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Integrating Clinical Trials and Practice : A New JAMA Series and Call for Papers

• 1 Executive Editor, JAMA
• Special Communication The Integration of Clinical Trials With the Practice of Medicine Derek C. Angus, MD, MPH; Alison J. Huang, MD, MAS; Roger J. Lewis, MD, PhD; Amy P. Abernethy, MD, PhD; Robert M. Califf, MD; Martin Landray, PhD; Nancy Kass, ScD; Kirsten Bibbins-Domingo, PhD, MD, MAS; JAMA Summit on Clinical Trials Participants; Ali B Abbasi; Kaleab Z Abebe; Amy P Abernethy; Stacey J. Adam; Derek C Angus; Jamy Ard; Rachel A Bender Ignacio ; Scott M Berry; Deepak L. Bhatt; Kirsten Bibbins-Domingo; Robert O. Bonow; Marc Bonten; Sharon A. Brangman; John Brownstein; Melinda J. B. Buntin; Atul J Butte; Robert M. Califf; Marion K Campbell; Anne R. Cappola; Anne C Chiang; Deborah Cook; Steven R Cummings; Gregory Curfman; Laura J Esserman; Lee A Fleisher; Joseph B Franklin; Ralph Gonzalez; Cynthia I Grossman; Tufia C. Haddad; Roy S. Herbst; Adrian F. Hernandez; Diane P Holder; Leora Horn; Grant D. Huang; Alison Huang; Nancy Kass; Rohan Khera; Walter J. Koroshetz; Harlan M. Krumholz; Martin Landray; Roger J. Lewis; Tracy A Lieu; Preeti N. Malani; Christa Lese Martin; Mark McClellan; Mary M. McDermott; Stephanie R. Morain; Susan A Murphy; Stuart G Nicholls; Stephen J Nicholls; Peter J. O'Dwyer; Bhakti K Patel; Eric Peterson; Sheila A. Prindiville; Joseph S. Ross; Kathryn M Rowan; Gordon Rubenfeld; Christopher W. Seymour; Rod S Taylor; Joanne Waldstreicher; Tracy Y. Wang JAMA
• Viewpoint Why Should the FDA Focus on Pragmatic Clinical Research? Ali B. Abbasi, MD; Lesley H. Curtis, PhD; Robert M. Califf, MD JAMA

Randomized clinical trials remain the cornerstone of evidence-based medicine. As a leading medical journal publishing the science that advances the clinical care of patients and the health of the public, JAMA is committed to the publication of clinical trials, as well as promoting the discourse on how clinical trial evidence can best serve the needs of patients and clinicians.

In autumn of 2023, JAMA hosted its inaugural in-person JAMA Summit 1 on the topic of randomized clinical trials and the challenges and opportunities to improve their design and conduct to be most responsive to the needs of clinical practice. The Special Communication published in JAMA, 2 “The Integration of Clinical Trials With the Practice of Medicine: Repairing a House Divided,” was written on behalf of the participants in the JAMA Summit and outlines many of the themes discussed during this provocative 2-day meeting.

A central theme of the JAMA Summit, which is elaborated on in the Special Communication in this issue, is how best to integrate clinical trials with clinical practice. Traditionally, clinical trialists and clinicians have worked independently, and, as the authors of the Special Communication underscore, their separate missions, incentives, and infrastructures have been siloed. The result is inefficiency in the performance of trials and limitations in their scope and impact. The authors offer solutions, including advances in implementation science, novel approaches to statistical analysis of trial data, and integration of trials with the electronic health record as a very rich source of clinical data. The clinical trial and health care delivery disciplines have functioned as a house divided. The authors proffer an approach to bridging the gap.

The future of clinical medicine will be greatly influenced by the data derived from randomized clinical trials, and trials will need to be accomplished more quickly, efficiently, and cheaply than they are today. A recent example is the platform trials 3 that were conducted during the COVID-19 pandemic. 4 - 6 These trials were embedded within clinical care and permitted the study of multiple therapeutic interventions simultaneously, with the results applicable to patient care in short order. The platform trials are exemplary of the types of novel approaches to clinical trials that are needed to realign the house divided.

With this Special Communication and an accompanying Viewpoint, 7 we launch a new series in JAMA— Integrating Clinical Trials and Practice. JAMA invites submissions that explore innovations in clinical trial design, implementation, funding, regulation, education, and application that may bring randomized trial evidence to more effectively address the needs in clinical practice. Our goal is to engage the research community in a significant publishing project to advance clinical trials and better align them with clinical practice. We welcome articles of any type, and we are happy to hear from you with presubmission inquiries. We are eager to chart a new path for randomized clinical trials and the delivery of health care, and we hope you will participate in navigating the road ahead.

Published Online: June 3, 2024. doi:10.1001/jama.2024.10266

Corresponding Author: Greg Curfman, MD, JAMA, Editorial Office, 330 N Wabash Ave, Chicago, IL 60611 ( [email protected] ).

Conflict of Interest Disclosures: None reported.

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Curfman G. Integrating Clinical Trials and Practice : A New JAMA Series and Call for Papers . JAMA. Published online June 03, 2024. doi:10.1001/jama.2024.10266

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What makes a high quality clinical research paper?

Affiliation.

• 1 BMJ, London, UK. [email protected]
• PMID: 20233312
• DOI: 10.1111/j.1601-0825.2010.01663.x

The quality of a research paper depends primarily on the quality of the research study it reports. However, there is also much that authors can do to maximise the clarity and usefulness of their papers. Journals' instructions for authors often focus on the format, style, and length of articles but do not always emphasise the need to clearly explain the work's science and ethics: so this review reminds researchers that transparency is important too. The research question should be stated clearly, along with an explanation of where it came from and why it is important. The study methods must be reported fully and, where appropriate, in line with an evidence based reporting guideline such as the CONSORT statement for randomised controlled trials. If the study was a trial the paper should state where and when the study was registered and state its registration identifier. Finally, any relevant conflicts of interest should be declared.

Publication types

• Clinical Trials as Topic*
• Ethics, Research*
• Guidelines as Topic
• Journalism, Medical / standards*
• Periodicals as Topic
• Publishing / standards*
• Writing / standards*

JAY SIWEK, M.D., MARGARET L. GOURLAY, M.D., DAVID C. SLAWSON, M.D., AND ALLEN F. SHAUGHNESSY, PHARM.D.

Am Fam Physician. 2002;65(2):251-258

Traditional clinical review articles, also known as updates, differ from systematic reviews and meta-analyses. Updates selectively review the medical literature while discussing a topic broadly. Nonquantitative systematic reviews comprehensively examine the medical literature, seeking to identify and synthesize all relevant information to formulate the best approach to diagnosis or treatment. Meta-analyses (quantitative systematic reviews) seek to answer a focused clinical question, using rigorous statistical analysis of pooled research studies. This article presents guidelines for writing an evidence-based clinical review article for American Family Physician . First, the topic should be of common interest and relevance to family practice. Include a table of the continuing medical education objectives of the review. State how the literature search was done and include several sources of evidence-based reviews, such as the Cochrane Collaboration, BMJ's Clinical Evidence , or the InfoRetriever Web site. Where possible, use evidence based on clinical outcomes relating to morbidity, mortality, or quality of life, and studies of primary care populations. In articles submitted to American Family Physician , rate the level of evidence for key recommendations according to the following scale: level A (randomized controlled trial [RCT], meta-analysis); level B (other evidence); level C (consensus/expert opinion). Finally, provide a table of key summary points.

American Family Physician is particularly interested in receiving clinical review articles that follow an evidence-based format. Clinical review articles, also known as updates, differ from systematic reviews and meta-analyses in important ways. 1 Updates selectively review the medical literature while discussing a topic broadly. An example of such a topic is, “The diagnosis and treatment of myocardial ischemia.” Systematic reviews comprehensively examine the medical literature, seeking to identify and synthesize all relevant information to formulate the best approach to diagnosis or treatment. Examples are many of the systematic reviews of the Cochrane Collaboration or BMJ's Clinical Evidence compendium. Meta-analyses are a special type of systematic review. They use quantitative methods to analyze the literature and seek to answer a focused clinical question, using rigorous statistical analysis of pooled research studies. An example is, “Do beta blockers reduce mortality following myocardial infarction?”

The best clinical review articles base the discussion on existing systematic reviews and meta-analyses, and incorporate all relevant research findings about the management of a given disorder. Such evidence-based updates provide readers with powerful summaries and sound clinical guidance.

In this article, we present guidelines for writing an evidence-based clinical review article, especially one designed for continuing medical education (CME) and incorporating CME objectives into its format. This article may be read as a companion piece to a previous article and accompanying editorial about reading and evaluating clinical review articles. 1 , 2 Some articles may not be appropriate for an evidence-based format because of the nature of the topic, the slant of the article, a lack of sufficient supporting evidence, or other factors. We encourage authors to review the literature and, wherever possible, rate key points of evidence. This process will help emphasize the summary points of the article and strengthen its teaching value.

Topic Selection

Choose a common clinical problem and avoid topics that are rarities or unusual manifestations of disease or that have curiosity value only. Whenever possible, choose common problems for which there is new information about diagnosis or treatment. Emphasize new information that, if valid, should prompt a change in clinical practice, such as the recent evidence that spironolactone therapy improves survival in patients who have severe congestive heart failure. 3 Similarly, new evidence showing that a standard treatment is no longer helpful, but may be harmful, would also be important to report. For example, patching most traumatic corneal abrasions may actually cause more symptoms and delay healing compared with no patching. 4

Searching the Literature

When searching the literature on your topic, please consult several sources of evidence-based reviews ( Table 1 ) . Look for pertinent guidelines on the diagnosis, treatment, or prevention of the disorder being discussed. Incorporate all high-quality recommendations that are relevant to the topic. When reviewing the first draft, look for all key recommendations about diagnosis and, especially, treatment. Try to ensure that all recommendations are based on the highest level of evidence available. If you are not sure about the source or strength of the recommendation, return to the literature, seeking out the basis for the recommendation.

In particular, try to find the answer in an authoritative compendium of evidence-based reviews, or at least try to find a meta-analysis or well-designed randomized controlled trial (RCT) to support it. If none appears to be available, try to cite an authoritative consensus statement or clinical guideline, such as a National Institutes of Health Consensus Development Conference statement or a clinical guideline published by a major medical organization. If no strong evidence exists to support the conventional approach to managing a given clinical situation, point this out in the text, especially for key recommendations. Keep in mind that much of traditional medical practice has not yet undergone rigorous scientific study, and high-quality evidence may not exist to support conventional knowledge or practice.

Patient-Oriented vs. Disease-Oriented Evidence

With regard to types of evidence, Shaughnessy and Slawson 5 – 7 developed the concept of Patient-Oriented Evidence that Matters (POEM), in distinction to Disease-Oriented Evidence (DOE). POEM deals with outcomes of importance to patients, such as changes in morbidity, mortality, or quality of life. DOE deals with surrogate end points, such as changes in laboratory values or other measures of response. Although the results of DOE sometimes parallel the results of POEM, they do not always correspond ( Table 2 ) . 2 When possible, use POEM-type evidence rather than DOE. When DOE is the only guidance available, indicate that key clinical recommendations lack the support of outcomes evidence. Here is an example of how the latter situation might appear in the text: “Although prostate-specific antigen (PSA) testing identifies prostate cancer at an early stage, it has not yet been proved that PSA screening improves patient survival.” (Note: PSA testing is an example of DOE, a surrogate marker for the true outcomes of importance—improved survival, decreased morbidity, and improved quality of life.)

Evaluating the Literature

Evaluate the strength and validity of the literature that supports the discussion (see the following section, Levels of Evidence). Look for meta-analyses, high-quality, randomized clinical trials with important outcomes (POEM), or well-designed, nonrandomized clinical trials, clinical cohort studies, or case-controlled studies with consistent findings. In some cases, high-quality, historical, uncontrolled studies are appropriate (e.g., the evidence supporting the efficacy of Papanicolaou smear screening). Avoid anecdotal reports or repeating the hearsay of conventional wisdom, which may not stand up to the scrutiny of scientific study (e.g., prescribing prolonged bed rest for low back pain).

Look for studies that describe patient populations that are likely to be seen in primary care rather than subspecialty referral populations. Shaughnessy and Slawson's guide for writers of clinical review articles includes a section on information and validity traps to avoid. 2

Levels of Evidence

Readers need to know the strength of the evidence supporting the key clinical recommendations on diagnosis and treatment. Many different rating systems of varying complexity and clinical relevance are described in the medical literature. Recently, the third U.S. Preventive Services Task Force (USPSTF) emphasized the importance of rating not only the study type (RCT, cohort study, case-control study, etc.), but also the study quality as measured by internal validity and the quality of the entire body of evidence on a topic. 8

While it is important to appreciate these evolving concepts, we find that a simplified grading system is more useful in AFP . We have adopted the following convention, using an ABC rating scale. Criteria for high-quality studies are discussed in several sources. 8 , 9 See the AFP Web site ( www.aafp.org/afp/authors ) for additional information about levels of evidence and see the accompanying editorial in this issue discussing the potential pitfalls and limitations of any rating system.

Level A (randomized controlled trial/meta-analysis): High-quality randomized controlled trial (RCT) that considers all important outcomes. High-quality meta-analysis (quantitative systematic review) using comprehensive search strategies.

Level B (other evidence): A well-designed, nonrandomized clinical trial. A nonquantitative systematic review with appropriate search strategies and well-substantiated conclusions. Includes lower quality RCTs, clinical cohort studies, and case-controlled studies with non-biased selection of study participants and consistent findings. Other evidence, such as high-quality, historical, uncontrolled studies, or well-designed epidemiologic studies with compelling findings, is also included.

Level C (consensus/expert opinion): Consensus viewpoint or expert opinion.

Each rating is applied to a single reference in the article, not to the entire body of evidence that exists on a topic. Each label should include the letter rating (A, B, C), followed by the specific type of study for that reference. For example, following a level B rating, include one of these descriptors: (1) nonrandomized clinical trial; (2) nonquantitative systematic review; (3) lower quality RCT; (4) clinical cohort study; (5) case-controlled study; (6) historical uncontrolled study; (7) epidemiologic study.

Here are some examples of the way evidence ratings should appear in the text:

“To improve morbidity and mortality, most patients in congestive heart failure should be treated with an angiotensin-converting enzyme inhibitor. [Evidence level A, RCT]”

“The USPSTF recommends that clinicians routinely screen asymptomatic pregnant women 25 years and younger for chlamydial infection. [Evidence level B, non-randomized clinical trial]”

“The American Diabetes Association recommends screening for diabetes every three years in all patients at high risk of the disease, including all adults 45 years and older. [Evidence level C, expert opinion]”

When scientifically strong evidence does not exist to support a given clinical recommendation, you can point this out in the following way:

“Physical therapy is traditionally prescribed for the treatment of adhesive capsulitis (frozen shoulder), although there are no randomized outcomes studies of this approach.”

Format of the Review

Introduction.

The introduction should define the topic and purpose of the review and describe its relevance to family practice. The traditional way of doing this is to discuss the epidemiology of the condition, stating how many people have it at one point in time (prevalence) or what percentage of the population is expected to develop it over a given period of time (incidence). A more engaging way of doing this is to indicate how often a typical family physician is likely to encounter this problem during a week, month, year, or career. Emphasize the key CME objectives of the review and summarize them in a separate table entitled “CME Objectives.”

The methods section should briefly indicate how the literature search was conducted and what major sources of evidence were used. Ideally, indicate what predetermined criteria were used to include or exclude studies (e.g., studies had to be independently rated as being high quality by an established evaluation process, such as the Cochrane Collaboration). Be comprehensive in trying to identify all major relevant research. Critically evaluate the quality of research reviewed. Avoid selective referencing of only information that supports your conclusions. If there is controversy on a topic, address the full scope of the controversy.

The discussion can then follow the typical format of a clinical review article. It should touch on one or more of the following subtopics: etiology, pathophysiology, clinical presentation (signs and symptoms), diagnostic evaluation (history, physical examination, laboratory evaluation, and diagnostic imaging), differential diagnosis, treatment (goals, medical/surgical therapy, laboratory testing, patient education, and follow-up), prognosis, prevention, and future directions.

The review will be comprehensive and balanced if it acknowledges controversies, unresolved questions, recent developments, other viewpoints, and any apparent conflicts of interest or instances of bias that might affect the strength of the evidence presented. Emphasize an evidence-supported approach or, where little evidence exists, a consensus viewpoint. In the absence of a consensus viewpoint, you may describe generally accepted practices or discuss one or more reasoned approaches, but acknowledge that solid support for these recommendations is lacking.

In some cases, cost-effectiveness analyses may be important in deciding how to implement health care services, especially preventive services. 10 When relevant, mention high-quality cost-effectiveness analyses to help clarify the costs and health benefits associated with alternative interventions to achieve a given health outcome. Highlight key points about diagnosis and treatment in the discussion and include a summary table of the key take-home points. These points are not necessarily the same as the key recommendations, whose level of evidence is rated, although some of them will be.

Use tables, figures, and illustrations to highlight key points, and present a step-wise, algorithmic approach to diagnosis or treatment when possible.

Rate the evidence for key statements, especially treatment recommendations. We expect that most articles will have at most two to four key statements; some will have none. Rate only those statements that have corresponding references and base the rating on the quality and level of evidence presented in the supporting citations. Use primary sources (original research, RCTs, meta-analyses, and systematic reviews) as the basis for determining the level of evidence. In other words, the supporting citation should be a primary research source of the information, not a secondary source (such as a nonsystematic review article or a textbook) that simply cites the original source. Systematic reviews that analyze multiple RCTs are good sources for determining ratings of evidence.

The references should include the most current and important sources of support for key statements (i.e., studies referred to, new information, controversial material, specific quantitative data, and information that would not usually be found in most general reference textbooks). Generally, these references will be key evidence-based recommendations, meta-analyses, or landmark articles. Although some journals publish exhaustive lists of reference citations, AFP prefers to include a succinct list of key references. (We will make more extensive reference lists available on our Web site or provide links to your personal reference list.)

You may use the following checklist to ensure the completeness of your evidence-based review article; use the source list of reviews to identify important sources of evidence-based medicine materials.

Checklist for an Evidence-Based Clinical Review Article

The topic is common in family practice, especially topics in which there is new, important information about diagnosis or treatment.

The introduction defines the topic and the purpose of the review, and describes its relevance to family practice.

A table of CME objectives for the review is included.

The review states how you did your literature search and indicates what sources you checked to ensure a comprehensive assessment of relevant studies (e.g., MEDLINE, the Cochrane Collaboration Database, the Center for Research Support, TRIP Database).

Several sources of evidence-based reviews on the topic are evaluated ( Table 1 ) .

Where possible, POEM (dealing with changes in morbidity, mortality, or quality of life) rather than DOE (dealing with mechanistic explanations or surrogate end points, such as changes in laboratory tests) is used to support key clinical recommendations ( Table 2 ) .

Studies of patients likely to be representative of those in primary care practices, rather than subspecialty referral centers, are emphasized.

Studies that are not only statistically significant but also clinically significant are emphasized; e.g., interventions with meaningful changes in absolute risk reduction and low numbers needed to treat. (See http://www.cebm.net/index.aspx?o=1116 .) 11

The level of evidence for key clinical recommendations is labeled using the following rating scale: level A (RCT/meta-analysis), level B (other evidence), and level C (consensus/expert opinion).

Acknowledge controversies, recent developments, other viewpoints, and any apparent conflicts of interest or instances of bias that might affect the strength of the evidence presented.

Highlight key points about diagnosis and treatment in the discussion and include a summary table of key take-home points.

Use tables, figures, and illustrations to highlight key points and present a step-wise, algorithmic approach to diagnosis or treatment when possible.

Emphasize evidence-based guidelines and primary research studies, rather than other review articles, unless they are systematic reviews.

The essential elements of this checklist are summarized in Table 3 .

Siwek J. Reading and evaluating clinical review articles. Am Fam Physician. 1997;55:2064-2069.

