what is scientific writing in research

Write Like a Scientist

A Guide to Scientific Communication

What is scientific writing ?

Scientific writing is a technical form of writing that is designed to communicate scientific information to other scientists. Depending on the specific scientific genre—a journal article, a scientific poster, or a research proposal, for example—some aspects of the writing may change, such as its  purpose , audience , or organization . Many aspects of scientific writing, however, vary little across these writing genres. Important hallmarks of all scientific writing are summarized below. Genre-specific information is located  here  and under the “By Genre” tab at the top of the page.

What are some important hallmarks of professional scientific writing?

1. Its primary audience is other scientists. Because of its intended audience, student-oriented or general-audience details, definitions, and explanations — which are often necessary in lab manuals or reports — are not terribly useful. Explaining general-knowledge concepts or how routine procedures were performed actually tends to obstruct clarity, make the writing wordy, and detract from its professional tone.

2. It is concise and precise . A goal of scientific writing is to communicate scientific information clearly and concisely. Flowery, ambiguous, wordy, and redundant language run counter to the purpose of the writing.

3. It must be set within the context of other published work. Because science builds on and corrects itself over time, scientific writing must be situated in and  reference the findings of previous work . This context serves variously as motivation for new work being proposed or the paper being written, as points of departure or congruence for new findings and interpretations, and as evidence of the authors’ knowledge and expertise in the field.

All of the information under “The Essentials” tab is intended to help you to build your knowledge and skills as a scientific writer regardless of the scientific discipline you are studying or the specific assignment you might be working on. In addition to discussions of audience and purpose , professional conventions like conciseness and specificity, and how to find and use literature references appropriately, we also provide guidelines for how to organize your writing and how to avoid some common mechanical errors .

If you’re new to this site or to professional scientific writing, we recommend navigating the sub-sections under “The Essentials” tab in the order they’re provided. Once you’ve covered these essentials, you might find information on  genre-  or discipline-specific writing useful.

What is Scientific Writing? Unveiling the Mystery

Scientific writing is a discipline that combines precision, clarity, and reliability, all of which are pivotal to the communication of scientific research. It is a structured form of writing that helps in explaining complex scientific ideas and data to an audience that may range from students to experts in the field. In this comprehensive exploration, we’ll answer key questions about scientific writing , concluding with its seven crucial benefits.

What is Scientific Writing?

Scientific writing is a specialized form of communication within the academic and research community, characterized by its precision, objectivity, and adherence to a structured format. It encompasses the creation of research papers, articles, and reports that convey scientific findings and insights. Scientific writers employ a formal tone, precise language, and a standardized structure to ensure clarity and reproducibility of information. The primary aim of scientific writing is to communicate research methodologies, results, and interpretations to a broader audience, fostering the exchange of knowledge and contributing to the advancement of scientific understanding in diverse fields.

Examples of Scientific Writing

Scientific writing is present in a vast number of scientific communications, including…

• Research Articles : These articles are the ‘bread and butter’ of scientific literature, presenting original research findings in specialized journals.
• Review Articles : Summarizing and synthesizing existing research on a topic, these articles help to provide a clear overview of the current state of knowledge on the given topic.
• Case Studies : Especially prevalent in the medical field, case studies focus on the specifics of individual scientific cases for educational purposes, or to highlight novel occurrences.
• Laboratory Reports : Fundamental to education in the sciences, lab reports record the process and outcomes of experimental research.
• Grant Proposals : Grant proposals are written to obtain funding, blending persuasive and scientific writing to make a case for the potential of a research project.
• Conference Papers : Often presenting preliminary research, these papers are shared within the academic community at scholarly conferences.
• Theses and Dissertations : Culminations of academic programs, these comprehensive documents report on extensive research conducted by students.
• Textbooks : Textbooks, education materials at the core, maintain the rigor and structure of scientific writing while remaining accessible in order to ensure accuracy and comprehensibility.

How Do You Write a Scientific Paper?

• Abstract : A brief overview that highlights the key points of the paper
• Introduction : Provides the background, sets up the problem, and states the research objectives or hypotheses
• Methods : Describes the methodology in exhaustive detail to allow reproducibility
• Results : An objective presentation of the data, typically with visual aids like graphs and tables
• Discussion : The author interprets the results, discussing their implications and relevance to existing knowledge
• Conclusion : Summarizes the main findings, their importance, and potential directions for future research
• References : All sources cited in the paper are listed here to credit original authors and allow readers to trace the research lineage

What is the Purpose of Scientific Writing?

The purpose of scientific writing is multifaceted. Scientific writing…

• Shares and archives knowledge
• Invites discussion, replication, and validation from the scientific community
• Educates budding scientists and informs experienced researchers
• Provides a record for future reference
• Helps in obtaining research funding
• Promotes academic progress and recognition

The Golden Rules of Scientific Writing

• Clarity : Use precise language that conveys your meaning unambiguously
• Conciseness : Be succinct without sacrificing completeness
• Consistency : Apply the same style and terminology throughout the document
• Coherence : Ensure the text flows logically from one idea to the next
• Context : Provide background that situates your research within the larger field
• Critical Thinking : Reflect a thorough analysis and synthesis of the research
• Citation : Properly acknowledge the contributions of others

Now, let’s delve into the benefits that underscore the importance of scientific writing.

7 Benefits of Scientific Writing

• Enhances Critical Thinking : Scientific writing requires the author to meticulously think through the research process, question findings, and present an argument based on evidence, thereby enhancing critical thinking skills.
• Fosters Clear Communication : The ability to distill complex ideas into understandable text is a key skill that benefits scientists both within their community and in public outreach.
• Promotes Research Integrity : Through detailed documentation, scientific writing upholds the integrity of the research process and findings.
• Facilitates Knowledge Preservation : Scientific documents serve as a permanent record of scientific knowledge, ensuring that valuable information is preserved over time.
• Enables Evidence-based Decision Making : Well-written scientific documents provide a foundation for decision-making in policy, industry, and healthcare by supplying reliable evidence.
• Cultivates Scientific Discourse : By presenting research for peer review and publication, scientific writing stimulates discussion and debate within the scientific community, which is essential for the advancement of science.
• Advances Professional Development : Engaging in scientific writing contributes to a scientist’s professional growth, often leading to recognition, collaboration opportunities, and career advancement.

In sum, scientific writing is the lynchpin of scientific progress, essential for sharing information, advancing knowledge, and cultivating a well-informed society. Through its systematic approach and disciplined application, scientific writing transcends mere documentation—it becomes a vital instrument for the continued evolution of science and technology. Whether for reporting groundbreaking research, educating future generations, or informing policy, scientific writing remains a critical skill for all scientists.

Technical Writers for Scientific Writing

Having a technical writer to craft your scientific documents brings a multitude of benefits. With their specialized skill set, technical writers can communicate complex topics in a clear, concise, and engaging way, ensuring that the information is both accessible and compelling to the target audience. Their expertise in research, data presentation, and structured writing ensures that the scientific paper is not only informative but also authoritative, proving the credibility of the content. By leveraging a technical writer’s proficiency, businesses can ensure that their scientific papers resonate with the intended readership, driving engagement, influencing decisions, and enhancing reputation in the industry. The expertise of a highly skilled science writer assists organizations in conveying in-depth knowledge, positioning themselves as industry leaders, and enhancing stakeholder trust. Such proficiency is invaluable for businesses aiming to solidify their authority, mitigate potential misunderstandings, and maintain an edge in today’s intricate market dynamics.

How Can Essential Data Help?

With a talent pool full of technical writers with experience across numerous industries, we are uniquely prepared to help you achieve the documentation of your dreams. Our proven expertise with over 30 years of happy customers, supplemented by our client-centric customized solutions, helps you create clear, authoritative, and comprehensive scientific and technical documentation with ease. If you’d like to learn more about our scientific document writing services and the benefits they provide, check out some of our related content below:

• Scientific Writing Services
• Medical and Scientific Writing Documentation
• What is Technical Writing?

Whether you need a single technical writer for a brief project or a team of consultants to produce a complete line of documentation , the quality of our work is guaranteed for you. Our clients work closely with an Engagement Manager from one of our 30 local offices for the entire length of your project at no additional cost. Contact us at (800) 221-0093 or [email protected] to get started.

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What this handout is about

Nearly every element of style that is accepted and encouraged in general academic writing is also considered good practice in scientific writing. The major difference between science writing and writing in other academic fields is the relative importance placed on certain stylistic elements. This handout details the most critical aspects of scientific writing and provides some strategies for evaluating and improving your scientific prose. Readers of this handout may also find our handout on scientific reports useful.

What is scientific writing?

There are several different kinds of writing that fall under the umbrella of scientific writing. Scientific writing can include:

• Peer-reviewed journal articles (presenting primary research)
• Grant proposals (you can’t do science without funding)
• Literature review articles (summarizing and synthesizing research that has already been carried out)

As a student in the sciences, you are likely to spend some time writing lab reports, which often follow the format of peer-reviewed articles and literature reviews. Regardless of the genre, though, all scientific writing has the same goal: to present data and/or ideas with a level of detail that allows a reader to evaluate the validity of the results and conclusions based only on the facts presented. The reader should be able to easily follow both the methods used to generate the data (if it’s a primary research paper) and the chain of logic used to draw conclusions from the data. Several key elements allow scientific writers to achieve these goals:

• Precision: ambiguities in writing cause confusion and may prevent a reader from grasping crucial aspects of the methodology and synthesis
• Clarity: concepts and methods in the sciences can often be complex; writing that is difficult to follow greatly amplifies any confusion on the part of the reader
• Objectivity: any claims that you make need to be based on facts, not intuition or emotion

How can I make my writing more precise?

Theories in the sciences are based upon precise mathematical models, specific empirical (primary) data sets, or some combination of the two. Therefore, scientists must use precise, concrete language to evaluate and explain such theories, whether mathematical or conceptual. There are a few strategies for avoiding ambiguous, imprecise writing.

Word and phrasing choice

Often several words may convey similar meaning, but usually only one word is most appropriate in a given context. Here’s an example:

• Word choice 1: “population density is positively correlated with disease transmission rate”
• Word choice 2: “population density is positively related to disease transmission rate”

In some contexts, “correlated” and “related” have similar meanings. But in scientific writing, “correlated” conveys a precise statistical relationship between two variables. In scientific writing, it is typically not enough to simply point out that two variables are related: the reader will expect you to explain the precise nature of the relationship (note: when using “correlation,” you must explain somewhere in the paper how the correlation was estimated). If you mean “correlated,” then use the word “correlated”; avoid substituting a less precise term when a more precise term is available.

This same idea also applies to choice of phrasing. For example, the phrase “writing of an investigative nature” could refer to writing in the sciences, but might also refer to a police report. When presented with a choice, a more specific and less ambiguous phraseology is always preferable. This applies even when you must be repetitive to maintain precision: repetition is preferable to ambiguity. Although repetition of words or phrases often happens out of necessity, it can actually be beneficial by placing special emphasis on key concepts.

Figurative language

Figurative language can make for interesting and engaging casual reading but is by definition imprecise. Writing “experimental subjects were assaulted with a wall of sound” does not convey the precise meaning of “experimental subjects were presented with 20 second pulses of conspecific mating calls.” It’s difficult for a reader to objectively evaluate your research if details are left to the imagination, so exclude similes and metaphors from your scientific writing.

Level of detail

Include as much detail as is necessary, but exclude extraneous information. The reader should be able to easily follow your methodology, results, and logic without being distracted by irrelevant facts and descriptions. Ask yourself the following questions when you evaluate the level of detail in a paper:

• Is the rationale for performing the experiment clear (i.e., have you shown that the question you are addressing is important and interesting)?
• Are the materials and procedures used to generate the results described at a level of detail that would allow the experiment to be repeated?
• Is the rationale behind the choice of experimental methods clear? Will the reader understand why those particular methods are appropriate for answering the question your research is addressing?
• Will the reader be able to follow the chain of logic used to draw conclusions from the data?

Any information that enhances the reader’s understanding of the rationale, methodology, and logic should be included, but information in excess of this (or information that is redundant) will only confuse and distract the reader.

Whenever possible, use quantitative rather than qualitative descriptions. A phrase that uses definite quantities such as “development rate in the 30°C temperature treatment was ten percent faster than development rate in the 20°C temperature treatment” is much more precise than the more qualitative phrase “development rate was fastest in the higher temperature treatment.”

How can I make my writing clearer?

