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Primacy of the research question, structure of the paper, writing a research article: advice to beginners.

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Thomas V. Perneger, Patricia M. Hudelson, Writing a research article: advice to beginners, International Journal for Quality in Health Care , Volume 16, Issue 3, June 2004, Pages 191–192, https://doi.org/10.1093/intqhc/mzh053

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Writing research papers does not come naturally to most of us. The typical research paper is a highly codified rhetorical form [ 1 , 2 ]. Knowledge of the rules—some explicit, others implied—goes a long way toward writing a paper that will get accepted in a peer-reviewed journal.

A good research paper addresses a specific research question. The research question—or study objective or main research hypothesis—is the central organizing principle of the paper. Whatever relates to the research question belongs in the paper; the rest doesn’t. This is perhaps obvious when the paper reports on a well planned research project. However, in applied domains such as quality improvement, some papers are written based on projects that were undertaken for operational reasons, and not with the primary aim of producing new knowledge. In such cases, authors should define the main research question a posteriori and design the paper around it.

Generally, only one main research question should be addressed in a paper (secondary but related questions are allowed). If a project allows you to explore several distinct research questions, write several papers. For instance, if you measured the impact of obtaining written consent on patient satisfaction at a specialized clinic using a newly developed questionnaire, you may want to write one paper on the questionnaire development and validation, and another on the impact of the intervention. The idea is not to split results into ‘least publishable units’, a practice that is rightly decried, but rather into ‘optimally publishable units’.

What is a good research question? The key attributes are: (i) specificity; (ii) originality or novelty; and (iii) general relevance to a broad scientific community. The research question should be precise and not merely identify a general area of inquiry. It can often (but not always) be expressed in terms of a possible association between X and Y in a population Z, for example ‘we examined whether providing patients about to be discharged from the hospital with written information about their medications would improve their compliance with the treatment 1 month later’. A study does not necessarily have to break completely new ground, but it should extend previous knowledge in a useful way, or alternatively refute existing knowledge. Finally, the question should be of interest to others who work in the same scientific area. The latter requirement is more challenging for those who work in applied science than for basic scientists. While it may safely be assumed that the human genome is the same worldwide, whether the results of a local quality improvement project have wider relevance requires careful consideration and argument.

Once the research question is clearly defined, writing the paper becomes considerably easier. The paper will ask the question, then answer it. The key to successful scientific writing is getting the structure of the paper right. The basic structure of a typical research paper is the sequence of Introduction, Methods, Results, and Discussion (sometimes abbreviated as IMRAD). Each section addresses a different objective. The authors state: (i) the problem they intend to address—in other terms, the research question—in the Introduction; (ii) what they did to answer the question in the Methods section; (iii) what they observed in the Results section; and (iv) what they think the results mean in the Discussion.

In turn, each basic section addresses several topics, and may be divided into subsections (Table 1 ). In the Introduction, the authors should explain the rationale and background to the study. What is the research question, and why is it important to ask it? While it is neither necessary nor desirable to provide a full-blown review of the literature as a prelude to the study, it is helpful to situate the study within some larger field of enquiry. The research question should always be spelled out, and not merely left for the reader to guess.

Typical structure of a research paper

The Methods section should provide the readers with sufficient detail about the study methods to be able to reproduce the study if so desired. Thus, this section should be specific, concrete, technical, and fairly detailed. The study setting, the sampling strategy used, instruments, data collection methods, and analysis strategies should be described. In the case of qualitative research studies, it is also useful to tell the reader which research tradition the study utilizes and to link the choice of methodological strategies with the research goals [ 3 ].

The Results section is typically fairly straightforward and factual. All results that relate to the research question should be given in detail, including simple counts and percentages. Resist the temptation to demonstrate analytic ability and the richness of the dataset by providing numerous tables of non-essential results.

The Discussion section allows the most freedom. This is why the Discussion is the most difficult to write, and is often the weakest part of a paper. Structured Discussion sections have been proposed by some journal editors [ 4 ]. While strict adherence to such rules may not be necessary, following a plan such as that proposed in Table 1 may help the novice writer stay on track.

References should be used wisely. Key assertions should be referenced, as well as the methods and instruments used. However, unless the paper is a comprehensive review of a topic, there is no need to be exhaustive. Also, references to unpublished work, to documents in the grey literature (technical reports), or to any source that the reader will have difficulty finding or understanding should be avoided.

Having the structure of the paper in place is a good start. However, there are many details that have to be attended to while writing. An obvious recommendation is to read, and follow, the instructions to authors published by the journal (typically found on the journal’s website). Another concerns non-native writers of English: do have a native speaker edit the manuscript. A paper usually goes through several drafts before it is submitted. When revising a paper, it is useful to keep an eye out for the most common mistakes (Table 2 ). If you avoid all those, your paper should be in good shape.

Common mistakes seen in manuscripts submitted to this journal

Huth EJ . How to Write and Publish Papers in the Medical Sciences , 2nd edition. Baltimore, MD: Williams & Wilkins, 1990 .

Browner WS . Publishing and Presenting Clinical Research . Baltimore, MD: Lippincott, Williams & Wilkins, 1999 .

Devers KJ , Frankel RM. Getting qualitative research published. Educ Health 2001 ; 14 : 109 –117.

Docherty M , Smith R. The case for structuring the discussion of scientific papers. Br Med J 1999 ; 318 : 1224 –1225.

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Welcome to the PLOS Writing Center

Your source for scientific writing & publishing essentials.

A collection of free, practical guides and hands-on resources for authors looking to improve their scientific publishing skillset.

ARTICLE-WRITING ESSENTIALS

Your title is the first thing anyone who reads your article is going to see, and for many it will be where they stop reading. Learn how to write a title that helps readers find your article, draws your audience in and sets the stage for your research!

The abstract is your chance to let your readers know what they can expect from your article. Learn how to write a clear, and concise abstract that will keep your audience reading.

A clear methods section impacts editorial evaluation and readers’ understanding, and is also the backbone of transparency and replicability. Learn what to include in your methods section, and how much detail is appropriate.

In many fields, a statistical analysis forms the heart of both the methods and results sections of a manuscript. Learn how to report statistical analyses, and what other context is important for publication success and future reproducibility.

The discussion section contains the results and outcomes of a study. An effective discussion informs readers what can be learned from your experiment and provides context for the results.

Ensuring your manuscript is well-written makes it easier for editors, reviewers and readers to understand your work. Avoiding language errors can help accelerate review and minimize delays in the publication of your research.

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Delivered to your inbox every two weeks, the Writing Toolbox features practical advice and tools you can use to prepare a research manuscript for submission success and build your scientific writing skillset. 

Discover how to navigate the peer review and publishing process, beyond writing your article.

The path to publication can be unsettling when you’re unsure what’s happening with your paper. Learn about staple journal workflows to see the detailed steps required for ensuring a rigorous and ethical publication.

Reputable journals screen for ethics at submission—and inability to pass ethics checks is one of the most common reasons for rejection. Unfortunately, once a study has begun, it’s often too late to secure the requisite ethical reviews and clearances. Learn how to prepare for publication success by ensuring your study meets all ethical requirements before work begins.

From preregistration, to preprints, to publication—learn how and when to share your study.

How you store your data matters. Even after you publish your article, your data needs to be accessible and useable for the long term so that other researchers can continue building on your work. Good data management practices make your data discoverable and easy to use, promote a strong foundation for reproducibility and increase your likelihood of citations.

You’ve just spent months completing your study, writing up the results and submitting to your top-choice journal. Now the feedback is in and it’s time to revise. Set out a clear plan for your response to keep yourself on-track and ensure edits don’t fall through the cracks.

There’s a lot to consider when deciding where to submit your work. Learn how to choose a journal that will help your study reach its audience, while reflecting your values as a researcher.

Are you actively preparing a submission for a PLOS journal? Select the relevant journal below for more detailed guidelines. 

How to Write an Article  

Share the lessons of the Writing Center in a live, interactive training.

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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.

PublishingState.com

How to write a research article

How to Write a Research Article

Table of contents, introduction, strategies for selecting a research topic, conducting preliminary research, conducting thorough research and literature review, the vital role of literature reviews, incorporating quality sources, examples of strong thesis statements, refining and revising the thesis statement, structuring the research article: creating an outline, writing the initial draft of the research article, the importance of an engaging introduction, framing the research question and context, creating an opening hook, developing a persuasive body of text.

Research articles are the primary means of communicating new research findings in academia. They advance knowledge within a field by presenting original studies that address research gaps or questions. Understanding how to structure and write a compelling research article properly is thus an essential skill for scholars.

The main purpose of a research article is to disseminate new data, theories, or perspectives on a topic to the scholarly community. By detailing the methodology and results of an original study, research articles validate the findings and allow others to evaluate, build upon, replicate, or refute the research. Strong research articles withstand rigorous peer review and add to the cumulative knowledge of a discipline.

Beyond communicating information, research articles also play a key role in furthering an academic career. Having research published, especially in prestigious journals, can bolster a scholar’s reputation and influence. The number and impact of research articles are often considered in hiring, promotion, and tenure decisions as measures of research productivity and contribution to one’s field.

While formats vary across disciplines, most research articles contain the same key sections: an introduction to frame the research topic and questions, a comprehensive review of relevant literature, an explanation of the methodology used in the study, a presentation of the results and data analysis, and a discussion of the implications of the findings.

Organizing the article clearly around these standard sections makes the research process and findings more accessible to readers. Additional elements like an abstract summarizing the article, properly formatted references, and well-labeled tables, graphs, and appendices characterize a well-structured article.

Employing clear, formal, and discipline-specific language is critical for accurately conveying complex information to an academic audience. Terminology and phrasing should allow readers to grasp the research design and results readily.

Likewise, research articles demand meticulous attention to detail regarding citations, data analysis, and the accurate representation of findings. Any errors or misleading statements threaten the validity of the research. Adhering to scholarly ethics in writing research articles is paramount.

By mastering the foundations of strong research article writing, including structure, language use, and integrity, scholars can effectively share their work while advancing knowledge for the betterment of their discipline.

Choosing a Compelling Research Topic

Selecting an intriguing and meaningful research topic is a crucial first step in crafting an impactful research article. The topic sets the foundation for the entire study, so researchers must choose wisely to align with their academic interests and goals. By conducting thorough preliminary research and identifying gaps in existing literature, scholars can refine their topics to offer original contributions.

When selecting a compelling research topic, choosing an area that genuinely captivates your curiosity and connects with your broader scholarly ambitions is crucial. Reflect on your academic journey thus far—what subjects or questions have consistently captured your attention?

Leveraging existing passions will sustain motivation during the lengthy research process. It also helps to assess your resources and access to data sources relevant to potential topics. A fruitful research topic aligns with available materials to facilitate a smooth investigation. Discuss prospective topics with mentors and colleagues to gain valuable outside perspectives on viability and contribution.

After identifying a broad domain of interest, delving into preliminary research helps sharpen the focus of your chosen topic. A thoughtful topic reflects careful consideration of existing literature to pinpoint meaningful gaps prime for exploration. Scan recent publications to assess the current state of research related to your initial area of interest.

Take notes on relevant theories, landmark studies, open questions, and methodological approaches. Gradually narrow down the scope of your topic as patterns emerge in the literature. Conducting preliminary research ensures your final topic offers an original perspective and advances scholarly understanding in your field.

For research to have a lasting impact, the topic must strive to enhance, expand upon, or challenge current academic discourse in some capacity. Seek out aspects of your broader research area that seem understudied or reflect oversights in dominant theoretical models. Consider diverging from mainstream topics to give voice to marginalized viewpoints.

Innovative topics that shift existing paradigms can profoundly influence how scholars approach certain phenomena. In applied fields, topics addressing unsolved real-world problems demonstrate great social value. Ultimately, selecting a research topic that meaningfully addresses gaps in understanding or practice will amplify the potential contributions of your work.

Comprehensive research is a critical first step in writing a strong research article. This involves gathering relevant sources, data, and background information to situate your study within the existing scholarly discourse. Here are some tips for conducting effective research:

  • Cast a wide net: Search top journal databases , libraries, and reputable journals for a broad range of sources related to your topic. Look for seminal works, recent studies, relevant theories and frameworks, and gaps in the literature. Take detailed notes and keep track of bibliographic information for all sources you review.
  • Refine and filter: Once you have a broad base of sources, begin evaluating their credibility, relevance, and significance to your specific research aims. Synthesize connections between sources and summarize the most timely, salient, and credible references to ground your study.
  • Critically analyze: Read and analyze your sources actively and critically. Look for limitations, biases, assumptions, and gaps that may inform your research. Take detailed notes on the content and the research methodologies used to inform your methods.

A literature review involves synthesizing previous research related to your topic or question. An effective literature review:

  • Demonstrates your knowledge of the field and seminal works
  • Highlights important theories, models, and frameworks
  • Reveals gaps, limitations, biases, or areas in need of further inquiry
  • Identifies your study within the ongoing scholarly conversation

Use your review of existing literature to provide context and rationale for your research aims, questions, and hypotheses. Refer to key sources in your literature review throughout your article to ground your ideas in established knowledge.

When writing your research article, thoughtfully incorporate evidence from credible primary and secondary sources. Use citations judiciously to substantiate claims, frame ideas, or provide context. Integrate visuals, statistics, and direct quotes seamlessly to enhance analysis without over-relying on external sources. Synthesize information from quality sources to contribute uniquely to the scholarly discourse.

Crafting a Strong Thesis Statement

A well-formulated thesis statement is the foundation of a compelling research article. It clearly defines the central argument or premise of the study while providing direction for the analysis and discussion to follow. An effective thesis statement generally has several key characteristics:

  • It concisely states the main claim or assertion: A strong thesis statement delineates the specific argument or claim in concise, precise language rather than overly broad or vague. This helps focus the scope of the research by establishing parameters for what will and will not be examined.
  • It introduces the key concepts or variables being studied: The terms, ideas, relationships, and phenomena that will form the crux of the analysis should be incorporated into the thesis statement. This orientates readers to the key variables and concepts underpinning the research.
  • It implies a cause-and-effect relationship: A compelling thesis suggests a causal link between concepts or variables rather than simply stating a fact. This causal relationship generally forms the basis for the arguments elaborated on in the body of the research article.
  • It can be tested or explored through analysis: An effective thesis provides a hypothesis or claim that can be supported or refuted through evidence-based analysis. This engages readers by suggesting the research will yield intriguing revelations.

Here are some examples of precisely worded thesis statements:

  • The implementation of stringent gun control policies in developed nations correlates with lower homicide rates over ten years.
  • Public health campaigns that use positive emotional framing are more effective at changing high-risk behavioral patterns than those relying on fear or negative messaging.
  • Cryptocurrency adoption has grown rapidly in developing countries with high inflation rates and unstable fiat currencies.

It is important to continually revisit and revise the thesis statement throughout the writing process. As the arguments and analysis evolve, the main claim may need adjustment to reflect the research content accurately. Ask the following questions when revising:

  • Is my central assertion clearly distinguished from other claims being made?
  • Does it establish an arguable premise that lends itself to testing and exploration?
  • Is it specific enough to determine the scope and limits of my analysis?
  • Does it imply a causal relationship that forms the basis of my arguments?

Refining the thesis statement in this manner is crucial for maintaining the coherence and direction of the research article.

A clear outline is crucial for organizing ideas and structuring a compelling research article. An outline serves as a roadmap that guides the writing process from start to finish. Here are some key tips for crafting an effective outline:

  • Use the standard framework: Most research articles follow a standard format consisting of an introduction, methods, results, and discussion/conclusion. When outlining, map out the key points to cover in each of these sections. Consider what background context needs to be provided, how to summarize the study design and procedures, what data/findings to highlight, and what conclusions can be drawn.
  • Organize ideas logically: Ensure your outline has a logical flow of ideas by grouping related points under headings and subheadings. Use numbering/bullet points to structure sequences. Logical organization strengthens the arguments made and enhances readability.
  • Flesh out details under each main point: Under each heading, include 2-3 key points that support that topic. Adding some detail at the outlining stage helps to map out the content and prevents important points from being missed later. Leave room for expansion when drafting the full article.
  • Pay attention to transitions between sections: When outlining, consider how to transition smoothly between different article sections. Think about sentences that conclude one section and introduce the next. Well-connected sections improve flow.

An organized, thoughtful outline lays the groundwork for an impactful research article. Allowing time for effective planning and structuring of ideas pays dividends when sitting down to write the first draft.

Drafting a research article’s initial version can be challenging. Breaking it down into manageable steps makes the writing process more approachable. Here is some practical advice on how to get started:

  • Brainstorm and outline first: Before writing full paragraphs, brainstorm key ideas and organize them into an outline. An outline provides a roadmap that makes the initial drafting stage far less intimidating. Use the research article’s thesis and main arguments to structure the outline.
  • Write without self-editing: The first draft should focus on getting ideas down on paper without self-editing along the way. Self-editing can bog writers down as they second-guess word choice and phrasing. Instead, make the first draft about expressing core ideas, even if the writing is rough. Resist the urge to obsess over small details at this stage.
  • Incorporate supporting evidence: While drafting the research article’s first version, bring evidence and analysis to back up key claims. This supporting information will later be crucial for constructing a persuasive argument. Sources to draw from include research data, relevant theories, expert opinions, statistics, case studies, and real-world examples. Build the first draft around this evidence.

By following these helpful tips on brainstorming, avoiding editing pitfalls, and substantiating ideas, scholars can overcome writer’s block and make steady progress on that all-important first draft. The key is to break the intimidating writing process down into smaller, more manageable steps.

Crafting a Captivating Introduction

The introduction is the first thing readers see when they open a research article. As such, it plays a pivotal role in capturing attention and drawing readers into the piece. An engaging introduction piques curiosity, establishes relevance, and motivates readers to continue reading. This section offers strategies for crafting an introduction that hooks readers and compels them to dive into the research.

The introduction sets the stage for the entire research article. A dull or unfocused introduction can cause readers to lose interest quickly. On the other hand, an intriguing introduction sparks curiosity and entices readers to learn more. Key reasons an engaging introduction matters include:

  • It is often the first section readers see, so it must capture attention immediately.
  • It shapes initial impressions about the research quality and importance.
  • An interesting hook encourages readers to invest time in reading further.

An engaging introduction gives a distinct edge in a sea of academic articles competing for readers’ limited time.

The introduction should frame the research question and establish an overall context for readers. Strategies to accomplish this include:

  • Succinctly state the research problem or gap in current knowledge.
  • Articulate the purpose and nature of the study.
  • Provide relevant background details so readers understand the research context.
  • Briefly discuss existing literature and how this study builds on or departs from it.

Framing the research clearly and contextualized allows readers to grasp its purpose and significance.