Shaughnessy AF, Slawson DC. Getting the most from review articles: a guide for readers and writers. Am Fam Physician. 1997;55:2155-60.

Pitt B, Zannad F, Remme WJ, Cody R, Castaigne A, Perez A, et al. The effect of spironolactone on morbidity and mortality in patients with severe heart failure. N Engl J Med. 1999;341:709-17.

Flynn CA, D'Amico F, Smith G. Should we patch corneal abrasions? A meta-analysis. J Fam Pract. 1998;47:264-70.

Slawson DC, Shaughnessy AF, Bennett JH. Becoming a medical information master: feeling good about not knowing everything. J Fam Pract. 1994;38:505-13.

Shaughnessy AF, Slawson DC, Bennett JH. Becoming an information master: a guidebook to the medical information jungle. J Fam Pract. 1994;39:489-99.

Slawson DC, Shaughnessy AF. Becoming an information master: using POEMs to change practice with confidence. Patient-oriented evidence that matters. J Fam Pract. 2000;49:63-7.

Harris RP, Helfand M, Woolf SH, Lohr KN, Mulrow CD, Teutsch SM, et al. Methods Work Group, Third U.S. Preventive Services Task Force. Current methods of the U.S. Preventive Services Task Force. A review of the process. Am J Prev Med. 2001;20(3 suppl):21-35.

CATbank topics: levels of evidence and grades of recommendations. Retrieved November 2001, from: http://www.cebm.net/ .

Saha S, Hoerger TJ, Pignone MP, Teutsch SM, Helfand M, Mandelblatt JS. for the Cost Work Group of the Third U.S. Preventive Services Task Force. The art and science of incorporating cost effectiveness into evidence-based recommendations for clinical preventive services. Am J Prev Med. 2001;20(3 suppl):36-43.

Evidence-based medicine glossary. Retrieved November 2001, from: http://www.cebm.net/index.aspx?o=1116 .

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• Volume 56, Issue 12
• Writing up your clinical trial report for a scientific journal: the REPORT trial guide for effective and transparent research reporting without spin
• Article Text
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• http://orcid.org/0000-0001-6884-1971 Thomas Bandholm 1 , 2 , 3 , 4 ,
• http://orcid.org/0000-0001-9102-4515 Kristian Thorborg 2 , 4 , 5 ,
• http://orcid.org/0000-0001-8102-3631 Clare L Ardern 6 , 7 , 8 ,
• Robin Christensen 9 , 10 ,
• http://orcid.org/0000-0003-1091-2962 Marius Henriksen 9
• 1 Department of Clinical Research , Copenhagen University Hospital, Amager and Hvidovre , Copenhagen , Denmark
• 2 Department of Occupational and Physical Therapy, Physical Medicine & Rehabilitation Research – Copenhagen (PMR-C) , Copenhagen University Hospital, Amager and Hvidovre , Copenhagen , Denmark
• 3 Department of Orthopaedic Surgery , Copenhagen University Hospital, Amager and Hvidovre , Copenhagen , Denmark
• 4 Department of Clinical Medicine , University of Copenhagen , Copenhagen , Denmark
• 5 Department of Orthopaedic Surgery, Sports Orthopedic Research Center – Copenhagen (SORC-C), Amager-Hvidovre Hospital, Faculty of Health Sciences , Copenhagen University , Copenhagen , Denmark
• 6 Musculoskeletal & Sports Injury Epidemiology Centre, Department of Health Promotion Science , Sophiahemmet University , Stockholm , Sweden
• 7 Sport and Exercise Medicine Research Centre , La Trobe University , Melbourne , Victoria , Australia
• 8 Department of Family Practice , University of British Columbia , Vancouver , British Columbia , Canada
• 9 The Parker Institute, Section for Biostatistics and Evidence-Based Research , Copenhagen University Hospital Bispebjerg Frederiksberg , Copenhagen , Denmark
• 10 Department of Clinical Research, Research Unit of Rheumatology , University of Southern Denmark, Odense University Hospital , Odense , Denmark
• Correspondence to Dr Thomas Bandholm, Dept of Clinical Research, Copenhagen University Hospital, Amager and Hvidovre, Hvidovre DK-2650, Denmark; thomas.quaade.bandholm{at}regionh.dk

The REPORT guide is a ‘How to’ guide to help you report your clinical research in an effective and transparent way. It is intended to supplement established first choice reporting tools, such as Consolidated Standards of Reporting Trials (CONSORT), by adding tacit knowledge (ie, learnt, informal or implicit knowledge) about reporting topics that we have struggled with as authors or see others struggle with as journal reviewers or editors. We focus on the randomised controlled trial, but the guide also applies to other study designs. Topics included in the REPORT guide cover reporting checklists, trial report structure, choice of title, writing style, trial registry and reporting consistency, spin or reporting bias, transparent data presentation (figures), open access considerations, data sharing and more. Preprint (open access): https://doi.org/10.31219/osf.io/qsxdz .

• sports medicine
• randomized controlled trial

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/bjsports-2021-105058

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Introduction

You worked hard as the primary investigator of a clinical research project. You spent months preparing the project, 1 and perhaps years collecting and analysing data. You are now ready to report the work as a scientific paper (hereafter ‘trial report’), and submit it to a peer-reviewed, academic journal. You aim for quality and transparency because you want the end-user to be able to read-and-implement for clinical work or read-and-replicate for research. Your coauthors have different and contrasting input to your manuscript draft. How do you navigate this scenario?

Let us introduce the REPORT guide. It is intended to improve reporting of clinical research in general. 2 It is not intended to replace established reporting checklists such as Consolidated Standards of Reporting Trials (CONSORT) 3 —they are always your ‘first choice’ reporting guidance resources. Rather, we intend the REPORT guide as a ‘How to’ implementation guide and directory that holds tacit knowledge (ie, learnt, informal or implicit knowledge) and references to sources of information about effective and transparent trial reporting. We have included information on topics we have struggled with ourselves as authors and see authors struggle with when we review or edit submitted clinical trial research. We published the PREPARE trial guide in 2017 1 which aimed to assist in the preparation and planning of clinical trial research. The REPORT guide is a natural extension of PREPARE—focusing on reporting of clinical trial research. If you used the PREPARE trial guide 1 to plan your research, the REPORT guide will likely help you report it. The REPORT guide can also function as a stand-alone guide to help you report research no matter how it was prepared.

The REPORT guide provides information to help improve reporting quality and transparency. The focus is the randomised controlled trial (RCT) (hereafter ‘trial’), but the guide is useful for other study designs.

The CONSORT checklist and CONSORT-based web tool writing aid tool: an important first step

An important first reporting step is to locate a reporting checklist that matches your study design. A comprehensive list of reporting checklists can be found at the EQUATOR network’s website. 4 For a trial, the appropriate reporting checklist is the CONSORT checklist 3 for which there are several extensions that may be relevant. We encourage you to go to the ‘Toolkits’ section at the EQUATOR network’s website 5 where you can find information to help you select the appropriate reporting checklist. You may also find the CONSORT-based WEB tool (COBWEB) 6 useful in your writing and checklist adherence. As stated on the COBWEB(site): ‘COBWEB is an online manuscript writing aid tool intended to guide authors through the process of manuscript writing of RCTs in line with the Consolidated Standards of Reporting Trials (CONSORT) and its subsequent extensions’. We highly recommend you use this tool, as it will facilitate effective trial reporting. It will help you avoid many of the documented problems with CONSORT adherence, such as poor reporting of randomisation methods or description of sample size estimation. 7

For more information on reporting checklists: 1 4 6 8 9

Keep the trial protocol and registration next to you as you write the report

Journal reviewers and editors will be some of the first professional readers of your trial report when submitted to an academic journal. They want to know if you did what you set out to do and—if not—why you made changes. They will look at your trial registration and protocol, if publicly available or submitted with the trial report—comparing the information in the trial registry to that in the trial report and looking for consistency for important trial characteristics. Authors of systematic reviews will do the same when they include your trial—once published—in their review and assess bias, for example, in the selection of your reported results. 10

We encourage you to take the same approach as reviewers and editors when you write your trial report. Have the trial protocol open and the registration available when you write—generally use a copy-paste approach for important trial characteristics to increase transparency and consistency for two related work packages of the same research project ( figure 1 ). Sometimes the trial report will be flagged by plagiarism checkers that journals use because the methods sections are very similar. Ensure you reference previous work and consider presenting the argument for this approach in the cover letter and/or the trial report itself. The guide ‘Avoiding Plagiarism, Self-plagiarism, and Other Questionable Writing Practices: A Guide to Ethical Writing’ by Dr Miguel Roig is a helpful and detailed resource. 11 Roig made the case for more editorial flexibility when it comes to textual reuse of technical descriptions—especially for writers who do not have English as their first language. 12 Finally, check any author/publisher copyright agreement if you have published your trial protocol to avoid any copyright infringement.

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We encourage you to have the protocol open and trial registration available when you write. If you use a copy-paste approach, it will facilitate consistency between trial protocol, registration and report.

Using a copy-paste approach will help you report important trial items in the same order and with the same wording as used in the registration. Examples of important trial items include aim, selection criteria and outcomes. If you deviated from the plan (common and acceptable with a reasonable explanation) transparently report it and why. Many journals require that you upload the trial protocol as a supplemental file to the trial report. A copy-paste approach creates a strong link between these two documents and increases readability. If wording cannot be copied and pasted 100% for consistency, we suggest you check carefully if the meaning is still the same. For example, you may have come up with a better title after having revised the trial report many times, or you realised that the trial objective could have had better wording.

Writing your trial report

Structure: introduction, methods, results and discussion.

Most scientific journals prefer a trial report style that follows the IMRaD-structure (ie, I ntroduction, M ethods, R esults a nd D iscussion). 13 You can find useful generic information on how to structure scientific papers from the PLOS collection. 14 We provide additional information relevant to the different sections of a trial report below.

Crafting a ‘tempting title’

Declarative and descriptive titles are the typical types of titles a reader is likely to encounter in the sports & exercise medicine field. A declarative title declares the key message (often a key result; eg,’ Meniscus or cartilage injury at the time of anterior cruciate ligament tear is associated with worse prognosis for patient-reported outcome 2–10 years after anterior cruciate ligament injury: a systematic review’). 15 A descriptive title describes what the reader can expect to find in the trial report (often the type of study, the population or the outcome; eg’ Which treatment is most effective for patients with Achilles tendinopathy? A living systematic review with network meta-analysis of 29 RCTs’). 16 When crafting a title for your trial report, consider whether you are aiming to engage the reader, inform the reader, or both, and if possible finalise the title with the design of your study.

Scientific writers can be creative without being frivolous, trivial or unscholarly/unscientific. A tempting title does not mean one has engaged in ‘spin’. 17 We recommend aiming for a declarative title where possible—the title is your chance to share a powerful first impression with your reader—although, we recognise you do not always have a choice. Adopting the engaging: informative style 18 offers a way to let your creativity flow, without straying too far from scholarly conventions and inviting the stroke of an obstinate editor’s correction pen. Here is one example:’ Running themselves into the ground? Incidence, prevalence, and impact of injury and illness in runners preparing for a half or full marathon’. 19

Your tempting title might comprise two, or even three, parts: (1) the hook: perhaps a play on words or a metaphor, (2) the key message, where you declare why the reader will want to read on or what she will find if she reads on, and (3) a key distinguishing feature of your trial report: perhaps a characteristic of the population, the type of trial (eg, double-blind superiority trial) or time frame for data collection). To facilitate correct PubMed indexing and identification, the CONSORT group 3 encourages authors to include the study design in the title (eg, ‘an RCT’).

The stylish academic writer: three suggestions to help you capture and engage your reader’s attention

Scientific writing and creative writing are not polar opposites. Our statement in the last section on tempting titles bears repeating: scientific writers can be creative without being frivolous or unscholarly. Like with your title, we recognise you may not always have a choice about some aspects of style (eg, some journals require third person perspective and forbid using first person pronouns like ‘ we measured quadriceps strength using an isokinetic dynamometer.’).

Suggestion 1: use concrete language and banish passive sentences

Consider replacing ‘There are numerous approaches to the quantification of training load’ with ‘There are at least three tools to measure training load’. Even more concrete is: ‘We describe three tools clinicians could use to measure training load in recreational runners’ because (1) your reader knows how many ways to measure training load she can expect to read about, and (2) she knows something about the population. She also knows who is doing what to whom: clinicians (who) are measuring (doing what) the training load of recreational runners (whom). Numbered or ordered lists help you organise your thoughts and convey a clear message to your reader.

Suggestion 2: write in active sentences that are driven by active vivid verbs

Even when your writing context is constrained or less flexible (or perhaps inflexible) given journal requirements, we encourage you to address your reader directly—with active writing. One can choose to write concise, clear, coherent sentences or one can choose vague, passive, verbose sentences. Which sentence holds your attention as a reader? Concrete language uses active verbs (eg, describe, explore, compete, measure), avoids abstract nouns (eg, quantification, conversation, completion, effectiveness, discretisation) and clarifies who is doing what, to whom.

Suggestion 3: comb your manuscript for be-verbs and replace them with active verbs

Forms of be, including was, were, been, being, are, is or shown, are also juicy targets for writers who are aiming to resurrect their writing. Passive verb constructions like ‘can be measured’ or ‘were shown’ weigh your writing down. Try replacing a few be- verbs in each paragraph with active, vivid verbs (eg, masquerade, prescribe, roll, shun).

Writing well is a deliberate, careful and considered process. It is a craft that requires time and practice. You will find writing resources and suggested reading on renowned Professor of Linguistics and scientific writing coach Helen Sword’s website. 20 Four of the five authors of the REPORT guide do not have English as their first language. In scientific writing, we use the three suggestions above. We also use a ‘how simple can you go’ approach to guard against major linguistic mistakes and to increase readability for readers whose first language is not English. In Lingard et al ’s excellent Writing Craft series, 21 they identify key grammatical challenges and offer practical tips for native Spanish, French, Dutch and German speakers who are writing in English ( table 1 ). 22

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Key grammatical challenges for Spanish, French, Dutch and German researchers writing in English

Three things to try:

Watch Professor Sword explain how to avoid nominalisations. 23

Run your writing through an online workout. 24

Train with some Wordcraft Workouts . 25

Abstract: the CONSORT-way

The trial report abstract is important because it will likely have many more reads than the full trial report. Most journals have a word limit for abstracts, and some have mandatory structure and headings. Each of these restrictions can pose a challenge when writing a clear, transparent and detailed abstract—you need to make every word count. 21 If journal formatting allows, use the CONSORT for reporting randomised trials in journal and conference abstracts. 26 It comes with an explanation and elaboration paper 27 as well as an abstract item checklist, which can be downloaded from the CONSORT website. 28 Preliminary work from the CONSORT group showed that all the checklist items can fit within 250–300 words. 27 The CONSORT website also has a sample study that implements the CONSORT checklist. 29 The sample study includes an example of how to write abstract results, which can be problematic. 30

When you state the trial framework, for example, ‘superiority trial’ it creates an excellent link to what follows in the abstract. It links to which intervention the authors hypothesise to be superior to the comparator (objective); the main outcome and time frame that this is assessed (primary outcome and endpoint); indication of risk of bias (randomised vs analysed, blinding, trial registration), indication of superiority (effect size, between-group difference in response for the primary outcome) and claim of superiority as hypothesised (conclusion). To avoid unintentional reporting 31 or spin 32 biases in the conclusion, we suggest you reserve the first line to conclude on your objective and corresponding primary outcome and use PICOT 33 as the framework (Population, Intervention, Comparator, Outcome, Time frame). For example, ‘Compared with intervention C (the comparator), the intervention of interest I was not superior in reducing O (primary outcome) at T (time frame) in P (population). We encourage you to then continue with secondary outcomes: ‘For the secondary outcomes X, Y and Z, we found that (…)’ ( figure 2 ).

We encourage you to create a strong link between the conclusion and the trial aim and hypothesis if you think ‘aim’, ‘hypothesis’ and ‘trial design’ when you write the first line of the conclusion.

If your trial was prospectively registered, we suggest you state this at the end 26 of the abstract as ‘Trial identifier: (number) followed by ‘(prospectively registered)’. If for some reason your trial was not registered before the first participant was included (prospectively/preregistered), we suggest you transparently report this at the bottom of the abstract as ‘Trial identifier: (number)’ followed by ‘(retrospectively registered)’. This is currently the editorial policy for all BMC journals when they consider retrospectively registered trials for publication. 34 In the main trial report we encourage you to explain the reason for this practice and state if important trial changes occurred after the trial began, as there will be no publicly available record of your research intentions. If you posted your trial report as an open access preprint, we encourage you to add the preprint information to the bottom of the abstract. In the REPORT guide, you will find an example of this use (more info about preprints below). It will help the reader find an open access version of your trial report and link the two documents via the digital object identifier (DOI) 35 ; ‘Preprint (open access): http://doi.org/ (doi number)’. We suggest you use a copy-paste approach for important abstract information, so that it is consistent with the trial registration and/or published protocol as well as main trial report document (eg, aim and conclusion).

For more information on abstract reporting: 21 27 36

Introduction: the ‘why’ of your trial

In this section, we encourage you to present the ‘why’, that is, an argument for why your trial is needed. If the ‘why’ is not clear to you and your coauthors, it will be difficult to convey it in a trial report. Readers are already motivated because they screened your title and abstract for relevance and results. However, the Introduction helps the journal’s reviewers and editors judge the importance of your trial report. It is therefore essential to making it interesting, while at the same time concise and describe the knowledge gap that your trial is intended to fill.

Your introduction should present the scientific background and rationale. 3 It should follow the background section of your protocol, as the reason for doing the trial has not changed. Thus, the introduction can more or less be copy-pasted from your protocol. During the planning and conduct of your trial, however, others may have published relevant research findings. They may support or oppose your results but should be mentioned. The introduction should include a summary of relevant studies as an up-to-date systematic review or at least include the latest published systematic review on your topic. It is important not to be selective in this literature review as it may mislead the reader, increase the risk of confirmation bias 37 or unintentionally communicate that the knowledge gap is larger or more important than it is. Consider letting the reader know that you have made steps to avoid this by stating that you have scrutinised all available evidence and use the best available evidence to inform the need of the trial: ‘The latest systematic review with meta-analysis on the effectiveness of (your intervention) on (your outcome of interest) concluded that (main finding). This is supported by two recent trial reports published after the systematic review by (author)’.

While the background information in a trial protocol oftentimes is very lengthy, the introduction part of a trial report can be shorter. Consider who will read your trial report and try to direct the introduction to that audience. For specialty journals it is not necessary to state general knowledge in the field. If you write about treatment of sports injuries and intend to publish in a sports medicine journal, it is unnecessary to write elaborately about the prevalence, costs, injury mechanisms or importance of treatment effectiveness. Readers of the journal will know this information already. Focus more on your trial rationale, specific research question, and aim. By cutting to the chase, you will save words that are better spent elsewhere.

End the introduction by stating the aim or the objective of your trial and include the hypothesis. Aims and hypotheses are not always easy to differentiate, but hypotheses are typically more specific and relate closely to the chosen trial design, outcome measures and statistical analysis plan (SAP). This is the most important part of the introduction. We suggest you copy/paste from the trial registry and/or published protocol for consistency ( figure 1 ). We also suggest using the copy/paste approach for abstract and main trial report so that the aim in the abstract is the same as the one in the main trial report.

For more information on systematic reviews to fully use previous research: 38 39

Methods: the ‘how’ of your trial

In this section, we encourage you to present the ‘how’ of your trial. What did you do in order to answer the ‘why’? The methods section is a detailed description of what was done and serves at least two main purposes: (1) to provide enough information to allow the reader to critically appraise and interpret the results, and (2) to convey as many details as possible so other researchers (in principle) will be able to replicate you trial entirely or in part. For clinical application of your trial results, it is important to give detailed descriptions of the population selection, assessment methods, and interventions. Other important aspects of the methods section are central for evaluating the scientific quality, validity and reliability of the trial.