When you’re writing about complex ideas and concepts, it’s easy to get sucked into complex writing. Distilling complicated ideas into simple explanations is challenging, but you’ll need to acquire this valuable skill to be an effective communicator in the sciences. Complexities in language use and sentence structure are perhaps the most common issues specific to writing in the sciences.

Language use

When given a choice between a familiar and a technical or obscure term, the more familiar term is preferable if it doesn’t reduce precision. Here are a just a few examples of complex words and their simple alternatives:

In these examples, the term on the right conveys the same meaning as the word on the left but is more familiar and straightforward, and is often shorter as well.

There are some situations where the use of a technical or obscure term is justified. For example, in a paper comparing two different viral strains, the author might repeatedly use the word “enveloped” rather than the phrase “surrounded by a membrane.” The key word here is “repeatedly”: only choose the less familiar term if you’ll be using it more than once. If you choose to go with the technical term, however, make sure you clearly define it, as early in the paper as possible. You can use this same strategy to determine whether or not to use abbreviations, but again you must be careful to define the abbreviation early on.

Sentence structure

Science writing must be precise, and precision often requires a fine level of detail. Careful description of objects, forces, organisms, methodology, etc., can easily lead to complex sentences that express too many ideas without a break point. Here’s an example:

The osmoregulatory organ, which is located at the base of the third dorsal spine on the outer margin of the terminal papillae and functions by expelling excess sodium ions, activates only under hypertonic conditions.

Several things make this sentence complex. First, the action of the sentence (activates) is far removed from the subject (the osmoregulatory organ) so that the reader has to wait a long time to get the main idea of the sentence. Second, the verbs “functions,” “activates,” and “expelling” are somewhat redundant. Consider this revision:

Located on the outer margin of the terminal papillae at the base of the third dorsal spine, the osmoregulatory organ expels excess sodium ions under hypertonic conditions.

This sentence is slightly shorter, conveys the same information, and is much easier to follow. The subject and the action are now close together, and the redundant verbs have been eliminated. You may have noticed that even the simpler version of this sentence contains two prepositional phrases strung together (“on the outer margin of…” and “at the base of…”). Prepositional phrases themselves are not a problem; in fact, they are usually required to achieve an adequate level of detail in science writing. However, long strings of prepositional phrases can cause sentences to wander. Here’s an example of what not to do from Alley (1996):

“…to confirm the nature of electrical breakdown of nitrogen in uniform fields at relatively high pressures and interelectrode gaps that approach those obtained in engineering practice, prior to the determination of the processes that set the criterion for breakdown in the above-mentioned gases and mixtures in uniform and non-uniform fields of engineering significance.”

The use of eleven (yes, eleven!) prepositional phrases in this sentence is excessive, and renders the sentence nearly unintelligible. Judging when a string of prepositional phrases is too long is somewhat subjective, but as a general rule of thumb, a single prepositional phrase is always preferable, and anything more than two strung together can be problematic.

Nearly every form of scientific communication is space-limited. Grant proposals, journal articles, and abstracts all have word or page limits, so there’s a premium on concise writing. Furthermore, adding unnecessary words or phrases distracts rather than engages the reader. Avoid generic phrases that contribute no novel information. Common phrases such as “the fact that,” “it should be noted that,” and “it is interesting that” are cumbersome and unnecessary. Your reader will decide whether or not your paper is interesting based on the content. In any case, if information is not interesting or noteworthy it should probably be excluded.

How can I make my writing more objective?

The objective tone used in conventional scientific writing reflects the philosophy of the scientific method: if results are not repeatable, then they are not valid. In other words, your results will only be considered valid if any researcher performing the same experimental tests and analyses that you describe would be able to produce the same results. Thus, scientific writers try to adopt a tone that removes the focus from the researcher and puts it only on the research itself. Here are several stylistic conventions that enhance objectivity:

Passive voice

You may have been told at some point in your academic career that the use of the passive voice is almost always bad, except in the sciences. The passive voice is a sentence structure where the subject who performs the action is ambiguous (e.g., “you may have been told,” as seen in the first sentence of this paragraph; see our handout on passive voice and this 2-minute video on passive voice for a more complete discussion).

The rationale behind using the passive voice in scientific writing is that it enhances objectivity, taking the actor (i.e., the researcher) out of the action (i.e., the research). Unfortunately, the passive voice can also lead to awkward and confusing sentence structures and is generally considered less engaging (i.e., more boring) than the active voice. This is why most general style guides recommend only sparing use of the passive voice.

Currently, the active voice is preferred in most scientific fields, even when it necessitates the use of “I” or “we.” It’s perfectly reasonable (and more simple) to say “We performed a two-tailed t-test” rather than to say “a two-tailed t-test was performed,” or “in this paper we present results” rather than “results are presented in this paper.” Nearly every current edition of scientific style guides recommends the active voice, but different instructors (or journal editors) may have different opinions on this topic. If you are unsure, check with the instructor or editor who will review your paper to see whether or not to use the passive voice. If you choose to use the active voice with “I” or “we,” there are a few guidelines to follow:

• Avoid starting sentences with “I” or “we”: this pulls focus away from the scientific topic at hand.
• Avoid using “I” or “we” when you’re making a conjecture, whether it’s substantiated or not. Everything you say should follow from logic, not from personal bias or subjectivity. Never use any emotive words in conjunction with “I” or “we” (e.g., “I believe,” “we feel,” etc.).
• Never use “we” in a way that includes the reader (e.g., “here we see trait evolution in action”); the use of “we” in this context sets a condescending tone.

Acknowledging your limitations

Your conclusions should be directly supported by the data that you present. Avoid making sweeping conclusions that rest on assumptions that have not been substantiated by your or others’ research. For example, if you discover a correlation between fur thickness and basal metabolic rate in rats and mice you would not necessarily conclude that fur thickness and basal metabolic rate are correlated in all mammals. You might draw this conclusion, however, if you cited evidence that correlations between fur thickness and basal metabolic rate are also found in twenty other mammalian species. Assess the generality of the available data before you commit to an overly general conclusion.

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Alley, Michael. 1996. The Craft of Scientific Writing , 3rd ed. New York: Springer.

Council of Science Editors. 2014. Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers , 8th ed. Chicago & London: University of Chicago Press.

Day, Robert A. 1994. How to Write and Publish a Scientific Paper , 4th ed. Phoenix: Oryx Press.

Day, Robert, and Nancy Sakaduski. 2011. Scientific English: A Guide for Scientists and Other Professionals , 3rd ed. Santa Barbara: Greenwood.

Gartland, John J. 1993. Medical Writing and Communicating . Frederick, MD: University Publishing Group.

Williams, Joseph M., and Joseph Bizup. 2016. Style: Ten Lessons in Clarity and Grace , 12th ed. New York: Pearson.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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What is Scientific Writing?

Browse this guide to learn more about the tools needed to write a scientific paper, such as APA style , AMA style , citation management , and resources related to literature reviews and other research content. 

Why Abstracts are Important

Abstracts are an essential part of scientific writing. Watch the following video to learn the three reasons why abstracts are important.

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WRITING A SCIENTIFIC RESEARCH ARTICLE | Format for the paper | Edit your paper! | Useful books | FORMAT FOR THE PAPER Scientific research articles provide a method for scientists to communicate with other scientists about the results of their research. A standard format is used for these articles, in which the author presents the research in an orderly, logical manner. This doesn't necessarily reflect the order in which you did or thought about the work.  This format is: | Title | Authors | Introduction | Materials and Methods | Results (with Tables and Figures ) | Discussion | Acknowledgments | Literature Cited | TITLE Make your title specific enough to describe the contents of the paper, but not so technical that only specialists will understand. The title should be appropriate for the intended audience. The title usually describes the subject matter of the article: Effect of Smoking on Academic Performance" Sometimes a title that summarizes the results is more effective: Students Who Smoke Get Lower Grades" AUTHORS 1. The person who did the work and wrote the paper is generally listed as the first author of a research paper. 2. For published articles, other people who made substantial contributions to the work are also listed as authors. Ask your mentor's permission before including his/her name as co-author. ABSTRACT 1. An abstract, or summary, is published together with a research article, giving the reader a "preview" of what's to come. Such abstracts may also be published separately in bibliographical sources, such as Biologic al Abstracts. They allow other scientists to quickly scan the large scientific literature, and decide which articles they want to read in depth. The abstract should be a little less technical than the article itself; you don't want to dissuade your potent ial audience from reading your paper. 2. Your abstract should be one paragraph, of 100-250 words, which summarizes the purpose, methods, results and conclusions of the paper. 3. It is not easy to include all this information in just a few words. Start by writing a summary that includes whatever you think is important, and then gradually prune it down to size by removing unnecessary words, while still retaini ng the necessary concepts. 3. Don't use abbreviations or citations in the abstract. It should be able to stand alone without any footnotes. INTRODUCTION What question did you ask in your experiment? Why is it interesting? The introduction summarizes the relevant literature so that the reader will understand why you were interested in the question you asked. One to fo ur paragraphs should be enough. End with a sentence explaining the specific question you asked in this experiment. MATERIALS AND METHODS 1. How did you answer this question? There should be enough information here to allow another scientist to repeat your experiment. Look at other papers that have been published in your field to get some idea of what is included in this section. 2. If you had a complicated protocol, it may helpful to include a diagram, table or flowchart to explain the methods you used. 3. Do not put results in this section. You may, however, include preliminary results that were used to design the main experiment that you are reporting on. ("In a preliminary study, I observed the owls for one week, and found that 73 % of their locomotor activity occurred during the night, and so I conducted all subsequent experiments between 11 pm and 6 am.") 4. Mention relevant ethical considerations. If you used human subjects, did they consent to participate. If you used animals, what measures did you take to minimize pain? RESULTS 1. This is where you present the results you've gotten. Use graphs and tables if appropriate, but also summarize your main findings in the text. Do NOT discuss the results or speculate as to why something happened; t hat goes in th e Discussion. 2. You don't necessarily have to include all the data you've gotten during the semester. This isn't a diary. 3. Use appropriate methods of showing data. Don't try to manipulate the data to make it look like you did more than you actually did. "The drug cured 1/3 of the infected mice, another 1/3 were not affected, and the third mouse got away." TABLES AND GRAPHS 1. If you present your data in a table or graph, include a title describing what's in the table ("Enzyme activity at various temperatures", not "My results".) For graphs, you should also label the x and y axes. 2. Don't use a table or graph just to be "fancy". If you can summarize the information in one sentence, then a table or graph is not necessary. DISCUSSION 1. Highlight the most significant results, but don't just repeat what you've written in the Results section. How do these results relate to the original question? Do the data support your hypothesis? Are your results consistent with what other investigators have reported? If your results were unexpected, try to explain why. Is there another way to interpret your results? What further research would be necessary to answer the questions raised by your results? How do y our results fit into the big picture? 2. End with a one-sentence summary of your conclusion, emphasizing why it is relevant. ACKNOWLEDGMENTS This section is optional. You can thank those who either helped with the experiments, or made other important contributions, such as discussing the protocol, commenting on the manuscript, or buying you pizza. REFERENCES (LITERATURE CITED) There are several possible ways to organize this section. Here is one commonly used way: 1. In the text, cite the literature in the appropriate places: Scarlet (1990) thought that the gene was present only in yeast, but it has since been identified in the platypus (Indigo and Mauve, 1994) and wombat (Magenta, et al., 1995). 2. In the References section list citations in alphabetical order. Indigo, A. C., and Mauve, B. E. 1994. Queer place for qwerty: gene isolation from the platypus. Science 275, 1213-1214. Magenta, S. T., Sepia, X., and Turquoise, U. 1995. Wombat genetics. In: Widiculous Wombats, Violet, Q., ed. New York: Columbia University Press. p 123-145. Scarlet, S.L. 1990. Isolation of qwerty gene from S. cerevisae. Journal of Unusual Results 36, 26-31.   EDIT YOUR PAPER!!! "In my writing, I average about ten pages a day. Unfortunately, they're all the same page." Michael Alley, The Craft of Scientific Writing A major part of any writing assignment consists of re-writing. Write accurately Scientific writing must be accurate. Although writing instructors may tell you not to use the same word twice in a sentence, it's okay for scientific writing, which must be accurate. (A student who tried not to repeat the word "hamster" produced this confusing sentence: "When I put the hamster in a cage with the other animals, the little mammals began to play.") Make sure you say what you mean. Instead of: The rats were injected with the drug. (sounds like a syringe was filled with drug and ground-up rats and both were injected together) Write: I injected the drug into the rat.

• Be careful with commonly confused words:

Temperature has an effect on the reaction. Temperature affects the reaction.

