig.  S1 ). Chemicals of ‘medium concern’ were those suspected to have CMR and/or STOT RE properties, as indicated by their classifications in category 2. Chemicals that have been classified based on other concerns, such as aquatic toxicity or skin sensitization, were marked as ‘other concern’. FCCs with data in at least one hazard category and without any classification were labeled as ‘not classified’. FCCs that were not included in the hazard inventories, or for which no data were available in any hazard category, were labelled with ‘no hazard data’.

Overall evidence for the presence of FCCs in humans

For a total of 3601 (or 25%) of the 14,402 known FCCs, we found evidence for their presence in human samples (Fig.  2 ). Of these, 194 FCCs have been detected in biomonitoring programs, and 3528 FCCs are listed in metabolome/exposome databases, with an overlap of 184 FCCs found in both types of sources. The total of 3601 FCCs also includes 63 out of 175 prioritized FCCs that have been detected in humans according to the results of the systematic evidence map (step 2).

Schematic representation of the FCCs monitored and detected in biomonitoring programs and/or listed in metabolome/exposome databases (step 1) and additional FCCs detected in humans, based on evidence from the scientific literature for a set of prioritized FCCs (step 2).

Based on the results of this stepwise approach, we set up the FCChumon database, which is provided as an interactive tool that is freely available, searchable, and linking to the relevant sources ( https://www.foodpackagingforum.org/fcchumon ).

Analysis of biomonitoring programs and metabolome/exposome databases

In step 1, we identified 3538 FCCs that have been detected in humans, which can be divided into 1883, 863, and 792 FCCs that are included only in the FCCdb, only in the FCCmigex, and in both databases, respectively (Fig.  3 , lower panel). These numbers indicate that 23% of the FCCs in the FCCdb and 41% of the FCCs in the FCCmigex are listed in at least one of the sources in Step 1. Sixty-seven percent of FCCs that are listed in both FCC databases have evidence of presence in humans.

The upper panel illustrates the FCCs from the FCCdb (green outline), the FCCmigex (yellow outline), and their overlap. The left part of the middle panel shows the number of known FCCs that have been detected in biomonitoring programs and, in brackets, the total number of monitored FCCs. The right part of the middle panel displays the FCCs that are listed in metabolome/exposome databases. FCCs that have been detected in humans are indicated by the orange filling of the respective areas; white areas represent FCCs without any evidence of the presence in humans and the FCCs that have been monitored but not detected. The figure in the lower panel is the result of the overall comparison of the known FCCs with all sources of step 1.

Of the 265 FCCs monitored in at least one of the five biomonitoring programs, 194 FCCs (or their metabolites) have been detected in human samples, and 71 FCCs (or their metabolites) have been monitored but not detected in any of the biomonitoring programs (Fig.  3 , middle panel; Table  S1 ). The most extensive national program, NHANES, has monitored over 400 different chemicals in human samples since 1999, and 154 of these are FCCs (Figure S2). We also found 84, 66, 66, and 25 FCCs with evidence for the presence in humans in the biomonitoring programs CHMS, HBM4EU, Biomonitoring California, and KoNEHS, respectively. One hundred and twenty-four FCCs have only been monitored in a single biomonitoring program, and 55 of these have not been detected, whereas 13 FCCs have been included across all five programs, of which 8 have been detected in all programs (Figure S3; Table  S1 ).

The overlap of known FCCs with metabolome/exposome databases is much larger than the overlap with biomonitoring programs: of the three metabolome/exposome databases, the Blood Exposome Database includes the highest number of FCCs (2918 FCCs), followed by the HMDB (2211 FCCs) and the Exposome Explorer (253 FCCs) (Fig.  3 , middle panel; Figure S4). The HMDB lists 367, 1072, and 772 FCCs that are labelled as “detected and quantified”, “detected but not quantified”, and “expected but not quantified”, respectively, according to the classification system of the database (Figure S5) [ 36 ].

Sixty-one out of the 71 FCCs that have been monitored but not detected in biomonitoring programs are listed in at least one of the metabolome/exposome databases. This means that only 10 FCCs fall under the category “monitored but not detected” in step 1 (Fig.  2 ).

Systematic evidence mapping of prioritized FCCs

In step 1 we show that 75% of the known FCCs are not listed in any of the biomonitoring programs or metabolome/exposome databases. However, for some of these FCCs, scoping searches resulted in additional evidence from the primary literature. Therefore, we decided to systematically map the evidence for 175 FCCs which we prioritized based on the number of FCCmigex database entries that report their detection in FCMs.

In this systematic approach, we found 3152 scientific studies for 147 out of the 175 prioritized FCCs (Figure S6) and considered 251 and 159 studies eligible after title-and abstract and full-text screening, respectively. These studies refer to 68 FCCs – for the other 107 FCCs, no studies fulfilled the eligibility criteria.