Ideally, the methods section should be a replica of your trial protocol. But completing a trial without ‘bending the rules’ laid out in the protocol is practically impossible. It is therefore important to report any deviations and violations of the protocol. It is not a ‘scientific crime’ to deviate from the protocol, but it is important to report any deviation with potential bearing on your primary and important secondary outcomes (and thus on the interpretation of the entire trial). It is particularly important to declare ‘planned’ deviations, such as changes to eligibility criteria (eg, due to safety or slow recruitment), changes in instruments (eg, change of MRI-scanner due to breakdown). We suggest you report the deviations with reasons and describe what you did.

When you write your trial methods, imagine that your trial report 1 day will be scrutinised as part of a systematic review or clinical guideline. Reviewers will appraise your trial report on the lookout for flaws (or risks of bias). While you may have conducted your trial scrupulously (ie, with a low risk of bias), reporting can be incomplete. Reviewers may be uncertain about aspects of your trial methodology, which may mean they must downgrade the quality of your trial. We suggest you consult The Cochrane Handbook for Systematic Reviews of Interventions. 40 It provides detailed information on how to appraise individual trials, and provides you useful hints on what reviewers are looking for. For example, a reviewer may look for the phrase ‘sequentially numbered, opaque, sealed envelopes’ when assessing risk of bias for ‘Allocation concealment’. Knowing this, will help you clearly report how this was done in your trial.

For more information on how to report protocol deviations and risk of bias assessment: 40 41

Methods: outcomes

The CONSORT checklist items for ‘Outcomes’ ask you to report ‘Completely defined pre-specified primary and secondary outcome measures, including how and when they were assessed’ and ‘Any changes to trial outcomes after the trial commenced, with reasons’. 3 If you use a copy-paste approach, it will be easy to copy from your protocol and preregistered trial summary and paste into the trial report. It will create consistency with regards to, for example, number of outcomes, outcome hierarchy and wording. If for some reason you had to add or remove outcomes during the trial, we recommend you report this transparently, with reasons.

The COMPare trials project 42 team systematically checked every trial published in the top five medical journals between October 2015 and January 2016, with the purpose of searching for misreported findings and outcome switching. This team’s effort revealed a large degree of inconsistency in outcome reporting. 43 44 If for some reason, you had to make changes to your trial outcomes after the trial began, state this transparently and give reasons for the changes. If you plan to report collected outcomes in subsequent (secondary) trial reports, we suggest you state in the primary trial report that the outcomes were collected—consistent with the trial registry—and that you plan to report them in a subsequent report. This could be the case if you collected mechanistic and more exploratory outcomes in your trial, such a blood samples that await future advanced molecular analysis. Stating that these were collected will help you avoid misreporting of outcomes. The COMPare trials project 42 state in their Frequently Asked Questions-section: ‘Question: What if some outcomes are reported in a different publication? Answer: This is fine, as long as this fact has been declared in the trial publication. For example, if a trial says here we are reporting A B and C, in a subsequent paper we will report X Y Z then the outcomes X Y Z are not considered as unreported, and they are removed from the denominator. ’. 45

For more information on how to report trial outcomes: 3 42 46

Methods: interventions

Proper reporting of interventions is especially important for clinical application of your trial interventions, correct interpretation of your trial results, comparison with other trials (with similar interventions) and ability to inform new research questions. Unfortunately, intervention reporting is generally poor. 47 To help you report your interventions, The Better Reporting of Interventions: Template for Intervention Description and Replication checklist was developed. 48 It will help you make a complete and thorough generic description of the interventions. You may also need to consult a more intervention-specific guide or reporting checklist, such as the Consensus on Exercise Reporting Template for exercise trials. 49 We suggest you describe any ‘usual care’ or other comparator intervention using the same standards and checklists. For some comparators, reporting checklists have been developed—one was just developed for placebo and sham controls. 50 You may already have published a detailed description of your intervention and comparator as part of a published protocol. In case changes were made to the intervention or its delivery during the trial, consider if the description needs to be updated and submitted with the trial report as supplemental material. It will help both replication and clinical implementation of your trial results. In case you have not already published a detailed intervention description, consider publishing it as supplemental material to your trial report. It will help you if the journal has a word limit for the main document.

For more information on how to report trial interventions: 48 49

Methods: sample size

This sample size paragraph is intended to outline how you, in the trial planning phase, ensured that the trial would have the required statistical power to identify whether a difference of a particular magnitude (the target difference) exists for the primary outcome. It is also intended to show that you did not include any extra participants than were needed for the trial. As you did all the thinking already, it should be feasible to copy/paste from the trial protocol. The basics of calculating sample size are covered in substantial detail in the PREPARE Trial guide. 1

For more information on how to determine and report the target difference and sample size estimation for a trial: 51

Methods: statistical analyses

The problem of poor statistical reporting is long-standing, widespread, potentially serious and yet is largely unsuspected by many readers of the biomedical literature. 52 General guidance on how to write SAPs is now available 53 and provides recommendations for a minimum set of items that should be addressed for clinical trials before analysing data. 53 If you have not written a specific SAP as part of the trial protocol, 1 we recommend that you consult a biostatistician and write one before viewing any data or starting the analysis.

An SAP ensures that the statistical methods are reported in sufficient detail to enable a knowledgeable reader (with potential access to the original data) to assess the appropriateness of the chosen statistical methods and the underlying assumptions, and to verify your reported results. In a SAP, the statistical methods are often described in great detail, and a complete copy-paste approach may be too much (given that most journals have restrictions on manuscript length). We therefore recommend always submitting the SAP (with final date on cover page) as supplemental material so that editors, peer reviewers and other readers can take a deeper dive into the statistical methods.

In the main text, we encourage you to give an extract of the primary statistical analyses (from the SAP). If you have stated a clear objective, the reader will be able to understand the primary purpose of the trial and what to expect to see next. We recommend that you describe fully the main methods for analysing the primary and key secondary objectives of the trial. It is common to analyse the data set under different assumptions—sensitivity analyses—to assess the robustness of the primary analyses. These are typically based on different strategies for handling missing data or analyses of different trial populations (eg, the per protocol population which is potentially biased but still informative). We recommend you carefully describe these strategies. Excellent educational resources exist to assist you. They include the CONSORT explanation and elaboration paper, 3 the SAMPL guidelines for statistical reporting, 54 and the recently developed Checklist for statistical Assessment of Medical Papers statement. 55

For more information on how to report statistical analyses for a trial: 3 54 55

Results: attrition

Attrition can introduce bias in your trial results if the characteristics of participants who are lost to follow-up differ between the randomised groups—especially if the differing characteristic is related to trial outcome measures. 56 If you use the CONSORT flow diagram to illustrate the trial profile, we suggest you report the demographics of the participants included in the intention-to-treat population with descriptive statistics for each group. We encourage you to create an overview by preparing a classic table 1 of baseline characteristics using the outline from the CONSORT explanation and elaboration paper. 3 You may also find it useful to supplement with table items as suggested by Dumville et al 56 and attach as a baseline appendix.

Reviewers will sometimes ask for results of statistical testing for baseline differences. The recommendation from the CONSORT group is clear: ‘Such hypothesis testing is superfluous and can mislead investigators and their readers. Rather, comparisons at baseline should be based on consideration of the prognostic strength of the variables measured and the size of any chance imbalances that have occurred’. 3 It means you should subjectively judge if any differences between groups that will occur by chance due to randomisation is of a magnitude that you think is clinically relevant.

For more information on how to report attrition: 56

Results: focus on the main analysis and between-group differences

Correct reporting of the results of the statistical analyses includes explicit estimates presented with appropriate indicators of measurement error or uncertainty, such as 95% CIs. Randomised trials are designed to analyse differences between groups, and the results should focus on these—not on changes within groups. However, it is helpful for transparent reporting and interpretation to present the estimates in each group. We strongly recommend that you avoid reporting only statistical hypothesis testing (eg, such as P values), as they do not contain much information and do not convey important information about effect sizes or precision of estimates. When you report p values, we recommend you report actual p values, rather than p<0.05, unless the value is very small (eg, p<0.0001).

We suggest you report your primary analyses first and hierarchically (primary outcome before secondary and other outcomes). This will most likely follow the hierarchy outlined in your trial protocol and SAP. By being consistent and use a copy/paste-approach, you will help the reader assess if you followed your SAP. We recommend you avoid interpretations or interpretative language in the results section, but instead help the reader by providing a direction of the results and whether it favours one of the groups. In cases where discrepancies between analysis sets occur among the primary analyses and the sensitivity analyses, we suggest you highlight them in the text. You may also need to devote more attention to interpreting the collective results because the confidence in the individual analyses is reduced.

During your data analyses, new and exciting ideas may arise, as well as unexpected findings that you did not consider during planning. Such results can be important and foster significant scientific advances. However, consider that your trial design may not support confirmatory analyses or statements of such findings, and it is important to state (both in the Statistical methods section and in the Results section) that these were not prespecified. Related to this topic is the situation where a peer reviewer asks for additional analyses of your data set; that is, frequently referred to as the ‘peer review pressure test’. These are often valuable and reasonable requests, but should very rarely replace the original analytical strategies, unless there are fundamental flaws in the trial design and/or the chosen analyses do not reflect the experimental design. We suggest that post hoc analyses requested by peer reviewers are reported in supplemental files and included in a response letter to the reviewers when submitting a revised manuscript.

For more information on how to report the results of statistical analyses for a trial: 54 55

Results: transparent illustration of your data

Your tables and figures should ideally be able to stand alone (eg, in presentations and lectures). It is valuable to provide brief summaries of the statistical methods used (eg, as foot notes to tables and figures). The CONSORT checklist and explanatory paper have great examples and descriptions of how to make certain illustrations. On the CONSORT website, you will find a flow diagram template freely available for download. 28 We suggest you add some additional information to the flow diagram, including numbers of participants included in the different analyses (eg, intention-to-treat and/or available case analysis) and number of imputations made for missing data, if applicable. For an example, please see Lysdal et al 57

Include specific information on your sampling strategy at the top of the flow diagram because it will facilitate interpretation of the trial findings with regards to clinical relevance. Consider reporting the total number of potentially eligible participants during the trial recruitment period and how many of these were assessed for eligibility, instead of only reporting the number of individuals assessed for eligibility. It allows the reader to judge how well the trial population represents all patients seen at the recruitment site while the trial was running. Because this issue relates to external validity it is important—but it is especially important if the trial findings have major implications for current clinical practice. Please see Clausen et al 58 for an example of how the number of potentially eligible participants can be incorporated into the trial flow chart. Please also see the rapid responses 59 to the FIMPACT 60 trial for a discussion of the importance of including the number of potentially eligible participants when trial findings have great implications for clinical practice.

Results may sometimes merit a figure in the form of a graph. Many bar or lines graphs—based on continuous data with different distributions—can lead to the same bar or line graph ( figure 3 ). 61 Unless you include raw data in the graph, most information will be invisible to the reader. We encourage you to making it visible by using scatter plots instead of bar charts.

Many different datasets can produce the same bar graph. The figure and legend are modified from Weissgerber et al 61 https://doi.org/10.1371/journal.pbio.1002128 under the terms of the creative commons CC by 4.0 license https://creativecommonsorg/licenses/by/40/ .

For more information on how to effectively use tables and figures in scientific papers: 61–63

Results: harms

When new healthcare interventions are studied, researchers tend to focus more on efficacy than safety. There is poor reporting of harms in trial reports across many clinical areas, 64 which makes it difficult to obtain a true estimate of the benefit-harms ratio. The CONSORT extension for harms 65 was developed to improve reporting of harms-related data in trials. Because the main focus of the CONSORT checklist is efficacy reporting, we suggest you supplement your trial reporting with the CONSORT extension for harms 65 to improve reporting of harms-related data.

For more information on reporting of harms-related data: 65

Discussion: consider clinical relevance and confirmation bias

The CONSORT checklist 46 holds the overall framework for the discussion and items you should address, but scientific journals may have additional requirements. We suggest you use the CONSORT checklist to structure the discussion, and supplement with requirements from your target journal, if needed. We would like to highlight two important items: clinical relevance and confirmation bias.

We suggest you focus on the primary analysis and outcome. Your trial was designed first and foremost to provide a reliable answer in terms of the hypothesis for this analysis and outcome. The test statistics will determine if the difference between groups is statistically significant. Judging and discussing whether a statistically significant difference between groups is also clinically relevant should be easy at this point. You will already have argued in your trial protocol and sample size paragraph what minimum theoretical difference between groups you consider clinically relevant and why. Now that you have the observed difference between groups, the main issue is to compare the two and discuss the size of the observed effect. An important aspect of this discussion is the precision of the observed effect. In general, the larger the sample size of your trial, the greater the precision of the observed effect. The precision is reflected in the 95% CI of the observed effect. The greater the precision, the smaller the 95% CI and vice versa. We suggest a balanced discussion of the clinical relevance of the observed effect to include both its size (in relation to the predefined minimal clinically importance difference) as well its precision. It will help you avoid unintentional confirmation bias (please see below).

Biases come in many forms and can affect healthcare in many ways. There may be biases that you want to acknowledge specifically under ‘Limitations’ in the discussion because you think they may have influenced trial procedures or outcomes. We suggest you consider your own ‘confirmation bias’ when writing the discussion—or the whole trial report for that matter. As stated by the Catalogue of Bias Collaboration 37 : ‘Confirmation bias occurs when an individual looks for and uses the information to support their own ideas or beliefs. It also means that information not supporting their ideas or beliefs is disregarded.’ Being researchers, we argue that most of us unintentionally wish for our intervention to be superior to the comparator for several reasons: (1) we want to help patients by advancing the field, or (2) we think it will bring promotion or other academic reward. By being intentionally aware of our own confirmation bias, we can better stay clear of issues such as unintentional secondary analysis emphasis (spin) and selective referencing of work that support our own findings.

For more information on statistical significance, clinical relevance, spin and confirmation bias: 17 37 66

Conclusion: what was your trial designed to test first and foremost?

When you write the trial report conclusion, we encourage you to think ‘aim’, ‘hypothesis’ and ‘trial design’. What was your trial designed to test primarily and how was this formulated in the aim? Was it to assess if the intervention of interest was better than (superiority trial), no worse than (non-inferiority trial), or whether it was as equally effective as (equivalence trial) the comparator? Using this line of thinking will help create a strong connection between aim, hypothesis and conclusion. It will also help you conclude only what the trial data support. If the aim of a superiority trial was ‘To investigate if I (Intervention of interest) is superior to C (comparator) in improving O (primary outcome) at T (timepoint) in P (population) and there was no difference in response between groups, the conclusion could start with: ‘Compared with C (comparator), I (Intervention of interest) was not superior in reducing O (primary outcome) at T (time point) in P (population). A very common mistake is to interpret the absence of evidence of superiority as evidence of equivalence or non-inferiority and conclude that the intervention of interest and comparator were equally effective or no different (for more details, please see refs 1 67 ).

Having addressed the main hypothesis, analysis and outcome the trial was designed to assess, we encourage you to proceed with interesting secondary analyses and—at the same time—inform the reader about the increase in risk of bias for these analyses: ‘For the secondary outcomes, X, Y and Z, we found that (………).’. When you conclude first on the primary analysis, you minimise the risk of unintentional reporting 31 or spin 32 biases. If your trial was more exploratory than confirmatory 1 —or had a flat outcome hierarchy with no single primary outcome—you may want to consider finishing the conclusion by acknowledging this. For example, ‘This finding needs replication in future trials’. Readers will often be interested in your thoughts on the implications of your trial findings. Some journals allow implication statements and others do not. If you do write about implications, we suggest you make it clear that this part of the conclusion is you speculating and conveying your expert opinion with phrasing like: ‘These findings may have implications for (……) insofar as (……).’. When you have finished writing the conclusion, check that it matches the trial aim and conclusion in the abstract.

Sharing research data

Depending on national legislation, you may or may not be able to share the raw trial data. Data sharing is one way of increasing transparency and maximising the trial participants’ research contribution by making the data they provided broadly available for secondary research purposes. 68 69 Data sharing is also expected by some non-private funding bodies. 70 If you can share your trial data, there are some things that you may want to consider. They include practical steps to data management, anonymisation and storage.

For more information on data sharing: 71–74

Alternative avenues for disseminating your research

When you are ready to submit your trial report to a scientific journal, consider publishing a preprint. A preprint is scientific work that has not undergone peer review and is not published in a scientific journal. 75 It is typically a manuscript draft that is ready to be submitted to a journal for peer review. A preprint can also be an earlier manuscript version that you want to make public. One advantage of publishing a preprint is that it is assigned a DOI, 35 which makes it searchable. Most publishers allow preprints, 76 but we suggest you check the preprint policy of the scientific journal that you aim to submit your trial report to. Elsevier states: ‘Preprint: Authors can share their preprint anywhere at any time. If accepted for publication, we encourage authors to link from the preprint to their formal publication via its Digital Object Identifier (DOI). Millions of researchers have access to the formal publications on ScienceDirect, and so links will help your users to find, access, cite, and use the best available version. Authors can update their preprints on arXiv or RePEc with their accepted manuscript. Please note: Some society-owned titles and journals that operate double-blind peer review have different preprint policies . ’. 77

Submission to preprint servers is typically free and it creates an open access option, even if you end up publishing your trial report behind a paywall. 78 It allows you to have crowdsourced feedback and to promote your open access research early (eg, during the period of peer review). Based on feedback, you can update your preprint version when you revise your manuscript. Some (but not all) publishers even allow you to update your preprint to the accepted (non-type set) manuscript version with proper reference to the journal publication. Please check the publisher’s preprint policy for guidance. If you look at the bottom of the abstract of this guide, you will see a link to an open access preprint. Had this guide not been published open access, an interested reader could see from the PubMed abstract where to find an open access full text (preprint).

For more information on preprints: 75

Researchers are familiar with social media platforms like Twitter for sharing new scientific content. When posting to social media, make space to include (1) the DOI 35 and (2) an image—two simple steps to help make your post visible to attention metrics-aggregators like Altmetric and capture the viewer who might otherwise scroll past your post. Across research areas, the Altmetric score has been associated with number of citations, journal impact factor, press releases and open access status. 79 80

Have you considered other forms of media? Researchers who embrace the rich ecosystem of digital media might find themselves partnering with clever infographics designers or using free (or freemium) websites to design their own. Consider writing for trusted outlets like The Conversation 81 —a news organisation that is dedicated to sharing information from the academic and research community, direct to the public, with ‘academic rigour and journalistic flair’. Sports medicine and sports physiotherapy journals including British Journal of Sports Medicine and Journal of Orthopaedic & Sports Physical Therapy have blogs dedicated to reaching a non-academic audience of clinicians, patients, athletes and coaches.

Consider approaching your academic institution’s media and communications department or press office. The staff are typically pleased to work with you to shape a press release, distribute the press release to mainstream media services, and connect with media contacts. Media and communications departments also share helpful tips for making your research visible to the media. 82

After publishing the trial report

After your trial report is published, consider (1) Is the ‘Trial status’ up to date in the trial registry? (2) Do I need to update the trial registry with a link to the published trial report and/or raw data if shared? (3) Do I need to report to funding bodies on the accomplished milestone (publication)? (4) Do I have a plan for disseminating the trial results other than the primary trial report? (5) Do I have a plan for storing and filing essential trial documents and data that adheres to national guidelines?

We hope the REPORT guide is helpful and a valuable supplement to ‘first choice’ trial reporting tools, such as CONSORT. We aimed to incorporate tacit knowledge about reporting, and flag issues we have struggled with. Quality decisions in healthcare depend on reliable evidence of treatment effects. Good research reporting practice does not cure ‘diseases’ that arise from poor research methodology—it helps the reader see the illness and appraise the research quality. No research is perfect. We do not profess to produce and report perfect research that is free from ‘disease’ 100% of the time. We implore all researchers to commit to conducting (and reporting) clear and transparent research.