I used solutions in various concentrations. (The solutions were 5 mg/ml, 10 mg/ml, and 15 mg/ml) I used solutions in varying concentrations. (The concentrations I used changed; sometimes they were 5 mg/ml, other times they were 15 mg/ml.)

 Less food (can't count numbers of food) Fewer animals (can count numbers of animals)

A large amount of food (can't count them) A large number of animals (can count them)

The erythrocytes, which are in the blood, contain hemoglobin. The erythrocytes that are in the blood contain hemoglobin. (Wrong. This sentence implies that there are erythrocytes elsewhere that don't contain hemoglobin.)

Write clearly

1. Write at a level that's appropriate for your audience.

"Like a pigeon, something to admire as long as it isn't over your head." Anonymous

 2. Use the active voice. It's clearer and more concise than the passive voice.

 Instead of: An increased appetite was manifested by the rats and an increase in body weight was measured. Write: The rats ate more and gained weight.

 3. Use the first person.

 Instead of: It is thought Write: I think

 Instead of: The samples were analyzed Write: I analyzed the samples

 4. Avoid dangling participles.

 "After incubating at 30 degrees C, we examined the petri plates." (You must've been pretty warm in there.)

  Write succinctly

 1. Use verbs instead of abstract nouns

 Instead of: take into consideration Write: consider

 2. Use strong verbs instead of "to be"

 Instead of: The enzyme was found to be the active agent in catalyzing... Write: The enzyme catalyzed...

 3. Use short words.

Instead of: Write: possess have sufficient enough utilize use demonstrate show assistance help terminate end

4. Use concise terms.

 Instead of: Write: prior to before due to the fact that because in a considerable number of cases often the vast majority of most during the time that when in close proximity to near it has long been known that I'm too lazy to look up the reference

5. Use short sentences. A sentence made of more than 40 words should probably be rewritten as two sentences.

 "The conjunction 'and' commonly serves to indicate that the writer's mind still functions even when no signs of the phenomenon are noticeable." Rudolf Virchow, 1928

Check your grammar, spelling and punctuation

1. Use a spellchecker, but be aware that they don't catch all mistakes.

 "When we consider the animal as a hole,..." Student's paper

 2. Your spellchecker may not recognize scientific terms. For the correct spelling, try Biotech's Life Science Dictionary or one of the technical dictionaries on the reference shelf in the Biology or Health Sciences libraries.

 3. Don't, use, unnecessary, commas.

 4. Proofread carefully to see if you any words out.

USEFUL BOOKS

Victoria E. McMillan, Writing Papers in the Biological Sciences , Bedford Books, Boston, 1997 The best. On sale for about $18 at Labyrinth Books, 112th Street. On reserve in Biology Library

Jan A. Pechenik, A Short Guide to Writing About Biology , Boston: Little, Brown, 1987

Harrison W. Ambrose, III & Katharine Peckham Ambrose, A Handbook of Biological Investigation , 4th edition, Hunter Textbooks Inc, Winston-Salem, 1987 Particularly useful if you need to use statistics to analyze your data. Copy on Reference shelf in Biology Library.

Robert S. Day, How to Write and Publish a Scientific Paper , 4th edition, Oryx Press, Phoenix, 1994. Earlier editions also good. A bit more advanced, intended for those writing papers for publication. Fun to read. Several copies available in Columbia libraries.

William Strunk, Jr. and E. B. White, The Elements of Style , 3rd ed. Macmillan, New York, 1987. Several copies available in Columbia libraries.  Strunk's first edition is available on-line.

Science and the scientific method: Definitions and examples

Here's a look at the foundation of doing science — the scientific method.

The scientific method

Hypothesis, theory and law, a brief history of science, additional resources, bibliography.

Science is a systematic and logical approach to discovering how things in the universe work. It is also the body of knowledge accumulated through the discoveries about all the things in the universe. 

The word "science" is derived from the Latin word "scientia," which means knowledge based on demonstrable and reproducible data, according to the Merriam-Webster dictionary . True to this definition, science aims for measurable results through testing and analysis, a process known as the scientific method. Science is based on fact, not opinion or preferences. The process of science is designed to challenge ideas through research. One important aspect of the scientific process is that it focuses only on the natural world, according to the University of California, Berkeley . Anything that is considered supernatural, or beyond physical reality, does not fit into the definition of science.

When conducting research, scientists use the scientific method to collect measurable, empirical evidence in an experiment related to a hypothesis (often in the form of an if/then statement) that is designed to support or contradict a scientific theory .

"As a field biologist, my favorite part of the scientific method is being in the field collecting the data," Jaime Tanner, a professor of biology at Marlboro College, told Live Science. "But what really makes that fun is knowing that you are trying to answer an interesting question. So the first step in identifying questions and generating possible answers (hypotheses) is also very important and is a creative process. Then once you collect the data you analyze it to see if your hypothesis is supported or not."

The steps of the scientific method go something like this, according to Highline College :

• Make an observation or observations.
• Form a hypothesis — a tentative description of what's been observed, and make predictions based on that hypothesis.
• Test the hypothesis and predictions in an experiment that can be reproduced.
• Analyze the data and draw conclusions; accept or reject the hypothesis or modify the hypothesis if necessary.
• Reproduce the experiment until there are no discrepancies between observations and theory. "Replication of methods and results is my favorite step in the scientific method," Moshe Pritsker, a former post-doctoral researcher at Harvard Medical School and CEO of JoVE, told Live Science. "The reproducibility of published experiments is the foundation of science. No reproducibility — no science."

Some key underpinnings to the scientific method:

• The hypothesis must be testable and falsifiable, according to North Carolina State University . Falsifiable means that there must be a possible negative answer to the hypothesis.
• Research must involve deductive reasoning and inductive reasoning . Deductive reasoning is the process of using true premises to reach a logical true conclusion while inductive reasoning uses observations to infer an explanation for those observations.
• An experiment should include a dependent variable (which does not change) and an independent variable (which does change), according to the University of California, Santa Barbara .
• An experiment should include an experimental group and a control group. The control group is what the experimental group is compared against, according to Britannica .

The process of generating and testing a hypothesis forms the backbone of the scientific method. When an idea has been confirmed over many experiments, it can be called a scientific theory. While a theory provides an explanation for a phenomenon, a scientific law provides a description of a phenomenon, according to The University of Waikato . One example would be the law of conservation of energy, which is the first law of thermodynamics that says that energy can neither be created nor destroyed. 

A law describes an observed phenomenon, but it doesn't explain why the phenomenon exists or what causes it. "In science, laws are a starting place," said Peter Coppinger, an associate professor of biology and biomedical engineering at the Rose-Hulman Institute of Technology. "From there, scientists can then ask the questions, 'Why and how?'"

Laws are generally considered to be without exception, though some laws have been modified over time after further testing found discrepancies. For instance, Newton's laws of motion describe everything we've observed in the macroscopic world, but they break down at the subatomic level.

This does not mean theories are not meaningful. For a hypothesis to become a theory, scientists must conduct rigorous testing, typically across multiple disciplines by separate groups of scientists. Saying something is "just a theory" confuses the scientific definition of "theory" with the layperson's definition. To most people a theory is a hunch. In science, a theory is the framework for observations and facts, Tanner told Live Science.

The earliest evidence of science can be found as far back as records exist. Early tablets contain numerals and information about the solar system , which were derived by using careful observation, prediction and testing of those predictions. Science became decidedly more "scientific" over time, however.

1200s: Robert Grosseteste developed the framework for the proper methods of modern scientific experimentation, according to the Stanford Encyclopedia of Philosophy. His works included the principle that an inquiry must be based on measurable evidence that is confirmed through testing.

1400s: Leonardo da Vinci began his notebooks in pursuit of evidence that the human body is microcosmic. The artist, scientist and mathematician also gathered information about optics and hydrodynamics.

1500s: Nicolaus Copernicus advanced the understanding of the solar system with his discovery of heliocentrism. This is a model in which Earth and the other planets revolve around the sun, which is the center of the solar system.

1600s: Johannes Kepler built upon those observations with his laws of planetary motion. Galileo Galilei improved on a new invention, the telescope, and used it to study the sun and planets. The 1600s also saw advancements in the study of physics as Isaac Newton developed his laws of motion.

1700s: Benjamin Franklin discovered that lightning is electrical. He also contributed to the study of oceanography and meteorology. The understanding of chemistry also evolved during this century as Antoine Lavoisier, dubbed the father of modern chemistry , developed the law of conservation of mass.

1800s: Milestones included Alessandro Volta's discoveries regarding electrochemical series, which led to the invention of the battery. John Dalton also introduced atomic theory, which stated that all matter is composed of atoms that combine to form molecules. The basis of modern study of genetics advanced as Gregor Mendel unveiled his laws of inheritance. Later in the century, Wilhelm Conrad Röntgen discovered X-rays , while George Ohm's law provided the basis for understanding how to harness electrical charges.

1900s: The discoveries of Albert Einstein , who is best known for his theory of relativity, dominated the beginning of the 20th century. Einstein's theory of relativity is actually two separate theories. His special theory of relativity, which he outlined in a 1905 paper, " The Electrodynamics of Moving Bodies ," concluded that time must change according to the speed of a moving object relative to the frame of reference of an observer. His second theory of general relativity, which he published as " The Foundation of the General Theory of Relativity ," advanced the idea that matter causes space to curve.

In 1952, Jonas Salk developed the polio vaccine , which reduced the incidence of polio in the United States by nearly 90%, according to Britannica . The following year, James D. Watson and Francis Crick discovered the structure of DNA , which is a double helix formed by base pairs attached to a sugar-phosphate backbone, according to the National Human Genome Research Institute .

2000s: The 21st century saw the first draft of the human genome completed, leading to a greater understanding of DNA. This advanced the study of genetics, its role in human biology and its use as a predictor of diseases and other disorders, according to the National Human Genome Research Institute .

• This video from City University of New York delves into the basics of what defines science.
• Learn about what makes science science in this book excerpt from Washington State University .
• This resource from the University of Michigan — Flint explains how to design your own scientific study.

Merriam-Webster Dictionary, Scientia. 2022. https://www.merriam-webster.com/dictionary/scientia

University of California, Berkeley, "Understanding Science: An Overview." 2022. ​​ https://undsci.berkeley.edu/article/0_0_0/intro_01  

Highline College, "Scientific method." July 12, 2015. https://people.highline.edu/iglozman/classes/astronotes/scimeth.htm  

North Carolina State University, "Science Scripts." https://projects.ncsu.edu/project/bio183de/Black/science/science_scripts.html  

University of California, Santa Barbara. "What is an Independent variable?" October 31,2017. http://scienceline.ucsb.edu/getkey.php?key=6045  

Encyclopedia Britannica, "Control group." May 14, 2020. https://www.britannica.com/science/control-group  

The University of Waikato, "Scientific Hypothesis, Theories and Laws." https://sci.waikato.ac.nz/evolution/Theories.shtml  

Stanford Encyclopedia of Philosophy, Robert Grosseteste. May 3, 2019. https://plato.stanford.edu/entries/grosseteste/  

Encyclopedia Britannica, "Jonas Salk." October 21, 2021. https://www.britannica.com/ biography /Jonas-Salk

National Human Genome Research Institute, "​Phosphate Backbone." https://www.genome.gov/genetics-glossary/Phosphate-Backbone  

National Human Genome Research Institute, "What is the Human Genome Project?" https://www.genome.gov/human-genome-project/What  

‌ Live Science contributor Ashley Hamer updated this article on Jan. 16, 2022.

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How to Present a Research Study’s Limitations

All studies have imperfections, but how to present them without diminishing the value of the work can be tricky..

Nathan Ni holds a PhD from Queens University. He is a science editor for The Scientist’s Creative Services Team who strives to better understand and communicate the relationships between health and disease.

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Scientists work with many different limitations. First and foremost, they navigate informational limitations, work around knowledge gaps when designing studies, formulating hypotheses, and analyzing data. They also handle technical limitations, making the most of what their hands, equipment, and instruments can achieve. Finally, researchers must also manage logistical limitations. Scientists will often experience sample scarcity, financial issues, or simply be unable to access the technology or materials that they want.

All scientific studies have limitations, and no study is perfect. Researchers should not run from this reality, but engage it directly. It is better to directly address the specific limitations of the work in question, and doing so is actually a way to demonstrate an author’s proficiency and aptitude.