An opening hook instantly intrigues readers. Effective hook types include:

  • An interesting anecdote or story
  • A thought-provoking question
  • An attention-grabbing statistic
  • A striking quote
  • A paradox or unexpected contrast

The tone should entice further reading without sensationalism. The goal is to stimulate the reader’s interest in learning more, not dramatic exaggeration.

The body of a research article is where authors present their key arguments, analysis, evidence, and findings. Structuring this section effectively is crucial for conveying complex ideas persuasively. Here are some tips:

  • Structuring and developing the body: Organize the body into logical sections that flow well together. Each section should focus on one main idea or finding that supports your thesis. Use transition sentences between paragraphs and sections to guide readers. When presenting data or evidence, properly contextualize figures and tables so readers understand how they fit your arguments.
  • Use clear and coherent language: Write clearly and precisely, defining key terms helpful. Break down complex concepts into understandable explanations that general audiences can comprehend. Use plain, straightforward language instead of overly academic or technical jargon. Summarize statistical analysis and results in an accessible way for those less familiar with the methodologies.
  • Integrate citations, data, and visuals: Use in-text citations to support statements with reputable sources. Quote or paraphrase subject matter experts where appropriate. Include properly formatted references. Supplement arguments by incorporating relevant data such as statistics, survey results, or experimental findings. Visualize data through graphs, charts, diagrams, or images when helpful for reader comprehension. The judicious use of citations, data, and graphics reinforces the credibility of your analysis.

By keeping these tips in mind when structuring the body of your research article, you can craft a persuasive text that conveys key ideas to convince readers of your arguments and conclusions.

We have delved into how to write a research article. Crafting a research article is a meticulous process that requires a clear understanding of the subject matter, a structured approach, and an unwavering commitment to scholarly standards. Starting with a comprehensive literature review, researchers set the stage for presenting new findings within the context of existing knowledge.

How to write a research article

Formulating research questions and hypotheses guides the investigative process, ensuring the study has direction and purpose. Methodological rigor in designing and executing research ensures that the results are reliable and valid, providing a sound basis for analysis and interpretation. The heart of the research article lies in the Results and Discussion sections, where data are presented in a manner that is both transparent and enlightening, and insights are drawn with a careful balance between confidence in the findings and humility about their limitations. Throughout the article, ethical considerations should be paramount, with honesty and integrity underpinning every aspect of the research and writing process. Effective communication is key; the writing should be clear and concise, making complex information accessible to a broad audience while avoiding oversimplification. Visual elements like tables, graphs, and figures can greatly enhance the readability and impact of the article, providing intuitive entry points into the dense material. The Conclusion then serves as a compass, pointing out the research implications, its relevance to the field, the potential for future inquiry, and the broader societal impact. Crafting a research article is both an art and a science, and upon completion, it represents a valuable contribution to the collective understanding of our world. Whether it confirms, challenges, or expands upon what is known, a well-written research article ensures that knowledge continues to increase, fostering continued exploration and dialogue in the pursuit of truth and understanding.

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  • How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

  • Search for relevant literature
  • Evaluate sources
  • Identify themes, debates, and gaps
  • Outline the structure
  • Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

  • Quick Run-through
  • Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

  • Demonstrate your familiarity with the topic and its scholarly context
  • Develop a theoretical framework and methodology for your research
  • Position your work in relation to other researchers and theorists
  • Show how your research addresses a gap or contributes to a debate
  • Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

Literature review guide

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Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

  • Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
  • Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
  • Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
  • Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

  • Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
  • Body image, self-perception, self-esteem, mental health
  • Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

  • Your university’s library catalogue
  • Google Scholar
  • Project Muse (humanities and social sciences)
  • Medline (life sciences and biomedicine)
  • EconLit (economics)
  • Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

  • What question or problem is the author addressing?
  • What are the key concepts and how are they defined?
  • What are the key theories, models, and methods?
  • Does the research use established frameworks or take an innovative approach?
  • What are the results and conclusions of the study?
  • How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
  • What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

  • Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
  • Themes: what questions or concepts recur across the literature?
  • Debates, conflicts and contradictions: where do sources disagree?
  • Pivotal publications: are there any influential theories or studies that changed the direction of the field?
  • Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

  • Most research has focused on young women.
  • There is an increasing interest in the visual aspects of social media.
  • But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

  • Look at what results have emerged in qualitative versus quantitative research
  • Discuss how the topic has been approached by empirical versus theoretical scholarship
  • Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

  • Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
  • Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
  • Critically evaluate: mention the strengths and weaknesses of your sources
  • Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

  • Sampling methods
  • Simple random sampling
  • Stratified sampling
  • Cluster sampling
  • Likert scales
  • Reproducibility

 Statistics

  • Null hypothesis
  • Statistical power
  • Probability distribution
  • Effect size
  • Poisson distribution

Research bias

  • Optimism bias
  • Cognitive bias
  • Implicit bias
  • Hawthorne effect
  • Anchoring bias
  • Explicit bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

  • To familiarize yourself with the current state of knowledge on your topic
  • To ensure that you’re not just repeating what others have already done
  • To identify gaps in knowledge and unresolved problems that your research can address
  • To develop your theoretical framework and methodology
  • To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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How to Write a Research Article: A Comprehensive Guide

Research Article

Writing a Research Article can be an unbelievably daunting task, but it is a vital skill for any researcher or academic. This blog post intends to provide a detailed instruction on how to create a Research Paper. It will delve into the crucial elements of a Research Article, including its format, various types, and how it differs from a Research Paper.   By following the steps provided, you will get vital insights on how to write a well-structured and successful research piece. Whether you are a student, researcher, or professional writer, this article will help you understand the key components required to produce a high-quality Research article. 

Table of Content

What is a research article .

A Research Article is a written document that represents the findings of original and authentic research. It is typically published in a peer-reviewed academic journal and is used to communicate new knowledge and ideas to the research community. Research Articles are often used as a basis for further research and are an essential part of scientific discourse. 

Components of a Research Article 

A Research Article typically consists of the following components: 

  • Abstract – A summary of the research article, including the research question, methodology, results, and conclusion. 
  • Introduction – This is an explanation of the purpose behind conducting the study, and a summary of the methodology adopted for the research. This section serves as the foundation of the research article and provides the reader with a contextual background for understanding the study’s objectives and methodology. It basically outlines the reason for conducting the research and provides a glimpse of the approach that will be used to answer the research question. 
  • Literature Review – This section entails a comprehensive examination of the relevant literature that offers a framework for the research question and presents the existing knowledge on the subject. 
  • Methodology – This section explains the study’s research design, data gathering, and analysis methods.  
  • Results – A description of the findings of the research. 
  • Discussion – An interpretation of the results, including their significance and implications, as well as a discussion of the limitations of the study. 
  • Conclusion – A summary of the research findings, their implications, and recommendations for future research. 

Research Article Format 

A Research Article typically follows a standard format including: 

  • Title : A clear and concise title that accurately reflects the research question. 
  • Authors : A list of authors who contributed to the research. 
  • Affiliations : The institutions or organizations that the authors are affiliated with. 
  • Abstract : A summary of the research article. 
  • Keywords : A list of keywords that describe the research topic. 
  • Introduction : A fine background of the research question and a complete overview of the methodology used. 
  • Literature Review : A review of the relevant literature. 
  • Methodology : A description of the research design, data collection, and analysis methods used. 
  • Results : A description of the findings of the research. 
  • Discussion : An interpretation of the results and their implications, as well as a discussion of the limitations of the study. 
  • Conclusion: A summary of the research findings and recommendations for future research. 

research article

Types of Research Articles 

There are several types of research articles including: 

  • Original Research Articles : These are articles that report on original research. 
  • Review articles : These are articles that summarize and synthesize the findings of existing research. 
  • Case studies : These are articles that describe and analyze a specific case or cases. 
  • Short communications : These are brief articles that report on original research. 

Research Article vs Research Paper 

While research articles and Research Papers are often used interchangeably, there are some differences between the two. A research article is typically a formal, peer-reviewed document that presents the findings of original research. A research paper, on the other hand, is a broader term that can refer to any written work that presents the findings of research, including essays, reports, and dissertations. 

Example of a Research Article 

Here is an example of a research article: 

  • Title: The effects of exercise on mental health in older adults.
  • Abstract :  This study investigated the effects of exercise on mental health in older adults. A sample of 100 participants aged 65 and over were randomly assigned to an exercise or control group. The exercise group participated in a 12-week exercise program, while the control group received no intervention. The results showed that the exercise group had significantly lower levels of depression and anxiety compared to the control group. Additionally, the exercise group reported higher levels of well-being and satisfaction with life. These findings suggest that exercise can be an effective intervention for improving mental health in older adults. 
  • Introduction:   Mental health issues such as depression and anxiety are common among older adults and can have a significant impact on quality of life. Exercise has been shown to have numerous physical health benefits, but its effects on mental health in older adults are less clear. This study aimed to investigate the effects of exercise on mental health outcomes in older adults. 
  • Literature Review:   Previous research has suggested that exercise can improve mental health outcomes in older adults. For example, a study by Mather et al. (2016) found that a 12-week exercise program resulted in significant improvements in depression and anxiety in a sample of older adults. Similarly, a meta-analysis by Smith et al. (2018) found that exercise interventions were associated with improvements in various mental health outcomes, including depression and anxiety, in older adults. 
  • Methodology:   A total of 100 participants aged 65 and over were recruited from a community centre and randomly assigned to an exercise or control group. The exercise group participated in a 12-week exercise program consisting of three 60-minute sessions per week. The program included a combination of aerobic and resistance exercises. The control group received no intervention. Both groups completed measures of depression, anxiety, well-being, and satisfaction with life at baseline and at the end of the 12-week period.
  • Results:   The results showed that the exercise group had significantly lower levels of depression and anxiety compared to the control group at the end of the 12-week period. Additionally, the exercise group reported higher levels of well-being and satisfaction with life. There were no significant differences between the groups in terms of physical health outcomes.  
  • Discussion:   These findings provide support for the use of exercise as an intervention for improving mental health outcomes in older adults. The results suggest that a 12-week exercise program can lead to significant reductions in depression and anxiety, and improvements in well-being and satisfaction with life. It is important to note, however, that the study had some limitations, including a relatively small sample size and a lack of long-term follow-up. Further research is needed to confirm these findings and explore the potential mechanisms underlying the effects of exercise on mental health in older adults. 

This study provides evidence that exercise can be an effective intervention for improving mental health outcomes in older adults. Given the high prevalence of mental health issues in this population, exercise programs may be an important tool for promoting well-being and improving quality of life. Further research is needed to determine the optimal duration, intensity, and type of exercise for improving mental health outcomes in older adults. 

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Research and teaching writing

  • Published: 12 July 2021
  • Volume 34 , pages 1613–1621, ( 2021 )

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  • Steve Graham 1 , 2 &
  • Rui A. Alves 3  

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Writing is an essential but complex skill that students must master if they are to take full advantage of educational, occupational, and civic responsibilities. Schools, and the teachers who work in them, are tasked with teaching students how to write. Knowledge about how to teach writing can be obtained from many different sources, including one’s experience teaching or being taught to write, observing others teach writing, and advise offered by writing experts. It is difficult to determine if much of the lore teachers acquire through these methods are effective, generalizable, or reliable unless they are scientifically tested. This special issue of Reading & Writing includes 11 writing intervention studies conducted primarily with students in the elementary grades. It provides important new information on evidence-based writing practices.

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There are many different ways that teachers can learn about how to teach writing. One way of acquiring such knowledge is by teaching this skill to others. As teachers apply different instructional procedures, they form judgments about the value and efficacy of these practices. In essence, they learn by doing (Graham, 2018 ).

A second way teachers learn about how to teach writing is by observing others and learning from them (Graham, 2018 ). Teachers likely remember some of the instructional methods used by those who taught them to write (e.g., teachers, mentors, parents, guardians, and peers). They may in turn adopt some of these practices when they teach their own students. This may be particularly true for instructional practices they considered effective.

Teachers can gain additional insight into teaching writing by observing and absorbing insights offered by others who have taught writing or studied how to teach it. This includes knowledge acquired from instructors teaching literacy and writing courses as well as experts offering advice on writing instruction at conferences, through workshops, podcasts, or other forms of information sharing. Teachers may also learn about teaching writing by discussing this topic with their peers or observing them as they teach writing.

A third source of knowledge that teachers can access are published materials about how to teach writing. This includes textbooks and articles on the subject, curriculum guides, commercial materials, and position statements from professional organizations to provide just a few examples. These resources can further involve digital sources such as videos demonstrating how to apply specific writing procedures, experts promoting specific teaching techniques, or web sites devoted to writing instruction.

The concern

Given all of the possible knowledge sources teachers can access or experience, there is an abundance of information, recommendations, and teaching materials on how to teach writing that is available to teachers. This blessing experiences at least one serious limitation. Too often, there is limited, circumscribed, or no evidence that the proffered advice, know-how, or wisdom works. There are many claims about what is effective, but too little proof. Unfortunately, this observation applies to much of the lore that teachers acquire about writing instruction.

Teaching lore mainly involves writing practices teachers experienced when they learned to write, instructional practices teachers develop and apply with their students, writing practices they see other teachers apply, and teaching practices promoted by experts (Graham & Harris, 2014 ). While we have no doubt that teachers and experts possess considerable knowledge and insight about how to teach writing, basing the teaching of this complex skill on such lore alone is risky.

Why is this the case? One reason is that it is difficult to determine which aspects of teaching lore are valid. For example, there are many things a teacher does while teaching writing. When their students’ writing improves, they may attribute this change to specific procedures they applied. While this evaluation may be correct, it is also possible that this judgment is incorrect or only applies to some students or to a procedure in a given context.

Teachers are not the only ones who can succumb to such selective bias. Specific teaching lore promoted by writing experts are also susceptible to misinterpretation in terms of their effectiveness. To illustrate, writing experts can overestimate the impact of favored instructional methods, forming judgments consistent with their philosophical views on writing development or instruction. For instance, proponents of the whole language approach to learning to read and write believed that writing and reading develop naturally just like oral language (Goodman, 1992 ). Consistent with these beliefs, they championed an approach to literacy instruction based on the use of informal teaching methods (e.g., reading and writing for real purposes), while at the same time deemphasizing explicitly and systematically teaching students foundational writing and reading skills and strategies (Graham & Harris, 1997 ). Instead, these skills are only taught when the need arises, mostly through short mini-lessons. Advocates for whole language frequently promoted the effectiveness of this two-pronged approach (Begeron, 1990 ), without providing much in the way of empirical evidence that it was effective, or perhaps even more importantly, that it was as effective as other alternatives such as reading and writing programs that emphasized reading and writing for real purposes, coupled with systematic and explicit skills and strategy instruction (Graham & Harris, 1994 ). Even for fundamental writing skills such as spelling, there is considerable evidence that both informal teaching and explicit instruction are effective (Graham, 2000 ; Graham & Santangelo, 2014 ), while whole language approaches are fundamentally misguided about what is written language (Liberman, 1999 ).

Whole language is not the only approach to teaching writing that has suffered from questionable claims about its effectiveness. Even the venerable Donald Graves was guilty of this to some degree with the process approach to writing that he supported and advocated (see Smagorinski, 1987 ). The evidence he offered in support of his favored approach to teaching writing relied in large part on testimonials and exemplar writing of selected students, presenting a potentially overly optimistic assessment of this approach. This is not to say that the process approach is ineffective, as there is now considerable empirical evidence supporting the opposite conclusion (Sandmel & Graham, 2011 ). Instead, this example illustrates that adopting whole cloth even highly popular and widely used teaching lore without careful consideration of its effectiveness and the evidence available to support it can be risky. The lack of evidence or the type of evidence provided can make it extremely difficult for teachers or other interested parties to determine if the testimonials or evidence used to support specific teaching lore in writing are representative or atypical.

A third issue that makes some teaching lore risky is that it may be based on the experience of a single or a very small number of teachers. As an example, this can occur for knowledge a teacher acquires as a result of his or her experience teaching writing. The teaching practice(s) may in fact be effective for the students in this teacher’s classroom, but they may not be effective when applied by another teacher or with different students. Until this proposition is tested, there is no way to determine if this teaching lore will produce reliable results when applied more broadly.

As these concerns demonstrate, the validity, generalizability, and replicability of instructional practices based on teaching lore are uncertain. This is not to devalue what teachers or experts know, but to demonstrate the limits of this knowledge.

Evidence-based writing practices

The concerns about the value of teaching lore raised above raises the question: How should the structure and details of writing instruction be determined? The solution that we recommend is to take an evidence-based practice approach to both enhance teachers’ knowledge and develop writing instruction. Starting with medicine in the 1990s, and spreading quickly to psychology, informational science, business, education, and a host of other disciplines, this movement promoted the idea that practitioners in a field should apply the best scientific evidence available to make informed and judicious decisions for their clients (Sackett et al., 1996 ). The basic assumption underlying this approach is that the findings from research can positively impact practice. The evidence-based practice movement was a reaction to practitioners basing what they did almost strictly on tradition and lore, without scientific evidence to validate it.

One reason why this represents a positive step forward in education and the teaching of writing is that instructional practices based on high quality intervention research addresses the three issues of concern we raised about teaching lore. First, high quality intervention studies address the issue of validity. They are designed specifically to isolate the effects of a specific instructional practice or set of instructional practices. They provide systematically gathered evidence on whether the instructional practices tested produced the desired impact. They further apply methodological procedures to rule out alternative explanations for observed effects. Second, high quality intervention studies address issues of generalizability by describing the participants and the context in which the practice was applied, and by using statistical procedures to determine the confidence that can be placed in specific findings. Three, they address the issue of replicability, as the replication of effects across multiple situations is the hall mark of scientific testing (Graham & Harris, 2014 ).

Another reason why the evidence-based approach represents a positive step forward in terms of teaching writing is that the evidence gathered from high quality intervention studies can provide a general set of guidelines for designing an effective writing program. Graham et al. ( 2016 ) created such a roadmap by drawing on three sources of scientific evidence: true-and quasi- experimental writing intervention studies, single-case design studies, and qualitative studies of how exceptional literacy teachers taught writing (see also Graham & Harris, 2018 ). They indicated that the scientific evidence from these three sources supports the development of writing programs that include the following. Students write frequently. They are supported by teachers and peers as they write. Essential writing skills, strategies, and knowledge are taught. Students use word processors and other twenty-first century tools to write. Writing occurs in a positive and motivating environment. Writing is used to support learning. Based on several recent meta-analyses of high quality intervention studies (Graham, et al., 2018a , b ; Graham, et al., 2018a , b ), Graham now recommends that the evidence also supports connecting writing and reading instruction (Graham, 2019 , 2020 ).