What is already known

Reporting of clinical trial research varies and is known to be poor.

What are the new findings

The REPORT Trial guide is a one-stop, ‘how-to’ implementation guide and directory that holds tacit knowledge and references to first-choice sources of information about effective and transparent trial reporting (eg, CONSORT).

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This study does not involve human participants.

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Twitter @TBandholm, @KThorborg, @clare_ardern, @drrchristensen, @henriksen_mh

Contributors Conception and design: TB. Drafting and critical revision for important intellectual content: all authors. Final approval of manuscript. all authors. Accountable for all aspects of the work: all authors.

Funding CLA has received research salary support for work in return to sport from the Australian National Health and Medical Research Council (Early Career Fellowship APP1109779), Swedish Research Council (2015-03687) and Swedish Research Council for Sport Science (Postdoctoral fellowship D2018-0041), and is Editor-in-Chief of JOSPT (Journal of Orthopaedic & Sports Physical Therapy). The Parker Institute, Bispebjerg and Frederiksberg Hospital is supported by a core grant from the Oak Foundation (OCAY-18-774-OFIL).

Competing interests CLA was Deputy Editor (Systematic Reviews) for BJSM from 2016 to 2018 and is currently the Editor-in-Chief for JOSPT. TB and KT are BJSM editorial board members.

Provenance and peer review Not commissioned; externally peer reviewed.

Read the full text or download the PDF:

AMBOSS Blog

• Student Life

How to Write and Publish Clinical Research in Medical School

From working hard on the USMLE® exams to holding leadership positions in a specialty’s academic society, there are many ways medical students can work towards matching into the residency of their choice. One such activity that looks great on residency applications is finding clinical research opportunities in medical school to write and publish papers. No one knows this better than Dr. Eve Bowers. 

An Otolaryngology resident at the University of Miami/Jackson Memorial Hospital, Eve became an expert in writing, submitting, and publishing manuscripts during her final years in medical school. Check out Eve’s blog post below to get valuable insights on how to get published in medical school. 

As medical students, we’re told that research is important and that publications are “good”, and even “necessary to match ” into residency, but we often aren’t given the tools we need to turn ideas into manuscripts. This is especially true given our rigorous schedules. 

When I looked through my CV, I saw I had a few abstracts and presentations, but no manuscripts. I wanted to write, but publishing seemed like just checking another resume box. On top of that, I didn’t know where to begin. 

My writing journey started with a case report I nervously picked up during my surgery clerkship . Then, over ten months of typing, editing, and sending unanswered emails, I went from writing 0 to ten manuscripts. The process was sometimes painful but mostly gratifying (yes, research can be gratifying), and you can do it, too.

To make finding, starting, and publishing high-quality research articles a little bit easier and a lot more enjoyable, check out my five tips for publishing clinical research in medical school.

1. Build your network to find publication opportunities in medical school

When looking for projects, finding great mentors is often more useful than finding the perfect project. This is especially true when starting out. Use your time on clerkships to identify attending and resident mentors who you trust to support your budding author ambitions.

At this stage, residents especially are your friends . When you demonstrate follow-through and receptiveness to feedback, you will be given more research opportunities. Don’t be shy about asking mentors for tasks if you can juggle multiple projects, but don’t bite off more than you can chew. It’s important to communicate honestly and be transparent about the amount of time you have.

2. Kickstarting your research during medical school: start small 

If you have no research experience, start with a case report. Volunteer to write an article about an interesting case you saw in the operating room or clinic. It’s much easier and more rewarding to write about patients you have experience with, and case reports are a great way to demonstrate your writing ability to more senior authors.

Pro tip : Try to figure out as much as you can independently by using published reports as blueprints before asking for help. Nevertheless, don’t be afraid to seek guidance when you need it! If you approach a mentor with a problem, come prepared with 2-3 realistic solutions or examples of how you tried to figure it out on your own.

3. Know the criteria for writing a clinical research paper 

Before you begin, ask your mentor where they would like to submit the completed work. Each journal has specific standards, styles, and submission criteria. For guidance, look to papers previously published in that journal. 

As far as annotations and citations are concerned, download and learn how to use Endnote or Zotero right now! You’ll save days of work formatting your references.

Additionally, consider creating folders and spreadsheets to keep track of projects. Set goals and timelines for yourself from the beginning, and block off dedicated time to conduct a literature review, analyze data, and write.

Pro tip : If you are the first author and overseeing a large team, improve communication and efficiency by making everyone’s roles and expectations very clear to the group via email.

4. Follow up with your mentor

Sometimes you’ll send your mentor a draft, but she won’t get back to you with edits and feedback in a reasonable timeframe. Surprisingly, many projects do not get past this point because of insufficient persistence. Here’s what to do if this happens:

• Politely nudge your mentor with follow-up emails and schedule a meeting to discuss in person or via Zoom.
• Set deadlines and give specific reasons why the paper needs to be submitted. Some reasons could include, “I need this submission for my residency application ” or “this is a requirement for my school.”
• Ask your co-author resident and/or fellow to advocate for edits and submission.

Whatever happens, don’t give up at this point. You’ve put in the work, and persistence makes or breaks a successful student-author.

5. Write about the medical topics that you love

Writing is fun when you focus on subjects you’re really passionate about. You also don’t have to stay within your institution: feel free to branch out if you come across an interesting research opportunity at a different program. A little cold email can go a long way!

If your goal is quantity, you can increase output by asking around about “productive” research mentors and sticking to topics related to clinical practice or medical education. However, my advice is to never let relatively quick publication opportunities compromise the quality of your work. Remember — every paper you write gets easier and more enjoyable, and your work will be truly important to advancing the field you care about. Good luck!

About the Author : Eve is an Otolaryngology Resident at the University of Miami/Jackson Memorial Hospital. She attended medical school at the University of Pittsburgh School of Medicine and undergrad at the University of Pennsylvania. She is passionate about medical education, mentorship, and increasing minority and female leadership in surgical fields. For more tips and tricks, follow her on Twitter and Instagram !

For more information on residency applications, check out the AMBOSS Residency Applications Clerkship Survival Guide. 

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Regulations: Good Clinical Practice and Clinical Trials

Fda regulations relating to good clinical practice and clinical trials.

Here are links to FDA regulations governing human subject protection and the conduct of clinical trials.

• Electronic Records; Electronic Signatures (21 CFR Part 11)
• Regulatory Hearing Before the Food and Drug Administration (21 CFR Part 16)
• Protection of Human Subjects (Informed Consent) (21 CFR Part 50)
• Financial Disclosure by Clinical Investigators (21 CFR Part 54)
• Institutional Review Boards (21 CFR Part 56)
• Good Laboratory Practice for Nonclinical Laboratory Studies (21 CFR Part 58)
• Investigational New Drug Application (21 CFR Part 312)
• Applications for FDA Approval to Market a New Drug (21 CFR Part 314)
• Bioavailability and Bioequivalence Requirements (21 CFR Part 320)
• New Animal Drugs for Investigational Use (21 CFR Part 511)
• New Animal Drug Applications (21 CFR Part 514)
• Applications for FDA Approval of a Biologic License (21 CFR Part 601)
• Investigational Device Exemptions (21 CFR Part 812)
• Premarket Approval of Medical Devices (21 CFR Part 814)

Preambles to GCP Regulations

Each time Congress enacts a law affecting products regulated by the Food and Drug Administration, the FDA develops rules to implement the law. The FDA takes various steps to develop these rules, including publishing a variety of documents in the Federal Register announcing the FDA's interest in formulating, amending or repealing a rule, and offering the public the opportunity to comment on the agency's proposal. The Federal Register notice explains the legal issues and basis for the proposal, and provides information about how interested persons can submit written data, views, or arguments on the proposal. Any comments that are submitted are addressed in subsequent publications that are part of the agency's decision-making process.

The "preamble" to each of these publications includes all of the printed information immediately preceding the codified regulation. The preamble provides information about the regulation such as why the regulation is being proposed, the FDA's interpretation of the meaning and impact of the proposed regulation, and in those cases where the agency has solicited public comment, the agency's review and commentary on those comments . The preamble can also include an environmental impact assessment, an analysis of the cost impact, comments related to the Paperwork Reduction Act, and the effective date of the implementation or revocation (as the case may be) of the regulation.

The documents posted below include the various publications that contributed to the development of final rules related to FDA's regulations on good clinical practice and clinical trials.

Part 50- Informed Consent

• Protection of Human Subjects; Informed Consent; Final Rule (46 FR 8942, January 27, 1981)
• Protection of Human Subjects; Informed Consent; Standards for Institutional Review Boards for Clinical Investigations (53 FR 45678, November 10,1988)
• Protection of Human Subjects; Informed Consent; Proposed Rule [text] | [ PDF ] (60 FR 49086, September 21, 1995)
• Protection of Human Subjects; Informed Consent [text] | [PDF] (60 FR 66530, December 22, 1995)
• Protection of Human Subjects; Informed Consent, Informed Consent and Waiver of Informed Consent Requirements in Certain Emergency Research; Final Rule [text] | [PDF] (61 FR 51498, October 2, 1996)
• Protection of Human Subjects; Informed Consent Verification; Final Rule [text]  |  [PDF]  (61 FR 57278, November 5, 1996)
• Human Drugs and Biologics; Determination That Informed Consent Is NOT Feasible or Is Contrary to the Best Interests of Recipients; Revocation of 1990 Interim Final Rule; Establishment of New Interim Final Rule [text] | [PDF]  (64 FR 54180, October 5, 1999)
• Medical Devices; Exception from General Requirements for Informed Consent; Interim Final Rule [text] | [PDF]  (71 FR 32827, June 7, 2006)
• Informed Consent Elements [text] | [PDF] (76 FR 256, January 4, 2011)
• Human Subjects Research Protections: Enhancing Protections for Research Subjects and Reducing Burden, Delay, and Ambiguity for Investigators; Advance Notice of Proposed Rulemaking (ANPRM) [text] [PDF] (76 FR 44512, July 26, 2011)
• Extension of Comment Period [text] | [PDF] (83 FR 65322, December 20, 2018)
• Reopening of Comment Period [text] | [PDF]  (84 FR 5968, February 25, 2019)

Additional Safeguards for Children in Clinical Investigations of FDA Regulated Products; 21 CFR 50, Subpart D

• Interim Final Rule[text]  |  [PDF]   (66 FR 20589-600, April 24, 2001)
• Final Rule [text] | [PDF] (78 FR 12937, February 26, 2013

Part 56- Institutional Review Boards

• Protection of Human Subjects, Standards for Institutional Review Boards for Clinical Investigations Proposed Rule (43 FR 35186, August 8, 1978)
• Protection of Human Research Subjects; Standards for Institutional Review Boards for Clinical Investigations (46 FR 8958, January 27, 1981)
• Protection of Human Research Subjects; Clinical Investigations Which May Be Reviewed Through Expedited Review Procedure Set Forth in FDA Regulations; Notice   (46 FR 8980, January 27, 1981)
• Protection of Human Subjects; Informed Consent; Standards for Institutional Review Boards for Clinical Investigations; Proposed Rule (53 FR 45678, November 10, 1988)
• Federal Policy for the Protection of Human Subjects; Final Rule (56 FR 28003, June 18, 1991)
• FDA Policy for the Protection of Human Subjects; Final Rule (56 FR 28025, June 18, 1991)
• Categories of Research That May Be Reviewed by the Institutional Review Board (IRB) Through an Expedited Review Procedure [text] | [PDF]   (63 FR 60353, November 9, 1998)
• Human Drugs and Biologics: Determination That Informed IS NOT Feasible or Is Contrary to the Best Interests of Recipients; Revocation of 1990 Interim Final Rule; Establishment of New Interim Final Rule [text]  | [PDF]   ( 64 FR 54180, October 5, 1999)

IRB Registration Requirements 21 CFR 56.106

• Proposed Rule [text] | [PDF] (69 FR 40556, July 6, 2004)
• Final Rule [text] | [PDF] (74 FR 2358, January 15, 2009)

IRB Shopping: Requiring Sponsors and Investigators to Inform Institutional Review Boards of Any Prior Institutional Review Boards Reviews

• Advance Notice of Proposed Rulemaking [text]  [ PDF ]  (67 FR 10115, March 6, 2002)
• Advance Notice of Proposed Rulemaking; Withdrawal [text]   [PDF]   (71 FR 2493, January 17, 2006)  

IRB Waiver or Alteration of Informed Consent for Minimal Risk Clinical Investigations

• Proposed Rule [text]  | [PDF] (83 FR 57378, November 15, 2018)
• Extension of Comment Period [text] | [PDF]  (83 FR 65322, December 20, 2018)
• Reopening on Comment Period [text] | [PDF]  (84 FR 5968, February 25, 2019)

Part 54- Financial Disclosure by Clinical Investigators

• Financial Disclosure by Clinical Investigators; Public Hearing [text] | [PDF]  ( 60 FR 29801, June 6, 1995 )
• Financial Disclosure by Clinical Investigators; Proposed Rule [text] | [PDF ] (63 FR 5233, February 2, 1998)
• Financial Disclosure by a Clinical Investigator; Final Rule [text]  |  [PDF] (63 FR 72171-81, December 31, 1998)

Part 210- Current Good Manufacturing Practice in Manufacturing, Processing, Packing, or Holding of Drugs; General

• Current Good Manufacturing Practice Regulations and Investigational New Drugs [text]  |  [PDF]   (January 17, 2006)

Part 312- Investigational New Drug Application

• Proposed New Drug, Antibiotic, and Biologic Drug Product Regulations (48 FR 26720, June 9, 1983)
• New Drug and Antibiotic Regulations (50 FR 7452, February 22, 1985)
• New Drug, Antibiotic, and Biologic Drug Product Regulations (52 FR 8850, March 19, 1987)
• Investigational New Drug Applications and New Drug Applications [text] | [PDF] ( September 8, 1995)
• Investigational New Drug Applications and New Drug Applications [text]  | [PDF]   ( February 11, 1998)
• Disqualification of a Clinical Investigator [text] | [PDF] (February 16, 1996)
• Disqualification of a Clinical Investigator [text] | [PDF] (September 5, 1997)
• Expedited Safety Reporting Requirements for Human Drug and Biological Products [text] | [PDF] (62 FR 52237, October 7, 1997)
• Clinical Hold for products intended for life threatening conditions [text]  | [PDF] (65 FR 34963-71, June 1, 2000)
• Human Subject Protection; Foreign Clinical Studies Not Conducted Under an Investigational New Drug Application; Final Rule [text] | [PDF] (73 FR 22800, April 28, 2008)
• Proposed Rule [text]  | [PDF] (75 FR 7412, February 19, 2010)
• Withdrawal Notice [text]  | [PDF] (83 FR 49023, September 28, 2018)
• Investigational New Drug Safety Reporting Requirements for Human Drug and Biological Products and Safety Reporting Requirements for Bioavailability and Bioequivalence Studies in Humans; Final Rule [text]  |  [PDF]   (75 FR 59935, September 29, 2010)
• Disqualification of a Clinical Investigator [text]  | [PDF]  (77 FR 25353, April 30, 2012)

Part 314 – Applications for FDA Approval to Market a New Drug Part 601 – Applications for FDA Approval of a Biologic License

• New Drug and Biological Drug Products; Evidence Needed to Demonstrate Effectiveness of New Drugs When Human Efficacy Studies Are Not Ethical or Feasible; Final Rule [text] | [PDF]  (67 FR 37988, May 31, 2002)

Part 320- Bioavailability and Bioequivalence Requirements

• Retention of BE and BA Testing Samples; Final Rule [text] (58 FR 25918, April 28, 1993)
• Investigational New Drug Safety Reporting Requirements for Human Drug and Biological Products and Safety Reporting Requirements for Bioavailability and Bioequivalence Studies in Humans;Final Rule [text] | [PDF] (75 FR 59935, September 29, 2010)

Part 812- Investigational Device Exemptions

• Medical Devices; Current Good Manufacturing Practice (CGMP)Quality System Regulations [text] | [PDF] ( 61 FR 52602, October 7, 1996)
• Treatment Use of Investigational Devices [text] | [PDF] ( 62 FR 48940, September 18, 1997)
• Withdrawal of Intraocular Lenses Regulation (Part 813) [text]  |  [PDF]   ( 62 FR 4164, January 29, 1997)
• Disqualification of Clinical Investigators [text] | [PDF] ( 62 FR 12087, March 14, 1997)
• FDA Modernization Act of 1997: Modifications to the List of Recognized Standards [text] | [PDF] ( 64 FR 37546, July 12, 1999)
• Medical Devices; Investigational Device Exemptions (Modifications to the Medical Device and/or Study Protocol); Final Rule [text] | [PDF] ( 63 FR 64617, November 23, 1998)
• Disqualification of a Clinical Investigator [text]  | [PDF] ( 77 FR 25353, April 30, 2012)

Human Subject Protection; Acceptance of Data From Clinical Studies for Medical Devices

• Proposed Rule [text] [PDF] (78 FR 12664, February 25, 2013)
• Final Rule [text] [PDF] (83 FR 7366, February 21, 2018)

Part 814- Premarket Approval of Medical Devices

• Medical Devices; Humanitarian Use Devices Part V ; Final Rule [text] | [PDF] ( 61 FR 33232, June 26, 1996)
• 30-Day Notices and 135-Day PMA Supplement Review; Final Rule [text] | [PDF] ( 63 FR 54042, October 8, 1998)
• Humanitarian Use of Devices; Final Rule [text]  | [PDF] (63 FR 59217, November 3, 1998)
• Medical Devices; Exception from General Requirements for Informed Consent; Interim Final Rule [text] | [PDF] (71 FR 32827, June 7, 2006)

Miscellaneous

• Determination of Mode of Action in Combination Products (PDF - 13KB) (70 FR 49848, August 25, 2005) [text] This rule defines "mode of action" and "primary mode of action" and sets forth the algorithm FDA will use to assign combination products to an agency component for regulatory oversight.
• Administrative Practices and Procedures; Good Guidance Practices; Proposed Rule [text] [PDF] (65 FR 7321, February 14, 2000)
• Administrative Practices and Procedures; Good Guidance Practices; Final Rule [text] [PDF] (65 FR 56468, September 19, 2000)
• Index and Copies of Presiding Officer Reports and Commissioner Decisions on the Eligibilty of a Clinical Investigator to Continue to Receive Investigational Products; Availabilty [text]  | [PDF] (66 FR 45317-8, August 28, 2001)
• Part 11 Electronic Records; Electronic Signatures [text]    | [PDF] ( 62 FR 13430, March 20, 1997)
• Privacy Act of 1974; Altered Sysytem of Records, Including Addition of Routine Use(s) to an Existing System of Records Notification of an altered system of records, including the addition of new routine use [text]   | [PDF] (63 FR 55873-6, October 19, 1998)

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Clinical Research Paper Topics

This page aims to provide a comprehensive list of clinical research paper topics spanning various subfields of clinical research. It further guides students on how to choose a fitting topic and how to write an effective clinical research paper. Additionally, it introduces iResearchNet’s writing services, offering a platform for students to order a custom clinical research paper. The ultimate goal of this resource is to support students in their quest for academic excellence and successful navigation through the realm of clinical research.

100 Clinical Research Paper Topics

Navigating through the extensive field of clinical research may seem daunting. To streamline this process, we present a comprehensive list of clinical research paper topics divided into ten categories. Each category features ten engaging and relevant topics that cover a wide range of current issues in the field of clinical research.