Do: Be Transparent

From a practical perspective, being transparent is the main key to directly addressing the specific limitations of a study. Was there an experiment that the researchers wanted to perform but could not, or a sample that existed that the scientists could not obtain? Was there a piece of knowledge that would explain a question raised by the data presented within the current study? If the answer is yes, the authors should mention this and elaborate upon it within the discussion section.

Asking and addressing these questions demonstrates that the authors have knowledge, understanding, and expertise of the subject area beyond what the study directly investigated. It further demonstrates a solid grasp of the existing literature—which means a solid grasp of what others are doing, what techniques they are using, and what limitations impede their own studies. This information helps the authors contextualize where their study fits within what others have discovered, thereby mitigating the perceived effect of a given limitation on the study’s legitimacy. In essence, this strategy turns limitations, often considered weaknesses, into strengths.

For example, in their 2021 Cell Reports study on macrophage polarization mechanisms, dermatologist Alexander Marneros and colleagues wrote the following. 1

A limitation of studying macrophage polarization in vitro is that this approach only partially captures the tissue microenvironment context in which many different factors affect macrophage polarization. However, it is likely that the identified signaling mechanisms that promote polarization in vitro are also critical for polarization mechanisms that occur in vivo. This is supported by our observation that trametinib and panobinostat inhibited M2-type macrophage polarization not only in vitro but also in skin wounds and laser-induced CNV lesions.

This is a very effective structure. In the first sentence ( yellow ), the authors outlined the limitation. In the next sentence ( green ), they offered a rationalization that mitigates the effect of the limitation. Finally, they provided the evidence ( blue ) for this rationalization, using not just information from the literature, but also data that they obtained in their study specifically for this purpose. 

Don't: Be Defensive

It can feel natural to avoid talking about a study’s limitations. Scientists may believe that mentioning the drawbacks still present in their study will jeopardize their chances of publication. As such, researchers will sometimes skirt around the issue. They will present “boilerplate faults”—generalized concerns about sample size/diversity and time limitations that all researchers face—rather than honestly discussing their own study. Alternatively, they will describe their limitations in a defensive manner, positioning their problems as something that “could not be helped”—as something beyond what science can currently achieve.

However, their audience can see through this, because they are largely peers who understand and have experienced how modern research works. They can tell the difference between global challenges faced by every scientific study and limitations that are specific to a single study. Avoiding these specific limitations can therefore betray a lack of confidence that the study is good enough to withstand problems stemming from legitimate limitations. As such, researchers should actively engage with the greater scientific implications of the limitations that they face. Indeed, doing this is actually a way to demonstrate an author’s proficiency and aptitude.

In an example, neurogeneticist Nancy Bonini and colleagues, in their publication in Nature , discussed a question raised by their data that they have elected not to directly investigate in this study, writing “ Among the intriguing questions raised by these data is how senescent glia promote LDs in other glia. ” To show both the legitimacy of the question and how seriously they have considered it, the authors provided a comprehensive summary of the literature in the following seven sentences, offering two hypotheses backed by a combined eight different sources. 2 Rather than shying away from a limitation, they attacked it as something to be curious about and to discuss. This is not just a very effective way of demonstrating their expertise, but it frames the limitation as something that, when overcome, will build upon the present study rather than something that negatively affects the legitimacy of their current findings.

Striking the Right Balance

Scientists have to navigate the fine line between acknowledging the limitations of their study while also not diminishing the effect and value of their own work. To be aware of legitimate limitations and properly assess and dissect them shows a profound understanding of a field, where the study fits within that field, and what the rest of the scientific community are doing and what challenges they face.

All studies are parts of a greater whole. Pretending otherwise is a disservice to the scientific community.

Looking for more information on scientific writing? Check out  The Scientist’ s  TS SciComm  section. Looking for some help putting together a manuscript, a figure, a poster, or anything else?  The Scientist ’s  Scientific Services  may have the professional help that you need.

• He L, et al. Global characterization of macrophage polarization mechanisms and identification of M2-type polarization inhibitors . Cell Rep . 2021;37(5):109955.
• Byrns CN, et al. Senescent glia link mitochondrial dysfunction and lipid accumulation . Nature . 2024.

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Graduate Writing Center: Strategies for Writing Effective Scientific Papers

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Presenter: Aidan Howenstine, Ecology and Evolutionary Biology, Graduate Writing ConsultantThis workshop will address basic principles for writing scientific papers and offer strategies for avoiding common pitfalls. We will also introduce key points from Joshua Schimel’s book Writing Scienceon developing good narrative structure and clarity to make writing engaging and impactful. 

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• Published: 26 May 2023

The craft (and art) of scientific writing

Nature Cancer volume  4 ,  pages 583–584 ( 2023 ) Cite this article

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What are the elements of a well-written, informative and widely accessible paper?

What will the scientific paper of the future look like? Will we cease to read long-form written manuscripts and instead consume research findings as we do news, through a mix of data, text, videos and animations to be synthesized and interpreted by the beholder? It will be exciting to see science communication reshaped as technology and digital integration continue to develop. But while the traditional form of the scientific manuscript still stands, it is important to consider how to write it in a manner that balances informativeness with accessibility and that does justice to the complexity of the data while keeping the reader engaged.

If planning to submit to a specific journal, authors should be aware of that outlet’s guidelines and formatting requirements. Although at Nature Cancer we do not require that manuscripts conform to our format guidelines on first submission (on the contrary, formatting does not factor into our editorial assessment at all), this may not be the case for other journals. Even if authors have not yet decided where to submit when they start writing (as is the case in many, if not most cases), it is still important to be aware of discipline-specific considerations and to have a general view of expected manuscript sections and typical length and referencing limits as these are some the most laborious and time-consuming issues to fix later in the pre-publication process. In addition, certain types of work, for instance clinical research, must conform to very specific reporting and formatting guidelines that constrain the way in which the manuscript must be written. This Editorial will not cover clinical studies and will instead focus on writing laboratory-generated research.

The first step to writing a manuscript does not involve any writing at all. Instead, it requires objectively considering the collected data in toto to identify the key scientific messages that emerge, as these will be the crux of the manuscript. During this process it is essential to take a step back and critically evaluate the conclusions that can be drawn from the data to guard against building a story around preferred but not validated hypotheses. The text should always stay true to the data, but that does not mean that data should be described in a dry manner or in the chronological order in which experiments were conducted. On the contrary, it is important to also identify the narrative thread that connects the key pieces of data that support the main findings, so that these may be presented in a logical manner that readers will be able to follow. This process includes formulating the figures in their basic, functional, if not polished form, and once this is completed, one can get to the writing part.

The typical scientific manuscript at Nature Cancer and elsewhere includes introduction, methods, results and discussion sections. It may help to think of the paper as an information sandwich: the most important, richer parts are the results and methods sections, held together by the less complex (but no less important) introduction and discussion sections. Thus, one should start by writing up the results, picking up the narrative thread of the dataset and describing the experiments that together support the main findings in appropriately entitled subsections. The results section should describe all the data presented in the figures in the correct order but should not be a laundry list of lengthy experimental descriptions. Rather, it should highlight the key features of the data presented in the figures in a way that complements the visual representation and guides the reader through the complexity of the dataset.

Next up is writing the introduction, the section that not only introduces the main question the paper seeks to answer but that provides context by covering the literature that is relevant to the study, and through this prism presents the rationale and objectives of the current research effort. Here too it is essential to be selective and concise. Rather than exhaustively discussing every paper that might be linked to the topic under study, it is important to identify and synthesize the most pertinent primary research, without shying away from conflicting findings, controversies in the field or similar conclusions published elsewhere. Rather, such aspects are always best presented clearly and addressed head-on. To do this it is necessary to be diligent about staying up to date with the published literature and compiling a comprehensive list of references relevant to the project that can be whittled down to the essential references to be included in the manuscript as writing progresses. The main point to remember is that the introduction should not only permit the non-expert reader to understand the broader topic, the key prior art and the specific questions that the manuscript seeks to answer, but also help them appreciate why these questions are important and spark the reader’s interest in reading on.

With the results and introduction written, it is time to write the discussion — the section that puts the presented findings in perspective by going over their key elements, connecting them to existing knowledge and highlighting implications, outstanding questions and future paths of study. This section too relies on a strong knowledge of the related literature and good citation practices, as the most closely connected prior studies (that should have been already mentioned in the introduction) should be discussed here in more depth. Brevity is again essential, as is avoiding hype. Highlighting the importance of findings while acknowledging their caveats and limitations is key.

And what of the methods? This section is crucial and should be written in as much detail as would permit others to replicate experiments and analyses to reproduce results. Ideally it should develop in an organic manner, as experiments are being conducted and reagents and tools used. It should also be written in line with journal policies and thus merits a separate Editorial.

The final two things to write are arguably among the most important — the title and abstract are the face of the paper, the elements that readers first encounter when they survey the literature or the journal’s table of contents. Hence, they should state the main findings of the study in a clear, specific and engaging manner, with the abstract essentially being a mini version of the paper. The reader should know what to expect from the paper and should be enticed to find out more.

As with any piece of writing, especially when it comes to collaborative efforts, it is essential (and mandated by our authorship policy ) to have the input of all co-authors, even if one or a few contributors have taken on writing responsibilities. It is good general practice when writing anything to seek comments from others, especially non-authors whose judgement can be trusted and who are not too close to the subject to be able to provide an objective and constructive critique. Stepping away from one’s own writings and revisiting them later is also helpful to gain more objectivity. Manuscripts go through several iterations before publication, and while retaining one’s own voice is key, it is helpful to remain open to changes suggested by collaborators, referees and editors as the manuscript develops through the peer-review and revision process. The one principle to stick to when writing, is that the data should always be the lodestar.

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The craft (and art) of scientific writing. Nat Cancer 4 , 583–584 (2023). https://doi.org/10.1038/s43018-023-00579-y

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What is Scientific Research and How Can it be Done?

Scientific researches are studies that should be systematically planned before performing them. In this review, classification and description of scientific studies, planning stage randomisation and bias are explained.

Research conducted for the purpose of contributing towards science by the systematic collection, interpretation and evaluation of data and that, too, in a planned manner is called scientific research: a researcher is the one who conducts this research. The results obtained from a small group through scientific studies are socialised, and new information is revealed with respect to diagnosis, treatment and reliability of applications. The purpose of this review is to provide information about the definition, classification and methodology of scientific research.

Before beginning the scientific research, the researcher should determine the subject, do planning and specify the methodology. In the Declaration of Helsinki, it is stated that ‘the primary purpose of medical researches on volunteers is to understand the reasons, development and effects of diseases and develop protective, diagnostic and therapeutic interventions (method, operation and therapies). Even the best proven interventions should be evaluated continuously by investigations with regard to reliability, effectiveness, efficiency, accessibility and quality’ ( 1 ).

The questions, methods of response to questions and difficulties in scientific research may vary, but the design and structure are generally the same ( 2 ).

Classification of Scientific Research

Scientific research can be classified in several ways. Classification can be made according to the data collection techniques based on causality, relationship with time and the medium through which they are applied.

• Observational
• Experimental
• Descriptive
• Retrospective
• Prospective
• Cross-sectional
• Social descriptive research ( 3 )

Another method is to classify the research according to its descriptive or analytical features. This review is written according to this classification method.

I. Descriptive research

• Case series
• Surveillance studies

II. Analytical research

• Observational studies: cohort, case control and cross- sectional research
• Interventional research: quasi-experimental and clinical research
• Case Report: it is the most common type of descriptive study. It is the examination of a single case having a different quality in the society, e.g. conducting general anaesthesia in a pregnant patient with mucopolysaccharidosis.
• Case Series: it is the description of repetitive cases having common features. For instance; case series involving interscapular pain related to neuraxial labour analgesia. Interestingly, malignant hyperthermia cases are not accepted as case series since they are rarely seen during historical development.
• Surveillance Studies: these are the results obtained from the databases that follow and record a health problem for a certain time, e.g. the surveillance of cross-infections during anaesthesia in the intensive care unit.

Moreover, some studies may be experimental. After the researcher intervenes, the researcher waits for the result, observes and obtains data. Experimental studies are, more often, in the form of clinical trials or laboratory animal trials ( 2 ).

Analytical observational research can be classified as cohort, case-control and cross-sectional studies.

Firstly, the participants are controlled with regard to the disease under investigation. Patients are excluded from the study. Healthy participants are evaluated with regard to the exposure to the effect. Then, the group (cohort) is followed-up for a sufficient period of time with respect to the occurrence of disease, and the progress of disease is studied. The risk of the healthy participants getting sick is considered an incident. In cohort studies, the risk of disease between the groups exposed and not exposed to the effect is calculated and rated. This rate is called relative risk. Relative risk indicates the strength of exposure to the effect on the disease.