A third reason why the evidence-based approach is a positive development is that it provides teachers with a variety of techniques for teaching writing that have been shown to be effective in other teachers’ classes and in multiple situations. While this does not guarantee that a specific evidence-based practices is effective in all situations, a highly unlikely proposition for any writing practice, it does provide teachers with instructional procedures with a proven track record. This includes, but is not limited to (Graham & Harris, 2018 ; Graham et al., 2016 ):

Setting goals for writing.

Teaching general as well as genre-specific strategies for planning, revising, editing, and regulating the writing process. Engaging students in prewriting practices for gathering, organizing, and evaluation possible writing contents and plans.

Teaching sentence construction skills with sentence-combining procedures.

Providing students with feedback about their writing and their progress learning new writing skills.

Teaching handwriting, spelling, and typing.

Increasing how much students write; analyzing and emulating model texts.

Teaching vocabulary for writing.

Creating routines for students to help each other as they write.

Putting into place procedures for enhancing motivation.

Teaching paragraph writing skills.

Employing technology such as word processing that makes it easier to write.

It is also important to realize that an evidence-based approach to writing does not mean that teachers should abandon the hard-earned knowledge they have acquired through their experiences as teachers or learners. The evidence-based movement emphasizes that teachers contextualize knowledge about teaching writing acquired through research with their own knowledge about their students, the context in which they work, and what they know about writing and teaching it (Graham et al., 2016 ). When applying instructional practices acquired through research as well as teaching lore, we recommend that teachers weigh the benefits, limitations, and possible harm that might ensue as a consequence of applying any teaching procedure. Once a decision is made to apply a specific practice, it is advisable to monitor its effectiveness and make adjustments as needed.

Finally, while the scientific testing of writing practices has provided considerable insight into how writing can be taught effectively, it is not broad, deep, or rich enough to tell us all we need to know about teaching writing. It is highly unlikely that this will ever be the case. We operate on the principle that there is no single best method for teaching writing to all students, nor is it likely that science will provide us with formulas to prescribe exactly how writing should be taught to each student individually. Writing, learning, children, and the contexts in which they operate are just too complex to make this a likely consequence of the evidence-based movement. As a result, we believe that the best writing instruction will be provided by teachers who apply evidence-based practices in conjunction with the best knowledge they have acquired as teachers and learners, using each of these forms of knowledge in an intelligent, judicious, and critical manner.

Over time, we anticipate that evidence-based practices will play an ever increasing role in the process described above. This is inevitable as our knowledge about evidence-based writing practices expands. This brings us to the purpose of this special issue of Reading & Writing: An Interdisciplinary Journal . This special issue presents 11 writing intervention studies focusing almost exclusively with students in the elementary grades. These studies were conducted in Europe and the United States, and they replicate and extend prior research conducted with young developing writers.

The special issue

Perhaps the most tested writing instructional practice of all time, and the one yielding the largest effects sizes (Graham et al., 2013 ), is the Self-regulated Strategy Development (SRSD) model developed by Karen Harris (see Harris et al., 2008 for a description of this approach). Several studies in the current special issue tested specific iterations of the use of the SRSD model as a means for teaching writing to elementary grade students. Collins and her colleagues examined the effectiveness of teaching third grade students in the United States task specific strategies for planning and drafting expository essays using information from social studies text using this model. This instruction enhanced the quality of students’ texts and resulted in improvement on a norm-referenced measure of writing where students identified their favorite game and provided reasons why this was the case.

In a second SRSD study conducted with second and third grade children in Spain, Salas and her colleagues examined if teaching planning and drafting strategies for writing an opinion essay was equally effective with children from more and less disadvantaged backgrounds. SRSD was equally effective in improving the opinion writing of children from both backgrounds, but carryover effects to reading comprehension (a skill not taught in this study) only occurred for students from less disadvantaged backgrounds.

A third study by Rosario and his colleagues involved a secondary analysis of data from an investigation in Portugal where third grade students were taught to write narratives using SRSD procedures and a story writing tool they developed. Their reanalysis focused on students experiencing difficulties learning to write showing that they differed in their approach and perceptions of teacher feedback. The majority of these children were able to use the feedback provided by their teacher and viewed it as helpful.

A fourth investigation by Hebert and his colleagues taught fourth grade students in the United States to write informational text using five text structures (description, compare/contrast, sequence of events, problem–solution, and cause effect). While the authors did not indicate they used SRSD to teach these strategies, the teaching methods mirrored this approach. In any event, the instruction provided to these children enhanced how well they wrote all five of these different kinds of text. These effects, however, did not generalize to better reading performance.

Lopez and her colleagues in Spain examined three approaches to improving sixth grade students’ writing. Students in all three conditions were taught how to set communicative goals for their writing. Students in one treatment condition were taught a strategy for revising. Students in a second treatment condition observed a reader trying to comprehend a text and suggesting ways it might be improved. Control students continued with the goal setting procedures. Students in both treatment conditions improved their writing and revising skills more than control students, but there were no differences between these two treatments.

In another Spanish study conducted by Rodriguez-Malaga and colleagues, the impact of two different treatments on the writing of fourth grade students was examined. One treatment group learned how to set product goals for their writing, whereas the other writing treatment group learned how to set product goals and strategies for planning compare/contrast texts. Only the students in the product goal and planning strategy treatment evidenced improved writing when compared to control students.

Philippakos and Voggt examined the effectiveness of on-line practice-based professional development (PBPD) for teaching genre-based writing strategies. Eighty-four second grade teachers were randomly assigned to PBPD or a no-treatment control condition. Treatment teachers taught the genre-based writing strategies with high fidelity and rated PBPD positively. Even more importantly, their students writing evidenced greater improvement than the writing of students in control teachers’ classes.

Walter and her colleagues in England examined the effectiveness of two writing interventions, sentence combining and spelling instruction, with 7 to 10 year old children experiencing difficulties learning to write. As expected, sentence combining instruction improved sentence construction skills, but even more importantly, these researchers found that the degree of improvements in sentence writing was related to students’ initial sentence, spelling, and reading skills.

In another study focused on improving students’ sentence construction skills, Arfé and her colleagues in Italy examined the effectiveness of an oral language intervention to improve the sentence construction skills of fifth and tenth grade students. This oral treatment did enhance the sentence writing skills of the younger fifth grade students. This study provides needed evidence that interventions aimed at improving oral language skills transfer to writing.

Chung and his colleagues in the United States examined if sixth grade students’ writing can be improved through self-assessment, planning and goal setting, and self-reflection when they revised a timed, on-demand essay. These students as well as students in the control condition were also taught how to revise such an essay. Treatment students evidenced greater writing gains, and were more confident about their revising capabilities than control students.

Lastly, Graham and his colleagues in the United States examined if the revising behavior of fourth grade students experiencing difficulties with writing can be enhanced through the use of revising goals that focused attention on making substantive when revising stories (e.g., change the setting of the story). Applying such goals across four stories had a positive effect on the revising behavior of these students when these goals were not in effect, resulting in more text-level revisions, more revisions that changed the meaning of text, and more revisions rated as improving text.

The 11 intervention studies in this special issue of Reading & Writing are particularly noteworthy for several reasons. One, some of these studies ( n  = 4) concentrated on improving students’ skills in writing informational and expository text. This is an area that has not received enough attention in existing writing literature. Two, enhancing students’ revising was the goal of multiple studies ( n  = 4). Again, too little attention has been given to this topic with either younger or older students. Three, it was especially gratifying to see that a pair of studies examined how to enhance sentence writing skills. This has been a neglected area of writing research since the 1980s. Four, multiple studies focused on improving the writing of students who experienced difficulties learning to write ( n  = 3). This is an area where we need much more research if we are to maximize these students’ writing success. Finally, more than half of the studies in this special issue ( n  = 6) were conducted in Europe, with the other half conducted in the United States. It is important to examine if specific writing treatments are effective in different social, cultural, political, institutional, and historical context (Graham, 2018 ), as was done with the four studies that applied SRSD to teach students strategies for writing.

We hope you enjoy the studies presented here. We further hope they serve as a catalyst to improve your own research if you are a writing scholar or your teaching if you are a practitioner.

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Graham, S., Alves, R.A. Research and teaching writing. Read Writ 34 , 1613–1621 (2021). https://doi.org/10.1007/s11145-021-10188-9

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  • v.15(3); Jul-Sep 2019

How to write an article: An introduction to basic scientific medical writing

Anil sharma.

Department of Minimal Access, Metabolic and Bariatric Surgery, Institute of Minimal Access, Metabolic and Bariatric Surgery, Max Healthcare Institute Ltd., Saket, New Delhi, India

An original scientific article published in a peer-reviewed professional journal of repute provides great personal satisfaction, adds stature and endows professional respectability to contributing authors. Various types of surgical publications that exist nowadays are case report, cohort study, case–control study, randomised controlled trial narrative review, systematic review, Cochrane review, meta-analysis, editorials and leading articles. A study/research protocol is a standardised document, common to all research projects that typically comprise study objectives, study design, selection of participants, study intervention, study evaluations, safety assessments, statistics and participant rights committees. Once the study protocol is completed and reviewed, it is submitted to the local Institutional Review Board/Institutional Ethics Committee for approval. An outline of the levels of evidence and grades of recommendation is available from the Centre for evidence-based medicine at the University of Oxford. A standardised, structured template exists for scientific presentations in the field of medicine which is also followed in medical writing and publications Introduction Methods Results And Discussion (IMRAD). Instructions to authors would normally include reference to International Committee of Medical Journal Editors and Committee on Publication Ethics guidelines for good and ethical publication practice. It is strongly advised to follow the recommended guidelines appropriate for the published study.

INTRODUCTION

The impact of the published article in a scientific journal of repute is powerful and protracted for as Kenneth Rothman states, ‘The written word reaches the widest audience and constitutes the archival message’. Authorship in a scientific journal implies that the authors have critically analysed and presented a scientific work of merit. ‘Reading maketh a full man, conference a ready man and writing an exact man’, (Francis Bacon). With scientific publishing, surgeons make their contributions to the profession for wide dissemination within their community and in the process create intellectual property that will be preserved down the ages. ‘The universal object of men of letters is reputation’, said John Adams.

A majority of practicing surgeons would not write and would remain engaged in busy surgical practices, bread winning and increasing administrative responsibilities. However, an increasing segment of surgeons in training and academic surgeons now feel the need to write and publish. The reasons for writing and publishing are both egoistic and altruistic.[ 1 ] Egoistic motives are the desire to progress academically and professionally, improve status and develop professional contacts. Altruistic motives are dissemination of knowledge and a moral obligation to publish a significant novel observation in the larger interest of better patient care. In several institutions, for academic appointments and promotions, the pressures to publish are sometimes inordinate. In many teaching institutions, to progress academically to whatever academic title one aspires, one's published output must constantly grow in number and quality. However, good-quality writing and publishing are not just in the domain of academic institutions. Several astute clinicians with clarity of vision from non-academic institutions have made significant contributions to surgical literature. It is imperative that contributions to surgical literature are derived from surgeons (academic and non-academic) at various locations (different continents, regions and nationalities) and workplaces (urban, semi-urban and rural). Such literature would be more relevant to the real world as opposed to surgical practice in highly sophisticated ivory towers. In the final analysis, an original scientific article published in a peer-reviewed professional journal of repute provides great personal satisfaction adds stature and endows professional respectability to contributing authors.

MANUSCRIPT TYPES

‘You don’t write because you want to say something; you write because you have something to say’, (Scot Fitzgerald). The essence of fine surgical writing is to write what you as a surgeon would want to read. Enumerated below is a list of various types of surgical publications that exist nowadays arranged in the order of increasing complexity.

  • Letter/communication to the Editor

Case report

Cohort study (non-randomised, observational study), case–control study (non-randomised, observational study).

  • Randomised controlled trial (RCT)

Narrative review

Systematic review and cochrane review, meta-analysis.

  • Editorials and leading articles.

Letter/communication to the editor

This would be with reference to an article that has previously been published. The letter should be polite, constructive and should provide comments that offer a novel perspective of the published article. The comments should add, detract or critically review the contents of the published article in a fair and reasonable manner. The objective is to closely focus on and examine critical issues that may not have been appropriately addressed.

Many esteemed surgical writers, even journal editors, began a literary career with a time-honoured case report.[ 2 ] The humble case report would probably be the first step that an aspiring surgeon takes in surgical writing. Unfortunately, pressure of space and editorial policies directed at enhancing the impact factor of individual journals have reduced the opportunities for publication of case reports.[ 3 ]

The cohort study, case–control study and RCT constitute ‘original articles’ in surgical publications. The narrative review, systematic review and meta-analysis are ‘review articles’.

A cohort study is when patients are followed forward and assessed from time of exposure until time of consequences of exposure (target outcome). An example is ‘initial experience with single incision laparoscopic cholecystectomy.’

A case–control study is when patients are selected once they have the target outcome or not and researchers look backward to try to determine the factors of exposure. An example is ‘bile duct injury with single incision laparoscopic cholecystectomy.’

Randomised controlled trial

An RCT is performed when investigators want to assess treatment effects, usually considered to be beneficial. An example is ‘an RCT comparing recurrence rates between laparoscopic hernioplasty and Shouldice repair for groin hernias’.

A cohort study is feasible when randomisation of exposure is not possible. A case–control study overcomes temporal delays and may only require small sample size. However, both these studies are susceptible to bias and therefore have limited validity. The advantage of an RCT is that it provides the highest level of evidence. It is therefore useful to disprove efficacy which is important in the present era of technology-driven surgery. There is immense pressure from the manufacturers to use devices and procedures, many of which may not measure up to the scientific scrutiny of a well-conducted RCT. The design and execution of an RCT in surgery, however, is fraught with several difficulties and challenges. The nature of treatment by surgical intervention may lead to ethical issues that make design of the study difficult. Moreover, surgical skills and competence may vary from one hospital and surgeon to another making comparison odious. In most surgical studies, blinding of procedure from assessor is very difficult, and therefore, bias is inevitable.

A narrative review is usually written by invitation to an expert. The expert objectively reviews the subject in a concise and impartial manner. He/she addresses new developments and summarises recent literature. A narrative review leaves an imprint of the approach and thought process of the expert on the subject.

A systematic review involves more rigorous compilation of evidence. A systematic review is designed to present complete and unbiased evidence on the subject that presently exists in the literature. Strict adherence to follow and complete all components of a clearly defined protocol is mandatory.

A meta-analysis is a type of systematic review that uses statistical methods to combine and summarise the results of clinical trials. A meta-analysis must always include a formal examination of heterogeneity as an indicator of similar or divergent results.

Editorials and leading articles

These are usually written by invitation on a specific research area. The opinion and judgement of the editor do not only be based on review of literature but also carry the imprimatur of his/her personal beliefs and experience.

EVIDENCE-BASED MEDICINE

We live in an era of evidence-based medicine where increasingly an evidence-based approach to surgical practice would dictate the refining of systems and processes of patient care. Evidence-based practice is the, explicit and judicious use of the current best evidence in making decisions about the care of individual patients’.[ 4 ] An outline of the levels of evidence and grades of recommendation is available from the Centre for evidence-based medicine at the University of Oxford[ 5 , 6 ] Table 1 describes the levels of evidence for therapeutic studies.[ 7 ]

Levels of evidence for therapeutic studies

CONSTRUCTING THE MANUSCRIPT

‘If you can’t explain it simply, you don’t understand it well enough’, (Albert Einstein).

At the outset, formulation of the study/research protocol is required. The study/research protocol is a standardised document, common to all research projects that should be available in teaching institutions. The protocol template typically comprises the following.

  • Study objectives
  • Study design
  • Selection of participants
  • Study intervention
  • Study evaluations
  • Safety assessments
  • Participant rights
  • Committees.

Once the study protocol is completed and reviewed, it is submitted to the local Institutional Review Board (IRB)/Institutional Ethics Committee (IEC) for approval. Written consent is obtained and the study is registered at the Clinical Trial Registry of India at www.ctri.in .

‘If you don’t know where you are going, you will end up someplace else’, (Yogi Berra).

A standardised, structured template exists for scientific presentations in the field of medicine, and this is also followed in Medical writing and publications Introduction Methods Results And Discussion (IMRAD).

  • Introduction: Why did we start?
  • Methods: What did we do?
  • Results: What did we find?
  • Discussion: Hence, what does it mean?

Enumerated below are the constituent segments and contents therein in an original article of a scientific medical manuscript.

Introduction (two paragraphs)

The Introduction commences with a brief lesson on the subject as described in literature. Current knowledge, insights and recent developments on the subject are briefly stated. A lacuna or gap in knowledge or incomplete information on some aspect of the subject forms the basis and reason to perform the present research/study. The last line in the Introduction section normally reads ‘The aim of this study was…’, ‘We report… or ‘We reviewed…’.

Methods (seven paragraphs)

The Methods section narrates the story of what the authors did. The narration is arranged in a logical framework of time. A logical sequence for presentation is ethical approval, patient selection, surgical intervention, outcome assessments and statistical methods employed.

Results (six paragraphs)

The Results Section is an overall description of the major findings of the study. The Results section presents measurements and data on all stated end-points (primary and secondary) of the study. Data presentation should be clear and concise.

Discussion (seven paragraphs)

The Discussion section summarises the article and presents a perspective of the message in the article. The first paragraph provides a summary of the main aim, methods and results of the study. The last paragraph provides a tentative answer to the research question posed in the study and also a suggestion for future research in a related area of the study. The limitations of the present study are discussed (e.g. nature of study, numbers of patients and limited follow-up). The strengths of the present study, if any, may be enumerated. Similar studies in the literature are discussed and how the present study fits in is analysed. The implications of the present study are discussed in terms of future research, change in patient management policies and suggested amendments to clinical practice.

The title should be descriptive yet concise while conveying the essential features of the contents of the article. The title should contain words that will make the article accessible to workers in the field. Clarity, brevity and above all human interest are the hallmarks of a good title.

Titles and abstracts are freely available to browse across a wide array of databases on the Internet. An attractive title and a concise abstract serve to attract the attention of readers. The abstract serves as a stand-alone summary that describes the major contents and message of the article. The abstract is structured (IMRAD) with a strict word limit. It serves as a quick reference and shortcut for busy researchers.

Keywords are short phrases that capture the main topics of the article. These follow the abstract in the article. Keywords assist in cross-indexing and literature search.

Most journal editors subscribe to guidance from the International Committee of Medical Journal Editors (ICMJE)[ 8 ] also known as the Vancouver group. Contributors who meet all four of the below-mentioned criteria qualify for authorship.