Of the 68 FCCs for which scientific studies were found, 63 have been detected in human samples and five have been monitored, but not detected, i.e., Irganox 1330 (CAS 1709-70-2), 2,6-(1,1-dimethylethyl)phenol (CAS 128-39-2), phenyl-bis-(2,4,6-trimethylbenzoyl) phosphinoxid (CAS 162881-26-7), 2,5-bis(5-tert-butyl-2-benzoxazolyl) thiophene (CAS 7128-64-5), and Tinuvin 622 (CAS 65447-77-0) (Fig.  4A ). The detected chemicals have been detected in urine (28 FCCs), serum (20), blood (13), and plasma (12) (Fig.  4B ). FCCs have also been found in breast milk (13) and samples taken from umbilical cords (18) and placentas (6). One hundred and thirteen studies have used targeted analyses, whereas 47 studies have used non-targeted approaches (Fig.  4C ), and only one study has applied both methods [ 51 ]. The vast majority of FCCs have been detected directly, i.e. as parent compounds, in human samples (Fig.  4D ), while antioxidant 1098 (CAS 23128-74-7) and Irganox 1035 (CAS 4148-35-9) have been putatively identified based on an unspecific common metabolite in one study [ 52 ].

A Numbers of FCCs with and without evidence from the primary scientific literature indicating their presence in humans. B Types of human samples in which the 63 FCCs have been detected (multiple sample types possible). C Types of applied analytical methods per study and per detected FCC. D Numbers of FCCs that have been analyzed directly (as parent compound) or as specific or unspecific metabolite.

FCCs monitored in humans

Fccs detected in biomonitoring programs.

Among the 235 FCCs present in FCMs that have been included in human biomonitoring programs, there are 51 volatile organic compounds (VOCs), 29 per- and polyfluoroalkyl substances (PFAS), 25 pesticides, 23 metals, 23 dioxin-like compounds, 20 flame retardants, and 19 phthalates and their alternatives (Fig.  5A , right panel; Table  S1 ). Phthalates and alternative plasticizers, and metals are frequently detected FCCs in FCMs and have also been often found in humans (Fig.  5A , bar charts). Furthermore, PFAS, VOCs, and phenolic compounds, including bisphenols, parabens, and benzophenones, have been frequently monitored and detected in FCMs and in humans. In contrast, for dioxin-like compounds, pesticides, flame retardants, polyaromatic hydrocarbons (PAHs), amines, and perchlorate there is less evidence for their presence in FCMs. Interestingly, 71 of the 95 FCCs belonging to these six groups would not be expected to be present in FCMs, since they are not included in the FCCdb (Table  S1 ). The evidence for presence of FCCs in FCMs varies widely between but also within chemical groups. For example, the VOC styrene (CAS 100-42-5) has been listed 99 times as “detected in FCMs” in the FCCmigex database, while 16 other VOCs found in humans have been listed less than ten times each (Table  S1 ). The presence of styrene, or its metabolites, in humans has been shown by NHANES, CHMS, and KoNEHS, but there is no evidence for 18 of the 51 VOCs from any of the five biomonitoring programs.

A 235 FCCs detected in FCMs and included in biomonitoring programs (step 1A). B 175 FCCs prioritized based on their detection in FCMs and their absence in step 1 (step 2). The yellow bar charts illustrate the evidence for the presence of FCC groups in FCMs, based on the sum of database entries from the FCCmigex that report the detection of FCCs in FCMs. The orange bar charts show the evidence of the presence of FCC groups in humans. In step 1A, this is based on the number of biomonitoring programs that have monitored individual FCCs in humans and the addition of these counts by group. In step 2, the orange bars represent the number of studies that have monitored at least one FCC of the respective group. The pie charts show how many FCCs per group have been monitored and detected at least once and how many FCCs have been monitored but not detected in any sample. For step 2, the pie charts also include the chemicals for which there is no evidence in the scientific literature.

FCCs included in the systematic evidence map

Among the 175 FCCs included in the systematic evidence map, there are 38 oligomers (mainly siloxane, polyamide, and polyethylene terephthalate (PET) derivatives), 15 antioxidants and degradation products, 14 photoinitiators, and 14 plasticizers (Fig.  5B , right panel; Table  S2 ).

For oligomers and antioxidants and their degradation products, 424 and 499 FCCmigex database entries, respectively, imply that FCMs play a role in human exposure to these chemical groups (Fig.  5B ). However, there is limited evidence for the presence of antioxidants and oligomers in humans, as indicated by 6 and 12 studies, respectively, reporting the detection of the chemicals of these groups. For only five out of 38 prioritized oligomers, we found evidence for their detection in humans: a PET cyclic trimer (CAS 7441-32-9), three cyclic siloxanes (D7, CAS 107-50-6; D8, CAS 556-68-3 and D9, CAS 556-71-8), and 1,6-dioxacyclododecane-7,12-dione (CAS 777-95-7) (Table  S2 ). With 209 FCCmigex database entries and 9 studies reporting detection in humans, photoinitiators are regularly found in FCMs, but less frequently monitored in humans. For the five BADGE derivatives BADGE·H 2 O, BADGE·2H 2 O, BADGE·HCl, BADGE·2HCl, and BADGE·H 2 O·HCl, 23 studies confirm the detection of at least one of these FCCs in humans. In addition, they have 65 database entries in the FCCmigex, confirming their regular detection in migrates and/or extracts from coated metal FCMs.