Cohort research may be observational and experimental. The follow-up of patients prospectively is called a prospective cohort study . The results are obtained after the research starts. The researcher’s following-up of cohort subjects from a certain point towards the past is called a retrospective cohort study . Prospective cohort studies are more valuable than retrospective cohort studies: this is because in the former, the researcher observes and records the data. The researcher plans the study before the research and determines what data will be used. On the other hand, in retrospective studies, the research is made on recorded data: no new data can be added.

In fact, retrospective and prospective studies are not observational. They determine the relationship between the date on which the researcher has begun the study and the disease development period. The most critical disadvantage of this type of research is that if the follow-up period is long, participants may leave the study at their own behest or due to physical conditions. Cohort studies that begin after exposure and before disease development are called ambidirectional studies . Public healthcare studies generally fall within this group, e.g. lung cancer development in smokers.

• Case-Control Studies: these studies are retrospective cohort studies. They examine the cause and effect relationship from the effect to the cause. The detection or determination of data depends on the information recorded in the past. The researcher has no control over the data ( 2 ).

Cross-sectional studies are advantageous since they can be concluded relatively quickly. It may be difficult to obtain a reliable result from such studies for rare diseases ( 2 ).

Cross-sectional studies are characterised by timing. In such studies, the exposure and result are simultaneously evaluated. While cross-sectional studies are restrictedly used in studies involving anaesthesia (since the process of exposure is limited), they can be used in studies conducted in intensive care units.

• Quasi-Experimental Research: they are conducted in cases in which a quick result is requested and the participants or research areas cannot be randomised, e.g. giving hand-wash training and comparing the frequency of nosocomial infections before and after hand wash.
• Clinical Research: they are prospective studies carried out with a control group for the purpose of comparing the effect and value of an intervention in a clinical case. Clinical study and research have the same meaning. Drugs, invasive interventions, medical devices and operations, diets, physical therapy and diagnostic tools are relevant in this context ( 6 ).

Clinical studies are conducted by a responsible researcher, generally a physician. In the research team, there may be other healthcare staff besides physicians. Clinical studies may be financed by healthcare institutes, drug companies, academic medical centres, volunteer groups, physicians, healthcare service providers and other individuals. They may be conducted in several places including hospitals, universities, physicians’ offices and community clinics based on the researcher’s requirements. The participants are made aware of the duration of the study before their inclusion. Clinical studies should include the evaluation of recommendations (drug, device and surgical) for the treatment of a disease, syndrome or a comparison of one or more applications; finding different ways for recognition of a disease or case and prevention of their recurrence ( 7 ).

Clinical Research

In this review, clinical research is explained in more detail since it is the most valuable study in scientific research.

Clinical research starts with forming a hypothesis. A hypothesis can be defined as a claim put forward about the value of a population parameter based on sampling. There are two types of hypotheses in statistics.

• H 0 hypothesis is called a control or null hypothesis. It is the hypothesis put forward in research, which implies that there is no difference between the groups under consideration. If this hypothesis is rejected at the end of the study, it indicates that a difference exists between the two treatments under consideration.
• H 1 hypothesis is called an alternative hypothesis. It is hypothesised against a null hypothesis, which implies that a difference exists between the groups under consideration. For example, consider the following hypothesis: drug A has an analgesic effect. Control or null hypothesis (H 0 ): there is no difference between drug A and placebo with regard to the analgesic effect. The alternative hypothesis (H 1 ) is applicable if a difference exists between drug A and placebo with regard to the analgesic effect.

The planning phase comes after the determination of a hypothesis. A clinical research plan is called a protocol . In a protocol, the reasons for research, number and qualities of participants, tests to be applied, study duration and what information to be gathered from the participants should be found and conformity criteria should be developed.

The selection of participant groups to be included in the study is important. Inclusion and exclusion criteria of the study for the participants should be determined. Inclusion criteria should be defined in the form of demographic characteristics (age, gender, etc.) of the participant group and the exclusion criteria as the diseases that may influence the study, age ranges, cases involving pregnancy and lactation, continuously used drugs and participants’ cooperation.

The next stage is methodology. Methodology can be grouped under subheadings, namely, the calculation of number of subjects, blinding (masking), randomisation, selection of operation to be applied, use of placebo and criteria for stopping and changing the treatment.

I. Calculation of the Number of Subjects

The entire source from which the data are obtained is called a universe or population . A small group selected from a certain universe based on certain rules and which is accepted to highly represent the universe from which it is selected is called a sample and the characteristics of the population from which the data are collected are called variables. If data is collected from the entire population, such an instance is called a parameter . Conducting a study on the sample rather than the entire population is easier and less costly. Many factors influence the determination of the sample size. Firstly, the type of variable should be determined. Variables are classified as categorical (qualitative, non-numerical) or numerical (quantitative). Individuals in categorical variables are classified according to their characteristics. Categorical variables are indicated as nominal and ordinal (ordered). In nominal variables, the application of a category depends on the researcher’s preference. For instance, a female participant can be considered first and then the male participant, or vice versa. An ordinal (ordered) variable is ordered from small to large or vice versa (e.g. ordering obese patients based on their weights-from the lightest to the heaviest or vice versa). A categorical variable may have more than one characteristic: such variables are called binary or dichotomous (e.g. a participant may be both female and obese).

If the variable has numerical (quantitative) characteristics and these characteristics cannot be categorised, then it is called a numerical variable. Numerical variables are either discrete or continuous. For example, the number of operations with spinal anaesthesia represents a discrete variable. The haemoglobin value or height represents a continuous variable.

Statistical analyses that need to be employed depend on the type of variable. The determination of variables is necessary for selecting the statistical method as well as software in SPSS. While categorical variables are presented as numbers and percentages, numerical variables are represented using measures such as mean and standard deviation. It may be necessary to use mean in categorising some cases such as the following: even though the variable is categorical (qualitative, non-numerical) when Visual Analogue Scale (VAS) is used (since a numerical value is obtained), it is classified as a numerical variable: such variables are averaged.

Clinical research is carried out on the sample and generalised to the population. Accordingly, the number of samples should be correctly determined. Different sample size formulas are used on the basis of the statistical method to be used. When the sample size increases, error probability decreases. The sample size is calculated based on the primary hypothesis. The determination of a sample size before beginning the research specifies the power of the study. Power analysis enables the acquisition of realistic results in the research, and it is used for comparing two or more clinical research methods.

Because of the difference in the formulas used in calculating power analysis and number of samples for clinical research, it facilitates the use of computer programs for making calculations.

It is necessary to know certain parameters in order to calculate the number of samples by power analysis.

• Type-I (α) and type-II (β) error levels
• Difference between groups (d-difference) and effect size (ES)
• Distribution ratio of groups
• Direction of research hypothesis (H1)

a. Type-I (α) and Type-II (β) Error (β) Levels

Two types of errors can be made while accepting or rejecting H 0 hypothesis in a hypothesis test. Type-I error (α) level is the probability of finding a difference at the end of the research when there is no difference between the two applications. In other words, it is the rejection of the hypothesis when H 0 is actually correct and it is known as α error or p value. For instance, when the size is determined, type-I error level is accepted as 0.05 or 0.01.

Another error that can be made during a hypothesis test is a type-II error. It is the acceptance of a wrongly hypothesised H 0 hypothesis. In fact, it is the probability of failing to find a difference when there is a difference between the two applications. The power of a test is the ability of that test to find a difference that actually exists. Therefore, it is related to the type-II error level.

Since the type-II error risk is expressed as β, the power of the test is defined as 1–β. When a type-II error is 0.20, the power of the test is 0.80. Type-I (α) and type-II (β) errors can be intentional. The reason to intentionally make such an error is the necessity to look at the events from the opposite perspective.

b. Difference between Groups and ES

ES is defined as the state in which statistical difference also has clinically significance: ES≥0.5 is desirable. The difference between groups is the absolute difference between the groups compared in clinical research.

c. Allocation Ratio of Groups

The allocation ratio of groups is effective in determining the number of samples. If the number of samples is desired to be determined at the lowest level, the rate should be kept as 1/1.

d. Direction of Hypothesis (H1)

The direction of hypothesis in clinical research may be one-sided or two-sided. While one-sided hypotheses hypothesis test differences in the direction of size, two-sided hypotheses hypothesis test differences without direction. The power of the test in two-sided hypotheses is lower than one-sided hypotheses.

After these four variables are determined, they are entered in the appropriate computer program and the number of samples is calculated. Statistical packaged software programs such as Statistica, NCSS and G-Power may be used for power analysis and calculating the number of samples. When the samples size is calculated, if there is a decrease in α, difference between groups, ES and number of samples, then the standard deviation increases and power decreases. The power in two-sided hypothesis is lower. It is ethically appropriate to consider the determination of sample size, particularly in animal experiments, at the beginning of the study. The phase of the study is also important in the determination of number of subjects to be included in drug studies. Usually, phase-I studies are used to determine the safety profile of a drug or product, and they are generally conducted on a few healthy volunteers. If no unacceptable toxicity is detected during phase-I studies, phase-II studies may be carried out. Phase-II studies are proof-of-concept studies conducted on a larger number (100–500) of volunteer patients. When the effectiveness of the drug or product is evident in phase-II studies, phase-III studies can be initiated. These are randomised, double-blinded, placebo or standard treatment-controlled studies. Volunteer patients are periodically followed-up with respect to the effectiveness and side effects of the drug. It can generally last 1–4 years and is valuable during licensing and releasing the drug to the general market. Then, phase-IV studies begin in which long-term safety is investigated (indication, dose, mode of application, safety, effectiveness, etc.) on thousands of volunteer patients.

II. Blinding (Masking) and Randomisation Methods

When the methodology of clinical research is prepared, precautions should be taken to prevent taking sides. For this reason, techniques such as randomisation and blinding (masking) are used. Comparative studies are the most ideal ones in clinical research.

Blinding Method

A case in which the treatments applied to participants of clinical research should be kept unknown is called the blinding method . If the participant does not know what it receives, it is called a single-blind study; if even the researcher does not know, it is called a double-blind study. When there is a probability of knowing which drug is given in the order of application, when uninformed staff administers the drug, it is called in-house blinding. In case the study drug is known in its pharmaceutical form, a double-dummy blinding test is conducted. Intravenous drug is given to one group and a placebo tablet is given to the comparison group; then, the placebo tablet is given to the group that received the intravenous drug and intravenous drug in addition to placebo tablet is given to the comparison group. In this manner, each group receives both the intravenous and tablet forms of the drug. In case a third party interested in the study is involved and it also does not know about the drug (along with the statistician), it is called third-party blinding.

Randomisation Method

The selection of patients for the study groups should be random. Randomisation methods are used for such selection, which prevent conscious or unconscious manipulations in the selection of patients ( 8 ).

No factor pertaining to the patient should provide preference of one treatment to the other during randomisation. This characteristic is the most important difference separating randomised clinical studies from prospective and synchronous studies with experimental groups. Randomisation strengthens the study design and enables the determination of reliable scientific knowledge ( 2 ).

The easiest method is simple randomisation, e.g. determination of the type of anaesthesia to be administered to a patient by tossing a coin. In this method, when the number of samples is kept high, a balanced distribution is created. When the number of samples is low, there will be an imbalance between the groups. In this case, stratification and blocking have to be added to randomisation. Stratification is the classification of patients one or more times according to prognostic features determined by the researcher and blocking is the selection of a certain number of patients for each stratification process. The number of stratification processes should be determined at the beginning of the study.

As the number of stratification processes increases, performing the study and balancing the groups become difficult. For this reason, stratification characteristics and limitations should be effectively determined at the beginning of the study. It is not mandatory for the stratifications to have equal intervals. Despite all the precautions, an imbalance might occur between the groups before beginning the research. In such circumstances, post-stratification or restandardisation may be conducted according to the prognostic factors.

The main characteristic of applying blinding (masking) and randomisation is the prevention of bias. Therefore, it is worthwhile to comprehensively examine bias at this stage.

Bias and Chicanery

While conducting clinical research, errors can be introduced voluntarily or involuntarily at a number of stages, such as design, population selection, calculating the number of samples, non-compliance with study protocol, data entry and selection of statistical method. Bias is taking sides of individuals in line with their own decisions, views and ideological preferences ( 9 ). In order for an error to lead to bias, it has to be a systematic error. Systematic errors in controlled studies generally cause the results of one group to move in a different direction as compared to the other. It has to be understood that scientific research is generally prone to errors. However, random errors (or, in other words, ‘the luck factor’-in which bias is unintended-do not lead to bias ( 10 ).