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1. Disease Prevention and Management:

• The Role of Clinical Research in the Prevention of Cardiovascular Diseases
• Advancements in Clinical Strategies for Diabetes Management
• Impact of Clinical Research in Cancer Prevention
• Novel Clinical Approaches to Managing Obesity
• Prevention and Control of Sexually Transmitted Infections: Clinical Perspectives
• Clinical Research in the Battle Against Alzheimer’s Disease
• Impact of Lifestyle Changes on Disease Prevention: Clinical Evidence
• Role of Vaccination in the Prevention of Infectious Diseases: A Clinical Overview
• Clinical Trials in the Prevention and Management of Mental Health Disorders
• Osteoporosis: Prevention and Management Strategies in Clinical Research

2. Clinical Trials:

• The Importance of Randomization in Clinical Trials
• Ethical Considerations in Conducting Clinical Trials
• The Role of Placebos in Clinical Trials
• Clinical Trials in Pediatric Populations
• Patient Recruitment Strategies in Clinical Trials
• Advances in Oncology: The Role of Clinical Trials
• The Impact of Clinical Trials on Drug Development
• Adaptive Design in Clinical Trials
• Challenges in the Conduct of Clinical Trials during a Pandemic
• Clinical Trials: From Bench to Bedside

3. Ethical Issues in Clinical Research:

• Informed Consent in Clinical Research
• Confidentiality and Privacy Issues in Clinical Research
• The Ethics of Using Animals in Clinical Research
• Ethical Dilemmas in Genetic Testing and Clinical Research
• Protection of Vulnerable Groups in Clinical Research
• Balancing Benefit and Risk in Clinical Research
• Ethical Aspects of Research using Human Tissue Samples
• Data Integrity and Ethical Considerations in Clinical Research
• Ethical Challenges in Conducting Research on Rare Diseases
• Conflict of Interest in Clinical Research

4. Technological Advancements in Clinical Research:

• The Role of Artificial Intelligence in Clinical Research
• Use of Mobile Technologies in Clinical Trials
• Big Data and Its Impact on Clinical Research
• The Potential of Virtual Reality in Clinical Trials
• The Role of Blockchain Technology in Clinical Research
• Wearable Technology and Patient Monitoring in Clinical Trials
• The Impact of Genomics and Precision Medicine on Clinical Research
• Telemedicine and Its Role in Clinical Research
• The Role of Robotic Surgery in Clinical Trials
• Application of Nanotechnology in Clinical Research

5. Pharmacological Clinical Research:

• Clinical Trials and Drug Development
• Clinical Research in Antibiotic Resistance
• Adverse Drug Reactions: Monitoring and Management in Clinical Research
• Clinical Research in Psychopharmacology
• Pharmacogenetics and Personalized Medicine
• Clinical Research in Opioid Use and Addiction
• Clinical Trials for Novel Vaccines
• Clinical Research and the Development of Anticancer Drugs
• Pediatric Pharmacology and the Challenges in Clinical Research
• Over-the-counter Drugs and Self-Medication: A Clinical Research Perspective

6. Health Policy and Clinical Research:

• The Impact of Health Policy on Clinical Research
• Health Insurance Policies and Accessibility to Clinical Trials
• The Role of Policy in Regulating Clinical Trials
• How Health Policies Influence Patient Participation in Clinical Trials
• Policies for Ethical Conduct in Clinical Research
• Health Policy and Its Influence on Drug Development in Clinical Research
• The Impact of Global Health Policies on Clinical Research
• Policy Considerations for Genetic Testing in Clinical Research
• The Role of Policy in the Prevention of Clinical Research Misconduct
• The Impact of Health Policy Changes on the Scope of Clinical Research

7. Mental Health and Clinical Research:

• Clinical Research on the Efficacy of Cognitive Behavioral Therapy
• Role of Clinical Trials in Developing New Psychotropic Medications
• Advances in Clinical Research for Treating Post-Traumatic Stress Disorder
• The Role of Clinical Research in Understanding the Biology of Depression
• Clinical Research Approaches in Managing Childhood Autism
• Clinical Trials in the Development of Therapies for Schizophrenia
• Impact of Clinical Research on the Treatment of Anxiety Disorders
• Clinical Research on Mental Health in the Elderly
• Novel Clinical Approaches to Treating Eating Disorders
• The Role of Clinical Research in Suicidal Behavior Studies

8. Public Health and Clinical Research:

• The Role of Clinical Research in Advancing Public Health
• The Impact of Public Health Policies on Clinical Research
• Clinical Research on Preventive Measures in Public Health
• Clinical Trials and Their Significance in Public Health Improvement
• The Role of Clinical Research in Reducing Health Disparities
• Clinical Research in the Field of Occupational Health
• The Impact of Environmental Health Factors: A Clinical Research Perspective
• Clinical Research in the Control and Prevention of Epidemics
• The Role of Public Health Interventions in Clinical Research
• Global Public Health and the Need for International Clinical Research

9. Pediatric Clinical Research:

• Ethical Considerations in Pediatric Clinical Research
• The Role of Clinical Trials in Advancing Pediatric Medicine
• Clinical Research on Pediatric Oncology
• The Impact of Clinical Research on Pediatric Neurological Disorders
• Clinical Research on Rare Genetic Disorders in Children
• The Role of Clinical Research in Understanding and Treating Autism in Children
• Clinical Trials in the Development of Pediatric Vaccines
• The Impact of Clinical Research on Neonatal Care
• Challenges and Opportunities in Pediatric Clinical Trials
• Clinical Research in Pediatric Cardiology

10. Clinical Research in the Era of COVID-19:

• The Role of Clinical Research in Understanding COVID-19
• Clinical Trials for the Development of COVID-19 Vaccines
• Impact of the COVID-19 Pandemic on Ongoing Clinical Trials
• The Role of Clinical Research in Understanding Long-COVID
• Clinical Trials for COVID-19 Treatments: Successes and Challenges
• The Impact of COVID-19 on Mental Health: A Clinical Research Perspective
• Clinical Research on the Effect of COVID-19 in Children
• Lessons from COVID-19: Clinical Research for Future Pandemics
• The Role of Telemedicine in Clinical Research During COVID-19
• Ethical Considerations for Clinical Research During a Global Pandemic

This comprehensive list ensures that students have a broad spectrum of contemporary and significant topics to choose from, allowing them to find a subject that fits their interests and the current demands of the field.

Choosing Clinical Research Paper Topics

Choosing the right clinical research paper topic is a critical first step in the writing process. The topic you choose can set the tone for your entire project and greatly affect your experience. Here are ten tips to guide you in making the right choice:

• Understand the Assignment: Before diving into topic selection, ensure you fully understand your assignment’s parameters. Are there specific guidelines about the type of topic you should choose? Is there a certain page or word limit? Do you need to incorporate specific resources? Understanding these requirements can help you tailor your topic appropriately.
• Passion and Interest: Choose a topic that genuinely interests you. Writing a research paper can be a long process, and your passion for the subject can keep you motivated. It also makes it easier to delve deeper and provide new insights.
• Scope of the Topic: Consider the breadth of your topic. Is it too broad to be adequately covered in your paper, or is it too narrow that it lacks sufficient material for research? Aim for a balance where your topic can be fully addressed within the constraints of your assignment.
• Relevance: Opt for topics that are relevant to your field of study and the current climate of research. These could be emerging trends, pressing issues, or gaps in the existing literature that need to be filled.
• Originality: Try to select a topic that is unique and original. While you don’t have to reinvent the wheel, having a fresh perspective or a novel aspect can make your paper more interesting.
• Availability of Resources: Before finalizing a topic, ensure there are enough resources available for you to research. These could be scholarly articles, books, reliable online sources, or primary research materials.
• Consult with Your Instructor or Advisor: If you’re struggling with choosing a topic, don’t hesitate to consult your instructor or advisor. They can provide valuable guidance, help you refine your ideas, and point you towards resources you may not have considered.
• Future Implications: Consider how the topic you choose might impact your future career or academic goals. Is it something that could contribute to your long-term research goals or lead to a specialization?
• Practicality: Consider the feasibility of your topic. Do you have the time and resources to complete this research? For instance, if your topic requires conducting surveys or interviews, will you have access to the required sample population?
• Preliminary Research: Carry out some preliminary research before finalizing your topic. This will give you a better idea of what’s been done before, the arguments that exist around your topic, and how you can contribute to the discussion.

By considering these factors, you can ensure that the topic you choose is suited to your interests, academic goals, and the requirements of the assignment. The right topic can make the research and writing process much smoother and more enjoyable. Remember, a well-chosen topic is the first step towards a successful research paper.

How to Write a Clinical Research Paper

Writing a clinical research paper can be an intimidating task, particularly for students who are just beginning their journey in the health sciences field. The process can be made much easier by breaking it down into manageable steps. Here are ten tips that will help you successfully write a clinical research paper:

• Understand the Assignment: Before starting, ensure you understand the scope and requirements of the assignment. Are there specific formatting guidelines? Are there any required sections? Are certain sources preferred over others? Understanding these elements can guide your writing process.
• Thorough Research: Once you’ve chosen a topic, start your in-depth research. Look for reputable sources, such as peer-reviewed journal articles, textbooks, and government reports. Always cross-check information from multiple sources to ensure accuracy.
• Develop a Thesis Statement: Your thesis statement should concisely summarize your paper’s main argument or focus. It should be clear, specific, and arguable. It will guide your research and writing, helping to keep your paper focused.
• Create an Outline: An outline serves as a roadmap for your paper. It organizes your thoughts and helps ensure you address all necessary points. Your outline should include an introduction, body sections (often following the IMRaD format: Introduction, Methods, Results, and Discussion), and a conclusion.
• Start with the Methods Section: In a clinical research paper, starting with the Methods section can often be easiest as it includes concrete details of the research conducted. Detail the study’s design, participants, procedures, and data analysis. Be thorough so other researchers could replicate your study if needed.
• Write the Results Section: Present your findings without interpretation in this section. Use visuals such as tables, graphs, or charts to help illustrate the data where appropriate.
• Discuss Your Findings: The Discussion section is where you interpret your results. Connect your findings to your original research question and the existing literature in the field. Discuss whether your results met your expectations, what implications they might have, and any limitations of your study.
• Craft Your Introduction and Conclusion: Your Introduction should provide background information, state the research problem, and outline your paper’s structure. The Conclusion should summarize your findings, discuss their implications, and suggest areas for future research.
• Cite Your Sources: Always properly cite your sources to give credit to the original authors and allow readers to refer to the original work. Be consistent with the citation style requested by your instructor or the one generally used in your field (APA, MLA, Chicago/Turabian, Harvard).
• Revise and Proofread: Revision is a critical part of the writing process. Look for areas where clarity or coherence can be improved. Check for grammar, punctuation, and spelling errors.

Remember, writing a clinical research paper is not an overnight process. It takes time and effort to research, write, and refine a scientific paper. Pace yourself and don’t be afraid to ask for help if you need it. Your instructors, advisors, or school’s writing center can all be valuable resources.

iResearchNet’s Custom Writing Services

Navigating the complexities of writing a clinical research paper can be daunting, especially for students who are new to the field or juggling multiple responsibilities. That’s where iResearchNet steps in. Offering a robust suite of writing services tailored to the needs of health science students, iResearchNet is committed to helping you deliver quality research papers that meet academic standards. Here’s a deeper look at what we offer:

• Expert Degree-Holding Writers: Our team comprises skilled writers holding degrees in health sciences. With a deep understanding of clinical research’s intricacies, they can craft papers that reflect rigorous research and sophisticated understanding of the subject matter.
• Custom Written Works: We don’t believe in one-size-fits-all solutions. Our writers work closely with you to understand your unique requirements and create papers tailored to your needs, ensuring your individual voice shines through.
• In-Depth Research: Our services go beyond just writing. Our experts conduct comprehensive research, diving deep into scholarly resources to gather relevant, up-to-date information for your paper.
• Custom Formatting: Proper formatting is crucial in academic writing. Whether your paper requires APA, MLA, Chicago/Turabian, or Harvard style, our writers are well-versed in these formats and will ensure your paper adheres to the requisite style guidelines.
• Top Quality: We strive for excellence. Our rigorous quality control process involves thorough proofreading and editing to ensure that the final paper is of the highest quality, free of grammatical errors and plagiarism.
• Customized Solutions: Whether you need help with topic selection, an outline, or a complete paper, we offer customized solutions to suit your needs. We are here to provide as much (or as little) help as you need.
• Flexible Pricing: We understand that students work with tight budgets. That’s why we’ve designed our pricing to be affordable and flexible, offering various options to cater to different financial capabilities.
• Short Deadlines up to 3 Hours: Facing a time crunch? We have got you covered. Our team can deliver high-quality work even on tight deadlines – as short as three hours, ensuring you never miss your submission deadlines.
• Timely Delivery: We pride ourselves on our punctuality. Our writers work diligently to ensure your paper is completed on time, if not ahead of schedule, allowing you ample time for review.
• 24/7 Support: Our customer support team is available round the clock to answer your queries, address concerns, and facilitate seamless communication between you and the writer.
• Absolute Privacy: We respect your privacy. Our encrypted systems ensure your personal and financial information remains secure. We adhere to strict confidentiality policies, and we never share your information with third parties.
• Easy Order Tracking: With our user-friendly interface, you can easily track your order’s progress. You can also communicate directly with your writer, providing feedback and clarifications where necessary.
• Money Back Guarantee: Your satisfaction is our top priority. If you’re not completely satisfied with the work, we offer a money-back guarantee, standing behind the quality of our services.

With iResearchNet, you don’t have to navigate the demanding process of writing a clinical research paper alone. Our dedicated team of experts is ready to help you every step of the way, ensuring you can focus on mastering your subject matter while we handle the complex task of crafting a compelling research paper.

Empower Your Academic Journey with iResearchNet

You’ve seen what it takes to write a clinical research paper and the breadth of fascinating topics waiting to be explored. The journey may seem challenging, but it is also an opportunity to deepen your understanding of the health sciences, to contribute to the body of knowledge in your field, and to hone your skills as a researcher and writer. But you don’t have to embark on this journey alone. iResearchNet is here to accompany you every step of the way.

We invite you to experience the unparalleled support and expertise that our team offers. With our extensive suite of writing services, you’ll find the tools and resources you need to produce a quality research paper that reflects your hard work and dedication to your studies. Take advantage of our expert degree-holding writers’ knowledge, our commitment to in-depth research, and our proficiency in academic formatting styles to turn the daunting task of writing a research paper into a manageable, even enjoyable, process.

Choosing iResearchNet means choosing peace of mind. With our timely delivery, 24/7 support, and privacy assurance, you can focus on what matters most—your learning. And with our money-back guarantee, you can rest easy knowing that we stand firmly behind the quality of our services.

Don’t miss this opportunity to take your academic journey to the next level. Contact us today, share your clinical research paper needs, and experience firsthand how iResearchNet can help pave your path to academic success. The journey of a thousand miles begins with a single step. Let iResearchNet be that step for you.

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Best Nursing Research Topics for Students

What is a nursing research paper.

• What They Include
• Choosing a Topic
• Best Nursing Research Topics
• Research Paper Writing Tips

Writing a research paper is a massive task that involves careful organization, critical analysis, and a lot of time. Some nursing students are natural writers, while others struggle to select a nursing research topic, let alone write about it.

If you're a nursing student who dreads writing research papers, this article may help ease your anxiety. We'll cover everything you need to know about writing nursing school research papers and the top topics for nursing research.  

Continue reading to make your paper-writing jitters a thing of the past.

A nursing research paper is a work of academic writing composed by a nurse or nursing student. The paper may present information on a specific topic or answer a question.

During LPN/LVN and RN programs, most papers you write focus on learning to use research databases, evaluate appropriate resources, and format your writing with APA style. You'll then synthesize your research information to answer a question or analyze a topic.

BSN , MSN , Ph.D., and DNP programs also write nursing research papers. Students in these programs may also participate in conducting original research studies.

Writing papers during your academic program improves and develops many skills, including the ability to:

• Select nursing topics for research
• Conduct effective research
• Analyze published academic literature
• Format and cite sources
• Synthesize data
• Organize and articulate findings

About Nursing Research Papers

When do nursing students write research papers.

You may need to write a research paper for any of the nursing courses you take. Research papers help develop critical thinking and communication skills. They allow you to learn how to conduct research and critically review publications.

That said, not every class will require in-depth, 10-20-page papers. The more advanced your degree path, the more you can expect to write and conduct research. If you're in an associate or bachelor's program, you'll probably write a few papers each semester or term.

Do Nursing Students Conduct Original Research?

Most of the time, you won't be designing, conducting, and evaluating new research. Instead, your projects will focus on learning the research process and the scientific method. You'll achieve these objectives by evaluating existing nursing literature and sources and defending a thesis.

However, many nursing faculty members do conduct original research. So, you may get opportunities to participate in, and publish, research articles.

Example Research Project Scenario:

In your maternal child nursing class, the professor assigns the class a research paper regarding developmentally appropriate nursing interventions for the pediatric population. While that may sound specific, you have almost endless opportunities to narrow down the focus of your writing. 

You could choose pain intervention measures in toddlers. Conversely, you can research the effects of prolonged hospitalization on adolescents' social-emotional development.

What Does a Nursing Research Paper Include?

Your professor should provide a thorough guideline of the scope of the paper. In general, an undergraduate nursing research paper will consist of:

Introduction : A brief overview of the research question/thesis statement your paper will discuss. You can include why the topic is relevant.

Body : This section presents your research findings and allows you to synthesize the information and data you collected. You'll have a chance to articulate your evaluation and answer your research question. The length of this section depends on your assignment.

Conclusion : A brief review of the information and analysis you presented throughout the body of the paper. This section is a recap of your paper and another chance to reassert your thesis.

The best advice is to follow your instructor's rubric and guidelines. Remember to ask for help whenever needed, and avoid overcomplicating the assignment!

How to Choose a Nursing Research Topic

The sheer volume of prospective nursing research topics can become overwhelming for students. Additionally, you may get the misconception that all the 'good' research ideas are exhausted. However, a personal approach may help you narrow down a research topic and find a unique angle.

Writing your research paper about a topic you value or connect with makes the task easier. Additionally, you should consider the material's breadth. Topics with plenty of existing literature will make developing a research question and thesis smoother.

Finally, feel free to shift gears if necessary, especially if you're still early in the research process. If you start down one path and have trouble finding published information, ask your professor if you can choose another topic.

The Best Research Topics for Nursing Students

You have endless subject choices for nursing research papers. This non-exhaustive list just scratches the surface of some of the best nursing research topics.

1. Clinical Nursing Research Topics

• Analyze the use of telehealth/virtual nursing to reduce inpatient nurse duties.
• Discuss the impact of evidence-based respiratory interventions on patient outcomes in critical care settings.
• Explore the effectiveness of pain management protocols in pediatric patients.

2. Community Health Nursing Research Topics

• Assess the impact of nurse-led diabetes education in Type II Diabetics.
• Analyze the relationship between socioeconomic status and access to healthcare services.

3. Nurse Education Research Topics

• Review the effectiveness of simulation-based learning to improve nursing students' clinical skills.
• Identify methods that best prepare pre-licensure students for clinical practice.
• Investigate factors that influence nurses to pursue advanced degrees.
• Evaluate education methods that enhance cultural competence among nurses.
• Describe the role of mindfulness interventions in reducing stress and burnout among nurses.

4. Mental Health Nursing Research Topics

• Explore patient outcomes related to nurse staffing levels in acute behavioral health settings.
• Assess the effectiveness of mental health education among emergency room nurses .
• Explore de-escalation techniques that result in improved patient outcomes.
• Review the effectiveness of therapeutic communication in improving patient outcomes.

5. Pediatric Nursing Research Topics

• Assess the impact of parental involvement in pediatric asthma treatment adherence.
• Explore challenges related to chronic illness management in pediatric patients.
• Review the role of play therapy and other therapeutic interventions that alleviate anxiety among hospitalized children.

6. The Nursing Profession Research Topics

• Analyze the effects of short staffing on nurse burnout .
• Evaluate factors that facilitate resiliency among nursing professionals.
• Examine predictors of nurse dissatisfaction and burnout.
• Posit how nursing theories influence modern nursing practice.

Tips for Writing a Nursing Research Paper

The best nursing research advice we can provide is to follow your professor's rubric and instructions. However, here are a few study tips for nursing students to make paper writing less painful:

Avoid procrastination: Everyone says it, but few follow this advice. You can significantly lower your stress levels if you avoid procrastinating and start working on your project immediately.