FCCs of concern

Of the 235 FCCs included in biomonitoring studies and with evidence for their presence in FCMs, 100 FCCs have hazard properties of high concern for human health, and 44 FCCs have hazard properties of medium concern, i.e., they are assigned to categories 1 and 2, respectively (Fig.  6A , Table  S1 ). Among the FCCs detected in humans are several category 1 A and 1B carcinogens, of which, e.g., styrene, benzophenone (CAS 119-61-9), formaldehyde (CAS 50-00-0), and cadmium (CAS 7440-43-9) have also been frequently found in FCMs. Dozens of FCCs are classified as toxic to reproduction, for example, nine phthalates, which are all classified as 1B reprotoxicants. Over 30 FCCs are mutagens (e.g., benzene (CAS 71-43-2), lead, cadmium, and cobalt), and many more exhibit specific target organ toxicity after repeated exposure (e.g., 4,4’-methylenedianiline (CAS 101-77-9) and perfluorooctanoic acid (CAS 335-67-1)). Seventy-seven FCCs have other concerns or have not been classified as hazardous based on the available data, and 14 do not have hazard data or are not listed.

A 235 FCCs detected in FCMs and included in biomonitoring programs. B 175 FCCs prioritized based on their detection in FCMs and their absence in step 1. On the left side of both Sankey diagrams, the number of FCCs monitored and detected in humans (red), monitored but not detected in humans (light gray), and without any evidence for the presence in humans (dark gray) are shown. On the right sides, the diagrams visualize the number of chemicals of high (red) and medium concern (yellow), chemicals of other concerns or not classified chemicals (light gray), and chemicals with no hazard data (dark gray). The thickness of connecting lines represents the numbers of chemicals that belong to a hazard category and their evidence for presence in humans. *Many hazard classifications lack information for specific hazard categories. This means that chemicals may be newly categorized or reassigned to other hazard categories when more information becomes available in the future.

Among the 175 FCCs included in the systematic evidence map, 5 and 13 FCCs are classified in categories 1 and 2, respectively, resulting in high and medium concern for CMR and/or STOT RE properties (Fig.  6B , Table  S2 ). Di-n-octylisophthalate (CAS 137-89-3), 2-benzyl-2-(dimethylamino)-4-morpholino-butyrophenone (CAS 119313-12-1), ethyl-4-dimethylaminobenzoate (CAS 10287-53-3), and medium-chain chlorinated paraffins (CAS 85535-85-9) are reproductive toxicants of high concern (category 1B) and have been detected in FCMs and in humans. For the category 1B carcinogen 2,4’-methylenedianiline (CAS 1208-52-2), however, we found no evidence concerning its presence in humans. Ninety-eight FCCs are allocated to other hazard categories or have not been classified, and 59 FCCs are not listed in the hazard inventories, indicating a lack of data for these chemicals. Based on this evidence map, 49 FCCs without hazard data have also never been targeted in human samples, but they are known to migrate so the implications of the probable human exposure from these FCCs are unknown. Among these are 29 oligomers that have been mainly detected in PA, PET, and siloxane FCMs.

Relevance of this study

There is evidence of human exposure for at least 3601 (or 25%) of the known FCCs (Fig.  1 ). While other exposure sources (than FCMs) exist for FCCs, it is likely that humans are exposed to more FCCs than reported here, as we only searched the scientific literature for a small subset of chemicals. The novel database on FCCs monitored in humans (FCChumon) lends itself to integration with our previously published database of chemicals present in/migrating from specific FCMs (FCCmigex) [ 5 ], thereby enabling hypothesis-driven research for closing pertinent knowledge gaps on human exposure to chemicals originating from FCMs. Together, these databases can also be used as information sources for elucidating FCCs’ health impacts and highlighting other priority research needs.

Parent compounds vs. metabolites

For the exposure assessment of chemicals with well-known metabolic fate in humans, such as phthalates and certain VOCs, metabolites instead of their parent compounds are monitored [ 53 , 54 ]. We considered this aspect when comparing FCCs to chemicals from the biomonitoring programs and when analyzing the primary literature. Various tools could support identifying FCC metabolites by predicting chemical biotransformation [ 55 , 56 ], but they are associated with large scientific uncertainty, as shown, e.g., for the metabolism of agrochemicals in rats [ 57 ] or for 15 structurally different groups of flame retardants [ 58 ]. Given the high number of FCCs included in this study, we did not attempt to systematically predict potential metabolites and only considered information on specific metabolites if it was readily available in the biomonitoring programs. Only one unspecific metabolite was identified in the systematic evidence map, indicating potential exposure to two antioxidants [ 52 ].