Another issue, which is different from bias, is chicanery. It is defined as voluntarily changing the interventions, results and data of patients in an unethical manner or copying data from other studies. Comparatively, bias may not be done consciously.

In case unexpected results or outliers are found while the study is analysed, if possible, such data should be re-included into the study since the complete exclusion of data from a study endangers its reliability. In such a case, evaluation needs to be made with and without outliers. It is insignificant if no difference is found. However, if there is a difference, the results with outliers are re-evaluated. If there is no error, then the outlier is included in the study (as the outlier may be a result). It should be noted that re-evaluation of data in anaesthesiology is not possible.

Statistical evaluation methods should be determined at the design stage so as not to encounter unexpected results in clinical research. The data should be evaluated before the end of the study and without entering into details in research that are time-consuming and involve several samples. This is called an interim analysis . The date of interim analysis should be determined at the beginning of the study. The purpose of making interim analysis is to prevent unnecessary cost and effort since it may be necessary to conclude the research after the interim analysis, e.g. studies in which there is no possibility to validate the hypothesis at the end or the occurrence of different side effects of the drug to be used. The accuracy of the hypothesis and number of samples are compared. Statistical significance levels in interim analysis are very important. If the data level is significant, the hypothesis is validated even if the result turns out to be insignificant after the date of the analysis.

Another important point to be considered is the necessity to conclude the participants’ treatment within the period specified in the study protocol. When the result of the study is achieved earlier and unexpected situations develop, the treatment is concluded earlier. Moreover, the participant may quit the study at its own behest, may die or unpredictable situations (e.g. pregnancy) may develop. The participant can also quit the study whenever it wants, even if the study has not ended ( 7 ).

In case the results of a study are contrary to already known or expected results, the expected quality level of the study suggesting the contradiction may be higher than the studies supporting what is known in that subject. This type of bias is called confirmation bias. The presence of well-known mechanisms and logical inference from them may create problems in the evaluation of data. This is called plausibility bias.

Another type of bias is expectation bias. If a result different from the known results has been achieved and it is against the editor’s will, it can be challenged. Bias may be introduced during the publication of studies, such as publishing only positive results, selection of study results in a way to support a view or prevention of their publication. Some editors may only publish research that extols only the positive results or results that they desire.

Bias may be introduced for advertisement or economic reasons. Economic pressure may be applied on the editor, particularly in the cases of studies involving drugs and new medical devices. This is called commercial bias.

In recent years, before beginning a study, it has been recommended to record it on the Web site www.clinicaltrials.gov for the purpose of facilitating systematic interpretation and analysis in scientific research, informing other researchers, preventing bias, provision of writing in a standard format, enhancing contribution of research results to the general literature and enabling early intervention of an institution for support. This Web site is a service of the US National Institutes of Health.

The last stage in the methodology of clinical studies is the selection of intervention to be conducted. Placebo use assumes an important place in interventions. In Latin, placebo means ‘I will be fine’. In medical literature, it refers to substances that are not curative, do not have active ingredients and have various pharmaceutical forms. Although placebos do not have active drug characteristic, they have shown effective analgesic characteristics, particularly in algology applications; further, its use prevents bias in comparative studies. If a placebo has a positive impact on a participant, it is called the placebo effect ; on the contrary, if it has a negative impact, it is called the nocebo effect . Another type of therapy that can be used in clinical research is sham application. Although a researcher does not cure the patient, the researcher may compare those who receive therapy and undergo sham. It has been seen that sham therapies also exhibit a placebo effect. In particular, sham therapies are used in acupuncture applications ( 11 ). While placebo is a substance, sham is a type of clinical application.

Ethically, the patient has to receive appropriate therapy. For this reason, if its use prevents effective treatment, it causes great problem with regard to patient health and legalities.

Before medical research is conducted with human subjects, predictable risks, drawbacks and benefits must be evaluated for individuals or groups participating in the study. Precautions must be taken for reducing the risk to a minimum level. The risks during the study should be followed, evaluated and recorded by the researcher ( 1 ).

After the methodology for a clinical study is determined, dealing with the ‘Ethics Committee’ forms the next stage. The purpose of the ethics committee is to protect the rights, safety and well-being of volunteers taking part in the clinical research, considering the scientific method and concerns of society. The ethics committee examines the studies presented in time, comprehensively and independently, with regard to ethics and science; in line with the Declaration of Helsinki and following national and international standards concerning ‘Good Clinical Practice’. The method to be followed in the formation of the ethics committee should be developed without any kind of prejudice and to examine the applications with regard to ethics and science within the framework of the ethics committee, Regulation on Clinical Trials and Good Clinical Practice ( www.iku.com ). The necessary documents to be presented to the ethics committee are research protocol, volunteer consent form, budget contract, Declaration of Helsinki, curriculum vitae of researchers, similar or explanatory literature samples, supporting institution approval certificate and patient follow-up form.

Only one sister/brother, mother, father, son/daughter and wife/husband can take charge in the same ethics committee. A rector, vice rector, dean, deputy dean, provincial healthcare director and chief physician cannot be members of the ethics committee.

Members of the ethics committee can work as researchers or coordinators in clinical research. However, during research meetings in which members of the ethics committee are researchers or coordinators, they must leave the session and they cannot sign-off on decisions. If the number of members in the ethics committee for a particular research is so high that it is impossible to take a decision, the clinical research is presented to another ethics committee in the same province. If there is no ethics committee in the same province, an ethics committee in the closest settlement is found.

Thereafter, researchers need to inform the participants using an informed consent form. This form should explain the content of clinical study, potential benefits of the study, alternatives and risks (if any). It should be easy, comprehensible, conforming to spelling rules and written in plain language understandable by the participant.

This form assists the participants in taking a decision regarding participation in the study. It should aim to protect the participants. The participant should be included in the study only after it signs the informed consent form; the participant can quit the study whenever required, even when the study has not ended ( 7 ).

Peer-review: Externally peer-reviewed.

Author Contributions: Concept - C.Ö.Ç., A.D.; Design - C.Ö.Ç.; Supervision - A.D.; Resource - C.Ö.Ç., A.D.; Materials - C.Ö.Ç., A.D.; Analysis and/or Interpretation - C.Ö.Ç., A.D.; Literature Search - C.Ö.Ç.; Writing Manuscript - C.Ö.Ç.; Critical Review - A.D.; Other - C.Ö.Ç., A.D.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: The authors declared that this study has received no financial support.

New database features 250 AI tools that can enhance social science research

Assistant Research Professor at the Social Science Research Center, Mississippi State University

Professor of education, Mississippi State University

Research associate in sociology, Mississippi State University

Doctoral student in psychology, Baylor University

Disclosure statement

The authors do not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.

Mississippi State University provides funding as a member of The Conversation US.

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AI – or artificial intelligence – is often used as a way to summarize data and improve writing. But AI tools also represent a powerful and efficient way to analyze large amounts of text to search for patterns. In addition, AI tools can assist with developing research products that can be shared widely.

It’s with that in mind that we , as researchers in social science , developed a new database of AI tools for the field . In the database, we compiled information about each tool and documented whether it was useful for literature reviews, data collection and analyses, or research dissemination. We also provided information on the costs, logins and plug-in extensions available for each tool.

When asked about their perceptions of AI, many social scientists express caution or apprehension. In a sample of faculty and students from over 600 institutions, only 22% of university faculty reported that they regularly used AI tools .

From combing through lengthy transcripts or text-based data to writing literature reviews and sharing results, we believe AI can help social science researchers – such as those in psychology, sociology and communication – as well as others get the most out of their data and present it to a wider audience.

Analyze text using AI

Qualitative research often involves poring over transcripts or written language to identify themes and patterns. While this kind of research is powerful, it is also labor-intensive. The power of AI platforms to sift through large datasets not only saves researchers time, but it can also help them analyze data that couldn’t have been analyzed previously because of the size of the dataset.

Specifically, AI can assist social scientists by identifying potential themes or common topics in large, text-based data that scientists can interrogate using qualitative research methods. For example, AI can analyze 15 million social media posts to identify themes in how people coped with COVID-19. These themes can then give researchers insight into larger trends in the data, allowing us to refine criteria for a more in-depth, qualitative analysis.

AI tools can also be used to adapt language and scientists’ word choice in research designs. In particular, AI can reduce bias by improving the wording of questions in surveys or refining keywords used in social media data collection.

Identify gaps in knowledge

Another key task in research is to scan the field for previous work to identify gaps in knowledge. AI applications are built on systems that can synthesize text . This makes literature reviews – the section of a research paper that summarizes other research on the same topic – and writing processes more efficient.

Research shows that human feedback to AI, such as providing examples of simple logic, can significantly improve the tools’ ability to perform complex reasoning . With this in mind, we can continually revise our instructions to AI and refine its ability to pull relevant literature.

However, social scientists must be wary of fake sources – a big concern with generative AI . It is essential to verify any sources AI tools provide to ensure they come from peer-reviewed journals.

Share research findings

AI tools can quickly summarize research findings in a reader-friendly way by assisting with writing blogs, creating infographics and producing presentation slides and even images.

Our database contains AI tools that can also help scientists present their findings on social media. One tool worth highlighting is BlogTweet . This free AI tool allows users to copy and paste text from an article like this one to generate tweet threads and start conversations.

Be aware of the cost of AI tools

Two-thirds of the tools in the database cost money. While our primary objective was to identify the most useful tools for social scientists, we also sought to identify open-source tools and curated a list of 85 free tools that can support literature reviews, writing, data collection, analysis and visualization efforts.

In our analysis of the cost of AI tools, we also found that many offer “freemium” access to tools. This means you can explore a free version of the product. More advanced versions of the tool are available through the purchase of tokens or subscription plans.

For some tools, costs can be somewhat hidden or unexpected. For instance, a tool that seems open source on the surface may actually have rate limits, and users may find that they’ve run out of free questions to ask the AI.

The future of the database

Since the release of the Artificial Intelligence Applications for Social Science Research Database on Oct. 5, 2023, it has been downloaded over 400 times across 49 countries. In the database, we found 131 AI tools useful for literature reviews, summaries or writing. As many as 146 AI tools are useful for data collection or analysis, and 108 are useful for research dissemination.

We continue to update the database and hope that it can aid academic communities in their exploration of AI and generate new conversations. The more that social scientists use the database, the more they can work toward consensus of adopting ethical approaches to using AI in research and analysis.

• Artificial intelligence (AI)
• Social science

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Laboratory Head - RNA Biology

Why the Pandemic Probably Started in a Lab, in 5 Key Points

By Alina Chan

Dr. Chan is a molecular biologist at the Broad Institute of M.I.T. and Harvard, and a co-author of “Viral: The Search for the Origin of Covid-19.”

This article has been updated to reflect news developments.

On Monday, Dr. Anthony Fauci returned to the halls of Congress and testified before the House subcommittee investigating the Covid-19 pandemic. He was questioned about several topics related to the government’s handling of Covid-19, including how the National Institute of Allergy and Infectious Diseases, which he directed until retiring in 2022, supported risky virus work at a Chinese institute whose research may have caused the pandemic.

For more than four years, reflexive partisan politics have derailed the search for the truth about a catastrophe that has touched us all. It has been estimated that at least 25 million people around the world have died because of Covid-19, with over a million of those deaths in the United States.

Although how the pandemic started has been hotly debated, a growing volume of evidence — gleaned from public records released under the Freedom of Information Act, digital sleuthing through online databases, scientific papers analyzing the virus and its spread, and leaks from within the U.S. government — suggests that the pandemic most likely occurred because a virus escaped from a research lab in Wuhan, China. If so, it would be the most costly accident in the history of science.

Here’s what we now know:

1 The SARS-like virus that caused the pandemic emerged in Wuhan, the city where the world’s foremost research lab for SARS-like viruses is located.

• At the Wuhan Institute of Virology, a team of scientists had been hunting for SARS-like viruses for over a decade, led by Shi Zhengli.
• Their research showed that the viruses most similar to SARS‑CoV‑2, the virus that caused the pandemic, circulate in bats that live r oughly 1,000 miles away from Wuhan. Scientists from Dr. Shi’s team traveled repeatedly to Yunnan province to collect these viruses and had expanded their search to Southeast Asia. Bats in other parts of China have not been found to carry viruses that are as closely related to SARS-CoV-2.

The closest known relatives to SARS-CoV-2 were found in southwestern China and in Laos.