Plan Ahead: Break down the writing process into smaller sections, especially if it seems overwhelming. Give yourself time for each step in the process.

Research: Use your resources and ask for help from the librarian or instructor. The rest should come together quickly once you find high-quality studies to analyze.

Outline: Create an outline to help you organize your thoughts. Then, you can plug in information throughout the research process. 

Clear Language: Use plain language as much as possible to get your point across. Jargon is inevitable when writing academic nursing papers, but keep it to a minimum.

Cite Properly: Accurately cite all sources using the appropriate citation style. Nursing research papers will almost always implement APA style. Check out the resources below for some excellent reference management options.

Revise and Edit: Once you finish your first draft, put it away for one to two hours or, preferably, a whole day. Once you've placed some space between you and your paper, read through and edit for clarity, coherence, and grammatical errors. Reading your essay out loud is an excellent way to check for the 'flow' of the paper.

Helpful Nursing Research Writing Resources:

Purdue OWL (Online writing lab) has a robust APA guide covering everything you need about APA style and rules.

Grammarly helps you edit grammar, spelling, and punctuation. Upgrading to a paid plan will get you plagiarism detection, formatting, and engagement suggestions. This tool is excellent to help you simplify complicated sentences.

Mendeley is a free reference management software. It stores, organizes, and cites references. It has a Microsoft plug-in that inserts and correctly formats APA citations.

Don't let nursing research papers scare you away from starting nursing school or furthering your education. Their purpose is to develop skills you'll need to be an effective nurse: critical thinking, communication, and the ability to review published information critically.

Choose a great topic and follow your teacher's instructions; you'll finish that paper in no time.

Joleen Sams is a certified Family Nurse Practitioner based in the Kansas City metro area. During her 10-year RN career, Joleen worked in NICU, inpatient pediatrics, and regulatory compliance. Since graduating with her MSN-FNP in 2019, she has worked in urgent care and nursing administration. Connect with Joleen on LinkedIn or see more of her writing on her website.

Plus, get exclusive access to discounts for nurses, stay informed on the latest nurse news, and learn how to take the next steps in your career.

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SYSTEMATIC REVIEW article

This article is part of the research topic.

Reviews in Gastroenterology 2023

Electrogastrography Measurement Systems and Analysis Methods Used in Clinical Practice and Research: Comprehensive Review Provisionally Accepted

• 1 VSB-Technical University of Ostrava, Czechia

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

Electrogastrography (EGG) is a non-invasive method with high diagnostic potential for the prevention of gastroenterological pathologies in clinical practice. In this paper, a review of the measurement systems, procedures, and methods of analysis used in electrogastrography is presented. A critical review of historical and current literature is conducted, focusing on electrode placement, measurement apparatus, measurement procedures, and time-frequency domain methods of filtration and analysis of the non-invasively measured electrical activity of the stomach.As a result a total of 129 relevant articles with primary aim on experimental diet were reviewed in this study. Scopus, PubMed and Web of Science databases were used to search for articles in English language, according to the specific query and using PRISMA method. The research topic of electrogastrography has been continuously growing in popularity since the first measurement by professor Alvarez 100 years ago and there are many researchers and companies interested in EGG nowadays. Measurement apparatus and procedures are still being developed in both commercial and research settings. There are plenty variable electrode layouts, ranging from minimal numbers of electrodes for ambulatory measurements to very high numbers of electrodes for spatial measurements. Most authors used in their research anatomically approximated layout with 2 active electrodes in bipolar connection and commercial electrogastrograph with sampling rate of 2 or 4 Hz. Test subjects were usually healthy adults and diet was controlled. However, evaluation methods are being developed at a slower pace and usually the signals are classified only based on dominant frequency. The main review contributions include the overview of spectrum of measurement systems and procedures for electrogastrography developed by many authors, but a firm medical standard has not yet been defined. Therefore, it is not possible to use this method in clinical practice for objective diagnosis.

Keywords: electrogastrography, non-invasive method, Measurement systems, Electrode placement, Measurement apparatus, Signal processing

Received: 19 Jan 2024; Accepted: 03 Jun 2024.

Copyright: © 2024 Oczka, Augustynek, Penhaker and Kubicek. 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: Dr. Jan Kubicek, VSB-Technical University of Ostrava, Ostrava, 708 33, Moravian-Silesian Region, Czechia

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New policy recommends AI tech should augment physician decision-making, not replace it

by American College of Physicians

The use of artificial intelligence (AI) in clinical health care has the potential to transform health care delivery but it should not replace physician decision-making, says the American College of Physicians (ACP) in a new policy paper, titled " Artificial Intelligence in the Provision of Health Care ," published in the Annals of Internal Medicine . The paper offers recommendations on the ethical, scientific, and clinical components of AI use, and says that AI tools and systems should enhance human intelligence, not supplant it.

"AI has the potential to aid in solving some of the issues currently plaguing the health care industry, such as clinician shortages, burnout, and administrative burdens," said Isaac O. Opole, MBChB, Ph.D., MACP, president, ACP. "However, to ensure that we are able to realize the most benefit, with the fewest harms to patients, we need to fully understand the implications of the technology that we are implementing."

To navigate the risks and ensure best practices , ACP recommends that AI-enabled technology should be limited to a supportive role in clinical decision-making. ACP notes that when being used for clinical decision-making, the technology would more appropriately be called "augmented" intelligence, since the tools should ideally be used to assist clinicians, not replace them.

The tools must be developed, tested, and used transparently, while prioritizing privacy, clinical safety, and effectiveness. The use of technology should actively work to reduce, not exacerbate, disparities, ensuring a fair and just health care system.

ACP recommends that to ensure accountability and oversight of AI-enabled medical tools, there should be a coordinated federal strategy involving oversight of AI by governmental and non-governmental regulatory entities. The tools should be designed to reduce physician and other clinician burdens in support of patient care, while guided by unwavering principles of medical ethics.

Additionally, to ensure that AI tools are administered safely, ACP advises that training on AI in medicine be provided at all levels of medical education. Physicians must be able to both use the technology and remain able to make appropriate clinical decisions independently, in the case that AI decision support becomes unavailable. Lastly, efforts to quantify the environmental impacts of AI must continue and mitigation of those impacts should be considered.

"AI has already made an impact in the medical community , and ACP is excited about what it means for the future of health care," said Dr. Opole.

"There is so much potential to use this revolutionary technology to improve clinical practices and promote health equity. As we incorporate AI into medical practice , it is essential to maintain an awareness of the clinical and ethical implications of AI technology and its impacts on patient well-being."

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• Published: 17 October 2023

The impact of founder personalities on startup success

• Paul X. McCarthy 1 , 2 ,
• Xian Gong 3 ,
• Fabian Braesemann 4 , 5 ,
• Fabian Stephany 4 , 5 ,
• Marian-Andrei Rizoiu 3 &
• Margaret L. Kern 6  

Scientific Reports volume  13 , Article number:  17200 ( 2023 ) Cite this article

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• Information technology

An Author Correction to this article was published on 07 May 2024

This article has been updated

Startup companies solve many of today’s most challenging problems, such as the decarbonisation of the economy or the development of novel life-saving vaccines. Startups are a vital source of innovation, yet the most innovative are also the least likely to survive. The probability of success of startups has been shown to relate to several firm-level factors such as industry, location and the economy of the day. Still, attention has increasingly considered internal factors relating to the firm’s founding team, including their previous experiences and failures, their centrality in a global network of other founders and investors, as well as the team’s size. The effects of founders’ personalities on the success of new ventures are, however, mainly unknown. Here, we show that founder personality traits are a significant feature of a firm’s ultimate success. We draw upon detailed data about the success of a large-scale global sample of startups (n = 21,187). We find that the Big Five personality traits of startup founders across 30 dimensions significantly differ from that of the population at large. Key personality facets that distinguish successful entrepreneurs include a preference for variety, novelty and starting new things (openness to adventure), like being the centre of attention (lower levels of modesty) and being exuberant (higher activity levels). We do not find one ’Founder-type’ personality; instead, six different personality types appear. Our results also demonstrate the benefits of larger, personality-diverse teams in startups, which show an increased likelihood of success. The findings emphasise the role of the diversity of personality types as a novel dimension of team diversity that influences performance and success.

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Introduction.

The success of startups is vital to economic growth and renewal, with a small number of young, high-growth firms creating a disproportionately large share of all new jobs 1 , 2 . Startups create jobs and drive economic growth, and they are also an essential vehicle for solving some of society’s most pressing challenges.

As a poignant example, six centuries ago, the German city of Mainz was abuzz as the birthplace of the world’s first moveable-type press created by Johannes Gutenberg. However, in the early part of this century, it faced several economic challenges, including rising unemployment and a significant and growing municipal debt. Then in 2008, two Turkish immigrants formed the company BioNTech in Mainz with another university research colleague. Together they pioneered new mRNA-based technologies. In 2020, BioNTech partnered with US pharmaceutical giant Pfizer to create one of only a handful of vaccines worldwide for Covid-19, saving an estimated six million lives 3 . The economic benefit to Europe and, in particular, the German city where the vaccine was developed has been significant, with windfall tax receipts to the government clearing Mainz’s €1.3bn debt and enabling tax rates to be reduced, attracting other businesses to the region as well as inspiring a whole new generation of startups 4 .

While stories such as the success of BioNTech are often retold and remembered, their success is the exception rather than the rule. The overwhelming majority of startups ultimately fail. One study of 775 startups in Canada that successfully attracted external investment found only 35% were still operating seven years later 5 .

But what determines the success of these ‘lucky few’? When assessing the success factors of startups, especially in the early-stage unproven phase, venture capitalists and other investors offer valuable insights. Three different schools of thought characterise their perspectives: first, supply-side or product investors : those who prioritise investing in firms they consider to have novel and superior products and services, investing in companies with intellectual property such as patents and trademarks. Secondly, demand-side or market-based investors : those who prioritise investing in areas of highest market interest, such as in hot areas of technology like quantum computing or recurrent or emerging large-scale social and economic challenges such as the decarbonisation of the economy. Thirdly, talent investors : those who prioritise the foundation team above the startup’s initial products or what industry or problem it is looking to address.

Investors who adopt the third perspective and prioritise talent often recognise that a good team can overcome many challenges in the lead-up to product-market fit. And while the initial products of a startup may or may not work a successful and well-functioning team has the potential to pivot to new markets and new products, even if the initial ones prove untenable. Not surprisingly, an industry ‘autopsy’ into 101 tech startup failures found 23% were due to not having the right team—the number three cause of failure ahead of running out of cash or not having a product that meets the market need 6 .

Accordingly, early entrepreneurship research was focused on the personality of founders, but the focus shifted away in the mid-1980s onwards towards more environmental factors such as venture capital financing 7 , 8 , 9 , networks 10 , location 11 and due to a range of issues and challenges identified with the early entrepreneurship personality research 12 , 13 . At the turn of the 21st century, some scholars began exploring ways to combine context and personality and reconcile entrepreneurs’ individual traits with features of their environment. In her influential work ’The Sociology of Entrepreneurship’, Patricia H. Thornton 14 discusses two perspectives on entrepreneurship: the supply-side perspective (personality theory) and the demand-side perspective (environmental approach). The supply-side perspective focuses on the individual traits of entrepreneurs. In contrast, the demand-side perspective focuses on the context in which entrepreneurship occurs, with factors such as finance, industry and geography each playing their part. In the past two decades, there has been a revival of interest and research that explores how entrepreneurs’ personality relates to the success of their ventures. This new and growing body of research includes several reviews and meta-studies, which show that personality traits play an important role in both career success and entrepreneurship 15 , 16 , 17 , 18 , 19 , that there is heterogeneity in definitions and samples used in research on entrepreneurship 16 , 18 , and that founder personality plays an important role in overall startup outcomes 17 , 19 .

Motivated by the pivotal role of the personality of founders on startup success outlined in these recent contributions, we investigate two main research questions:

Which personality features characterise founders?

Do their personalities, particularly the diversity of personality types in founder teams, play a role in startup success?

We aim to understand whether certain founder personalities and their combinations relate to startup success, defined as whether their company has been acquired, acquired another company or listed on a public stock exchange. For the quantitative analysis, we draw on a previously published methodology 20 , which matches people to their ‘ideal’ jobs based on social media-inferred personality traits.

We find that personality traits matter for startup success. In addition to firm-level factors of location, industry and company age, we show that founders’ specific Big Five personality traits, such as adventurousness and openness, are significantly more widespread among successful startups. As we find that companies with multi-founder teams are more likely to succeed, we cluster founders in six different and distinct personality groups to underline the relevance of the complementarity in personality traits among founder teams. Startups with diverse and specific combinations of founder types (e. g., an adventurous ‘Leader’, a conscientious ‘Accomplisher’, and an extroverted ‘Developer’) have significantly higher odds of success.

We organise the rest of this paper as follows. In the Section " Results ", we introduce the data used and the methods applied to relate founders’ psychological traits with their startups’ success. We introduce the natural language processing method to derive individual and team personality characteristics and the clustering technique to identify personality groups. Then, we present the result for multi-variate regression analysis that allows us to relate firm success with external and personality features. Subsequently, the Section " Discussion " mentions limitations and opportunities for future research in this domain. In the Section " Methods ", we describe the data, the variables in use, and the clustering in greater detail. Robustness checks and additional analyses can be found in the Supplementary Information.

Our analysis relies on two datasets. We infer individual personality facets via a previously published methodology 20 from Twitter user profiles. Here, we restrict our analysis to founders with a Crunchbase profile. Crunchbase is the world’s largest directory on startups. It provides information about more than one million companies, primarily focused on funding and investors. A company’s public Crunchbase profile can be considered a digital business card of an early-stage venture. As such, the founding teams tend to provide information about themselves, including their educational background or a link to their Twitter account.

We infer the personality profiles of the founding teams of early-stage ventures from their publicly available Twitter profiles, using the methodology described by Kern et al. 20 . Then, we correlate this information to data from Crunchbase to determine whether particular combinations of personality traits correspond to the success of early-stage ventures. The final dataset used in the success prediction model contains n = 21,187 startup companies (for more details on the data see the Methods section and SI section  A.5 ).

Revisions of Crunchbase as a data source for investigations on a firm and industry level confirm the platform to be a useful and valuable source of data for startups research, as comparisons with other sources at micro-level, e.g., VentureXpert or PwC, also suggest that the platform’s coverage is very comprehensive, especially for start-ups located in the United States 21 . Moreover, aggregate statistics on funding rounds by country and year are quite similar to those produced with other established sources, going to validate the use of Crunchbase as a reliable source in terms of coverage of funded ventures. For instance, Crunchbase covers about the same number of investment rounds in the analogous sectors as collected by the National Venture Capital Association 22 . However, we acknowledge that the data source might suffer from registration latency (a certain delay between the foundation of the company and its actual registration on Crunchbase) and success bias in company status (the likeliness that failed companies decide to delete their profile from the database).

The definition of startup success

The success of startups is uncertain, dependent on many factors and can be measured in various ways. Due to the likelihood of failure in startups, some large-scale studies have looked at which features predict startup survival rates 23 , and others focus on fundraising from external investors at various stages 24 . Success for startups can be measured in multiple ways, such as the amount of external investment attracted, the number of new products shipped or the annual growth in revenue. But sometimes external investments are misguided, revenue growth can be short-lived, and new products may fail to find traction.

Success in a startup is typically staged and can appear in different forms and times. For example, a startup may be seen to be successful when it finds a clear solution to a widely recognised problem, such as developing a successful vaccine. On the other hand, it could be achieving some measure of commercial success, such as rapidly accelerating sales or becoming profitable or at least cash positive. Or it could be reaching an exit for foundation investors via a trade sale, acquisition or listing of its shares for sale on a public stock exchange via an Initial Public Offering (IPO).

For our study, we focused on the startup’s extrinsic success rather than the founders’ intrinsic success per se, as its more visible, objective and measurable. A frequently considered measure of success is the attraction of external investment by venture capitalists 25 . However, this is not in and of itself a good measure of clear, incontrovertible success, particularly for early-stage ventures. This is because it reflects investors’ expectations of a startup’s success potential rather than actual business success. Similarly, we considered other measures like revenue growth 26 , liquidity events 27 , 28 , 29 , profitability 30 and social impact 31 , all of which have benefits as they capture incremental success, but each also comes with operational measurement challenges.

Therefore, we apply the success definition initially introduced by Bonaventura et al. 32 , namely that a startup is acquired, acquires another company or has an initial public offering (IPO). We consider any of these major capital liquidation events as a clear threshold signal that the company has matured from an early-stage venture to becoming or is on its way to becoming a mature company with clear and often significant business growth prospects. Together these three major liquidity events capture the primary forms of exit for external investors (an acquisition or trade sale and an IPO). For companies with a longer autonomous growth runway, acquiring another company marks a similar milestone of scale, maturity and capability.

Using multifactor analysis and a binary classification prediction model of startup success, we looked at many variables together and their relative influence on the probability of the success of startups. We looked at seven categories of factors through three lenses of firm-level factors: (1) location, (2) industry, (3) age of the startup; founder-level factors: (4) number of founders, (5) gender of founders, (6) personality characteristics of founders and; lastly team-level factors: (7) founder-team personality combinations. The model performance and relative impacts on the probability of startup success of each of these categories of founders are illustrated in more detail in section  A.6 of the Supplementary Information (in particular Extended Data Fig.  19 and Extended Data Fig.  20 ). In total, we considered over three hundred variables (n = 323) and their relative significant associations with success.

The personality of founders

Besides product-market, industry, and firm-level factors (see SI section  A.1 ), research suggests that the personalities of founders play a crucial role in startup success 19 . Therefore, we examine the personality characteristics of individual startup founders and teams of founders in relationship to their firm’s success by applying the success definition used by Bonaventura et al. 32 .

Employing established methods 33 , 34 , 35 , we inferred the personality traits across 30 dimensions (Big Five facets) of a large global sample of startup founders. The startup founders cohort was created from a subset of founders from the global startup industry directory Crunchbase, who are also active on the social media platform Twitter.

To measure the personality of the founders, we used the Big Five, a popular model of personality which includes five core traits: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Emotional stability. Each of these traits can be further broken down into thirty distinct facets. Studies have found that the Big Five predict meaningful life outcomes, such as physical and mental health, longevity, social relationships, health-related behaviours, antisocial behaviour, and social contribution, at levels on par with intelligence and socioeconomic status 36 Using machine learning to infer personality traits by analysing the use of language and activity on social media has been shown to be more accurate than predictions of coworkers, friends and family and similar in accuracy to the judgement of spouses 37 . Further, as other research has shown, we assume that personality traits remain stable in adulthood even through significant life events 38 , 39 , 40 . Personality traits have been shown to emerge continuously from those already evident in adolescence 41 and are not significantly influenced by external life events such as becoming divorced or unemployed 42 . This suggests that the direction of any measurable effect goes from founder personalities to startup success and not vice versa.

As a first investigation to what extent personality traits might relate to entrepreneurship, we use the personality characteristics of individuals to predict whether they were an entrepreneur or an employee. We trained and tested a machine-learning random forest classifier to distinguish and classify entrepreneurs from employees and vice-versa using inferred personality vectors alone. As a result, we found we could correctly predict entrepreneurs with 77% accuracy and employees with 88% accuracy (Fig.  1 A). Thus, based on personality information alone, we correctly predict all unseen new samples with 82.5% accuracy (See SI section  A.2 for more details on this analysis, the classification modelling and prediction accuracy).

We explored in greater detail which personality features are most prominent among entrepreneurs. We found that the subdomain or facet of Adventurousness within the Big Five Domain of Openness was significant and had the largest effect size. The facet of Modesty within the Big Five Domain of Agreeableness and Activity Level within the Big Five Domain of Extraversion was the subsequent most considerable effect (Fig.  1 B). Adventurousness in the Big Five framework is defined as the preference for variety, novelty and starting new things—which are consistent with the role of a startup founder whose role, especially in the early life of the company, is to explore things that do not scale easily 43 and is about developing and testing new products, services and business models with the market.