  • Substantial contributions to the conception or design of the work or the acquisition, analysis or interpretation of data for the work
  • Drafting the work or revising it critically for important intellectual content
  • Final approval of the version to be published
  • Agreement to be accountable for all aspects of the work.

Acknowledgements

Those whose contributions do not justify authorship may be acknowledged and their contributions should be specified (e.g., ‘served as scientific advisors’, ‘critically reviewed the study proposal’, ‘collected data’, ‘provided and cared for study patients’ and ‘participated in writing or technical editing of the manuscript’).[ 8 ]

Conflict of interest

The ICMJE states that ‘a conflict of interest exists when professional judgement concerning a primary interest (such as patient's welfare or the validity of research) may be influenced by a secondary interest (such as financial gain)’. Public trust in the scientific process and the credibility of published articles depend in part on how transparently conflicts of interest are handled during the planning, implementation, writing, peer review, editing and publication of scientific work. Financial relationships (such as employment, consultancies, stock ownership or options, honoraria, patents and paid expert testimony) are the most easily identifiable conflicts of interest and the most likely to undermine the credibility of the journal, the authors, and science itself.[ 8 ]

A reference to articles serves to guide readers to a connected body of literature. Conference abstracts should not be used as references. They can be cited in the text, in parentheses, but not as page footnotes. References to papers accepted but not yet published should be designated as ‘in press’ or ‘forthcoming’. Information from manuscripts submitted but not accepted should be cited in the text as ‘unpublished observations’ with written permission from the source. Avoid citing a ‘personal communication’ unless it provides essential information not available from a public source, in which case the name of the person and date of communication should be cited in parentheses in the text.[ 8 ]

INSTRUCTIONS TO AUTHORS

It is mandatory to read and follow ‘Instructions to Authors’ provided by the journal where the manuscript is being sent for evaluation. Journals require electronic submission of manuscripts through specially designed editorial software (e.g. edition manager, manuscript central). The instructions provide detailed submission guidelines to Authors for submission of manuscripts. Instructions would normally include reference to ICMJE what an editor expects…pg 1124[ 9 ] and Committee on Publication Ethics (COPE) Guidelines[ 10 ] for good and ethical publication practice.

REPORTING GUIDELINES

It is strongly advised to follow recommended guidelines appropriate for the published study. These guidelines set international standards for reporting different types of research studies. A good checklist is provided for preparing the publication. The guidelines standardise trial design, facilitate accurate reporting and correct interpretation of results [ Table 2 ].[ 11 ]

Reporting guidelines for main study types

ROLE OF BIOSTATISTICIAN

The biostatistician provides invaluable input, advice and suggestions in construction of the manuscript. He/she should be consulted right from the concept and planning stage. He/she assists in protocol development with study design and study evaluations. He/she plans data management by confirming assessment of data on primary and secondary end-points of the study. He/she supervises data collection, archival and analysis. He/she implements and monitors the study on a periodic basis to its conclusion. Finally, the biostatistician assists with reporting results during writing of the manuscript.

DATA MANAGEMENT

Data management is the strategy used for collecting, organising and analysing data. The ultimate aim of conducting a study is to generate data to provide answers to the research question. The quality of data generated plays an important role in the outcome of the study. It follows that if primary data collection and entry are not considerate and meticulous, subsequent data analysis for outcome measures would not be satisfactory. Data need to be ultimately stored in electronic data capturing systems for ease of data management and analysis.

Several data analysis software systems are available that provide statistical results when data are fed into then in a predetermined format (Analyse-it, SPSS, WINKS SDA, Stata, Vitalnet).

WRITING STYLE

An effective writing style is easy to read and simple to understand. The connoisseur writer filters out unnecessary details and distills the essence of his/her communication in the manuscript. A short manuscript presented clear and lucidly is the most effective. Simple sentences in straightforward language convey the most information. A short sentence is easier to read and comprehend than a long rambling one, short, simple and familiar words are more reader-friendly than longer complicated phrases (replace ‘illustrate’ with ‘show’, ‘fundamental’ with ‘basic’ and ‘remainder’ with ‘rest’). A spell check and grammar check are mandatory after completing the manuscript.

New information is provided in a new paragraph. The main point appears at the start and should be clear, succinct and easy to find. The author consciously needs to avoid elitism/triumphalism in the article (the first report, the only study, the largest cohort). Exclamation and quotation marks are avoided in a formal medical manuscript. Proper punctuation marks such as full stops and commas are mandatory.

Text verbatim (copy and paste) from a previously published article or book must be marked as reference source. The author needs to follow the reference style required for submission to the journal. The Vancouver system[ 12 ] is the most commonly used. Abbreviations (INR – international normalised ratio, PT – prothrombin time) and acronyms (IMV – inferior mesenteric vein) should always be defined the first time they are used in the text. Abbreviations are useful to avoid unnecessary and frequent use of long phrases in the text. However, their use should be restricted in the text and never used in the title and abstract. In figures, abbreviations need to be explained in the legend and for tables in the footnote.

Tables and figures must be sufficiently clear, well labelled and interpretable without having to refer to the text. These should be placed in the text as near as possible to the place where they are referred to. Tables should not be used when data can be summarised in text (e.g. population sizes, sex ratios) or where data are better represented in graphs and figures. The legend carries descriptive information on the tables and figures to make them understandable as stand-alone segments. Table legends are placed above the body of the table, and figure legends are placed below the figures. Footnotes in a table explain abbreviations and P values.

PUBLICATION ETHICS

The COPE was founded in 1997 as a voluntary body to attempt to define best practice in the ethics of scientific publishing. The COPE guidelines on good publication practice are useful for authors, editors, editorial board members, readers, owners of journals and publishers. They address study design and ethical approval, data analysis, authorship, conflicts of interest, peer-review process, redundant publication, plagiarism, duties of editors, media relations, advertising and how to deal with misconduct.

  • Study design and ethical approval: Good research should be well justified, well planned appropriately designed and ethically approved. To conduct research to a lower standard may constitute misconduct
  • Data analysis: Data should be appropriately analysed, but inappropriate analysis does not necessarily amount to misconduct. Fabrication and falsification of data do constitute misconduct
  • Authorship: There is no universally agreed definition of authorship although attempts have been made. As a minimum, authors should take responsibility for a particular section of the study

They may be personal, commercial, political, academic or financial. ‘Financial’ interests may include employment, research funding, stock or share ownership, payment for lectures or travel, consultancies and company support for staff

  • Peer review: Peer reviewers are external experts chosen by editors to provide written opinions, with the aim of improving the study. Working methods vary from journal to journal, but some use open procedure in which the name of the reviewer is disclosed, together with the full or ‘edited’ report
  • Redundant publication: Redundant publication occurs when two or more papers, without full cross-references, share the same hypothesis, data, discussion points, or conclusions
  • Plagiarism: Plagiarism ranges from the unreferenced use of others published and unpublished ideas, including research grant applications to submission under ‘new’ authorship of a complete paper, something in a different language. It may occur at any stage of planning, research writing or publication: It applies to print and electronic versions
  • Duties of editors: Editors are stewards of journals. They usually take over their journal from the previous editor(s) and always want to hand over the journal in good shape. Most editors provide direction for the journal and build a strong management team. They must consider and balance the interests of many constituents, including readers, authors, staff, owners, editorial board members, advertisers and the media
  • Media relations: Medical research findings are of increasing interest to the print and broadcast media. Journalists may attend scientific meetings at which preliminary research findings are presented, leading to their premature publication in the mass media
  • Advertising: Many scientific journals and meetings derive significant income from advertising. Reprints may also be lucrative.

Financial support and sponsorship

Conflicts of interest.

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Academia Insider

The best AI tools for research papers and academic research (Literature review, grants, PDFs and more)

As our collective understanding and application of artificial intelligence (AI) continues to evolve, so too does the realm of academic research. Some people are scared by it while others are openly embracing the change. 

Make no mistake, AI is here to stay!

Instead of tirelessly scrolling through hundreds of PDFs, a powerful AI tool comes to your rescue, summarizing key information in your research papers. Instead of manually combing through citations and conducting literature reviews, an AI research assistant proficiently handles these tasks.

These aren’t futuristic dreams, but today’s reality. Welcome to the transformative world of AI-powered research tools!

The influence of AI in scientific and academic research is an exciting development, opening the doors to more efficient, comprehensive, and rigorous exploration.

This blog post will dive deeper into these tools, providing a detailed review of how AI is revolutionizing academic research. We’ll look at the tools that can make your literature review process less tedious, your search for relevant papers more precise, and your overall research process more efficient and fruitful.

I know that I wish these were around during my time in academia. It can be quite confronting when trying to work out what ones you should and shouldn’t use. A new one seems to be coming out every day!

Here is everything you need to know about AI for academic research and the ones I have personally trialed on my Youtube channel.

Best ChatGPT interface – Chat with PDFs/websites and more

I get more out of ChatGPT with HeyGPT . It can do things that ChatGPT cannot which makes it really valuable for researchers.

Use your own OpenAI API key ( h e re ). No login required. Access ChatGPT anytime, including peak periods. Faster response time. Unlock advanced functionalities with HeyGPT Ultra for a one-time lifetime subscription

AI literature search and mapping – best AI tools for a literature review – elicit and more

Harnessing AI tools for literature reviews and mapping brings a new level of efficiency and precision to academic research. No longer do you have to spend hours looking in obscure research databases to find what you need!

AI-powered tools like Semantic Scholar and elicit.org use sophisticated search engines to quickly identify relevant papers.

They can mine key information from countless PDFs, drastically reducing research time. You can even search with semantic questions, rather than having to deal with key words etc.

With AI as your research assistant, you can navigate the vast sea of scientific research with ease, uncovering citations and focusing on academic writing. It’s a revolutionary way to take on literature reviews.

  • Elicit –  https://elicit.org
  • Supersymmetry.ai: https://www.supersymmetry.ai
  • Semantic Scholar: https://www.semanticscholar.org
  • Connected Papers –  https://www.connectedpapers.com/
  • Research rabbit – https://www.researchrabbit.ai/
  • Laser AI –  https://laser.ai/
  • Litmaps –  https://www.litmaps.com
  • Inciteful –  https://inciteful.xyz/
  • Scite –  https://scite.ai/
  • System –  https://www.system.com

If you like AI tools you may want to check out this article:

  • How to get ChatGPT to write an essay [The prompts you need]

AI-powered research tools and AI for academic research

AI research tools, like Concensus, offer immense benefits in scientific research. Here are the general AI-powered tools for academic research. 

These AI-powered tools can efficiently summarize PDFs, extract key information, and perform AI-powered searches, and much more. Some are even working towards adding your own data base of files to ask questions from. 

Tools like scite even analyze citations in depth, while AI models like ChatGPT elicit new perspectives.

The result? The research process, previously a grueling endeavor, becomes significantly streamlined, offering you time for deeper exploration and understanding. Say goodbye to traditional struggles, and hello to your new AI research assistant!

  • Bit AI –  https://bit.ai/
  • Consensus –  https://consensus.app/
  • Exper AI –  https://www.experai.com/
  • Hey Science (in development) –  https://www.heyscience.ai/
  • Iris AI –  https://iris.ai/
  • PapersGPT (currently in development) –  https://jessezhang.org/llmdemo
  • Research Buddy –  https://researchbuddy.app/
  • Mirror Think – https://mirrorthink.ai

AI for reading peer-reviewed papers easily

Using AI tools like Explain paper and Humata can significantly enhance your engagement with peer-reviewed papers. I always used to skip over the details of the papers because I had reached saturation point with the information coming in. 

These AI-powered research tools provide succinct summaries, saving you from sifting through extensive PDFs – no more boring nights trying to figure out which papers are the most important ones for you to read!

They not only facilitate efficient literature reviews by presenting key information, but also find overlooked insights.

With AI, deciphering complex citations and accelerating research has never been easier.

  • Open Read –  https://www.openread.academy
  • Chat PDF – https://www.chatpdf.com
  • Explain Paper – https://www.explainpaper.com
  • Humata – https://www.humata.ai/
  • Lateral AI –  https://www.lateral.io/
  • Paper Brain –  https://www.paperbrain.study/
  • Scholarcy – https://www.scholarcy.com/
  • SciSpace Copilot –  https://typeset.io/
  • Unriddle – https://www.unriddle.ai/
  • Sharly.ai – https://www.sharly.ai/

AI for scientific writing and research papers

In the ever-evolving realm of academic research, AI tools are increasingly taking center stage.

Enter Paper Wizard, Jenny.AI, and Wisio – these groundbreaking platforms are set to revolutionize the way we approach scientific writing.

Together, these AI tools are pioneering a new era of efficient, streamlined scientific writing.

  • Paper Wizard –  https://paperwizard.ai/
  • Jenny.AI https://jenni.ai/ (20% off with code ANDY20)
  • Wisio – https://www.wisio.app

AI academic editing tools

In the realm of scientific writing and editing, artificial intelligence (AI) tools are making a world of difference, offering precision and efficiency like never before. Consider tools such as Paper Pal, Writefull, and Trinka.

Together, these tools usher in a new era of scientific writing, where AI is your dedicated partner in the quest for impeccable composition.

  • Paper Pal –  https://paperpal.com/
  • Writefull –  https://www.writefull.com/
  • Trinka –  https://www.trinka.ai/

AI tools for grant writing

In the challenging realm of science grant writing, two innovative AI tools are making waves: Granted AI and Grantable.

These platforms are game-changers, leveraging the power of artificial intelligence to streamline and enhance the grant application process.

Granted AI, an intelligent tool, uses AI algorithms to simplify the process of finding, applying, and managing grants. Meanwhile, Grantable offers a platform that automates and organizes grant application processes, making it easier than ever to secure funding.

Together, these tools are transforming the way we approach grant writing, using the power of AI to turn a complex, often arduous task into a more manageable, efficient, and successful endeavor.

  • Granted AI – https://grantedai.com/
  • Grantable – https://grantable.co/

Free AI research tools

There are many different tools online that are emerging for researchers to be able to streamline their research processes. There’s no need for convience to come at a massive cost and break the bank.

The best free ones at time of writing are:

  • Elicit – https://elicit.org
  • Connected Papers – https://www.connectedpapers.com/
  • Litmaps – https://www.litmaps.com ( 10% off Pro subscription using the code “STAPLETON” )
  • Consensus – https://consensus.app/

Wrapping up

The integration of artificial intelligence in the world of academic research is nothing short of revolutionary.

With the array of AI tools we’ve explored today – from research and mapping, literature review, peer-reviewed papers reading, scientific writing, to academic editing and grant writing – the landscape of research is significantly transformed.

The advantages that AI-powered research tools bring to the table – efficiency, precision, time saving, and a more streamlined process – cannot be overstated.

These AI research tools aren’t just about convenience; they are transforming the way we conduct and comprehend research.

They liberate researchers from the clutches of tedium and overwhelm, allowing for more space for deep exploration, innovative thinking, and in-depth comprehension.

Whether you’re an experienced academic researcher or a student just starting out, these tools provide indispensable aid in your research journey.

And with a suite of free AI tools also available, there is no reason to not explore and embrace this AI revolution in academic research.

We are on the precipice of a new era of academic research, one where AI and human ingenuity work in tandem for richer, more profound scientific exploration. The future of research is here, and it is smart, efficient, and AI-powered.

Before we get too excited however, let us remember that AI tools are meant to be our assistants, not our masters. As we engage with these advanced technologies, let’s not lose sight of the human intellect, intuition, and imagination that form the heart of all meaningful research. Happy researching!

Thank you to Ivan Aguilar – Ph.D. Student at SFU (Simon Fraser University), for starting this list for me!

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Dr Andrew Stapleton has a Masters and PhD in Chemistry from the UK and Australia. He has many years of research experience and has worked as a Postdoctoral Fellow and Associate at a number of Universities. Although having secured funding for his own research, he left academia to help others with his YouTube channel all about the inner workings of academia and how to make it work for you.

Thank you for visiting Academia Insider.

We are here to help you navigate Academia as painlessly as possible. We are supported by our readers and by visiting you are helping us earn a small amount through ads and affiliate revenue - Thank you!

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Literature review

A general guide on how to conduct and write a literature review.

Please check course or programme information and materials provided by teaching staff, including your project supervisor, for subject-specific guidance.

What is a literature review?

A literature review is a piece of academic writing demonstrating knowledge and understanding of the academic literature on a specific topic placed in context.  A literature review also includes a critical evaluation of the material; this is why it is called a literature review rather than a literature report. It is a process of reviewing the literature, as well as a form of writing.

To illustrate the difference between reporting and reviewing, think about television or film review articles.  These articles include content such as a brief synopsis or the key points of the film or programme plus the critic’s own evaluation.  Similarly the two main objectives of a literature review are firstly the content covering existing research, theories and evidence, and secondly your own critical evaluation and discussion of this content. 

Usually a literature review forms a section or part of a dissertation, research project or long essay.  However, it can also be set and assessed as a standalone piece of work.

What is the purpose of a literature review?

…your task is to build an argument, not a library. Rudestam, K.E. and Newton, R.R. (1992) Surviving your dissertation: A comprehensive guide to content and process. California: Sage, p49.

In a larger piece of written work, such as a dissertation or project, a literature review is usually one of the first tasks carried out after deciding on a topic.  Reading combined with critical analysis can help to refine a topic and frame research questions.  Conducting a literature review establishes your familiarity with and understanding of current research in a particular field before carrying out a new investigation. After doing a literature review, you should know what research has already been done and be able to identify what is unknown within your topic.

When doing and writing a literature review, it is good practice to:

  • summarise and analyse previous research and theories;
  • identify areas of controversy and contested claims;
  • highlight any gaps that may exist in research to date.

Conducting a literature review

Focusing on different aspects of your literature review can be useful to help plan, develop, refine and write it.  You can use and adapt the prompt questions in our worksheet below at different points in the process of researching and writing your review.  These are suggestions to get you thinking and writing.

Developing and refining your literature review (pdf)

Developing and refining your literature review (Word)

Developing and refining your literature review (Word rtf)

Writing a literature review has a lot in common with other assignment tasks.  There is advice on our other pages about thinking critically, reading strategies and academic writing.  Our literature review top tips suggest some specific things you can do to help you submit a successful review.

Literature review top tips (pdf)

Literature review top tips (Word rtf)

Our reading page includes strategies and advice on using books and articles and a notes record sheet grid you can use.

Reading at university

The Academic writing page suggests ways to organise and structure information from a range of sources and how you can develop your argument as you read and write.

Academic writing

The Critical thinking page has advice on how to be a more critical researcher and a form you can use to help you think and break down the stages of developing your argument.

Critical thinking

As with other forms of academic writing, your literature review needs to demonstrate good academic practice by following the Code of Student Conduct and acknowledging the work of others through citing and referencing your sources.  