Large cities

Mine in Yunnan province

Cave in Laos

South China Sea

The closest known relatives to SARS-CoV-2

were found in southwestern China and in Laos.

philippines

The closest known relatives to SARS-CoV-2 were found

in southwestern China and Laos.

Sources: Sarah Temmam et al., Nature; SimpleMaps

Note: Cities shown have a population of at least 200,000.

There are hundreds of large cities in China and Southeast Asia.

There are hundreds of large cities in China

and Southeast Asia.

The pandemic started roughly 1,000 miles away, in Wuhan, home to the world’s foremost SARS-like virus research lab.

The pandemic started roughly 1,000 miles away,

in Wuhan, home to the world’s foremost SARS-like virus research lab.

The pandemic started roughly 1,000 miles away, in Wuhan,

home to the world’s foremost SARS-like virus research lab.

• Even at hot spots where these viruses exist naturally near the cave bats of southwestern China and Southeast Asia, the scientists argued, as recently as 2019 , that bat coronavirus spillover into humans is rare .
• When the Covid-19 outbreak was detected, Dr. Shi initially wondered if the novel coronavirus had come from her laboratory , saying she had never expected such an outbreak to occur in Wuhan.
• The SARS‑CoV‑2 virus is exceptionally contagious and can jump from species to species like wildfire . Yet it left no known trace of infection at its source or anywhere along what would have been a thousand-mile journey before emerging in Wuhan.

2 The year before the outbreak, the Wuhan institute, working with U.S. partners, had proposed creating viruses with SARS‑CoV‑2’s defining feature.

• Dr. Shi’s group was fascinated by how coronaviruses jump from species to species. To find viruses, they took samples from bats and other animals , as well as from sick people living near animals carrying these viruses or associated with the wildlife trade. Much of this work was conducted in partnership with the EcoHealth Alliance, a U.S.-based scientific organization that, since 2002, has been awarded over $80 million in federal funding to research the risks of emerging infectious diseases.
• The laboratory pursued risky research that resulted in viruses becoming more infectious : Coronaviruses were grown from samples from infected animals and genetically reconstructed and recombined to create new viruses unknown in nature. These new viruses were passed through cells from bats, pigs, primates and humans and were used to infect civets and humanized mice (mice modified with human genes). In essence, this process forced these viruses to adapt to new host species, and the viruses with mutations that allowed them to thrive emerged as victors.
• By 2019, Dr. Shi’s group had published a database describing more than 22,000 collected wildlife samples. But external access was shut off in the fall of 2019, and the database was not shared with American collaborators even after the pandemic started , when such a rich virus collection would have been most useful in tracking the origin of SARS‑CoV‑2. It remains unclear whether the Wuhan institute possessed a precursor of the pandemic virus.
• In 2021, The Intercept published a leaked 2018 grant proposal for a research project named Defuse , which had been written as a collaboration between EcoHealth, the Wuhan institute and Ralph Baric at the University of North Carolina, who had been on the cutting edge of coronavirus research for years. The proposal described plans to create viruses strikingly similar to SARS‑CoV‑2.
• Coronaviruses bear their name because their surface is studded with protein spikes, like a spiky crown, which they use to enter animal cells. T he Defuse project proposed to search for and create SARS-like viruses carrying spikes with a unique feature: a furin cleavage site — the same feature that enhances SARS‑CoV‑2’s infectiousness in humans, making it capable of causing a pandemic. Defuse was never funded by the United States . However, in his testimony on Monday, Dr. Fauci explained that the Wuhan institute would not need to rely on U.S. funding to pursue research independently.

The Wuhan lab ran risky experiments to learn about how SARS-like viruses might infect humans.

1. Collect SARS-like viruses from bats and other wild animals, as well as from people exposed to them.

2. Identify high-risk viruses by screening for spike proteins that facilitate infection of human cells.

2. Identify high-risk viruses by screening for spike proteins that facilitate infection of

human cells.

In Defuse, the scientists proposed to add a furin cleavage site to the spike protein.

3. Create new coronaviruses by inserting spike proteins or other features that could make the viruses more infectious in humans.

4. Infect human cells, civets and humanized mice with the new coronaviruses, to determine how dangerous they might be.

• While it’s possible that the furin cleavage site could have evolved naturally (as seen in some distantly related coronaviruses), out of the hundreds of SARS-like viruses cataloged by scientists, SARS‑CoV‑2 is the only one known to possess a furin cleavage site in its spike. And the genetic data suggest that the virus had only recently gained the furin cleavage site before it started the pandemic.
• Ultimately, a never-before-seen SARS-like virus with a newly introduced furin cleavage site, matching the description in the Wuhan institute’s Defuse proposal, caused an outbreak in Wuhan less than two years after the proposal was drafted.
• When the Wuhan scientists published their seminal paper about Covid-19 as the pandemic roared to life in 2020, they did not mention the virus’s furin cleavage site — a feature they should have been on the lookout for, according to their own grant proposal, and a feature quickly recognized by other scientists.
• Worse still, as the pandemic raged, their American collaborators failed to publicly reveal the existence of the Defuse proposal. The president of EcoHealth, Peter Daszak, recently admitted to Congress that he doesn’t know about virus samples collected by the Wuhan institute after 2015 and never asked the lab’s scientists if they had started the work described in Defuse. In May, citing failures in EcoHealth’s monitoring of risky experiments conducted at the Wuhan lab, the Biden administration suspended all federal funding for the organization and Dr. Daszak, and initiated proceedings to bar them from receiving future grants. In his testimony on Monday, Dr. Fauci said that he supported the decision to suspend and bar EcoHealth.
• Separately, Dr. Baric described the competitive dynamic between his research group and the institute when he told Congress that the Wuhan scientists would probably not have shared their most interesting newly discovered viruses with him . Documents and email correspondence between the institute and Dr. Baric are still being withheld from the public while their release is fiercely contested in litigation.
• In the end, American partners very likely knew of only a fraction of the research done in Wuhan. According to U.S. intelligence sources, some of the institute’s virus research was classified or conducted with or on behalf of the Chinese military . In the congressional hearing on Monday, Dr. Fauci repeatedly acknowledged the lack of visibility into experiments conducted at the Wuhan institute, saying, “None of us can know everything that’s going on in China, or in Wuhan, or what have you. And that’s the reason why — I say today, and I’ve said at the T.I.,” referring to his transcribed interview with the subcommittee, “I keep an open mind as to what the origin is.”

3 The Wuhan lab pursued this type of work under low biosafety conditions that could not have contained an airborne virus as infectious as SARS‑CoV‑2.

• Labs working with live viruses generally operate at one of four biosafety levels (known in ascending order of stringency as BSL-1, 2, 3 and 4) that describe the work practices that are considered sufficiently safe depending on the characteristics of each pathogen. The Wuhan institute’s scientists worked with SARS-like viruses under inappropriately low biosafety conditions .

In the United States, virologists generally use stricter Biosafety Level 3 protocols when working with SARS-like viruses.

Biosafety cabinets prevent

viral particles from escaping.

Viral particles

Personal respirators provide

a second layer of defense against breathing in the virus.

DIRECT CONTACT

Gloves prevent skin contact.

Disposable wraparound

gowns cover much of the rest of the body.

Personal respirators provide a second layer of defense against breathing in the virus.

Disposable wraparound gowns

cover much of the rest of the body.

Note: ​​Biosafety levels are not internationally standardized, and some countries use more permissive protocols than others.

The Wuhan lab had been regularly working with SARS-like viruses under Biosafety Level 2 conditions, which could not prevent a highly infectious virus like SARS-CoV-2 from escaping.

Some work is done in the open air, and masks are not required.

Less protective equipment provides more opportunities

for contamination.

Some work is done in the open air,

and masks are not required.

Less protective equipment provides more opportunities for contamination.

• In one experiment, Dr. Shi’s group genetically engineered an unexpectedly deadly SARS-like virus (not closely related to SARS‑CoV‑2) that exhibited a 10,000-fold increase in the quantity of virus in the lungs and brains of humanized mice . Wuhan institute scientists handled these live viruses at low biosafet y levels , including BSL-2.
• Even the much more stringent containment at BSL-3 cannot fully prevent SARS‑CoV‑2 from escaping . Two years into the pandemic, the virus infected a scientist in a BSL-3 laboratory in Taiwan, which was, at the time, a zero-Covid country. The scientist had been vaccinated and was tested only after losing the sense of smell. By then, more than 100 close contacts had been exposed. Human error is a source of exposure even at the highest biosafety levels , and the risks are much greater for scientists working with infectious pathogens at low biosafety.
• An early draft of the Defuse proposal stated that the Wuhan lab would do their virus work at BSL-2 to make it “highly cost-effective.” Dr. Baric added a note to the draft highlighting the importance of using BSL-3 to contain SARS-like viruses that could infect human cells, writing that “U.S. researchers will likely freak out.” Years later, after SARS‑CoV‑2 had killed millions, Dr. Baric wrote to Dr. Daszak : “I have no doubt that they followed state determined rules and did the work under BSL-2. Yes China has the right to set their own policy. You believe this was appropriate containment if you want but don’t expect me to believe it. Moreover, don’t insult my intelligence by trying to feed me this load of BS.”
• SARS‑CoV‑2 is a stealthy virus that transmits effectively through the air, causes a range of symptoms similar to those of other common respiratory diseases and can be spread by infected people before symptoms even appear. If the virus had escaped from a BSL-2 laboratory in 2019, the leak most likely would have gone undetected until too late.
• One alarming detail — leaked to The Wall Street Journal and confirmed by current and former U.S. government officials — is that scientists on Dr. Shi’s team fell ill with Covid-like symptoms in the fall of 2019 . One of the scientists had been named in the Defuse proposal as the person in charge of virus discovery work. The scientists denied having been sick .

4 The hypothesis that Covid-19 came from an animal at the Huanan Seafood Market in Wuhan is not supported by strong evidence.

• In December 2019, Chinese investigators assumed the outbreak had started at a centrally located market frequented by thousands of visitors daily. This bias in their search for early cases meant that cases unlinked to or located far away from the market would very likely have been missed. To make things worse, the Chinese authorities blocked the reporting of early cases not linked to the market and, claiming biosafety precautions, ordered the destruction of patient samples on January 3, 2020, making it nearly impossible to see the complete picture of the earliest Covid-19 cases. Information about dozens of early cases from November and December 2019 remains inaccessible.
• A pair of papers published in Science in 2022 made the best case for SARS‑CoV‑2 having emerged naturally from human-animal contact at the Wuhan market by focusing on a map of the early cases and asserting that the virus had jumped from animals into humans twice at the market in 2019. More recently, the two papers have been countered by other virologists and scientists who convincingly demonstrate that the available market evidence does not distinguish between a human superspreader event and a natural spillover at the market.
• Furthermore, the existing genetic and early case data show that all known Covid-19 cases probably stem from a single introduction of SARS‑CoV‑2 into people, and the outbreak at the Wuhan market probably happened after the virus had already been circulating in humans.

An analysis of SARS-CoV-2’s evolutionary tree shows how the virus evolved as it started to spread through humans.

SARS-COV-2 Viruses closest

to bat coronaviruses

more mutations

Source: Lv et al., Virus Evolution (2024) , as reproduced by Jesse Bloom

The viruses that infected people linked to the market were most likely not the earliest form of the virus that started the pandemic.

• Not a single infected animal has ever been confirmed at the market or in its supply chain. Without good evidence that the pandemic started at the Huanan Seafood Market, the fact that the virus emerged in Wuhan points squarely at its unique SARS-like virus laboratory.

5 Key evidence that would be expected if the virus had emerged from the wildlife trade is still missing.

In previous outbreaks of coronaviruses, scientists were able to demonstrate natural origin by collecting multiple pieces of evidence linking infected humans to infected animals.

Infected animals

Earliest known

cases exposed to

live animals

Antibody evidence

of animals and

animal traders having

been infected

Ancestral variants

of the virus found in

Documented trade

of host animals

between the area

where bats carry

closely related viruses

and the outbreak site

Infected animals found

Earliest known cases exposed to live animals

Antibody evidence of animals and animal

traders having been infected

Ancestral variants of the virus found in animals

Documented trade of host animals

between the area where bats carry closely

related viruses and the outbreak site

For SARS-CoV-2, these same key pieces of evidence are still missing , more than four years after the virus emerged.

For SARS-CoV-2, these same key pieces of evidence are still missing ,

more than four years after the virus emerged.