Once we derived and tested the Big Five personality features for each entrepreneur in our data set, we examined whether there is evidence indicating that startup founders naturally cluster according to their personality features using a Hopkins test (see Extended Data Figure  6 ). We discovered clear clustering tendencies in the data compared with other renowned reference data sets known to have clusters. Then, once we established the founder data clusters, we used agglomerative hierarchical clustering. This ‘bottom-up’ clustering technique initially treats each observation as an individual cluster. Then it merges them to create a hierarchy of possible cluster schemes with differing numbers of groups (See Extended Data Fig.  7 ). And lastly, we identified the optimum number of clusters based on the outcome of four different clustering performance measurements: Davies-Bouldin Index, Silhouette coefficients, Calinski-Harabas Index and Dunn Index (see Extended Data Figure  8 ). We find that the optimum number of clusters of startup founders based on their personality features is six (labelled #0 through to #5), as shown in Fig.  1 C.

To better understand the context of different founder types, we positioned each of the six types of founders within an occupation-personality matrix established from previous research 44 . This research showed that ‘each job has its own personality’ using a substantial sample of employees across various jobs. Utilising the methodology employed in this study, we assigned labels to the cluster names #0 to #5, which correspond to the identified occupation tribes that best describe the personality facets represented by the clusters (see Extended Data Fig.  9 for an overview of these tribes, as identified by McCarthy et al. 44 ).

Utilising this approach, we identify three ’purebred’ clusters: #0, #2 and #5, whose members are dominated by a single tribe (larger than 60% of all individuals in each cluster are characterised by one tribe). Thus, these clusters represent and share personality attributes of these previously identified occupation-personality tribes 44 , which have the following known distinctive personality attributes (see also Table  1 ):

Accomplishers (#0) —Organised & outgoing. confident, down-to-earth, content, accommodating, mild-tempered & self-assured.

Leaders (#2) —Adventurous, persistent, dispassionate, assertive, self-controlled, calm under pressure, philosophical, excitement-seeking & confident.

Fighters (#5) —Spontaneous and impulsive, tough, sceptical, and uncompromising.

We labelled these clusters with the tribe names, acknowledging that labels are somewhat arbitrary, based on our best interpretation of the data (See SI section  A.3 for more details).

For the remaining three clusters #1, #3 and #4, we can see they are ‘hybrids’, meaning that the founders within them come from a mix of different tribes, with no one tribe representing more than 50% of the members of that cluster. However, the tribes with the largest share were noted as #1 Experts/Engineers, #3 Fighters, and #4 Operators.

To label these three hybrid clusters, we examined the closest occupations to the median personality features of each cluster. We selected a name that reflected the common themes of these occupations, namely:

Experts/Engineers (#1) as the closest roles included Materials Engineers and Chemical Engineers. This is consistent with this cluster’s personality footprint, which is highest in openness in the facets of imagination and intellect.

Developers (#3) as the closest roles include Application Developers and related technology roles such as Business Systems Analysts and Product Managers.

Operators (#4) as the closest roles include service, maintenance and operations functions, including Bicycle Mechanic, Mechanic and Service Manager. This is also consistent with one of the key personality traits of high conscientiousness in the facet of orderliness and high agreeableness in the facet of humility for founders in this cluster.

Founder-Level Factors of Startup Success. ( A ), Successful entrepreneurs differ from successful employees. They can be accurately distinguished using a classifier with personality information alone. ( B ), Successful entrepreneurs have different Big Five facet distributions, especially on adventurousness, modesty and activity level. ( C ), Founders come in six different types: Fighters, Operators, Accomplishers, Leaders, Engineers and Developers (FOALED) ( D ), Each founder Personality-Type has its distinct facet.

Together, these six different types of startup founders (Fig.  1 C) represent a framework we call the FOALED model of founder types—an acronym of Fighters, Operators, Accomplishers, Leaders, Engineers and D evelopers.

Each founder’s personality type has its distinct facet footprint (for more details, see Extended Data Figure  10 in SI section  A.3 ). Also, we observe a central core of correlated features that are high for all types of entrepreneurs, including intellect, adventurousness and activity level (Fig.  1 D).To test the robustness of the clustering of the personality facets, we compare the mean scores of the individual facets per cluster with a 20-fold resampling of the data and find that the clusters are, overall, largely robust against resampling (see Extended Data Figure  11 in SI section  A.3 for more details).

We also find that the clusters accord with the distribution of founders’ roles in their startups. For example, Accomplishers are often Chief Executive Officers, Chief Financial Officers, or Chief Operating Officers, while Fighters tend to be Chief Technical Officers, Chief Product Officers, or Chief Commercial Officers (see Extended Data Fig.  12 in SI section  A.4 for more details).

The ensemble theory of success

While founders’ individual personality traits, such as Adventurousness or Openness, show to be related to their firms’ success, we also hypothesise that the combination, or ensemble, of personality characteristics of a founding team impacts the chances of success. The logic behind this reasoning is complementarity, which is proposed by contemporary research on the functional roles of founder teams. Examples of these clear functional roles have evolved in established industries such as film and television, construction, and advertising 45 . When we subsequently explored the combinations of personality types among founders and their relationship to the probability of startup success, adjusted for a range of other factors in a multi-factorial analysis, we found significantly increased chances of success for mixed foundation teams:

Initially, we find that firms with multiple founders are more likely to succeed, as illustrated in Fig.  2 A, which shows firms with three or more founders are more than twice as likely to succeed than solo-founded startups. This finding is consistent with investors’ advice to founders and previous studies 46 . We also noted that some personality types of founders increase the probability of success more than others, as shown in SI section  A.6 (Extended Data Figures  16 and 17 ). Also, we note that gender differences play out in the distribution of personality facets: successful female founders and successful male founders show facet scores that are more similar to each other than are non-successful female founders to non-successful male founders (see Extended Data Figure  18 ).

The Ensemble Theory of Team-Level Factors of Startup Success. ( A ) Having a larger founder team elevates the chances of success. This can be due to multiple reasons, e.g., a more extensive network or knowledge base but also personality diversity. ( B ) We show that joint personality combinations of founders are significantly related to higher chances of success. This is because it takes more than one founder to cover all beneficial personality traits that ‘breed’ success. ( C ) In our multifactor model, we show that firms with diverse and specific combinations of types of founders have significantly higher odds of success.

Access to more extensive networks and capital could explain the benefits of having more founders. Still, as we find here, it also offers a greater diversity of combined personalities, naturally providing a broader range of maximum traits. So, for example, one founder may be more open and adventurous, and another could be highly agreeable and trustworthy, thus, potentially complementing each other’s particular strengths associated with startup success.

The benefits of larger and more personality-diverse foundation teams can be seen in the apparent differences between successful and unsuccessful firms based on their combined Big Five personality team footprints, as illustrated in Fig.  2 B. Here, maximum values for each Big Five trait of a startup’s co-founders are mapped; stratified by successful and non-successful companies. Founder teams of successful startups tend to score higher on Openness, Conscientiousness, Extraversion, and Agreeableness.

When examining the combinations of founders with different personality types, we find that some ensembles of personalities were significantly correlated with greater chances of startup success—while controlling for other variables in the model—as shown in Fig.  2 C (for more details on the modelling, the predictive performance and the coefficient estimates of the final model, see Extended Data Figures  19 , 20 , and 21 in SI section  A.6 ).

Three combinations of trio-founder companies were more than twice as likely to succeed than other combinations, namely teams with (1) a Leader and two Developers , (2) an Operator and two Developers , and (3) an Expert/Engineer , Leader and Developer . To illustrate the potential mechanisms on how personality traits might influence the success of startups, we provide some examples of well-known, successful startup founders and their characteristic personality traits in Extended Data Figure  22 .

Startups are one of the key mechanisms for brilliant ideas to become solutions to some of the world’s most challenging economic and social problems. Examples include the Google search algorithm, disability technology startup Fingerwork’s touchscreen technology that became the basis of the Apple iPhone, or the Biontech mRNA technology that powered Pfizer’s COVID-19 vaccine.

We have shown that founders’ personalities and the combination of personalities in the founding team of a startup have a material and significant impact on its likelihood of success. We have also shown that successful startup founders’ personality traits are significantly different from those of successful employees—so much so that a simple predictor can be trained to distinguish between employees and entrepreneurs with more than 80% accuracy using personality trait data alone.

Just as occupation-personality maps derived from data can provide career guidance tools, so too can data on successful entrepreneurs’ personality traits help people decide whether becoming a founder may be a good choice for them.

We have learnt through this research that there is not one type of ideal ’entrepreneurial’ personality but six different types. Many successful startups have multiple co-founders with a combination of these different personality types.

To a large extent, founding a startup is a team sport; therefore, diversity and complementarity of personalities matter in the foundation team. It has an outsized impact on the company’s likelihood of success. While all startups are high risk, the risk becomes lower with more founders, particularly if they have distinct personality traits.

Our work demonstrates the benefits of personality diversity among the founding team of startups. Greater awareness of this novel form of diversity may help create more resilient startups capable of more significant innovation and impact.

The data-driven research approach presented here comes with certain methodological limitations. The principal data sources of this study—Crunchbase and Twitter—are extensive and comprehensive, but there are characterised by some known and likely sample biases.

Crunchbase is the principal public chronicle of venture capital funding. So, there is some likely sample bias toward: (1) Startup companies that are funded externally: self-funded or bootstrapped companies are less likely to be represented in Crunchbase; (2) technology companies, as that is Crunchbase’s roots; (3) multi-founder companies; (4) male founders: while the representation of female founders is now double that of the mid-2000s, women still represent less than 25% of the sample; (5) companies that succeed: companies that fail, especially those that fail early, are likely to be less represented in the data.

Samples were also limited to those founders who are active on Twitter, which adds additional selection biases. For example, Twitter users typically are younger, more educated and have a higher median income 47 . Another limitation of our approach is the potentially biased presentation of a person’s digital identity on social media, which is the basis for identifying personality traits. For example, recent research suggests that the language and emotional tone used by entrepreneurs in social media can be affected by events such as business failure 48 , which might complicate the personality trait inference.

In addition to sampling biases within the data, there are also significant historical biases in startup culture. For many aspects of the entrepreneurship ecosystem, women, for example, are at a disadvantage 49 . Male-founded companies have historically dominated most startup ecosystems worldwide, representing the majority of founders and the overwhelming majority of venture capital investors. As a result, startups with women have historically attracted significantly fewer funds 50 , in part due to the male bias among venture investors, although this is now changing, albeit slowly 51 .

The research presented here provides quantitative evidence for the relevance of personality types and the diversity of personalities in startups. At the same time, it brings up other questions on how personality traits are related to other factors associated with success, such as:

Will the recent growing focus on promoting and investing in female founders change the nature, composition and dynamics of startups and their personalities leading to a more diverse personality landscape in startups?

Will the growth of startups outside of the United States change what success looks like to investors and hence the role of different personality traits and their association to diverse success metrics?

Many of today’s most renowned entrepreneurs are either Baby Boomers (such as Gates, Branson, Bloomberg) or Generation Xers (such as Benioff, Cannon-Brookes, Musk). However, as we can see, personality is both a predictor and driver of success in entrepreneurship. Will generation-wide differences in personality and outlook affect startups and their success?

Moreover, the findings shown here have natural extensions and applications beyond startups, such as for new projects within large established companies. While not technically startups, many large enterprises and industries such as construction, engineering and the film industry rely on forming new project-based, cross-functional teams that are often new ventures and share many characteristics of startups.

There is also potential for extending this research in other settings in government, NGOs, and within the research community. In scientific research, for example, team diversity in terms of age, ethnicity and gender has been shown to be predictive of impact, and personality diversity may be another critical dimension 52 .

Another extension of the study could investigate the development of the language used by startup founders on social media over time. Such an extension could investigate whether the language (and inferred psychological characteristics) change as the entrepreneurs’ ventures go through major business events such as foundation, funding, or exit.

Overall, this study demonstrates, first, that startup founders have significantly different personalities than employees. Secondly, besides firm-level factors, which are known to influence firm success, we show that a range of founder-level factors, notably the character traits of its founders, significantly impact a startup’s likelihood of success. Lastly, we looked at team-level factors. We discovered in a multifactor analysis that personality-diverse teams have the most considerable impact on the probability of a startup’s success, underlining the importance of personality diversity as a relevant factor of team performance and success.

Data sources

Entrepreneurs dataset.

Data about the founders of startups were collected from Crunchbase (Table  2 ), an open reference platform for business information about private and public companies, primarily early-stage startups. It is one of the largest and most comprehensive data sets of its kind and has been used in over 100 peer-reviewed research articles about economic and managerial research.

Crunchbase contains data on over two million companies - mainly startup companies and the companies who partner with them, acquire them and invest in them, as well as profiles on well over one million individuals active in the entrepreneurial ecosystem worldwide from over 200 countries and spans. Crunchbase started in the technology startup space, and it now covers all sectors, specifically focusing on entrepreneurship, investment and high-growth companies.

While Crunchbase contains data on over one million individuals in the entrepreneurial ecosystem, some are not entrepreneurs or startup founders but play other roles, such as investors, lawyers or executives at companies that acquire startups. To create a subset of only entrepreneurs, we selected a subset of 32,732 who self-identify as founders and co-founders (by job title) and who are also publicly active on the social media platform Twitter. We also removed those who also are venture capitalists to distinguish between investors and founders.

We selected founders active on Twitter to be able to use natural language processing to infer their Big Five personality features using an open-vocabulary approach shown to be accurate in the previous research by analysing users’ unstructured text, such as Twitter posts in our case. For this project, as with previous research 20 , we employed a commercial service, IBM Watson Personality Insight, to infer personality facets. This service provides raw scores and percentile scores of Big Five Domains (Openness, Conscientiousness, Extraversion, Agreeableness and Emotional Stability) and the corresponding 30 subdomains or facets. In addition, the public content of Twitter posts was collected, and there are 32,732 profiles that each had enough Twitter posts (more than 150 words) to get relatively accurate personality scores (less than 12.7% Average Mean Absolute Error).

The entrepreneurs’ dataset is analysed in combination with other data about the companies they founded to explore questions about the nature and patterns of personality traits of entrepreneurs and the relationships between these patterns and company success.

For the multifactor analysis, we further filtered the data in several preparatory steps for the success prediction modelling (for more details, see SI section  A.5 ). In particular, we removed data points with missing values (Extended Data Fig.  13 ) and kept only companies in the data that were founded from 1990 onward to ensure consistency with previous research 32 (see Extended Data Fig.  14 ). After cleaning, filtering and pre-processing the data, we ended up with data from 25,214 founders who founded 21,187 startup companies to be used in the multifactor analysis. Of those, 3442 startups in the data were successful, 2362 in the first seven years after they were founded (see Extended Data Figure  15 for more details).

Entrepreneurs and employees dataset

To investigate whether startup founders show personality traits that are similar or different from the population at large (i. e. the entrepreneurs vs employees sub-analysis shown in Fig.  1 A and B), we filtered the entrepreneurs’ data further: we reduced the sample to those founders of companies, which attracted more than US$100k in investment to create a reference set of successful entrepreneurs (n \(=\) 4400).

To create a control group of employees who are not also entrepreneurs or very unlikely to be of have been entrepreneurs, we leveraged the fact that while some occupational titles like CEO, CTO and Public Speaker are commonly shared by founders and co-founders, some others such as Cashier , Zoologist and Detective very rarely co-occur seem to be founders or co-founders. To illustrate, many company founders also adopt regular occupation titles such as CEO or CTO. Many founders will be Founder and CEO or Co-founder and CTO. While founders are often CEOs or CTOs, the reverse is not necessarily true, as many CEOs are professional executives that were not involved in the establishment or ownership of the firm.

Using data from LinkedIn, we created an Entrepreneurial Occupation Index (EOI) based on the ratio of entrepreneurs for each of the 624 occupations used in a previous study of occupation-personality fit 44 . It was calculated based on the percentage of all people working in the occupation from LinkedIn compared to those who shared the title Founder or Co-founder (See SI section  A.2 for more details). A reference set of employees (n=6685) was then selected across the 112 different occupations with the lowest propensity for entrepreneurship (less than 0.5% EOI) from a large corpus of Twitter users with known occupations, which is also drawn from the previous occupational-personality fit study 44 .

These two data sets were used to test whether it may be possible to distinguish successful entrepreneurs from successful employees based on the different patterns of personality traits alone.

Hierarchical clustering

We applied several clustering techniques and tests to the personality vectors of the entrepreneurs’ data set to determine if there are natural clusters and, if so, how many are the optimum number.

Firstly, to determine if there is a natural typology to founder personalities, we applied the Hopkins statistic—a statistical test we used to answer whether the entrepreneurs’ dataset contains inherent clusters. It measures the clustering tendency based on the ratio of the sum of distances of real points within a sample of the entrepreneurs’ dataset to their nearest neighbours and the sum of distances of randomly selected artificial points from a simulated uniform distribution to their nearest neighbours in the real entrepreneurs’ dataset. The ratio measures the difference between the entrepreneurs’ data distribution and the simulated uniform distribution, which tests the randomness of the data. The range of Hopkins statistics is from 0 to 1. The scores are close to 0, 0.5 and 1, respectively, indicating whether the dataset is uniformly distributed, randomly distributed or highly clustered.

To cluster the founders by personality facets, we used Agglomerative Hierarchical Clustering (AHC)—a bottom-up approach that treats an individual data point as a singleton cluster and then iteratively merges pairs of clusters until all data points are included in the single big collection. Ward’s linkage method is used to choose the pair of groups for minimising the increase in the within-cluster variance after combining. AHC was widely applied to clustering analysis since a tree hierarchy output is more informative and interpretable than K-means. Dendrograms were used to visualise the hierarchy to provide the perspective of the optimal number of clusters. The heights of the dendrogram represent the distance between groups, with lower heights representing more similar groups of observations. A horizontal line through the dendrogram was drawn to distinguish the number of significantly different clusters with higher heights. However, as it is not possible to determine the optimum number of clusters from the dendrogram, we applied other clustering performance metrics to analyse the optimal number of groups.

A range of Clustering performance metrics were used to help determine the optimal number of clusters in the dataset after an apparent clustering tendency was confirmed. The following metrics were implemented to evaluate the differences between within-cluster and between-cluster distances comprehensively: Dunn Index, Calinski-Harabasz Index, Davies-Bouldin Index and Silhouette Index. The Dunn Index measures the ratio of the minimum inter-cluster separation and the maximum intra-cluster diameter. At the same time, the Calinski-Harabasz Index improves the measurement of the Dunn Index by calculating the ratio of the average sum of squared dispersion of inter-cluster and intra-cluster. The Davies-Bouldin Index simplifies the process by treating each cluster individually. It compares the sum of the average distance among intra-cluster data points to the cluster centre of two separate groups with the distance between their centre points. Finally, the Silhouette Index is the overall average of the silhouette coefficients for each sample. The coefficient measures the similarity of the data point to its cluster compared with the other groups. Higher scores of the Dunn, Calinski-Harabasz and Silhouette Index and a lower score of the Davies-Bouldin Index indicate better clustering configuration.

Classification modelling

Classification algorithms.