Good academic practice

As with any writing task, you will need to review, edit and rewrite sections of your literature review.  The Editing and proofreading page includes tips on how to do this and strategies for standing back and thinking about your structure and checking the flow of your argument.

Editing and proofreading

Guidance on literature searching from the University Library

The Academic Support Librarians have developed LibSmart I and II, Learn courses to help you develop and enhance your digital research skills and capabilities; from getting started with the Library to managing data for your dissertation.

Searching using the library’s DiscoverEd tool: DiscoverEd

Finding resources in your subject: Subject guides

The Academic Support Librarians also provide one-to-one appointments to help you develop your research strategies.

1 to 1 support for literature searching and systematic reviews

Advice to help you optimise use of Google Scholar, Google Books and Google for your research and study: Using Google

Managing and curating your references

A referencing management tool can help you to collect and organise and your source material to produce a bibliography or reference list. 

Referencing and reference management

Information Services provide access to Cite them right online which is a guide to the main referencing systems and tells you how to reference just about any source (EASE log-in may be required).

Cite them right

Published study guides

There are a number of scholarship skills books and guides available which can help with writing a literature review.  Our Resource List of study skills guides includes sections on Referencing, Dissertation and project writing and Literature reviews.

Study skills guides

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Something felt ‘off’ – how AI messed with our human research, and what we learned

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Senior Lecturer in Health Psychology, Te Herenga Waka — Victoria University of Wellington

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Research Fellow, School of Health, Te Herenga Waka — Victoria University of Wellington

Disclosure statement

Alexandra Gibson receives funding from Te Apārangi - Royal Society of New Zealand.

Alex Beattie does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

Te Herenga Waka — Victoria University of Wellington provides funding as a member of The Conversation NZ.

Te Herenga Waka—Victoria University of Wellington provides funding as a member of The Conversation AU.

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All levels of research are being changed by the rise of artificial intelligence (AI). Don’t have time to read that journal article? AI-powered tools such as TLDRthis will summarise it for you.

Struggling to find relevant sources for your review? Inciteful will list suitable articles with just the click of a button. Are your human research participants too expensive or complicated to manage? Not a problem – try synthetic participants instead.

Each of these tools suggests AI could be superior to humans in outlining and explaining concepts or ideas. But can humans be replaced when it comes to qualitative research?

This is something we recently had to grapple with while carrying out unrelated research into mobile dating during the COVID-19 pandemic . And what we found should temper enthusiasm for artificial responses over the words of human participants.

Encountering AI in our research

Our research is looking at how people might navigate mobile dating during the pandemic in Aotearoa New Zealand. Our aim was to explore broader social responses to mobile dating as the pandemic progressed and as public health mandates changed over time.

As part of this ongoing research, we prompt participants to develop stories in response to hypothetical scenarios.

Read more: What happens when we outsource boring but important work to AI? Research shows we forget how to do it ourselves

In 2021 and 2022 we received a wide range of intriguing and quirky responses from 110 New Zealanders recruited through Facebook. Each participant received a gift voucher for their time.

Participants described characters navigating the challenges of “Zoom dates” and clashing over vaccination statuses or wearing masks. Others wrote passionate love stories with eyebrow-raising details. Some even broke the fourth wall and wrote directly to us, complaining about the mandatory word length of their stories or the quality of our prompts.

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These responses captured the highs and lows of online dating, the boredom and loneliness of lockdown, and the thrills and despair of finding love during the time of COVID-19.

But, perhaps most of all, these responses reminded us of the idiosyncratic and irreverent aspects of human participation in research – the unexpected directions participants go in, or even the unsolicited feedback you can receive when doing research.

But in the latest round of our study in late 2023, something had clearly changed across the 60 stories we received.

This time many of the stories felt “off”. Word choices were quite stilted or overly formal. And each story was quite moralistic in terms of what one “should” do in a situation.

Using AI detection tools, such as ZeroGPT, we concluded participants – or even bots – were using AI to generate story answers for them, possibly to receive the gift voucher for minimal effort.

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Contrary to claims that AI can sufficiently replicate human participants in research, we found AI-generated stories to be woeful.

We were reminded that an essential ingredient of any social research is for the data to be based on lived experience.

Is AI the problem?

Perhap the biggest threat to human research is not AI, but rather the philosophy that underscores it.

It is worth noting the majority of claims about AI’s capabilities to replace humans come from computer scientists or quantitative social scientists. In these types of studies, human reasoning or behaviour is often measured through scorecards or yes/no statements.

This approach necessarily fits human experience into a framework that can be more easily analysed through computational or artificial interpretation.

In contrast, we are qualitative researchers who are interested in the messy, emotional, lived experience of people’s perspectives on dating. We were drawn to the thrills and disappointments participants originally pointed to with online dating, the frustrations and challenges of trying to use dating apps, as well as the opportunities they might create for intimacy during a time of lockdowns and evolving health mandates.

Read more: AI is in danger of becoming too male – new research

In general, we found AI poorly simulated these experiences.

Some might accept generative AI is here to stay, or that AI should be viewed as offering various tools to researchers. Other researchers might retreat to forms of data collection, such as surveys, that might minimise the interference of unwanted AI participation.

But, based on our recent research experience , we believe theoretically-driven, qualitative social research is best equipped to detect and protect against AI interference.

There are additional implications for research. The threat of AI as an unwanted participant means researchers will have to work longer or harder to spot imposter participants.

Academic institutions need to start developing policies and practices to reduce the burden on individual researchers trying to carry out research in the changing AI environment.

Regardless of researchers’ theoretical orientation, how we work to limit the involvement of AI is a question for anyone interested in understanding human perspectives or experiences. If anything, the limitations of AI reemphasise the importance of being human in social research.

  • Artificial intelligence (AI)
  • New Zealand stories
  • qualitative research
  • Artificial Intelligence ethics

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What the Data Says About Pandemic School Closures, Four Years Later

The more time students spent in remote instruction, the further they fell behind. And, experts say, extended closures did little to stop the spread of Covid.

Sarah Mervosh

By Sarah Mervosh ,  Claire Cain Miller and Francesca Paris

Four years ago this month, schools nationwide began to shut down, igniting one of the most polarizing and partisan debates of the pandemic.

Some schools, often in Republican-led states and rural areas, reopened by fall 2020. Others, typically in large cities and states led by Democrats, would not fully reopen for another year.

A variety of data — about children’s academic outcomes and about the spread of Covid-19 — has accumulated in the time since. Today, there is broad acknowledgment among many public health and education experts that extended school closures did not significantly stop the spread of Covid, while the academic harms for children have been large and long-lasting.

While poverty and other factors also played a role, remote learning was a key driver of academic declines during the pandemic, research shows — a finding that held true across income levels.

Source: Fahle, Kane, Patterson, Reardon, Staiger and Stuart, “ School District and Community Factors Associated With Learning Loss During the COVID-19 Pandemic .” Score changes are measured from 2019 to 2022. In-person means a district offered traditional in-person learning, even if not all students were in-person.

“There’s fairly good consensus that, in general, as a society, we probably kept kids out of school longer than we should have,” said Dr. Sean O’Leary, a pediatric infectious disease specialist who helped write guidance for the American Academy of Pediatrics, which recommended in June 2020 that schools reopen with safety measures in place.

There were no easy decisions at the time. Officials had to weigh the risks of an emerging virus against the academic and mental health consequences of closing schools. And even schools that reopened quickly, by the fall of 2020, have seen lasting effects.

But as experts plan for the next public health emergency, whatever it may be, a growing body of research shows that pandemic school closures came at a steep cost to students.

The longer schools were closed, the more students fell behind.

At the state level, more time spent in remote or hybrid instruction in the 2020-21 school year was associated with larger drops in test scores, according to a New York Times analysis of school closure data and results from the National Assessment of Educational Progress , an authoritative exam administered to a national sample of fourth- and eighth-grade students.

At the school district level, that finding also holds, according to an analysis of test scores from third through eighth grade in thousands of U.S. districts, led by researchers at Stanford and Harvard. In districts where students spent most of the 2020-21 school year learning remotely, they fell more than half a grade behind in math on average, while in districts that spent most of the year in person they lost just over a third of a grade.

( A separate study of nearly 10,000 schools found similar results.)

Such losses can be hard to overcome, without significant interventions. The most recent test scores, from spring 2023, show that students, overall, are not caught up from their pandemic losses , with larger gaps remaining among students that lost the most ground to begin with. Students in districts that were remote or hybrid the longest — at least 90 percent of the 2020-21 school year — still had almost double the ground to make up compared with students in districts that allowed students back for most of the year.

Some time in person was better than no time.

As districts shifted toward in-person learning as the year went on, students that were offered a hybrid schedule (a few hours or days a week in person, with the rest online) did better, on average, than those in places where school was fully remote, but worse than those in places that had school fully in person.

Students in hybrid or remote learning, 2020-21

80% of students

Some schools return online, as Covid-19 cases surge. Vaccinations start for high-priority groups.

Teachers are eligible for the Covid vaccine in more than half of states.

Most districts end the year in-person or hybrid.

Source: Burbio audit of more than 1,200 school districts representing 47 percent of U.S. K-12 enrollment. Note: Learning mode was defined based on the most in-person option available to students.

Income and family background also made a big difference.

A second factor associated with academic declines during the pandemic was a community’s poverty level. Comparing districts with similar remote learning policies, poorer districts had steeper losses.

But in-person learning still mattered: Looking at districts with similar poverty levels, remote learning was associated with greater declines.

A community’s poverty rate and the length of school closures had a “roughly equal” effect on student outcomes, said Sean F. Reardon, a professor of poverty and inequality in education at Stanford, who led a district-level analysis with Thomas J. Kane, an economist at Harvard.

Score changes are measured from 2019 to 2022. Poorest and richest are the top and bottom 20% of districts by percent of students on free/reduced lunch. Mostly in-person and mostly remote are districts that offered traditional in-person learning for more than 90 percent or less than 10 percent of the 2020-21 year.

But the combination — poverty and remote learning — was particularly harmful. For each week spent remote, students in poor districts experienced steeper losses in math than peers in richer districts.

That is notable, because poor districts were also more likely to stay remote for longer .

Some of the country’s largest poor districts are in Democratic-leaning cities that took a more cautious approach to the virus. Poor areas, and Black and Hispanic communities , also suffered higher Covid death rates, making many families and teachers in those districts hesitant to return.

“We wanted to survive,” said Sarah Carpenter, the executive director of Memphis Lift, a parent advocacy group in Memphis, where schools were closed until spring 2021 .

“But I also think, man, looking back, I wish our kids could have gone back to school much quicker,” she added, citing the academic effects.

Other things were also associated with worse student outcomes, including increased anxiety and depression among adults in children’s lives, and the overall restriction of social activity in a community, according to the Stanford and Harvard research .

Even short closures had long-term consequences for children.

While being in school was on average better for academic outcomes, it wasn’t a guarantee. Some districts that opened early, like those in Cherokee County, Ga., a suburb of Atlanta, and Hanover County, Va., lost significant learning and remain behind.

At the same time, many schools are seeing more anxiety and behavioral outbursts among students. And chronic absenteeism from school has surged across demographic groups .

These are signs, experts say, that even short-term closures, and the pandemic more broadly, had lasting effects on the culture of education.

“There was almost, in the Covid era, a sense of, ‘We give up, we’re just trying to keep body and soul together,’ and I think that was corrosive to the higher expectations of schools,” said Margaret Spellings, an education secretary under President George W. Bush who is now chief executive of the Bipartisan Policy Center.

Closing schools did not appear to significantly slow Covid’s spread.

Perhaps the biggest question that hung over school reopenings: Was it safe?

That was largely unknown in the spring of 2020, when schools first shut down. But several experts said that had changed by the fall of 2020, when there were initial signs that children were less likely to become seriously ill, and growing evidence from Europe and parts of the United States that opening schools, with safety measures, did not lead to significantly more transmission.

“Infectious disease leaders have generally agreed that school closures were not an important strategy in stemming the spread of Covid,” said Dr. Jeanne Noble, who directed the Covid response at the U.C.S.F. Parnassus emergency department.

Politically, though, there remains some disagreement about when, exactly, it was safe to reopen school.

Republican governors who pushed to open schools sooner have claimed credit for their approach, while Democrats and teachers’ unions have emphasized their commitment to safety and their investment in helping students recover.

“I do believe it was the right decision,” said Jerry T. Jordan, president of the Philadelphia Federation of Teachers, which resisted returning to school in person over concerns about the availability of vaccines and poor ventilation in school buildings. Philadelphia schools waited to partially reopen until the spring of 2021 , a decision Mr. Jordan believes saved lives.

“It doesn’t matter what is going on in the building and how much people are learning if people are getting the virus and running the potential of dying,” he said.

Pandemic school closures offer lessons for the future.

Though the next health crisis may have different particulars, with different risk calculations, the consequences of closing schools are now well established, experts say.

In the future, infectious disease experts said, they hoped decisions would be guided more by epidemiological data as it emerged, taking into account the trade-offs.

“Could we have used data to better guide our decision making? Yes,” said Dr. Uzma N. Hasan, division chief of pediatric infectious diseases at RWJBarnabas Health in Livingston, N.J. “Fear should not guide our decision making.”

Source: Fahle, Kane, Patterson, Reardon, Staiger and Stuart, “ School District and Community Factors Associated With Learning Loss During the Covid-19 Pandemic. ”

The study used estimates of learning loss from the Stanford Education Data Archive . For closure lengths, the study averaged district-level estimates of time spent in remote and hybrid learning compiled by the Covid-19 School Data Hub (C.S.D.H.) and American Enterprise Institute (A.E.I.) . The A.E.I. data defines remote status by whether there was an in-person or hybrid option, even if some students chose to remain virtual. In the C.S.D.H. data set, districts are defined as remote if “all or most” students were virtual.

An earlier version of this article misstated a job description of Dr. Jeanne Noble. She directed the Covid response at the U.C.S.F. Parnassus emergency department. She did not direct the Covid response for the University of California, San Francisco health system.

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  • Published: 14 March 2024

Python farming as a flexible and efficient form of agricultural food security

  • D. Natusch   ORCID: orcid.org/0000-0002-3275-518X 1   na1 ,
  • P. W. Aust   ORCID: orcid.org/0000-0002-5660-0799 2 , 3   na1 ,
  • C. Caraguel 4 ,
  • P. L. Taggart   ORCID: orcid.org/0000-0001-9523-0463 4 ,
  • V. T. Ngo 5 ,
  • G. J. Alexander   ORCID: orcid.org/0000-0003-3991-4099 3 ,
  • R. Shine   ORCID: orcid.org/0000-0001-7529-5657 1 &
  • T. Coulson 2  

Scientific Reports volume  14 , Article number:  5419 ( 2024 ) Cite this article

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  • Animal physiology
  • Herpetology

Diminishing natural resources and increasing climatic volatility are impacting agri-food systems, prompting the need for sustainable and resilient alternatives. Python farming is well established in Asia but has received little attention from mainstream agricultural scientists. We measured growth rates in two species of large pythons ( Malayopython reticulatus and Python bivittatus ) in farms in Thailand and Vietnam and conducted feeding experiments to examine production efficiencies. Pythons grew rapidly over a 12-month period, and females grew faster than males. Food intake and growth rates early in life were strong predictors of total lifetime growth, with daily mass increments ranging from 0.24 to 19.7 g/day for M. reticulatus and 0.24 to 42.6 g/day for P. bivittatus , depending on food intake. Pythons that fasted for up to 4.2 months lost an average of 0.004% of their body mass per day, and resumed rapid growth as soon as feeding recommenced. Mean food conversion rate for dressed carcasses was 4.1%, with useable products (dressed carcass, skin, fat, gall bladder) comprising 82% of the mass of live animals. In terms of food and protein conversion ratios, pythons outperform all mainstream agricultural species studied to date. The ability of fasting pythons to regulate metabolic processes and maintain body condition enhances food security in volatile environments, suggesting that python farming may offer a flexible and efficient response to global food insecurity.

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Introduction

The raising of livestock is a cornerstone of human civilization, has underpinned the rise of global economies, and continues to play a central role in the well-being of people in many cultures 1 , 2 , 3 . Livestock production traditionally has relied on a small number of domesticated species and production models—a little-changed formula that until now has served humanity well 2 . A central characteristic of conventional livestock systems has been a high rate of production, driven by energy intensive endothermic (warm-blooded) animals 2 , 4 . High performance endothermic physiologies generating nutrient-dense food, and cheap horsepower in the form of draft animals were important enablers for early civilisations 2 . Essential feed inputs were sustained by primary productivity, and livestock systems often developed within a context of resource abundance and stability 5 , 6 . These parameters are now no longer the norm, and the twin challenges of resource limitations and climate volatility are rapidly changing the production imperatives of our food systems 7 , 8 , 9 .

Conventional livestock and plant crop systems are faltering. Twelve percent of the global human population is undernourished and acute protein deficiency in low-income countries is compromising workforce productivity and development 10 , 11 , 12 . Global food security is predicted to worsen with global change 10 . Infectious diseases, diminishing natural resources, and climate change are having significant and compounding impacts on the agricultural sector 13 , 14 , 15 . Many conventional livestock systems fail to satisfy the criteria for sustainability and/or resilience, and there is an urgent need to explore alternatives 13 .

Ectotherms (cold-blooded animals) are approximately 90% more energy efficient than endotherms 16 . In the context of agriculture, this energy differential readily translates into a potential for higher production efficiency 17 , 18 . It is partly for this reason that the aquaculture and insect farming industries are currently experiencing rapid growth rates 17 , 19 . Like insects, snakes are a traditional source of protein in many tropical countries 20 , 21 , and their consumption is linked to important food, medicinal, and cultural values 22 , 23 , 24 . As demand for snake meat and co-products has increased in line with development, so too have production systems. Over the last two decades, snake farming has expanded to include more species, production models, and markets, partly as a result of competitive agricultural advantages 20 . For example, some snake production systems require minimal land and freshwater, they can rely on waste protein from other industries, and some snake species have specialised adaptations for mitigating the impacts of environmental shocks 20 , 25 , 26 , 27 . Another reason for recent expansion is appeal. Reptile meat is not unlike chicken: high in protein, low in saturated fats, and with widespread aesthetic and culinary appeal 22 , 28 , 29 , 30 .

We examined the potential of pythons as a novel form of livestock for commercial agriculture. To achieve this aim, we studied the growth patterns of two python species in two commercial farms in Southeast Asia. We assessed growth rates of juvenile snakes and conducted feeding experiments on a subset of the snakes to assess production efficiencies and key variables influencing growth. We compared the data gathered during our study to the results of research on other agricultural species (both endothermic and ectothermic) to assess the potential of commercial pythonfarming to enhance food security in the context of global change.