• Despite the intense search trained on the animal trade and people linked to the market, investigators have not reported finding any animals infected with SARS‑CoV‑2 that had not been infected by humans. Yet, infected animal sources and other connective pieces of evidence were found for the earlier SARS and MERS outbreaks as quickly as within a few days, despite the less advanced viral forensic technologies of two decades ago.
• Even though Wuhan is the home base of virus hunters with world-leading expertise in tracking novel SARS-like viruses, investigators have either failed to collect or report key evidence that would be expected if Covid-19 emerged from the wildlife trade . For example, investigators have not determined that the earliest known cases had exposure to intermediate host animals before falling ill. No antibody evidence shows that animal traders in Wuhan are regularly exposed to SARS-like viruses, as would be expected in such situations.
• With today’s technology, scientists can detect how respiratory viruses — including SARS, MERS and the flu — circulate in animals while making repeated attempts to jump across species . Thankfully, these variants usually fail to transmit well after crossing over to a new species and tend to die off after a small number of infections. In contrast, virologists and other scientists agree that SARS‑CoV‑2 required little to no adaptation to spread rapidly in humans and other animals . The virus appears to have succeeded in causing a pandemic upon its only detected jump into humans.

The pandemic could have been caused by any of hundreds of virus species, at any of tens of thousands of wildlife markets, in any of thousands of cities, and in any year. But it was a SARS-like coronavirus with a unique furin cleavage site that emerged in Wuhan, less than two years after scientists, sometimes working under inadequate biosafety conditions, proposed collecting and creating viruses of that same design.

While several natural spillover scenarios remain plausible, and we still don’t know enough about the full extent of virus research conducted at the Wuhan institute by Dr. Shi’s team and other researchers, a laboratory accident is the most parsimonious explanation of how the pandemic began.

Given what we now know, investigators should follow their strongest leads and subpoena all exchanges between the Wuhan scientists and their international partners, including unpublished research proposals, manuscripts, data and commercial orders. In particular, exchanges from 2018 and 2019 — the critical two years before the emergence of Covid-19 — are very likely to be illuminating (and require no cooperation from the Chinese government to acquire), yet they remain beyond the public’s view more than four years after the pandemic began.

Whether the pandemic started on a lab bench or in a market stall, it is undeniable that U.S. federal funding helped to build an unprecedented collection of SARS-like viruses at the Wuhan institute, as well as contributing to research that enhanced them . Advocates and funders of the institute’s research, including Dr. Fauci, should cooperate with the investigation to help identify and close the loopholes that allowed such dangerous work to occur. The world must not continue to bear the intolerable risks of research with the potential to cause pandemics .

A successful investigation of the pandemic’s root cause would have the power to break a decades-long scientific impasse on pathogen research safety, determining how governments will spend billions of dollars to prevent future pandemics. A credible investigation would also deter future acts of negligence and deceit by demonstrating that it is indeed possible to be held accountable for causing a viral pandemic. Last but not least, people of all nations need to see their leaders — and especially, their scientists — heading the charge to find out what caused this world-shaking event. Restoring public trust in science and government leadership requires it.

A thorough investigation by the U.S. government could unearth more evidence while spurring whistleblowers to find their courage and seek their moment of opportunity. It would also show the world that U.S. leaders and scientists are not afraid of what the truth behind the pandemic may be.

More on how the pandemic may have started

Where Did the Coronavirus Come From? What We Already Know Is Troubling.

Even if the coronavirus did not emerge from a lab, the groundwork for a potential disaster had been laid for years, and learning its lessons is essential to preventing others.

By Zeynep Tufekci

Why Does Bad Science on Covid’s Origin Get Hyped?

If the raccoon dog was a smoking gun, it fired blanks.

By David Wallace-Wells

A Plea for Making Virus Research Safer

A way forward for lab safety.

By Jesse Bloom

The Times is committed to publishing a diversity of letters to the editor. We’d like to hear what you think about this or any of our articles. Here are some tips . And here’s our email: [email protected] .

Follow the New York Times Opinion section on Facebook , Instagram , TikTok , WhatsApp , X and Threads .

Alina Chan ( @ayjchan ) is a molecular biologist at the Broad Institute of M.I.T. and Harvard, and a co-author of “ Viral : The Search for the Origin of Covid-19.” She was a member of the Pathogens Project , which the Bulletin of the Atomic Scientists organized to generate new thinking on responsible, high-risk pathogen research.

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Being Open about LGBTQ+ Identities in the Classroom Creates Positive Learning Environments

Three LGBTQ+ professors share their experiences “queering the classroom” in ways that students embrace

Photo by simarik/iStock

Jessica Colarossi

Teachers play a unique role in the world—not only creating spaces to learn, but also helping students think critically, grow, and feel seen. Keenly aware how important it is to create welcoming learning environments, three Boston University health science professors embarked on an experiment.

Sophie Godley, Jesse Moreira-Bouchard, and Shelly DeBiasse, who all identify in the LGBTQ+ (lesbian, gay, bisexual, transgender, queer) community, made an intentional effort to be open and authentic about their identities and have inclusive dialogue in the classroom relating to queerness—then studied the impact on their students. The results of their research , published in Advances in Physiology Education , showed the majority of students had an overwhelmingly positive experience to what the professors called, “queering the classroom.” The study includes 86 students who voluntarily participated in a survey at the end of semester-long courses about their experiences. Some participants identified as members of the LGBTQ+ community and some did not. 

Considering that LGBTQ+ college students have reported feeling silenced and disillusioned in academia —especially queer students in science, technology, engineering, and mathematics (STEM)—the study authors say it’s crucial that queer students feel that they belong. They add that a sense of belonging can contribute to degree completion. 

“Queer approaches to curricula and the classroom may help improve awareness and ultimately improve the lives of LGBTQ+ students in those classes,” they write in the paper. To reflect on their personal experiences and teaching practices, these three experts share what queering the classroom means to them and why it’s important for students and faculty to be seen and heard, not only during Pride Month, but all the time.

“Speaking to my 19-year-old self…”

Sophie godley, school of public health clinical associate professor and associate director of kilachand honors college.

I came out as gay when I was 19 years old—a first-year in college. I lost a lot when I first came out and was told repeatedly that being gay meant I would never have a family or children, or a real “home.” So, for me, being my authentic self in the classroom—talking about my wife, my son, my home, my family, my pets, my full, vibrant life—is incredibly important. I want students to know that not only can they be themselves and be OK, they can also thrive. Yes it’s a bit cheesy, but I am trying to speak back in time to my 19-year-old self who was lost and scared, and could have really used a voracious example of thriving queer authenticity.

One of my favorite moments in the classroom that has happened a few different times over the years is when a student will tell me they come from a two-mom family and how much they appreciate me talking about my family, so they see themselves represented.

The motivations for this study included a wide range of hypotheses, including pushing back at the notion that instructors’ true authentic selves have no place in the classroom. We want to resist the idea that showing up as us , as our true selves, is inappropriate or unnecessary. It is necessary for us as teachers—and as author and Columbia University professor Bettina Love says, “coconspirators” with our students—to be ourselves and be real with our students. I think all of us on the team were not surprised, as much as affirmed to hear that our authenticity matters and supports students. It was a surprise to hear how much of a difference it makes for students across all identities.

We need increased scholarship on effective pedagogy in health sciences so that we can continue to provide our students with an excellent classroom experience that prepares them to become excellent health professionals.

“Being a genuine human is not incompatible with being an expert…”

Jesse moreira-bouchard, sargent college of health & rehabilitation sciences clinical assistant professor of human physiology.

Queering my classroom means I show up as myself every day to teach. I dress in a way that feels authentic to my queer gender identity, I share my pronouns with my students, I talk about my life, my husband, something fun we might be doing on the weekend. It means showing the students that you can be queer and a professional. That being a real, genuine human is not at all incompatible or mutually exclusive from being perceived as an expert. Students often tell me they feel seen, like I know them as people and not just numbers, and that they enjoy the comfort my classroom provides for learning. 

Students, like any person, want to be included in their environment. All anyone wants is for others to accept them, regardless of what identity they may hold. Student sense of belonging is a very strong predictor of persistence and retention, and LGBTQ+ students are at higher risk of dropping out of STEM than their cisgender/heterosexual peers. We wanted to demonstrate with this study that it doesn’t take content revision of your entire course to foster space for diverse thought or inclusive sentiments—you simply have to be intentional and authentic with your students. I hope this research encourages academia to engage LGBTQ+ faculty more authentically and begins to reshape cultural expectations of professionalism, from concealing our identities being the norm to expressing them more openly being the norm.

Our data suggest whether or not students resonated with my queer identity as the instructor, they still felt like I was a genuine person who cared, allowed them to be comfortable. Nonetheless, a small percentage of students reported feeling a liberal bias in the room. This was unsurprising to me, since LGBTQ+ topics have been highly politicized. If a student grew up surrounded by less accepting values, then such radical authenticity might very well make them uncomfortable. It’s worth noting, though, that it’s okay to be uncomfortable and have your views challenged. When you engage with and interrogate your views in the context of new experiences, you tend to grow. So, hopefully these experiences were an impetus for students who had less experience understanding LGBTQ+ people. In the future, more research is needed to identify specific practices that are high-impact and which yield the greatest net effect on student engagement and retention—and, moreover, must be done in more regions than the northeast.

“We need to support faculty authenticity in the classroom…”

Shelly debiasse, sargent clinical associate professor of nutrition.

My view of queering the classroom involves looking to, giving space to, and amplifying views from the margins. Traditional pedagogy in most universities in the United States centers on knowledge that has been gathered, created, and expounded by white, cisgender (mostly male identified), heterosexual individuals. In the context of our study, queering the classroom also means embodying my authentic self, and making sure that my teaching included voices from the margins, including diverse racial and ethnic representation and contributions from individuals who identify outside of the gender binary.

My motivation for developing and implementing this study was to gather information from a diverse group of students regarding their thoughts, feelings, and behaviors in response to queer faculty intentionally being authentic in the classroom. Our work demonstrated that students of all identities embraced our inclusive pedagogy. It is always wonderful to have students of all identities thank me for my intentionality in terms of creating an inclusive classroom. Unfortunately, there are some students for whom this approach is new and uncomfortable—particularly those who have not been exposed to this content. As our data showed, there was some pushback from some students in the study. This feedback is helpful to remind faculty who want to create inclusive classrooms to be mindful and implement strategies to ensure that all students’ viewpoints are considered. 

There can be no greater disservice to all members of the classroom community than to have some student voices stifled while other voices pervade the space. I firmly believe that college is a time when we all have an opportunity to learn so much about the world we live in. To deny the opportunity for any student to learn about other perspectives, in my opinion, is tragic. My hope is that the results of our study can inform faculty and administration of the need to support faculty authenticity and safety in the classroom. Whether it is race, gender, sexuality, ability, body size, and myriad other marginalized identities, having faculty who hold those identities feel valued, safe, and comfortable living their identities in classroom spaces is important not only for student retention and success, but also for faculty retention and success. Administrators need to be aware of the additional emotional and, at times, physical work required to hold a marginalized identity in the academy. Support and understanding can go a long way.

Sophie Godley (SPH’17) teaches courses in public health, maternal and child health, and population health; Jesse Moreira-Bouchard (Sargent’18,’21) researches and teaches with a focus on LGBTQIA2S+ equity and inclusion in STEM and physiology education, as well as cardiovascular health risk in LGBTQIA2S+ communities; Michele A. “Shelly” DeBiasse (CAMED’16) has been a registered dietitian nutritionist for 35 years and their current research focus is on issues related to equity, diversity, inclusion, and social justice in healthcare and healthcare professions.

“Expert Take”  is a research-led opinion page that provides commentaries from BU researchers on a variety of issues—local, national, or international—related to their work. Anyone interested in submitting a piece should contact  [email protected] .  The Brink  reserves the right to reject or edit submissions. The views expressed are solely those of the author and are not intended to represent the views of Boston University.

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Jessica Colarossi is a science writer for The Brink . She graduated with a BS in journalism from Emerson College in 2016, with focuses on environmental studies and publishing. While a student, she interned at ThinkProgress in Washington, D.C., where she wrote over 30 stories, most of them relating to climate change, coral reefs, and women’s health. Profile

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There is 1 comment on Being Open about LGBTQ+ Identities in the Classroom Creates Positive Learning Environments

This was a great article! I taught middle school in an extremely conservative town (90% of voters voted for Trump in 2016), and one of my friends and fellow teachers was a young gay woman science teacher and coach with a wife and son. She was a fantastic role model for all of her students and athletes, and they loved her. I’d like to think that our school was a better place and more open minded because of her and her family.

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