Focus on chemical groups

FCMs are a well-known and relevant exposure source for phthalates and their alternatives, metals, VOCs, and phenolic compounds. These chemicals are regularly monitored and detected in human biomonitoring programs and frequently found in FCMs (Fig.  5A ), and there is ample evidence for their migration, e.g. [ 17 , 59 , 60 , 61 ]. There is also evidence for the presence of PFAS in humans and in FCMs. Although most PFAS have never been authorized for food contact use [ 62 ], the contribution of food packaging to human exposure has been mapped [ 63 ]. Dioxin-like compounds, many pesticides, and flame retardants are not intentionally added FCCs, but they may be present in FCMs because they are introduced or formed during FCM use, manufacture, and recycling, as their detection in FCMs shows [ 64 , 65 , 66 ]. FCMs may therefore contribute to human exposure to FCCs intentionally used in the manufacture of FCMs, various types of NIAS, and illicitly added chemicals. Yet, for most FCCs, comprehensive assessments of the relative contribution of FCMs to human body burden are missing.

Antioxidants are of special interest because many are high-production volume chemicals that are widely used in plastic food packaging [ 67 ] and robust evidence for their presence in FCMs exists (Fig.  5B , Table  S2 ). Important groups of antioxidants are sterically hindered phenols and phosphite antioxidants that are very common in FCMs, e.g., Irgafos 168 (CAS 31570-04-4), Irganox 1076 (CAS 2082-79-3), and Irganox 1010 (CAS 6683-19-8). However, neither of these substances is included in the biomonitoring programs and exposome/metabolome databases (step 1), and we found only limited evidence for their presence in humans in step 2 [ 52 , 68 , 69 ]. Major degradation products of these antioxidants, such as 2,4-di-tert-butylphenol (CAS 96-76-4), 2,6-di-tert-butylbenzoquinone (CAS 719-22-2), and tris(2,4-di-tert-butylphenyl)phosphate (CAS 95906-11-9), have been detected in humans in a few studies, but at high levels and with frequent detection in sampled populations [ 70 , 71 , 72 ]. These results show that the contribution of FCMs to human exposure to antioxidants and their degradation products has not yet received much attention. Such gaps need to be filled by better understanding the overall exposure to antioxidants and their metabolism in humans.

Oligomers are another group of FCCs requiring more attention. PET, PA, and siloxane oligomers are known side-products of polymerization, and they have been detected in extracts and migrates of FCMs. There is however only very limited evidence for their presence in humans, e.g. for PET oligomers [ 73 ]. This is likely due to the challenging chemical analysis of oligomers, especially in complex media, such as human samples, and the fact that chemical standards required for the identification and quantification of oligomers are rarely available [ 74 , 75 ]. BADGE and its derivatives are commonly observed side-products formed during the polymerization of epoxy resins [ 76 ]. Toxic effects, such as endocrine disruption, genotoxicity, and allergic reactions, have been linked to BADGE derivatives and epoxy resins, but information on their toxicity is still limited [ 77 ]. Seventeen BADGE derivatives have been detected in extracts or migrates of FCMs, and five of them have been found in humans. This illustrates that targeted analysis of structurally related chemicals is possible and should be prioritized, to close this important knowledge gap on human exposure to expected side-products of polymerization reactions [ 76 ].

Photoinitiators form a group of structurally diverse FCCs that are used in various FCMs, such as coatings, printing inks, and adhesives [ 78 ]. While there is substantial evidence for their presence in FCMs, their presence in human samples has not been extensively investigated. Liu and Mabury showed that 18 photoinitiators and their sulfoxidation products are present in human sera [ 79 ], and human exposure, environmental occurrence, and toxicity of 25 photoinitiators have recently been reviewed [ 78 ]. According to the FCCmigex and FCChumon databases, several of these photoinitiators have been detected in FCMs and there is evidence for human exposure. Among these, benzophenone (CAS 119-61-9) is the most frequently detected photoinitiator in FCMs. Since benzophenone is a presumed carcinogen (class 1B, Table  S1 ) as well as a suspected endocrine disruptor [ 80 ], exposure via FCMs should be prevented.

Limitations affecting data interpretation

The sources used for the compilation of the FCChumon data vary with respect to the chemical space, curation level, and details provided. In general, we consider data collected in biomonitoring programs (Step 1A) as having a high level of confidence because they are usually derived from a representative population by following strict analytical standards and guidelines [ 81 ]. However, only a limited number of several hundred chemicals is monitored in these programs. We also rate the results of step 2 with a high level of confidence because they were generated by the robust approach of a systematic evidence map (including data extraction by a trained team of scientists but excluding the quality rating of each included study [ 29 ]). Conversely, the metabolome/exposome databases contain many thousands of different chemicals that have been assembled by different means, also including automated approaches [ 36 , 38 ]. The matches between the known FCCs and these databases may therefore require further review before being used in future assessments (e.g., by checking the “metabolite status” integrated in the HMDB).

Some of the FCCs listed in the FCCdb and FCCmigex consist of chemical mixtures of, e.g., polymeric molecules, stereoisomers, or structural isomers. Converting the CAS Registry Number of such mixtures into other identifiers was not always possible and could therefore result in some FCCs not being found in some sources of step 1. For example, short-chain chlorinated paraffins (SCCPs, CAS 85535-84-8) and medium-chain chlorinated paraffins (MCCPs, CAS 85535-85-9) do not have any identifiers other than CAS and were not matched in step 1, but we found ample evidence for the presence of these mixtures in humans in step 2, because they have been monitored regularly and the chemical names are reported in a standardized manner in the primary literature e.g. [ 82 , 83 , 84 ]. Nonylphenol (CAS 25154-52-3) is another example of a mixture of undefined stereoisomers and structural isomers that was not found in step 1 but prioritized in step 2. However, due to the listing of more defined nonylphenol isomers in the FCC databases as well as the metabolome/exposome databases, we decided to exclude this technical mixture from the systematic evidence map. These examples show that searches for (alternative) names and/or identifiers were helpful during the systematic evidence map and may be recommended for users of the FCChumon database.