Materials and methods

We collected data from two Asian python farms within the natural range of the model species used in this study: one in Uttaradit Province, central Thailand (17° 38′ N, 100° 07′ E) and the other in Ho Chi Minh City, in southern Vietnam (10°58'N, 106°30'E). The farm in Thailand farms both reticulated ( Malayopython reticulatus ) and Burmese ( Python bivittatus ) pythons, whereas the Vietnamese farm produces only the latter. Both Burmese and reticulated pythons are large-bodied (can grow to > 100 kg), fast growing , and highly fecund, with females reaching maturity within 3 years and producing up to 100 eggs per year for 20 years or more 31 . They are thus well suited for commercial production.

In both Thailand and Vietnam, pythons are housed in enclosures situated within warehouses. The warehouses are constructed and managed in a semi-open fashion to facilitate ventilation and provide optimal temperatures. We did not record the temperature of pythons or their enclosures during this study, but temperatures anecdotally varied between 25 and 32 °C. Pythons were housed communally at stocking densities of approximately 15 kg per m 2 . Captive-bred pythons in Thailand and Vietnam were fed on a variety of food types depending on local protein resources. The most common feed inputs were wild-caught rodents and waste protein from agri-food supply chains (e.g., pork, chicken, fish 20 , 32 ). Many of the larger python farms make sausages from processed waste protein. Sausages are typically introduced into the diet only after the young pythons have developed a robust feeding response 32 .

Trials of growth rate

To quantify growth rates and related attributes, individual pythons were repeatedly measured over a 12-month period. Most pythons are grown for 1 to 1.5 years before slaughter for meat, skins, and other products 32 . At each farm we collected hatchling pythons from eggs produced and hatched onsite. To identify individual snakes, we either maintained a photographic database of the skin patterns on a dorsolateral section of skin immediately posterior to the head, or implanted snakes with passive integrated transponder (PIT) tags 33 .

In Thailand, we measured snout-vent length (hereafter, SVL; using a flexible measuring tape run along the spine of each snake) and body mass (to the nearest g) of pythons on three occasions over the 12-month growing period: (1) at hatching, (2) at six months of age, and (3) at 12 months of age. We sexed snakes by inserting a lubricated probe into the cloacal bursae and recording depth. Pythons were each offered a frozen-thawed day-old chicken to eat once per week for the first two months. From two to 12 months pythons were offered a combination of frozen-thawed day-old chickens and sausages on a weekly basis (Table 1 ). The mass of food offered was not measured but was estimated to be less than 15% of the snakes’ bodyweight per feeding event.

In Vietnam, we measured SVL and body mass of pythons at six intervals over a 12-month period (approximately 0, 2, 4, 7, 9, and 12 months of age) and sexed snakes at hatching by eversion of the hemipenes. Non-hatchling pythons were fed pork-based sausages or experimental diets (see below; Table 1 ). Feeding regimes followed farm protocols for maximum growth rates (food equal to ~ 15% of body mass provided once every 5 days). Hatchlings were started on vertebrate prey (i.e., rodents, day-old quail, or day-old chickens). Apart from one of the experimental groups, the diet of all snakes in treatment groups was changed to sausages at approximately two months of age.

Intensive trials on growth rate

To quantify the influence of food intake on growth rates of pythons and to better quantify food-conversion efficiencies, we conducted a detailed feeding trial on a subset of Burmese pythons at the Vietnamese farm. When python eggs hatched, we divided snakes into five experimental groups, each comprising seven males and seven females (14 snakes total per treatment); we used systematic random allocation to distribute individuals among treatment groups (to deconfound treatments from maternal effects). Diet treatments included: (1) 100% pork; (2) 90% pork, 10% chicken pellets; (3) 90% pork, 10% fish pellets; (4) 80% pork, 20% fish pellets; and (5) 100% wild-caught rodents. We chose these diet treatments because they reflected those currently used in the python farming industry 20 , 32 . Rodents were sourced from local rice fields via professional trappers 20 and humanely euthanized immediately prior to being fed to the pythons. The pork used in the sausages comprised of still-born piglets obtained from local farms, defrosted in vats of water then ground in an industrial meat grinder. The dry pellets used were commercial catfish and chicken grower pellets (31% and 16% protein, respectively) made predominantly from processed anchovies and rice-bran (Ha Lan Aquafeed, Viet Nam). The dry pellets were added to the pork immediately after grinding to facilitate rehydration. The homogenised paste was reconstituted into appropriately sized sausages using a commercial sausage-making machine.

Pythons were offered food approximately once every five days throughout the year, except for three months over the coldest period of the year when they were offered food less often. At each feeding event, we weighed each sausage before one or more was offered to the pythons. Food was offered using forceps and snakes were never force-fed. We recorded whenever snakes refused food. After feeding, pythons were weighed to calculate the pre-feeding body mass of each snake. This procedure allowed us to not disturb the pythons before feeding, ensuring a natural feeding response. We did not measure SVL due to the potential impact of handling stress on feeding behaviour. All study animals were provided drinking water ad libitum .

During the growth trials in Vietnam, we recorded the length of time pythons went without food to examine the influence of fasting on growth and mass loss. Depending on prey size, pythons typically digest meals within two weeks (range = 4–13 days 34 ). To eliminate the influence of energy derived from previous food consumption we only considered pythons to be fasting if they had gone without food for at least 20 consecutive days. We used body mass measurements derived from feeding records before versus after fasting to calculate total mass lost during the fasting event. We divided total mass lost during the fasting event by the duration of each event to calculate mean mass loss per day.

Carcass processing

At the completion of the intensive growth trials, pythons were humanely killed using standard procedures (i.e., captive bolt pistol 35 ) and processed to record carcass characteristics. We dissected and weighed parts of the snake that are of commercial value, including the fat, gall bladder, skin, and dressed carcass (excluding head, tail, visceral organs and skin). We weighed the remaining organs and tissues to calculate the percentage of each item relative to total body mass. Finally, we calculated food conversion ratios (FCR) by dividing the total amount of food consumed by the mass of the dressed carcass.

Analysis of data

Because commercially valuable products from pythons are sold by mass, we mostly report rates of growth in body mass; however, in Fig.  1 and Table 2 we also provide growth rates as changes in SVL. Body mass in snakes is strongly correlated with SVL 36 . To assist with visualisation, we plotted variation in growth rates of individual pythons by presenting the growth rates of the 1 st , 25 th , 50 th , 75 th , and 99 th growth percentiles for pythons in each treatment. However, for our analysis we used the mean rate of growth from hatching to slaughter. We examined the influence of farm site and sex on growth rates for each python species in our non-intensive growth trials (separately) using a two-way analysis of variance (ANOVA) with sex and site (and their interaction) as factors, and growth rate over 12 months as the dependent variable.

figure 1

Change in snout-vent length (SVL) over time of ( a ) Burmese pythons in Vietnam, ( b ) reticulated pythons in Thailand, and ( c ) Burmese pythons in Thailand over a 12-month period. Solid lines show calculated averages (50th percentile) whereas dotted lines show other percentile values.

To explore the factors influencing variability in growth rates of Burmese pythons in our intensive trial, we modelled mean 12-month growth rate against five attributes of the pythons and their husbandry (ln mass at birth, diet, ln 2-month growth rate, total amount of food consumed, and days spent fasting) in a multiple regression. We used a model selection approach to rank all possible models (and two-way interaction terms) based on AIC c values 37 . We applied a one-way ANOVA with food type as the factor and growth rate over 12 months as the dependent variable to explore the potential influence of food type on rate of growth.

In some cases, our fasting dataset contained pythons that underwent multiple fasting events. We tested for differences in the likelihood of fasting between diet treatments using contingency table analysis. To account for pseudoreplication and the influence of individual-specific growth rates in our analysis, we analysed the influence of fasting duration, and the influence of mass prior to fasting, on the rate of loss of body mass using a generalized linear mixed model incorporating individual python ID as a random effect. We ln-transformed our data wherever necessary to meet the normality and homogeneity of variance assumptions required for our statistical tests, and conducted all analyses in JMP Pro 14 (SAS Institute: Cary, NC).

Ethics statement

We stress that no snakes were harmed for the purpose of our study; we utilised existing farm operations and trade. Our data were gathered from snakes bred for a commercial industry, which employs humane methods of killing reptiles (by brain destruction 38 ). All work was carried out with relevant permissions from the farm owners and authorities (Administration of Forestry of the Socialist Republic of Viet Nam 114/TCLN-CTVN). All procedures were approved by the Animal Ethics Screening Committee of the University of Witwatersrand, South Africa (approval number: 2014/17/B), the University of Adelaide, Australia (approval number: S-2018-084), were consistent with ARRIVE guidelines 39 , and all methods were performed in accordance with the relevant guidelines and regulations.

Growth rates

Both species of python grew rapidly at both farms (up to a maximum of 46 g/day; Tables 2 ,  S1 ; Figs. 1 , 2 ). Our ANOVA revealed that growth rates of Burmese pythons were slower at the Thai farm than at the Vietnamese farm (F 1,2591  = 1005, P  < 0.0001; Table 2 ) and females grew more rapidly than males at both farms (F 1,2591  = 8.97, P  < 0.0028; Table 2 ). Sex differences in growth did not vary between farms (interaction sex*site: F 1,2591  = 2.01, P  = 0.1559). At the Thai farm where both species were raised and husbandry and feeding procedures were similar, reticulated pythons grew faster than Burmese pythons held in the same facility (F 1,4526  = 124, P  < 0.0001) but still slower than Burmese pythons in Vietnam (Table 2 ; Fig.  2 ).

figure 2

Change in body mass over time of ( a ) Burmese pythons in Vietnam in intensive trials, ( b ) Burmese pythons in Vietnam in rapid growth trials, ( c ) reticulated pythons in Thailand, and ( d ) Burmese pythons in Thailand. All data were gathered over a 12-month period. Solid lines show calculated averages (50th percentile) whereas dotted lines show other percentile values.

Our most parsimonious model included growth rates over the first two months of life and the amount of food consumed (Fig.  3 ). Pythons that grew fastest in their first two months of life, and which consumed the most food, grew the fastest over the 12-month period (Figs. 1 , 2 , 3 ). The model with the best support that included only a single predictive variable included the amount of food consumed, confirming that food intake is the primary determinant of python growth rates (Fig.  3 ). A follow-up ANOVA with food type as the factor and ln 12-month growth rate as the dependent variable confirmed that the different food types provided as part of our experimental trials (Table S1 ) did not significantly influence growth rates in Burmese pythons (although this difference was close to statistical significance: F 4,54  = 2.50, P  = 0.054).

figure 3

Relationship between growth rate over the first 12 months of life in captive Burmese pythons, and two significant predictors of that long term rate of growth: ( a ) growth rate over the first two months of life, and ( b ) total amount of food consumed over 12 months. See text for results of statistical significance tests.

Influence of fasting

Over the course of our intensive growth study, 61% (43/70) of Burmese pythons fasted for periods of 20 days or more (up to 127 days). Some pythons fasted multiple times throughout the study, for a maximum fasting duration of 228 days. Fasting was recorded in pythons from all diet regimes and although the proportion of pythons fasting was higher in animals fed on the two diets containing fishmeal, contingency-table analysis confirmed that the difference was not statistically significant (χ 2 4  = 5.7, P  = 0.23). Mean daily mass loss during episodes of fasting was 0.16 ± 0.7 g per day. When calculated as a percentage of body mass prior to the fasting event, pythons lost an average of 0.004 ± 0.03% of their body mass per day. Some snakes gained body mass while fasting (likely due to drinking), and our mixed effects model showed no significant correlation between the rate of mass loss (or gain) and the duration of time spent fasting (F 1,72  = 1.89, P  = 0.174). Our mixed effects model also confirmed that larger pythons fasted for longer durations than did smaller conspecifics (F 1,72  = 9.08, P  = 0.0037). Although fasting did not result in a significant loss of body mass, it did reduce the total amount of food consumed, which significantly reduced overall growth rates.

Food conversion ratios and useable products

Mean food conversion ratio for the 58 snakes followed throughout their lives was 4.1: 1 (4.1 ± 0.06 g; range 3.15–4.85). That is, pythons consumed an average of 4.1 g of food for every 1 g of dressed carcass produced. The mass of commercially valuable body parts obtained from each snake increased with the mass of the animal (and hence, with its growth rate; all correlations have P  < 0.0001). After removal of non-useable organs, useable parts of the snake (including dressed carcass, gall bladder, fat, and skin) averaged 82 ± 0.8% (range: 69–90%) of overall snake mass (Table 3 ).

An extensive literature documents fast growth rates for pythons, and our experimental trials confirm that pythons can grow very rapidly over their first year of life. Despite this ability, pythons have been overlooked as a mainstream agricultural species 40 . Instead, concerns have been raised that commercial production of these snakes in captivity is not feasible and that Asian farms are simply laundering wild-caught snakes under the guise of being captive-bred 41 , 42 . We have no data to support or refute the latter claim, but our studies confirm earlier work that it is biologically and economically feasible to breed and raise pythons in captive production facilities for commercial trade 32 . We first discuss the significance and limitations of our results before turning our attention to the assessment of pythons as a novel livestock species for commercial agriculture.

Growth rates in both python species that we assessed were highly plastic and were strongly influenced by the amount of food consumed. Although fasting resulted in slower growth, variation in growth rates was best explained by overall food intake rates; that is, fasting pythons grow slower due to reduced food intake, but there did not appear to be any additional growth cost to fasting per se. In keeping with other studies on snakes, body mass at hatching did not influence growth rates. Instead, a snake’s growth trajectory over the first two months of its life predicted its subsequent growth rate and hence its body size later in life 43 .

Females of both species grew faster than males. Although female-biased growth rates are common in snakes, growth rates in pythons do not typically diverge until after reaching maturity 44 , 45 . We detected sexual divergence in growth rates well before maturation, suggesting that sex-based divergences in growth rate divergence are subtle and may only be detectable with large sample sizes such as those used in our study.

Pythons grew faster in the Vietnamese farm than in the Thai farm, likely due to a more frequent feeding regime. Although reticulated pythons grew faster than Burmese pythons in the Thai facility, where both species are maintained, we are reluctant to conclude that this species exhibits faster overall growth rates in the wild, or that the growth potential of the reticulated python exceeds that of the Burmese python. Growth rates are very flexible and driven primarily by food consumption. Burmese pythons in both trials in Vietnam had faster growth rates than did Thai reticulated pythons, and overall snakes in Thailand were offered less food than their Vietnamese conspecifics.

Why were the costs of fasting (in terms of mass loss) so low? Pythons have specialised physiological and morphological responses to both feeding and fasting 46 , 47 , 48 . The gastrointestinal tract is adapted for long periods of quiescence punctuated by rapid metabolic upregulation for digestion and assimilation of large meals (sometimes, > 100% of body mass 49 ). During digestion, pythons exhibit a tenfold increase in metabolic rate above resting levels; organ performance increases up to 40-fold; and circulating hormones and metabolites increase by as much as a 100-fold 46 , 47 , 48 . After digestion is completed, the process is reversed and metabolic functions are rapidly downregulated. Ingested macronutrients are partitioned and selectively oxidised in preparation for fasting 50 . Lipids are stored in specialised fat bodies and leveraged during fasting to fuel atrophic energy requirements 50 , 51 . Our study provides further evidence for these remarkable physiological processes and identifies their utilitarian potential in an agricultural context.

We now turn our attention to the agricultural potential of pythons as it relates to the biology of these snakes. As large-bodied, fast-growing ectotherms with flexible digestive physiologies, our study confirms that pythons have considerable agricultural potential. The pythons in our study were capable of high food conversion ratios and rapid growth rates, and can tolerate long periods of fasting without substantial loss of mass. The dietary treatments that we offered did not significantly influence growth rates of the snakes, suggesting that pythons exhibit efficient protein conversion ratios under a range of dietary and production scenarios. Our findings support previous studies highlighting the role of snake farms in facilitating efforts to control rodent pests, and in upcycling waste-protein resources to close nutrient cycle loops 20 , 21 , 32 , 52 .

Pythons are obligate carnivores, and thus belong to a trophic level (predators) that classical Lindeman trophic pyramids would regard as poorly suited to farming: that is, inefficient and environmentally unsustainable 53 , 54 . Our results suggest otherwise. Table 4 provides a comparison of some key production criteria in livestock systems. Production efficiencies for pythons were higher than those reported for poultry, pork, beef, salmon, and crickets (Table 4 ). This remarkable outcome reflects the synergistic effects of ectothermic physiology 16 , sessile behaviour 55 , efficient digestive physiology 56 , and economic serpentine morphology (e.g., no legs or wings ~ higher edible carcass ratio). High assimilation efficiencies also translate into low volumes of faeces, and the nitrogenous wastes that pythons produce are excreted as water-insoluble urates rather than more volatile urea 57 . Python farms, therefore, produce fewer greenhouse gasses (CO 2 , methane and nitrous oxide) than do endothermic livestock systems 58 , 59 .

One caveat to the rapid growth rates reported here is that in one of our diet treatments (Burmese pythons in Vietnam), a significant proportion (~ 20%) of pythons died due to respiratory infections. Similar growth rates of pythons from a different treatment at the same farm, and from Thailand, did not result in such high mortalities (< 5%). It is not known what caused such a high incidence of respiratory infection in one year, but the experimental diet (e.g., possible micronutrient deficiencies) coupled with unseasonably cool weather may be contributing factors.

The ability of pythons to fast for extended periods without jeopardizing survival or body condition is remarkable. For example, five 6-month-old pythons ceased feeding for four months (approximately 45% of their lives) but only lost 30 to 70 g (2.7–5.4% of their pre-fasting body mass) over that period. Few other animals can downregulate metabolic costs to this degree, and species utilized by the mainstream agricultural industry certainly cannot do so (Table 4 ). That ability of pythons to maintain near-stasis in body mass over prolonged periods of food deprivation confers great flexibility for producers. Food systems resilience is closely linked to disruptions in supply chains and famine tolerance 15 , 71 . Pandemics and extreme weather events coupled with the inability of livestock to retain body condition in the absence of reliable feed supplies present increasing risks to food security. Pythons offer farmers the flexibility needed to regulate both feed inputs and product outputs in response to unpredictable external factors.

In addition to flexibility in feeding regimes and rapid growth rates, the natural history of at least some species of pythons is characterised by early maturity and high reproductive output 31 , 72 . Most species are ecological generalists, exploiting both above- and below-ground habitat niches to evade extreme weather events 27 , 55 , 73 , 74 . They can survive without fresh water for extended periods 25 , 75 , and in captivity they have undemanding spatial requirements, especially since they are ambush foragers with highly sedentary lifestyles that co-exist amicably in communal aggregations 32 , 76 . They display few of the complex animal welfare issues commonly seen in caged birds and mammals 77 , 78 . Reptiles also seldom transmit endotherm-centric zoonotic viruses such as bird flu, swine flu or Covid-19 79 , 80 .

Despite their impressive physiologies, the hands-on production of pythons differs in several important ways to mainstream livestock. For example, feeding pythons can be labour-intensive because of the current necessity to remove them from their enclosures for individual feeding (to prevent agonistic encounters with conspecifics over food). However, this labour cost may be offset against the need to only feed pythons once per week. Technical expertise and capacity is another barrier to realising the agricultural potential of pythons. The biology and husbandry requirements of pythons are poorly understood relative to many endothermic taxa. Coupled with the general fear humans have towards snakes, it may be some time before the agricultural potential of pythons is realised at the global scale.

Commercial production of pythons is in its infancy, with farms receiving minimal scientific input or optimisation through formal channels for agricultural development. Even in its current relatively crude format, python farming appears to offer tangible benefits for sustainability and food systems resilience. Our study suggests that python farming can not only complement existing livestock systems, but may offer better returns in terms of production efficiencies. When compared to existing endotherm-based livestock industries, pythons are more efficient mass producers of animal protein. In countries with a cultural precedent for eating reptiles, and where food security is increasingly compromised through the impacts of global challenges such as climate change, reptiles offer an efficient, safe, and flexible source of protein. To exploit that potential, we urgently need more research into the agricultural potential of reptiles, and the most effective and humane ways to produce this novel group of livestock animals.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We thank Cao Tran Thinh, Cao Tran Tung, and Emilio and Liceno Malucchi for allowing us to use their python breeding facilities and specimens for our research. Thanks to Tomas Waller for assistance in collecting data from captive pythons. This study was undertaken with the support of the Python Conservation Partnership, the University of Witwatersrand Research Council, and the Carnegie Corporation of New York through the Global Change and Sustainability Research Institute.

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These authors contributed equally: D. Natusch and P. W. Aust.

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School of Natural Sciences, Macquarie University, Sydney, NSW, 2109, Australia

D. Natusch & R. Shine

Department of Zoology, University of Oxford, Oxford, UK

P. W. Aust & T. Coulson

Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg, South Africa

P. W. Aust & G. J. Alexander

School of Animal & Veterinary Science, The University of Adelaide, Adelaide, SA, 5371, Australia

C. Caraguel & P. L. Taggart

National Key Laboratory, Institute of Tropical Biology, Vietnamese Academy of Sciences and Technology, 9/621 Hanoi Highway, Thu Duc City, Ho Chi Minh City, Vietnam

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D.N. and P.A. defined the concept, D.N., P.A., V.T., C.C., and P.T. collected the data; all authors wrote the manuscript.

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None of the authors are involved in the meat industry, but this research took place on existing commercial snake farms. This work was partly funded by an initiative working to better understand snakes used in the leather trade, which is itself partially funded by companies that use snake skins. Funders had no influence at any stage of this research.

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Natusch, D., Aust, P.W., Caraguel, C. et al. Python farming as a flexible and efficient form of agricultural food security. Sci Rep 14 , 5419 (2024). https://doi.org/10.1038/s41598-024-54874-4

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man in blue shirt and briefcase walking away from camera in a environment with lines and circles connected together to look like a computer system

Since ChatGPT   dropped in the fall of 2022, everyone and their donkey has tried their hand at prompt engineering —finding a clever way to phrase your query to a large language model (LLM) or AI art or video generator to get the best results or sidestep protections . The Internet is replete with prompt-engineering guides , cheat sheets , and advice threads to help you get the most out of an LLM.

In the commercial sector, companies are now wrangling LLMs to build product copilots , automate tedious work , create personal assistants , and more, says Austin Henley, a former Microsoft employee who conducted a series of interviews with people developing LLM-powered copilots. “Every business is trying to use it for virtually every use case that they can imagine,” Henley says.

“The only real trend may be no trend. What’s best for any given model, dataset, and prompting strategy is likely to be specific to the particular combination at hand.” —Rick Battle & Teja Gollapudi, VMware

To do so, they’ve enlisted the help of prompt engineers professionally.

However, new research suggests that prompt engineering is best done by the model itself, and not by a human engineer. This has cast doubt on prompt engineering’s future—and increased suspicions that a fair portion of prompt-engineering jobs may be a passing fad, at least as the field is currently imagined.

Autotuned prompts are successful and strange

Rick Battle and Teja Gollapudi at California-based cloud computing company VMware were perplexed by how finicky and unpredictable LLM performance was in response to weird prompting techniques. For example, people have found that asking models to explain its reasoning step-by-step—a technique called chain-of-thought —improved their performance on a range of math and logic questions. Even weirder, Battle found that giving a model positive prompts, such as “this will be fun” or “you are as smart as chatGPT,” sometimes improved performance.

Battle and Gollapudi decided to systematically test how different prompt-engineering strategies impact an LLM’s ability to solve grade-school math questions. They tested three different open-source language models with 60 different prompt combinations each. What they found was a surprising lack of consistency. Even chain-of-thought prompting sometimes helped and other times hurt performance. “The only real trend may be no trend,” they write. “What’s best for any given model, dataset, and prompting strategy is likely to be specific to the particular combination at hand.”

According to one research team, no human should manually optimize prompts ever again.

There is an alternative to the trial-and-error-style prompt engineering that yielded such inconsistent results: Ask the language model to devise its own optimal prompt. Recently, new tools have been developed to automate this process. Given a few examples and a quantitative success metric, these tools will iteratively find the optimal phrase to feed into the LLM. Battle and his collaborators found that in almost every case, this automatically generated prompt did better than the best prompt found through trial-and-error. And, the process was much faster, a couple of hours rather than several days of searching.

The optimal prompts the algorithm spit out were so bizarre, no human is likely to have ever come up with them. “I literally could not believe some of the stuff that it generated,” Battle says. In one instance, the prompt was just an extended Star Trek reference: “Command, we need you to plot a course through this turbulence and locate the source of the anomaly. Use all available data and your expertise to guide us through this challenging situation.” Apparently, thinking it was Captain Kirk helped this particular LLM do better on grade-school math questions.

Battle says that optimizing the prompts algorithmically fundamentally makes sense given what language models really are—models. “A lot of people anthropomorphize these things because they ‘speak English.’ No, they don’t,” Battle says. “It doesn’t speak English. It does a lot of math.”

In fact, in light of his team’s results, Battle says no human should manually optimize prompts ever again.

“You’re just sitting there trying to figure out what special magic combination of words will give you the best possible performance for your task,” Battle says, “But that’s where hopefully this research will come in and say ‘don’t bother.’ Just develop a scoring metric so that the system itself can tell whether one prompt is better than another, and then just let the model optimize itself.”

Autotuned prompts make pictures prettier, too

Image-generation algorithms can benefit from automatically generated prompts as well. Recently, a team at Intel labs , led by Vasudev Lal , set out on a similar quest to optimize prompts for the image-generation model Stable Diffusion . “It seems more like a bug of LLMs and diffusion models, not a feature, that you have to do this expert prompt engineering,” Lal says. “So, we wanted to see if we can automate this kind of prompt engineering.”

“Now we have this full machinery, the full loop that’s completed with this reinforcement learning.… This is why we are able to outperform human prompt engineering.” —Vasudev Lal, Intel Labs

Lal’s team created a tool called NeuroPrompts that takes a simple input prompt, such as “boy on a horse,” and automatically enhances it to produce a better picture. To do this, they started with a range of prompts generated by human prompt-engineering experts. They then trained a language model to transform simple prompts into these expert-level prompts. On top of that, they used reinforcement learning to optimize these prompts to create more aesthetically pleasing images, as rated by yet another machine-learning model, PickScore , a recently developed image-evaluation tool.

Here too, the automatically generated prompts did better than the expert-human prompts they used as a starting point, at least according to the PickScore metric. Lal found this unsurprising. “Humans will only do it with trial and error,” Lal says. “But now we have this full machinery, the full loop that’s completed with this reinforcement learning.… This is why we are able to outperform human prompt engineering.”

Since aesthetic quality is infamously subjective, Lal and his team wanted to give the user some control over how the prompt was optimized. In their tool , the user can specify the original prompt (say, “boy on a horse”) as well as an artist to emulate, a style, a format, and other modifiers.

Lal believes that as generative AI models evolve, be it image generators or large language models, the weird quirks of prompt dependence should go away. “I think it’s important that these kinds of optimizations are investigated and then ultimately, they’re really incorporated into the base model itself so that you don’t really need a complicated prompt-engineering step.”

Prompt engineering will live on, by some name

Even if autotuning prompts becomes the industry norm, prompt-engineering jobs in some form are not going away, says Tim Cramer , senior vice president of software engineering at Red Hat . Adapting generative AI for industry needs is a complicated, multistage endeavor that will continue requiring humans in the loop for the foreseeable future.

“Maybe we’re calling them prompt engineers today. But I think the nature of that interaction will just keep on changing as AI models also keep changing.” —Vasudev Lal, Intel Labs

“I think there are going to be prompt engineers for quite some time, and data scientists,” Cramer says. “It’s not just asking questions of the LLM and making sure that the answer looks good. But there’s a raft of things that prompt engineers really need to be able to do.”

“It’s very easy to make a prototype,” Henley says. “It’s very hard to production-ize it.” Prompt engineering seems like a big piece of the puzzle when you’re building a prototype, Henley says, but many other considerations come into play when you’re making a commercial-grade product.

Challenges of making a commercial product include ensuring reliability—for example, failing gracefully when the model goes offline; adapting the model’s output to the appropriate format, since many use cases require outputs other than text; testing to make sure the AI assistant won’t do something harmful in even a small number of cases; and ensuring safety, privacy, and compliance. Testing and compliance are particularly difficult, Henley says, as traditional software-development testing strategies are maladapted for nondeterministic LLMs.

To fulfill these myriad tasks, many large companies are heralding a new job title: Large Language Model Operations, or LLMOps, which includes prompt engineering in its life cycle but also entails all the other tasks needed to deploy the product. Henley says LLMOps’ predecessors, machine learning operations (MLOps) engineers, are best positioned to take on these jobs.

Whether the job titles will be “prompt engineer,” “LLMOps engineer,” or something new entirely, the nature of the job will continue evolving quickly. “Maybe we’re calling them prompt engineers today,” Lal says, “But I think the nature of that interaction will just keep on changing as AI models also keep changing.”

“I don’t know if we’re going to combine it with another sort of job category or job role,” Cramer says, “But I don’t think that these things are going to be going away anytime soon. And the landscape is just too crazy right now. Everything’s changing so much. We’re not going to figure it all out in a few months.”

Henley says that, to some extent in this early phase of the field, the only overriding rule seems to be the absence of rules. “It’s kind of the Wild, Wild West for this right now.” he says.

  • How Coders Can Survive—and Thrive—in a ChatGPT World ›
  • Why OpenAI’s Codex Won’t Replace Coders ›
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Dina Genkina is an associate editor at IEEE Spectrum focused on computing and hardware. She holds a PhD in atomic physics and lives in Brooklyn.

James Intriligator

It is easy to optimize something when you know WHAT you are optimizing and what your final (correct) state might be. But, that is only a small part of what prompt engineering is about. The greater challenge (which has yet to be optimized!) is knowing what questions to ask, understanding what matters, and having a clear sense of what might be a correct end-state. That is easy to do with math problems. Much harder in the real-world! This analogy might help: just because a camera can auto-focus, doesn't mean photographers are out of work!

Eli Brosh

As prompt engineering increasingly relies on LLMs, it is worthwhile to note that some automatic prompt tuning methods, such as AutoPrompt (https://arxiv.org/pdf/2402.03099.pdf), achieve interpretable prompts by utilizing a synthetic benchmark of edge cases. These cases help to explain the reasoning and effectiveness behind certain prompts.

R Watkins

A) Whatever it is, it isn't engineering.

B) IEEE members should know better.

Supercomputing’s Future Is Green and Interconnected

The 5 spacecraft behind china’s moon rock sample mission, these courses will sharpen your knowledge on 6 emerging technologies, related stories, nvidia unveils blackwell, its next gpu, why are large ai models being red teamed, cerebras unveils its next waferscale ai chip.

BRIEF RESEARCH REPORT article

Writing performance in primary grade: exploring the links between cognitive and motivational variables provisionally accepted.

  • 1 Faculty of Psychology and Education Science, University of Porto, Portugal

The final, formatted version of the article will be published soon.

Current theoretical models of writing suggest that cognitive and motivational processes interact with each other during written production. However, despite the growing interest in motivational variables in writing, there are still few efforts to study them together with cognitive variables. Therefore, this study aimed to test the possibility that the cognitive processes of transcription and executive functions may be related to writing performance, through their link with the writing-motivational variables of self-efficacy and attitudes. For that, 157 Portuguese third and fourth graders planned and completed one opinion essay, performed transcription tasks, and completed motivation-related questionnaires. Furthermore, schoolteachers completed an executive function questionnaire about each student and provided their school grades. Results showed that motivation, specifically self-efficacy, did not predict Grade 3 and 4 writing performance. However, attitudes were predictors of written planning and text length. More specifically, attitudes and handwriting fluency contributed to text length just as attitudes and spelling accuracy contributed to written planning. There was no evidence of indirect effects from cognitive variables on writing performance via motivation variables. These findings provide original information on the links between cognition and motivation in writing, which may be useful to guide the teaching of writing. In line with effective instructional approaches to writing, current findings further support the importance of jointly targeting the cognitive and affective dimensions of writing.

Keywords: transcription, executive functions, attitudes, self-efficacy, Writing performance

Received: 17 Oct 2023; Accepted: 20 Mar 2024.

Copyright: © 2024 Rocha, Magalhães, Castro and Limpo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Teresa Limpo, Faculty of Psychology and Education Science, University of Porto, Porto, Portugal

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Our research allowed us to identify the campaign’s multiple connections with a China-nexus threat actor we track as Earth Lusca . However, since the campaign employs independent infrastructure and unique backdoors, we believe it to be a separate intrusion set that we named Earth Krahang. We will examine these connections, as well as potential links to a Chinese company named I-Soon, in a separate section.

One of the threat actor’s favorite tactics involves using its malicious access to government infrastructure to attack other government entities, abusing the infrastructure to host malicious payloads, proxy attack traffic, and send spear-phishing emails to government-related targets using compromised government email accounts. Earth Krahang also uses other tactics, such as building VPN servers on compromised public-facing servers to establish access into the private network of victims and performing brute-force attacks to obtain email credentials. These credentials are then used to exfiltrate victim emails, with the group’s ultimate goal being cyberespionage.

Due to mistakes on the attacker’s side, we managed to retrieve multiple files from Earth Krahang’s servers, including samples, configuration files, and log files from its attack tools. Combining this information with our telemetry helped us understand the Earth Krahang operation and build a clear view of the threat actor’s victimology and interests. In addition, we will also share their preferred malware families and post-exploitation tools in this report.

Reconnaissance and initial access

Infection chain of an Earth Krahang’s spear-phishing attack (see the MITRE ATT&CK section for the details of each technique ID)

One of the infection vectors used involves the scanning of public-facing servers. Earth Krahang heavily employs open-source scanning tools that perform recursive searches of folders such as .git or .idea . The threat actor also resorts to simply brute-forcing directories to help identify files that may contain sensitive information such as file paths or passwords on the victim’s servers. They also tend to examine the subdomains of their targets to find interesting and possible unmaintained servers. Earth Krahang also conducts vulnerability scanning with tools like sqlmap , nuclei , xray , vscan , pocsuite , and wordpressscan to find web server vulnerabilities  that will allow them to access the server, drop web shells, and install backdoors.

The threat actor abused the following vulnerabilities multiple times:

  • CVE-2023-32315 : command execution on OpenFire
  • CVE-2022-21587 : command execution on Oracle Web Applications Desktop Integrator

Earth Krahang also makes use of spear phishing email to attack its targets. Like most spear phishing attacks, the emails are intended trick their targets into opening attachments or embedded URL links that ultimately lead to the execution of a prepared backdoor file on the victim’s machine. Our telemetry data and some of the group’s backdoors uploaded on VirusTotal revealed that the backdoor filenames are usually related to geopolitical topics, indicating their preferred type of lure:

  • "Plan of Action (POA) - TH-VN - TH_Counterdraft_as of Feb 2022.doc.exe"
  • คำบอกกล่าวคำฟ้อง.rar (translated as “Notice of complaint.rar” )
  • “ร่างสถานะ ครม. รว. ไทย-โรมาเนีย as of 25 Feb 2022.doc.exe” (translated as “Draft Cabinet status of Thailand-Romania as of 25 Feb 2022.doc.exe”)
  • “Malaysian defense minister visits Hungary.Malaysian defense minister visits Hungary.exe”
  • “ICJ public hearings- Guyana vs. Venezuela.ICJ public hearings- Guyana vs. Venezuela.exe”
  • “On the visit of Paraguayan Foreign Minister to Turkmenistan.exe”
  • “pay-slip run persal payslip.pay-slip run persal payslip.docx.exe”

We noticed that Earth Krahang retrieves hundreds of email addresses from their targets during the reconnaissance phase. In one case, the actor used a compromised mailbox from a government entity to send a malicious attachment to 796 email addresses belonging to the same entity. The malicious attachment was a RAR archive containing an LNK file that deployed the Xdealer malware (which we will discuss in the Delivered malware families section) and opened a decoy document (available online) related to the governmental entity. It is likely that the actor discovered the weak credentials of the compromised mailbox using brute-forcing tools.

Earth Krahang abuses the trust between governments to conduct their attacks. We found that the group frequently uses compromised government webservers to host their backdoors and send download links to other government entities via spear phishing emails. Since the malicious link uses a legitimate government domain of the compromised server, it will appear less suspicious to targets and may even bypass some domain blacklists.

In addition, the actor used a compromised government email account to send email to other governments. We noticed the following email subjects being used for spear-phishing emails:

  • Malaysian Ministry of Defense Circular
  • Malaysian defense minister visits Hungary
  • ICJ public hearings- Guyana vs. Venezuela
  • About Guyana Procurement Proposal for Taiwan <redacted>

The Python script used by Earth Krahang to send spear-phishing emails to other governments via a stolen government account (redacted)

Our telemetry also showed that the threat actor compromised a government web server and leveraged it to scan vulnerabilities in other government targets.