Implications for assessing and managing FCCs

The data presented here lend support to the possible contribution of FCMs towards human exposure to FCCs. Since there are various FCCs with hazard properties of concern among the chemicals detected in humans and FCMs, their use in FCMs should be restricted to minimize human exposure. This is now recognized and currently under discussion for a few of these chemicals, including PFAS [ 85 , 86 ], BPA [ 10 , 16 ] and phthalates [ 87 ]. However, it does not mean that the remaining FCCs can be considered safe, as shown, e.g., by the absence of biomonitoring and hazard data for 107 (61%) and 59 (34%), respectively, of the 175 FCCs included in step 2. Importantly, even for chemicals where hazard data have been submitted to authorities there are significant data gaps for one or more hazard categories, as has been demonstrated for certain PFAS [ 62 , 88 ]. For FCCs migrating into foods, such related hazard data gaps need to be filled with high priority to characterize risk on human health [ 89 ]. This is especially urgent for intentionally added FCCs found at high levels in humans, such as antioxidants and photoinitiators, and expected NIAS, such as oligomers and BADGE derivatives.

In summary, this study systematically maps 3601 chemicals from different FCAs (food packaging, tableware, etc.) for which there is evidence for human exposure, and for 10,786 FCCs, no evidence could be provided at all. Only 15 FCCs have been monitored but have never been detected in humans. Based on two subsets totalling 410 FCCs, this study further identifies 105 FCCs of high concern due to their hazard properties and highlights the many data gaps related to hazards and human health risks. We make these data accessible in the user-friendly, freely accessible FCChumon dashboard, which complements our previously published FCCmigex dashboard on extractable and migrating FCCs. In combination, FCChumon and FCCmigex enable the prioritization of FCCs requiring more detailed investigations, either because they are frequently found in FCMs, despite having only little or no information on their presence in humans, or because they are measured in humans but lack hazard information. Furthermore, this evidence base supports policy and decision-making and highlights the urgent need to ban the most hazardous chemicals shown to migrate from food packaging and other types of FCAs into foods, to protect human health.

Data availability

The data are publicly and freely available as interactive dashboard that is based on Microsoft PowerBI under the following link ( https://www.foodpackagingforum.org/fcchumon ). The references that were included in the systematic evidence map (step 2) are also provided under this link.

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Acknowledgements

We thank all members of the FCCH project’s scientific advisory group for their contributions, especially John Peterson Myers, Katie Pelch, Rob Sargis, Emma Schymanski, and Martin Wagner. We thank Jozica Dolenc for help with the development of the literature search strategy and Frank Gwodsz and Christian Kohl for technical support during the compilation of the systematic evidence map.

This work was carried out as part of the FCCH project, which is funded by project-related funds from Adessium Foundation, MAVA Foundation, Stiftung Minerva, Sympany Stiftung, and the Food Packaging Forum’s own resources from unrestricted donations. All FPF funding sources are listed here: https://www.foodpackagingforum.org/about-us/funding .

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Birgit Geueke, Lindsey V. Parkinson, Lisa Zimmermann & Jane Muncke

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BG: Conceptualization, Literature screening, Data extraction, Visualization, Writing (original draft), Project administration; LVP: Data processing, Dashboard development, Writing (review & editing); LZ: Literature screening, Data extraction, Writing (review & editing); KJG: Conceptualization, Writing (review & editing); CK: Conceptualization, Writing (review & editing); MVM: Conceptualization, Writing (review & editing); OVM: Conceptualization, Writing (review & editing); MS: Data interpretation, Writing (review & editing); JM : Conceptualization, Data interpretation, Writing (review & editing), Funding acquisition. All authors reviewed the results and approved the final version of the manuscript.

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Geueke, B., Parkinson, L.V., Groh, K.J. et al. Evidence for widespread human exposure to food contact chemicals. J Expo Sci Environ Epidemiol (2024). https://doi.org/10.1038/s41370-024-00718-2

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National Research Council (US) Committee on Responsibilities of Authorship in the Biological Sciences. Sharing Publication-Related Data and Materials: Responsibilities of Authorship in the Life Sciences. Washington (DC): National Academies Press (US); 2003.

Sharing Publication-Related Data and Materials: Responsibilities of Authorship in the Life Sciences.

• Hardcopy Version at National Academies Press

2 The Purpose of Publication and Responsibilities for Sharing

• THE TRADITION OF SCIENTIFIC PUBLICATION

The roots of scholarly scientific publishing can be traced to 1665, when Henry Oldenburg of the British Royal Society established the Philosophical Transactions of the Royal Society . Oldenburg was motivated, in part, by a desire to remove himself as diplomatic interlocutor between the dispersed, independent scientists of the time with whom he communicated individually. The aim of the new publication was to create a public record of original contributions to knowledge and to encourage scientists to “speak” directly to one another. By providing intellectual credit publicly for innovative claims in natural philosophy, the journal encouraged scientists to disclose knowledge that they might otherwise have kept secret.