Post-exploitation TTPs

The threat actor installs the SoftEther VPN on compromised public-facing servers and uses certutil commands to download and install the SoftEther VPN server. The SoftEther server executable is renamed to either taskllst.exe , tasklist.exe , or tasklist_32.exe for the Windows executable and curl for the Linux executable to make it look like a legitimate file on the installed system. With the VPN server installed, the actor can then connect to the victim’s network to conduct their post-exploitation movements.

Additional post-exploitation movements include:

  • Maintaining backdoor persistence with task scheduling
  • Enabling Remote Desktop connections by modifying the Windows Registry “fDenyTSConnections”
  • Accessing credentials by dumping Local Security Authority Subsystem Service (LSASS) with Mimikatz or ProcDump
  • Accessing credentials by dumping the SAM database ( HKLM/sam ) from the Windows Registry
  • Scanning the network using Fscan
  • Lateral code execution via WMIC
  • Using tools such as BadPotato, SweetPotato, GodPotato, or PrinterNotifyPotato for privilege escalation on Windows systems
  • Exploiting CVE-2021-4034, CVE-2021-22555, and CVE-2016-5195 for privilege escalation on Linux systems

Email exfiltration

We observed Earth Krahang conducting brute force attacks on Exchange servers via their Outlook on the web (formerly known as Outlook Web Access, or OWA) portals of its victims. The threat uses a list of common passwords to test the email accounts on the target’s email server.  We have observed the group using a custom Python script targeting the ActiveSync service on the OWA server to perform their brute-force attack.

We also found the threat actor using the open-source tool ruler to brute force email accounts and passwords. Email accounts using weak passwords can be identified by the attacker, who can then perform email exfiltration or abuse the compromised account to send spear phishing emails (as we discussed earlier).

We also identified another Python script that the actor used to exfiltrate emails from a Zimbra mail server. The script can package the victim’s mailbox via the mail server API using an authenticated cookie stolen by the threat actor. However, our investigation was unable to determine how the authenticated tokens were stolen from the victim’s server.

The Python script used by Earth Krahang to exfiltrate the victim’s mailbox

Delivered malware families

Earth Krahang delivers backdoors to establish access to victim machines. Cobalt Strike and two custom backdoors, RESHELL and XDealer, were employed during the initial stage of attack. We found that these backdoors were delivered either through spear-phishing emails or deployed via web shell on compromised servers.

We found the RESHELL backdoor being used several times in attacks during 2022. It was mentioned being used in a targeted attack against a Southeast Asian government by Palo Alto in a previous research report . RESHELL is a simple .NET backdoor that possesses the basic capabilities of collecting information, dropping files, or executing system commands. Its binaries are packed with ConfuserEX and its command-and-control (C&C) communication is encrypted with the AES algorithm.

Since 2023, the Earth Krahang shifted to another backdoor (named XDealer by TeamT5 and DinodasRAT by ESET). Compared to RESHELL, XDealer provides more comprehensive backdoor capabilities. In addition, we found that the threat actor employed both Windows and Linux versions of XDealer to target different systems.

Each XDealer sample embeds a mark string that represents the backdoor’s version. We observed the following marks:

Table 1. The list of the identified marks embedded on XDealer samples

This finding indicates that the backdoor may have been used in the wild for some time now and is still under active development.

It's worth noting that many early XDealer samples were developed as a DLL file packaged with an installer, a stealer module DLL, a text file contents ID string, and an LNK file. The LNK file executes the installer, which then installs the XDealer DLL and the stealer module DLL on the victim’s machine. The stealer module can take screenshots, steal clipboard data, and log keystrokes.

In one case, we found that the LNK file was replaced with another executable, which is an installer loader (it’s likely that Earth Krahang employed a different execution scheme instead of a standalone executable). Furthermore, we found that some of the XDealer DLL loaders were signed with valid code signing certificates issued by GlobalSign to two Chinese companies. According to public information available on the internet, one is a human resource company, while the other is a game development company. It’s likely that their certificates were stolen and abused to sign malicious executables.

Table 2. The list of packages delivering XDealer DLL and other files

Table 3. The list of certificates abused to sign the XDealer loader

Cobalt Strike was also frequently used during the initial stage of an attack. Interestingly, we found that instead of the typical Cobalt Strike usage, Earth Krahang adds additional protection to their C&C server through the adoption of the open-source project RedGuard , which is basically a proxy that helps red teams hinder the discovery of their Cobalt Strike C&C profile.

The threat actor abused RedGuard to prevent its C&C servers from being identified by blue team Cobalt Strike C&C scanners or search engine web crawlers. It also helps the group monitor who is collecting their C&C profiles. We found that Earth Krahang’s C&C server redirected invalid C&C requests to security vendor websites due to RedGuard’s protections.

Cobalt Strike exploits the DLL side-loading vulnerability. In one case we analyzed, the threat actor dropped three files, fontsets.exe , faultrep.dll , and faultrep.dat . The file fontsets.exe (SHA256: 97c668912c29b8203a7c3bd7d5d690d5c4e5da53) is a legitimate executable that was abused to side-load the DLL file faultrep.dll (SHA256: a94d0e51df6abbc4a7cfe84e36eb8f38bc011f46).

The faultrep.dll  file is a custom shellcode loader that will decode the encoded shellcode — which is Cobalt Strike — stored inside faultrep.dat . We also found another DLL loader with a similar decoding routine, but with different byte values for decoding and loads shellcode from a different filename ( conf.data ).

Using our telemetry data, we found that the threat actor also dropped PlugX and ShadowPad samples in victim environments. The PlugX sample, named fualtrep.dll , is likely used for side-loading, similar to the Cobalt Strike routine mentioned above. The ShadowPad samples had the exact same characteristics as seen in our previous Earth Lusca report .

Victimology

We found approximately 70 different victims (organizations that were confirmed to be compromised) spread across 23 different countries. Since we had access to some of Earth Krahang’s logs, we were also able to identify 116 different targets (including those that were not confirmed to be compromised) in 35 countries.

In total, the threat actor was able to compromise or target victims in 45 different countries spread across different regions, most of them in Asia and America, but also in Europe and Africa.

The map of victims targeted by Earth Krahang (countries in red are those that at least one entity compromised, while countries in yellow are those with at least one entity targeted)

Government organizations seem to be Earth Krahang’s primary targets. As an example, in the case of one country, we found that the threat actor compromised a diverse range of organizations belonging to 11 different government ministries.

We found that at least 48 government organizations were compromised, with a further 49 other government entities being targeted. Foreign Affairs ministries and departments were a top target, compromising 10 such organizations and targeting five others.

Education is another sector of interest to the threat actor. We found at least two different victims and 12 targets belonging to this sector. The communications industry was also targeted; we found multiple compromised telecommunications providers. Other target organizations and entities include post offices (targeted in at least three different countries), logistics platforms, and job services.

There were other industries targeted, but on a smaller scale, including the following:

  • Finance/Insurance
  • Foundations/NGOs/Thinkthanks
  • Manufacturing
  • Real estate

Attribution

Initially, we had no attribution for this campaign since we found no infrastructure overlaps, and had never seen the RESHELL malware family before. Palo Alto published a report that attributes, with moderate confidence, a particular cluster using RESHELL malware to GALLIUM . However, the assessment is based on a toolset that is shared among many different threat actors, and we were hesitant to use this link for proper attribution.  We also considered the possibility that RESHELL is a shared malware family.

Earth Krahang switched to the XDealer malware family in later campaigns. In a research paper presented by TeamT5, XDealer was shown to be associated with Luoyu , a threat actor with Chinese origins that used the WinDealer and ReverseWindow malware families. Our colleague, who was previously involved in the research of Luoyu, shared with us the insights on this association, particularly the sharing of an encryption key between an old XDealer sample and a SpyDealer sample — suggesting a connection between both malware families. ESET, which named this malware DinodasRAT, wrote an extensive report on its features. However they had no particular attribution apart from the possible China-nexus origin.

While we believe it could be possible that this campaign has links to LuoYu, we found no traces of other malware families used by this threat actor. Also, the encryption key mentioned above is different from the samples we found in this campaign, meaning that this malware family has multiple builders. This could suggest that either the key was changed at some point in development, or that the tool is shared among different groups.

In January 2022, we reported on a China-nexus threat actor we called Earth Lusca , following up with updates on their use of a newly discovered backdoor named SprySOCKS and their recent activities capitalizing on the Taiwanese presidential election. During our investigation, we noticed malware being downloaded from IP addresses we attribute to Earth Lusca (45[.]32[.]33[.]17 and 207[.]148[.]75[.]122, for example) at the lateral movement stage of this campaign. This suggests a strong link between this threat actor and Earth Lusca. We also found infrastructure overlaps between some C&C servers that communicated with malware we found during our investigation, and domain names such as googledatas[.]com that we attribute to Earth Lusca.

While the infrastructure and the preference of the initial stage backdoors look to be very different between this new campaign and the previously reported activities of Earth Lusca, our speculation is that they are two intrusion sets running independently but targeting a similar range of victims, becoming more intertwined as they approach their goal — possibly even being  managed by the same threat group. Due to these characteristics, we decided to give the independent name, Earth Krahang, to this intrusion set.

Our previous report suggests Earth Lusca might be the penetration team behind the Chinese company I-Soon, which had their information leaked on GitHub recently. Using this leaked information, we found that the company organized their penetration team into two different subgroups. This could be the possible reason why we saw two independent clusters of activities active in the wild but with limited association. Earth Krahang could be another penetration team under the same company.

In this report, we shared our investigation on a new campaign we named Earth Krahang. Our findings show that this threat actor focuses its efforts on government entities worldwide and abuses compromised government infrastructure to enable its malicious operations.

We were also able to identify two unique malware families used in Earth Krahang’s attacks while also illustrating the larger picture involving the group’s targets and malicious activities via our telemetry data and the exposed files on their servers.

Our investigation also identified multiple links between Earth Krahang and Earth Lusca. We suspected these two intrusion sets are managed by the same threat actor.

Given the importance of Earth Krahang’s targets and their preference of using compromised government email accounts, we strongly advise organizations to adhere to security best practices, including educating employees and other individuals involved with the organization on how to avoid social engineering attacks, such as developing a healthy skepticism when it involves potential security issues, and developing habits such as refraining from clicking on links or opening attachments without verification from the sender. Given the threat actor’s exploitation of vulnerabilities in its attacks, we also encourage organizations to update their software and systems with the latest security patches to avoid any potential compromise.

Indicators of Compromise

The indicators of compromise for this entry can be found here .

Acknowledgment

Special thanks to Leon M Chang who shared to us insights about the overlap of  the TEA encryption key between XDealer and SpyDealer samples.

MITRE ATT&CK

The listed techniques are a subset of the MITRE ATT&CK list .

Joseph C Chen

Threat Researcher

Daniel Lunghi

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2024 NCAA Tournament bracket predictions: March Madness expert picks, winners, favorites to win, upsets

Our experts have filled out their brackets, so check who they predict will be cutting down the nets.

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After the field of 68 teams chasing the national title was officially revealed on Selection Sunday, we're down to 66 after Tuesday's wins by Wagner and Colorado State during First Four games. We'll be down to 64 by the end of Wednesday.   

Now all that's left is to make picks for the start of Thursday's first round.

Our CBS Sports experts did exactly that below. We've spent months on end watching, analyzing and projecting teams. We've stayed up late to catch games in the Mountain West and Pac-12. We've woken up early to grind film and interview players and coaches. We've now filled out our brackets below using all that accumulated knowledge in an attempt to help guide you through your own picks.

Think of this as a cheat sheet, if you will. You're more than welcome to autofill your bracket using my picks -- and honestly I wouldn't blame you, seeing as I won our pool last year -- but there's also no shame in leaning on our brackets as a crutch. Have strong feelings about Purdue but didn't catch a Nevada game? Curious about what GP thinks about Tennessee's chances to make the Final Four? You can check out different sections below and get a feel for how we as a team collectively see the bracket before it all busts.

It's not March without brackets.  Get your bracket pools ready now  and join our men's and women's challenges for the chance to win big-time prizes! 

OK, let's dive into the good stuff: The brackets. ...  

2024 NCAA Tournament bracket predictions

Click each bracket to enlarge.

Gary Parrish

Watching UConn become the first back-to-back national champion since Florida in 2006 and 2007 would be a blast. And let the record show that the Huskies are the betting-market favorites. So I realize picking against them might prove dumb. But, that acknowledged, I'm going to continue to do what I've been doing most of this season and put my faith in the Boilermakers. Wouldn't that be a great story -- Purdue winning the 2024 NCAA Tournament after losing to a No. 16 seed in the opening round of the 2023 NCAA Tournament? Zach Edey holding the championship trophy as a two-time National Player of the Year? Matt Painter shedding his label as the best coach yet to make a Final Four by becoming the first coach to take Purdue to the final weekend of the season since 1980? It's all such good stuff. Just getting to the Final Four will be challenging considering Tennessee, Creighton and Kansas are also in the MIdwest Region. But I'm still taking the Boilermakers to make it to Arizona. And then, once they get there, I think they'll win two more games and cut nets on the second Monday in April.

Matt Norlander

A locomotive screaming down the tracks. The 31-3 reigning national champions enter this NCAA Tournament as the strongest team with the best chance to repeat of any squad since Florida in 2007. Dan Hurley's Huskies are led by All-American guard Tristen Newton (15.2 ppg, 7.0 rpg, 6.0 apg), who holds the school record for triple-doubles. In the middle is 7-foot-2 "Cling Kong," Donvan Clingan, a menace of a defender and the type of player you can't simulate in practice. The Huskies boast the nation's most efficient offense (126.6 adjusted points per 100 possessions, via KenPom.com) and overwhelm teams in a variety of ways. Sophomore Alex Karaban (39.5%) and senior Cam Spencer (44.4%) are both outstanding 3-point shooters. The Huskies have been beaten by Kansas, Seton Hall and Creighton, but all of those were road games, and there are no more road games left this season. UConn will try to become the fourth No. 1 overall seed to win the national title, joining 2007 Florida, 2012 Kentucky and 2013 Louisville.

The antagonistic side of me initially picked Purdue over UConn in the title game. But I sat and thought about it and couldn't make any reasonable case to pick any team other than UConn as champion. Of course, that doesn't guarantee the Huskies win it all and become the first repeat champs since Florida in 2007. There's a lot that can happen in the next few weeks. But they have the electric offense, the guard depth, the size down low, the shooting [takes breath] .. the passing and the pizzazz of a team that's best in the country and knows it. Every top team in this field has a high level at which they can play but no one has a top gear like UConn.

Get every pick, every play, every upset and fill out your bracket with our help! Visit SportsLine now to see which teams will make and break your bracket, and see who will cut down the nets , all from the model that nailed a whopping 20 first-round upsets by double-digit seeds.

Purdue is set for redemption after an embarrassing 2023 loss to No. 16 seed Fairleigh Dickinson in the first round. This time around, the Boilermakers are a much better 3-point shooting team and have a more favorable path than No. 1 overall seed UConn. The Huskies were the most dominant team leading up to the Big Dance the East Region bracket is filled with peril.

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This is not the Purdue you have seen the last few years. Braden Smith has made a big jump from last season to this one. Fletcher Loyer is better. Lance Jones gives Purdue defense, shooting and another ball handler. And Zach Edey is better too. This is a team on a mission. This is the year they accomplish it.

Dennis Dodd

What is there not to like? The Heels won the ACC regular season. They beat Tennessee and swept Duke. RJ Davis is an elite guard and ACC Player of the Year. Hubert Davis has settled in after going to the national championship game in his first season and missing the tournament in his second. This is his best team. There will be/and always is pressure to win it all. 

Armando Bacot is not as dominating as previous. Harrison Ingram (Stanford) and Cormac Ryan (Notre Dame) have been big additions in the portal. The West Region is friendly, assuming here that Alabama and Michigan State don't get in the way before the regional in L.A. An interesting regional final against Arizona looms. In the end, sometimes you go with chalk. UNC has been to the most Final Fours (21) and No. 1 seeds (18) all-time. It is tied with Kentucky for the most tournament wins ever (131). This is what the Heels do.

Chip Patterson

The selection committee set up plenty of stumbling blocks for the reigning champs, placing what I believe to be the best No. 1 seed, the best No. 2 seed (Iowa State), the best No. 3 seed (Illinois) and the best No. 4 seed (Auburn) in the Huskies bracket. And if accomplishing a historic feat like the first back-to-back title runs since 2007 is going to require that kind of epic journey, UConn has every skill and tool needed to make it back to the top of the mountain. UConn can win in all different ways, overwhelming teams with their offense in high-scoring track meets or out-executing the opponent in low-possession grinders, and it has a handful of key contributors who could each step up as needed during a title run.

Cameron Salerno

Defense wins championships. That is part of the reason why I'm picking Houston to win it all. The Cougars have the top-ranked scoring defense in the country and terrific guard play on offense to complement it. Jamal Shead is arguably the best point guard in the nation, and J'wan Roberts is an X-Factor on both ends of the floor. Houston's path to the Final Four is favorable. The Cougars weren't able to reach the Final Four in their home state last spring, but this will be the year they run the table and win their first national championship in program history.

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    Adhering to scholarly ethics in writing research articles is paramount. By mastering the foundations of strong research article writing, including structure, language use, and integrity, scholars can effectively share their work while advancing knowledge for the betterment of their discipline. Choosing a Compelling Research Topic

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    Writing a Research Article can be an unbelievably daunting task, but it is a vital skill for any researcher or academic. This blog post intends to provide a detailed instruction on how to create a Research Paper. It will delve into the crucial elements of a Research Article, including its format, various types, and how it differs from a Research Paper.

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    Writing is an essential but complex skill that students must master if they are to take full advantage of educational, occupational, and civic responsibilities. Schools, and the teachers who work in them, are tasked with teaching students how to write. Knowledge about how to teach writing can be obtained from many different sources, including one's experience teaching or being taught to ...

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    Title. The title should be descriptive yet concise while conveying the essential features of the contents of the article. The title should contain words that will make the article accessible to workers in the field. Clarity, brevity and above all human interest are the hallmarks of a good title.

  22. The best AI tools for research papers and academic research (Literature

    With AI as your research assistant, you can navigate the vast sea of scientific research with ease, uncovering citations and focusing on academic writing. It's a revolutionary way to take on literature reviews. Elicit - https://elicit.org; Supersymmetry.ai: https://www.supersymmetry.ai; Semantic Scholar: https://www.semanticscholar.org

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  24. Something felt 'off'

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  29. Earth Krahang Exploits Intergovernmental Trust to Launch Cross

    Earth Krahang switched to the XDealer malware family in later campaigns. In a research paper presented by TeamT5, XDealer was shown to be associated with Luoyu, a threat actor with Chinese origins that used the WinDealer and ReverseWindow malware families. Our colleague, who was previously involved in the research of Luoyu, shared with us the ...

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