The Philosophical Transactions of the Royal Society created a sense of competition among scientists to be the first to publish a new scientific finding, an incentive that is continued in modern scientific journals. If the journal is a prominent one, publication endows the author with an extra measure of prestige. In addition, as Cell editor Vivian Siegel and other workshop participants noted, publications also yield indirect rewards. For example, they affect a researcher's job prospects and ability to be promoted or gain tenure. Publishing a scientific paper can result in fruitful new scientific collaborations, including financially profitable arrangements for authors in academe, as a result of commercial overtures for collaboration or consultancy.

Publishing also holds some risks for an author. Competitors might use results presented in a paper to advance their own research and “scoop” the original author in future publications. The careers of young scientists might be particularly vulnerable to having prospective research “picked off” by others. (However, if a researcher chooses not to publish his or her results or chooses to delay publication, someone else might publish the same findings first and receive the credit.) Another risk associated with publishing is that other researchers will use information presented in a paper to invalidate or question the author's own findings, and publish conflicting results.

Are the benefits and risks of publishing any different for companies whose investigators publish than those for academic scientists? It was pointed out at the workshop that companies whose scientists publish their findings typically receive the intellectual credit, recognition, and prestige that come with such disclosure to the entire scientific community. Such nonfinancial benefits can translate into increased publicity and increased perceived value of a company to potential investors and business partners. They also strengthen the scientific reputation of companies in the eyes of potential collaborators. By encouraging others to use their methods and materials, companies can develop a net of researchers who are extolling and extending the value of the technology that the company has published. Moreover, companies that encourage their investigators to publish are attractive to employees or potential employees who wish to build and maintain their publication record, either in anticipation of someday returning to academe, as a vehicle for facilitating their participation in and recognition by their peer scientific community, or in buttressing their own career prospects within the company.

For a for-profit research entity, publication also carries financial risks. By revealing proprietary data or other trade secrets, publishing may harm a company's competitiveness in the marketplace and thus endanger the return to investors. A competitor might use information disclosed in a scientific paper to develop a competing product or otherwise gain commercial advantage or to discredit the product claims of the company making the disclosure.

While companies whose scientists publish may worry about their competitive edge in the commercial market, researchers in academe worry about gaining a competitive edge in the rewards process and about getting their research grants renewed. Where academics are rewarded by priority, “fame,” and career advancement, companies whose investigators publish receive benefits in terms of visibility, public relations, and validation. Although there are different tradeoffs involved in publishing, in practice, researchers from these two worlds often have similar goals and are motivated by common incentives. Their common interests converge in the forum of scientific publication.

• PUBLISHING AND COMMUNITY STANDARDS

By facilitating communication between individuals who had worked in isolation from one another, the Philosophical Transactions of the Royal Society also contributed to the development of a scientific community. As a result, modern journals do more than simply register the intellectual accomplishments of individual scientists; they record a collective body of knowledge. Journals are a centerpiece of the scientific enterprise and serve as a focal point for the description of scientific results. Journal articles supply information that helps scientists to develop new hypotheses, and they provide a foundation on which new scientific discoveries and inventions are built. As Eric Lander noted at the workshop, “science is fundamentally a cumulative enterprise. Each new discovery plays the role of one more brick in an edifice.” Authors cite previously published papers to make a case for their conclusions that is based on a combination of previously documented scientific evidence and the new information they have gathered. Scientific journals, many established by learned societies, provide a forum for a continuing dialogue of sorts, as authors discuss findings that add new pieces to others' previously published results or announce alternative conclusions to those made by other authors or contradict them. Science moves forward in this way.

Because publication is central to the activity of the scientific community, and consequently, to scientific progress, principles and standards that govern an author's responsibilities related to publication have always been paramount. As the 1992 National Research Council report Responsible Science observed, “For centuries scientists have relied on each other, on the self correcting mechanisms intrinsic to the nature of science, and on the traditions of their community to safeguard the integrity of the research process. This approach has been successful largely because of the widespread acknowledgement that science cannot work otherwise, and also because high standards and reputation are important to scientists” ( NRC, 1992 ).

Because standards related to publication are so important to the functioning of the community, calls for the publication system to adapt to the different risks of publication to scientists working in different circumstances are not easily implemented. Chapter 5 addresses specific arguments related to exceptions, but in general, applying a standard to some authors and not others weakens the incentive of distinction that has attracted scientists since Oldenburg's day to publish publicly in a journal. When exceptions to the community standard are sought and granted, there is a danger that the value of publishing is diminished, not only for the author who requests an exception, but for the entire community. Moreover, if the same standard does not apply to all authors, then the community cannot assume that the quality of scientific papers and the information they purport to represent is reliable. That jeopardizes the integrity of the publication system.

That is not to say that publication-related community standards are insensitive to other important societal interests, such as protecting the identities of research subjects. Measures to protect that information do affect how data are reported and made available to other investigators; nevertheless, the community has striven to find ways to maximize the availability of relevant data without compromising privacy.

A current topic of discussion in the scientific community is the possibility that published information in the life sciences will be exploited by bioterrorists. It is too early to say where those discussions will lead, but current community standards abide by regulations on access to some research materials (for example, radioisotopes, explosives, controlled substances, and pathogens) for good reason. If additional safeguards are found to be necessary in providing access to research data and materials, the community must make accommodations for them.

Similarly, the community complies with prohibitions imposed by some nations on the distribution of biological materials and organisms collected in those countries. Biological materials that are paleontological, archeological, or anthropological in nature, and sometimes samples of organisms, may by national law be required to be deposited in the country of origin, and even when material is allowed to be exported, there are often legal restrictions on its subsequent distribution and use. For example, the commercial use of such samples may be prohibited or restricted. Nonetheless, all such material is made fully available for study at the repository, and not normally under the control of the authors who published results derived from studying it. The details of the results of the original study, and images, DNA sequences, and other information derived from the specimens, are also made available.

The principles and standards of scientific publication are also consistent with society's interest in the applications of scientific knowledge and their economic and other benefits. An author who publishes a paper is expected to share materials related to that publication to other scientists for research purposes, but that does not prevent an author from seeking intellectual property rights protection in order to realize the commercial value of those materials. To encourage the disclosure of scientific information, the patent system bestows inventors of a novel, nonobvious, and useful innovation with the right, for a limited time, to prevent others from making or using that innovation, unless licensed to do so. Scientific publication provides no such incentive, but to the contrary, encourages other scientists to use and integrate into new research those things described in a scientific publication. An author who publishes a scientific paper describing a patented process, for example, may have a legal right to prevent others from using it, but the scientific community holds the expectation that an author will make available a license to use that process for research. From a social perspective, the two systems are complementary: patenting fosters the commercialization of ideas; scientific publication communicates the ideas that build the edifice of science. Scientific publications also influence the issuance of patent rights by defining the landscape of the “prior art” and “obviousness” criteria used in assessing the novelty of putative patent claims.

• JOURNAL POLICIES AND COMMUNITY STANDARDS

Journals have their own policies that describe an author's responsibilities related to publication and sharing publication-related data and materials. Publishers of journals include for-profit companies and not-for-profit enterprises, such as university presses, scientific societies, and associations, and each publisher is motivated by the intellectual objectives and fiduciary responsibilities of its own constituencies. Journal editors often compete for papers that increase the impact and standing of their journals in the scientific community and their mass media coverage. On occasion, journal editors have been willing to make exceptions to their usual policies on data sharing in return for the opportunity to publish a paper they believe will be of high impact in the scientific community and, increasingly, in the general public.

The extent to which journals state their policies for the sharing of materials and data is highly variable ( Table 2-1 ). That variability and the diverse nature of journals might suggest that common principles and standards do not exist. But even the stated policies of journals do not capture what are generally recognized as accepted practices and expectations of the community. For example, most journals today explicitly require that authors provide enough detail about their materials and methods to allow a qualified reader to replicate all experimental procedures. A logical, often implicit, extension of that requirement is that authors must make available the data and materials needed for others to verify or refute the findings reported in a paper. Thus, for example, in a paper citing genetic results from one or a series of organisms, voucher specimens should be cited and deposited in an appropriate public repository where the identity of the organisms can be checked by subsequent workers (with the obvious exception of well-known and easily-available strains). Insofar that scientific publication is central to the forward progress of the scientific community, it is presumed that an author must provide data and materials in a way that others can build on them. These widely held expectations are not necessarily incorporated in current journal policies.

Policies of 56 Most Frequently Cited Life-Science and Medical Journals.

• THE PRINCIPLES OF PUBLICATION

At the workshop and in its deliberations, the committee attempted to distill the community's most basic interests in the process of publication. It found that a majority of the scientific community held common ideas and values about publication and the role it plays in science, and that those ideas have guided the development of community standards that facilitate the use of scientific information and ensure its quality. Central to those ideas is a concept the committee called “the uniform principle for sharing integral data and materials expeditiously (UPSIDE),” as follows:

Community standards for sharing publication-related data and materials should flow from the general principle that the fundamental purpose of publication of scientific information is to move science forward. More specifically, the act of publishing is a quid pro quo in which authors receive credit and acknowledgment in exchange for disclosure of their scientific findings. An author's obligation is not only to release data and materials to enable others to verify or replicate published findings (as journals already implicitly or explicitly require) but also to provide them in a form on which other scientists can build with further research. All members of the scientific community—whether working in academia, government, or commercial enterprise—share responsibility for upholding community standards as equal participants in the publication system, and all should be equally able to derive benefits from it.

Along with UPSIDE, five additional principles guide the development and implementation of community standards. Chapters 3 and 4 discuss those principles and the nuances of how they are embodied in examples of community standards for sharing data, software, and materials. New community standards are likely to evolve as science itself changes, but the principles remain a fundamental underpinning of the their development. The principles motivate the creation of standards that maximize the value of scientific findings to the community, because this has proved to be the way that science progresses most rapidly. In addition to the principles of publication, Chapters 3 and 4 include the Committee's recommendations for increasing the effectiveness of community standards for sharing data and materials.

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Factors Influencing Adherence to Halal Food Consumption Among Muallafs: Reviewing the Theory of Planned Behaviour

• Nasyitah Ahmad ,
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Published 30-06-2024

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Muallafs, individuals who convert to Islam, often face challenges in adapting to new religious practices, including adherence to Islamic dietary laws. Halal food consumption, which involves permissible food and specific slaughtering practices, is a fundamental aspect of these laws. Despite the increasing number of converts, research on Muallafs' adherence to halal food consumption remains limited. This paper aims to address this gap by expanding the theory of planned behaviour (TPB) to understand the factors influencing Muallafs’ dietary practices. Through library research, this review paper will discuss factors such as attitude, subjective norm, perceived behavioural control, pre-conversion eating habit as well as the role of religiosity as an extension of the theory of planned behaviour (TPB). Given that improper guidance can lead to confusion and potential apostasy among Muallafs, understanding these factors is crucial for providing the necessary support and nurturing in their transition to Islam. By shedding light on the lifestyle changes and challenges faced by recent Muslim converts, this paper seeks to offer a comprehensive framework for future research and practical interventions to support Muallafs in maintaining halal dietary practices, thereby reducing the likelihood of confusion and apostasy.

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Endangered sea corals moved from South Florida to the Texas Gulf Coast for research and restoration

Scientists have moved about about 300 endangered sea corals from South Florida to the Texas Gulf Coast for research and restoration. (AP Video/David Fischer)

Researchers with Texas A&M University-Corpus Christi and Nova Southeastern University prepare live corals for transport at the NSU’s Oceanographic Campus in Dania Beach, Fla., Sept. 18, 2024. (AP Photo/David Fischer)

Texas A&M University-Corpus Christi researcher Keisha Bahr and Nova Southeastern University researcher Shane Wever prepare live corals for transport at the NSU’s Oceanographic Campus in Dania Beach, Fla., Sept. 18, 2024. (AP Photo/David Fischer)

Texas A&M University-Corpus Christi researcher Keisha Bahr prepares live corals for transport at the Nova Southeastern University’s Oceanographic Campus in Dania Beach, Fla., Sept. 18, 2024. (AP Photo/David Fischer)

Nova Southeastern University researcher Shane Wever prepares live corals for transport at the school’s Oceanographic Campus in Dania Beach, Fla., Sept. 18, 2024. (AP Photo/David Fischer)

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DANIA BEACH, Fla. (AP) — Scientists have moved about 300 endangered sea corals from South Florida to the Texas Gulf Coast for research and restoration.

Nova Southeastern University and Texas A&M University-Corpus Christi researchers packed up the corals Wednesday at the NSU’s Oceanographic Campus in Dania Beach. The sea creatures were then loaded onto a van, taken to a nearby airport and flown to Texas.

Researchers were taking extreme caution with the transfer of these delicate corals, NSU researcher Shane Wever said.

“The process that we’re undertaking today is a really great opportunity for us to expand the representation of the corals that we are working with and the locations where they’re stored,” Wever said. “Increasing the locations that they’re stored really acts as safeguards for us to protect them and to preserve them for the future.”

Each coral was packaged with fresh clean sea water and extra oxygen, inside of a protective case and inside of insulated and padded coolers, and was in transport for the shortest time possible.

NSU’s marine science research facility serves as a coral reef nursery, where rescued corals are stored, processed for restoration and transplanted back into the ocean. The school has shared corals with other universities, like the University of Miami, Florida Atlantic University and Texas State University, as well as the Coral Restoration Foundation in the Florida Keys.

Despite how important corals are, it is easy for people living on land to forget how important things in the ocean are, Texas A&M University-Corpus Christi researcher Keisha Bahr said.

“Corals serve a lot of different purposes,” Bahr said. “First of all, they protect our coastlines, especially here in Florida, from wave energy and coastal erosion. They also supply us with a lot of the food that we get from our oceans. And they are nurseries for a lot of the organisms that come from the sea.”

Abnormally high ocean temperatures caused widespread coral bleaching in 2023, wiping out corals in the Florida Keys. Texas A&M University-Corpus Christi turned to NSU when its partners in the Keys were no longer able to provide corals for its research. Broward County was spared from the majority of the 2023 bleaching so the NSU offshore coral nursery had healthy corals to donate.

“We’re losing corals at an alarming rate,” Bahr said. “We lost about half of our corals in last three decades. So we need to make sure that we continue to have these girls into the future.”

Texas A&M University-Corpus Christi is using some of these corals to study the effects of sediment from Port Everglades on coral health. The rest will either help the university with its work creating a bleaching guide for the Caribbean or act as a genetic bank, representing nearly 100 genetically distinct Staghorn coral colonies from across South Florida’s reefs.

“We wanted to give them as many genotypes, which are genetic individuals, as we could to really act as a safeguard for these this super important species,” Wever said.