To obtain a comprehensive and robust conclusion in the analysis predicting whether a given set of personality traits corresponds to an entrepreneur or an employee, we explored the following classifiers: Naïve Bayes, Elastic Net regularisation, Support Vector Machine, Random Forest, Gradient Boosting and Stacked Ensemble. The Naïve Bayes classifier is a probabilistic algorithm based on Bayes’ theorem with assumptions of independent features and equiprobable classes. Compared with other more complex classifiers, it saves computing time for large datasets and performs better if the assumptions hold. However, in the real world, those assumptions are generally violated. Elastic Net regularisation combines the penalties of Lasso and Ridge to regularise the Logistic classifier. It eliminates the limitation of multicollinearity in the Lasso method and improves the limitation of feature selection in the Ridge method. Even though Elastic Net is as simple as the Naïve Bayes classifier, it is more time-consuming. The Support Vector Machine (SVM) aims to find the ideal line or hyperplane to separate successful entrepreneurs and employees in this study. The dividing line can be non-linear based on a non-linear kernel, such as the Radial Basis Function Kernel. Therefore, it performs well on high-dimensional data while the ’right’ kernel selection needs to be tuned. Random Forest (RF) and Gradient Boosting Trees (GBT) are ensembles of decision trees. All trees are trained independently and simultaneously in RF, while a new tree is trained each time and corrected by previously trained trees in GBT. RF is a more robust and straightforward model since it does not have many hyperparameters to tune. GBT optimises the objective function and learns a more accurate model since there is a successive learning and correction process. Stacked Ensemble combines all existing classifiers through a Logistic Regression. Better than bagging with only variance reduction and boosting with only bias reduction, the ensemble leverages the benefit of model diversity with both lower variance and bias. All the above classification algorithms distinguish successful entrepreneurs and employees based on the personality matrix.

Evaluation metrics

A range of evaluation metrics comprehensively explains the performance of a classification prediction. The most straightforward metric is accuracy, which measures the overall portion of correct predictions. It will mislead the performance of an imbalanced dataset. The F1 score is better than accuracy by combining precision and recall and considering the False Negatives and False Positives. Specificity measures the proportion of detecting the true negative rate that correctly identifies employees, while Positive Predictive Value (PPV) calculates the probability of accurately predicting successful entrepreneurs. Area Under the Receiver Operating Characteristic Curve (AUROC) determines the capability of the algorithm to distinguish between successful entrepreneurs and employees. A higher value means the classifier performs better on separating the classes.

Feature importance

To further understand and interpret the classifier, it is critical to identify variables with significant predictive power on the target. Feature importance of tree-based models measures Gini importance scores for all predictors, which evaluate the overall impact of the model after cutting off the specific feature. The measurements consider all interactions among features. However, it does not provide insights into the directions of impacts since the importance only indicates the ability to distinguish different classes.

Statistical analysis

T-test, Cohen’s D and two-sample Kolmogorov-Smirnov test are introduced to explore how the mean values and distributions of personality facets between entrepreneurs and employees differ. The T-test is applied to determine whether the mean of personality facets of two group samples are significantly different from one another or not. The facets with significant differences detected by the hypothesis testing are critical to separate the two groups. Cohen’s d is to measure the effect size of the results of the previous t-test, which is the ratio of the mean difference to the pooled standard deviation. A larger Cohen’s d score indicates that the mean difference is greater than the variability of the whole sample. Moreover, it is interesting to check whether the two groups’ personality facets’ probability distributions are from the same distribution through the two-sample Kolmogorov-Smirnov test. There is no assumption about the distributions, but the test is sensitive to deviations near the centre rather than the tail.

Privacy and ethics

The focus of this research is to provide high-level insights about groups of startups, founders and types of founder teams rather than on specific individuals or companies. While we used unit record data from the publicly available data of company profiles from Crunchbase , we removed all identifiers from the underlying data on individual companies and founders and generated aggregate results, which formed the basis for our analysis and conclusions.

Data availability

A dataset which includes only aggregated statistics about the success of startups and the factors that influence is released as part of this research. Underlying data for all figures and the code to reproduce them are available on GitHub: https://github.com/Braesemann/FounderPersonalities . Please contact Fabian Braesemann ( [email protected] ) in case you have any further questions.

Change history

07 may 2024.

A Correction to this paper has been published: https://doi.org/10.1038/s41598-024-61082-7

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Acknowledgements

We thank Gary Brewer from BuiltWith ; Leni Mayo from Influx , Rachel Slattery from TeamSlatts and Daniel Petre from AirTree Ventures for their ongoing generosity and insights about startups, founders and venture investments. We also thank Tim Li from Crunchbase for advice and liaison regarding data on startups and Richard Slatter for advice and referrals in Twitter .

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All authors designed research; All authors analysed data and undertook investigation; F.B. and F.S. led multi-factor analysis; P.M., X.G. and M.A.R. led the founder/employee prediction; M.L.K. led personality insights; X.G. collected and tabulated the data; X.G., F.B., and F.S. created figures; X.G. created final art, and all authors wrote the paper.

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Correspondence to Fabian Braesemann .

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The original online version of this Article was revised: The Data Availability section in the original version of this Article was incomplete, the link to the GitHub repository was omitted. Full information regarding the corrections made can be found in the correction for this Article.

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McCarthy, P.X., Gong, X., Braesemann, F. et al. The impact of founder personalities on startup success. Sci Rep 13 , 17200 (2023). https://doi.org/10.1038/s41598-023-41980-y

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Publishing a Clinical Research Manuscript

Elizabeth m. viglianti.

a Department of Internal Medicine, Division of Pulmonary Critical Care, University of Michigan, Ann Arbor, MI

Andrew J. Admon

Erin f. carlton.

b Department of Pediatrics, Division of Pediatric Critical Care Medicine, University of Michigan, Ann Arbor, MI

Matthew K. Hensley

Hallie c. prescott.

c Veterans Affairs Center for Clinical Management Research, HSR&D Center for Innovation, Ann Arbor, MI

Theodore J. Iwashyna

d Institute of Social Research, University of Michigan, Ann Arbor, MI

Jakob I. McSparron

Disseminating research findings through scientific manuscripts is critical for advancing both science and the careers of individual scientists. Although several publications provide general guidance on the writing process, few resources provide specific, pragmatic guidance for early-career clinicians in pulmonary and critical care medicine who are writing a clinical research manuscript.

In light of this gap, we offer our advice on how to compose a clinical research manuscript, highlighting frequent hurdles—and strategies to overcome those hurdles—in the scientific writing process.

Before Writing

Good science.

At the core of any good manuscript is good science. Mentors and senior researchers should guide the science and methodology from conception to ensure that it is interesting, sound, and ethical. Beginning researchers should keep a log of the methodological decisions made at the outset of a project, as this will form the backbone of the introduction and methods sections of the resulting manuscript. Diligent notes related to the design and analysis of a project will also enhance transparency and reproducibility, key components of high-quality science.

Establish Authorship

Science should rarely be done in isolation; identifying authors and authorship order at the conception of a project ensures everyone is aware of their role ( Fig 1 ). Clear expectations for each co-author will help avoid delays and miscommunication later in the writing process. The International Committee of Medical Journal Editors provides guidance on criteria for authorship and acknowledgement in a scientific paper ( Fig 2 ). We generally expect that the first author will lead the writing, revision, and submission of the manuscript; will respond to comments during peer review; and will serve as corresponding author. The senior author will lay out the manuscript structure and provide iterative, critical revisions of the manuscript. Middle authors should have clearly defined roles and be utilized to maximize their strengths.

Conceptual framework, from research idea to manuscript submission.

Defining authorship. ICMJE = International Committee of Medical Journal Editors.

What Type of Article?

There are two types of original scientific articles: the brief report (or research letter) and the original research manuscript. Although both articles convey original research findings, the number of findings informs manuscript format.

If there are one or two significant findings, a brief report is appropriate. Brief report formats are available at select journals (eg, JAMA , Critical Care Medicine , Thorax ). These papers can have significant impact. Specific instructions vary by journal, but a typical brief report permits only 600 to 800 words, five to 10 references, and one to two tables/figures. There is often a limit on the number of authors. Supplemental appendixes may be allowed. We recommend asking senior mentors for examples of well-executed reports so as to learn from them as models.

The original research manuscript is the more traditional scientific research format. These papers typically have three to five significant findings reported in 2,400 to 3,000 words. There are fewer limitations on the number of authors and references, and tables/figures are normally limited to five. However, if there are multiple important findings (at least six or more), consider dividing the findings into multiple manuscripts. Including more than six findings will leave the editor and reader overwhelmed.

Prioritizing Writing

Sitting down to write an entire scientific manuscript can be paralyzing. Fortunately, there are strategies to consider in overcoming writer’s block—from joining existing or creating peer writing groups (where people meet to write and are held accountable) to writing “sprints,” where one writes as much as possible for a short period of time without editing ( Fig 3 ).

Barriers to writing and strategies to consider implementing.

The Sections of a Scientific Manuscript

Introduction: creating tension.

We recommend the three-paragraph introduction proposed by Welch in 1999. The introduction’s central task is to make visible the tension in our current understanding or practice that is being addressed by the manuscript ( Table 1 ). The first paragraph identifies the general problem. The second paragraph identifies a conflict or gap and creates the tension that motivates the research being discussed in the manuscript. The most effective second paragraphs make clear why this tension is consequential. The third paragraph explains how the current study will solve the conflict or fill the gap.

Table 1

Highlights of Each Section in a Scientific Manuscript

EQUATOR = Enhancing the Quality and Transparency of Health Research (a list of the most common study designs with specific guidelines; http://www.equator-network.org ).

Methods: Just the Facts

The methods show how the study was conducted at a level of specificity that should permit independent replication. The methods should be a clear description of “just the facts” written in the past tense. The reader should easily understand the type of study, as well as who was studied and excluded. Data extraction or collection techniques should be explicit, and all primary and secondary outcomes should be clearly identifiable. If decisions were made as to how the data were collected or why they were analyzed a certain way, these should be clearly stated and justified. Methodological details that are important for understanding and replicating a study but which may not be important for all readers of a manuscript (eg, diagnostic codes used to define a cohort) should be included in an online supplement/appendix.

Guidance on specific study designs is provided by the Enhancing the Quality and Transparency of Health Research (EQUATOR) Network ( http://www.equator-network.org ) ( Table 2 ). Specific journals have also offered guidance to authors. In a statement endorsed by a number of pulmonary and critical care medicine journals, Lederer et al offered guidance for authors and reviewers on control of confounding and causal inference in observational studies.

Table 2

The EQUATOR Network

CONSORT = Consolidated Standards of Reporting Trials; COREQ = Consolidated Criteria for Reporting Qualitative Research; PRISMA = Preferred Reporting Items for Systematic Reviews and Meta-Analyses; STROBE = Strengthening the Reporting of Observational Studies in Epidemiology; TRIPOD = Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis. See Table 1 legend for expansion of other abbreviation.

Finally, the type of analysis performed, and the software used to perform the analysis, should be clearly stated. In the push for transparency, it is now best practice for authors to post the code utilized to perform the analysis as a supplement, appendix, or on online venues such as GitHub. Add-on statistical packages not native to the original software should also be described and referenced.

Institutional review board approval or exemption status should always be noted in the methods section.

Results: A Story Through Figures and Tables

The results section must balance two competing obligations. On one hand, it is essential to provide the results in such a way that facilitates interpretation by the reader. A results section that is simply a list of decontextualized measurements will rarely bring the reader to a better understanding of the phenomena under study. On the other hand, the authors have a paramount obligation to present all relevant facts and to make clear to the reader the limits of their findings.

We recommend beginning by building consensus among the coauthors on what single main story the data tell. Prior to starting the study, we recommend making skeleton tables/figures as a way of prespecifying the analysis. The tables/figures may be tweaked, but the main analysis should usually be prespecified.

The general structure to reporting the results parallels the aims of the study identified in the abstract and introduction. Specifically, build from what was done to what was found. The study population and interventions or measurements performed should be shown with a flow diagram. This is typically followed by a description of the demographic characteristics of the cohort, the famed “ Table 1 .”

The subsequent paragraphs build from descriptive to complex statistical analysis. If there are regressions performed, the point estimates and 95% CIs will be reported in a table.

Tables and figures can be effective tools to communicate complex information in a well-defined, comprehensive way. Both require clear titles that explain the content and the take-away point. Furthermore, in the era of social media and PowerPoint, figures can help disseminate the significant findings from a manuscript.

We often recommend a section of explicit sensitivity analyses, in which one analyzes the data in other reasonable ways and presents those results. The readers can then judge for themselves the persuasiveness of the data. Online appendixes allow sensitivity analyses to be presented in detail online and summarized in the main report. We recommend asking senior mentors for examples of well-designed and justified sensitivity analyses so as to learn from them as models.

Discussion: Fill the Gap

The discussion section highlights the main findings of the study, puts the results in context of the greater scientific literature, acknowledges the limitations of the study, and lays out next steps for investigation. If the authors cannot make it clear why a manuscript is important, it is unlikely that the reader will do that work for them. The discussion should highlight the results from the study and help the reader understand why the results are important and how they move the science forward. The discussion echoes the introduction, integrating new results into the gaps that were highlighted previously.

There are several different structures that have been successfully implemented for discussion sections. We highlight our general structure with the caveat that our discussion section will focus more heavily on implications and next steps when the literature is sparse.

Generally, we start with clearly labeled subsections: Key findings; Relationship to previous studies; Implications and next steps; Strengths/limitations; and Conclusion.

Key findings: In the first paragraph, the purpose is to re-emphasize the significant findings from the results section.

Relationship to previous studies : In two to three paragraphs, the purpose of the study is put into the greater context of the scientific literature. These paragraphs allow the reader to see how this manuscript helps fill in the gaps of previous research in this area.

Implications and next steps: In one to two paragraphs, the authors explore what this study means in clinical practice (ie, what is the potential significance).

Strength/limitations : In one paragraph, highlight the strengths of the study and acknowledge the limitations.

Conclusion: This is the last paragraph. It should provide a succinct summary in one to two sentences and call for the next steps of research that are left to be addressed.

Abstract: It Really Matters

The abstract is crucial for a scientific manuscript. After the title, it is the most-read section of a manuscript and will encourage or discourage editors and readers from reading any further. The abstract is typically limited to 250 to 300 words depending on the journal, and each journal offers specific guidance on structure. It can be sketched early in the writing process but should be reviewed immediately prior to submission to ensure that it truly captures the most important points of the manuscript. Key findings introduced in the abstract should be present in the manuscript and vice versa. There should be no surprises for the readers as they read the manuscript.

Title: The More Versions, the Better

Having a clear, attention-grabbing title can move the manuscript beyond the desk of the editor and motivate people to read the abstract. However, too often the title is given little attention. We strongly recommend that authors generate up to 10 different titles for the manuscript, consult someone not directly familiar with the article, and then pick one. In general, eschew metaphors and clearly describe the context, direction of the association, and study design. We favor the basic formula of “X is associated with greater Y in Z, a multicenter cohort study.”

From Initial Draft to Submission

Feedback is a gift.

No scientific article is written perfectly on first draft. Once the draft is written, it should be shared with the senior author to begin the revision process. Do not be surprised if the draft is significantly covered in tracked-changes, with comments throughout the manuscript. Learn from the comments and go through all of the track-changes. Each version shared with the co-authors should be free of track-changes, fully incorporating all previous comments. Early in one’s career, there will be at least 10 drafts of a manuscript before it is shared with middle authors. Given the necessity of multiple iterations, it is important to date each version so that co-authors are working on the most recent edition (eg, Surname_title_year_month_day.docx).

We recommend explicit conversations between first and senior authors about the senior author’s preferred approach to how much work should be done between drafts, and how fast those iterations should occur.

Middle Authors: Setting Expectations

We highly recommend that the manuscript be nearly ready for submission before sharing it with middle authors. When sending the manuscript to the middle authors, provide them with guidance on what is expected of them and a specific time frame (eg, within 2 weeks).

Writing with a team of authors can significantly improve the quality of a manuscript while also introducing specific challenges. There are different “types” of middle authors ( Table 3 ) and knowing what type of middle authors are engaged in the manuscript is necessary to: (1) create the best written manuscript; (2) utilize them for their specific knowledge and skills; and (3) know whose comments take priority. Discussing with the senior author the comments that are received can help to put the critiques and feedback into perspective.

Table 3

“ Characteristics” of Middle Authors

Journal Submission, Revision, and Resubmission

Picking a journal.

Not all manuscripts are destined to be published in high-impact journals . Great science is published in many other journals, and building a successful research portfolio means writing for different audiences and building a collection of well-written manuscripts in different journals.

When identifying a potential home for a manuscript, consider: Where is similar work being published? How novel are the results? To whom do the results apply: would only a pulmonary and critical care audience be interested, or would the greater medical community be eager to read these findings as well? Brainstorm with senior mentors and colleagues about which journals may be appropriate, with a clear succession plan to allow rapid resubmission in the event of rejection.

Rejection is common; do not internalize it. Discuss the rejection with senior mentors and colleagues, but do not let the rejection stop the momentum of resubmitting the manuscript to another journal. Unless substantial, meaningful flaws are identified by the reviewers or the comments are easily addressable and will improve the manuscript, we tend to aim for resubmission to a new journal after rejection within 72 h and rarely more than 1 week. Brooding does not advance science; incorporating useful feedback does.

Cover Letters

The cover letter is the letter addressed to the editor of the journal and consists of a few short paragraphs. The first paragraph should tell the editor the title and the type of article being submitted. The second paragraph should highlight the major findings, implications, and why the manuscript should be published in their specific journal for their specific readers; simple, plain language should be used that can help the editor fight for this article. The third paragraph may contain journal-specific requirements such as conflict of interest statements, funding sources, or author contribution. Always end by thanking them for taking the time to consider the work.

Revise and Resubmit Letter

Once the manuscript has been reviewed, a letter is sent to the corresponding author with a decision and comments. The manuscript may be: (1) rejected following the comments of the reviewers; (2) sent back to the author with comments and clarifications that need to be addressed before a decision will be made, a so-called “revise and resubmit” (R&R) letter; or (3) accepted on first submission (extremely rare).

First-time authors often mistake the language in R&R letters as rejections. At first, they nearly all look like a rejection, with language to the effect of “the manuscript is not acceptable in its present form.” However, this wording will typically be followed by an explicit statement: “We would be willing to reconsider a manuscript that addressed the concerns raised by the reviewers.” Most R&R letters contain a time frame by which a manuscript should be revised, which should be considered an absolute deadline. It is our opinion that an R&R letter should be prioritized as the most important task on a young first author’s list.

The comments are generally in two categories (major and minor) and are provided by the reviewing editor and external reviewers. It is important to be thankful for the comments when responding.

Example: We agree with the reviewer that ---- and have included an additional analysis addressing the concerns.

It does not behoove the authors to be condescending or argumentative. If the author disagrees with a reviewer, be considerate in the response because the reviewers are very likely to read the response letter.

Example: With all due respect to the reviewer, we believe that this point is not correct because…

Each comment should be bulleted and addressed. If changes in the manuscript are needed, include the language changed and where in the manuscript it can located (eg, page 7 line 47) in the response. Do not make it hard for the editors and reviewers to verify that the changes were made.

Once the response letter and changes to the manuscript have been made, recall that all authors need to: (1) approve the response letter and manuscript; and (2) be given adequate time to consider the changes. Providing a time frame to co-authors is advisable; we typically request middle authors review the revisions in 1 week. Flag any important areas in the revisions where feedback is particularly desired.

Conclusions

Writing a scientific manuscript can be challenging and time-consuming but also extremely rewarding for researchers and valuable to the scientific community. Writing is rarely done alone, and many resources are available to support authors. Being open to feedback from senior mentors and colleagues will make the manuscript better. Our hope is that the advice and guidance we have provided will make it easier for early-career researchers to write their first of many scientific research manuscripts.

Acknowledgments

Financial/nonfinancial disclosures: None declared.

Role of sponsors: The sponsor had no role in the design of the study, the collection and analysis of the data, or the preparation of the manuscript.

Other contributions: This work does not represent the official position of the United States Government or the Department of Veterans Affairs.

FUNDING/SUPPORT: This work was supported by grants from the National Heart, Lung, and Blood Institute (NHLBI) at the National Institutes of Health (T32 HL007749 to E. M. V., A. J. A.; K12 HL138039 to T. J. I).

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40 Facts About Elektrostal

Written by Lanette Mayes

Modified & Updated: 01 Jun 2024

Reviewed by Jessica Corbett

Elektrostal is a vibrant city located in the Moscow Oblast region of Russia. With a rich history, stunning architecture, and a thriving community, Elektrostal is a city that has much to offer. Whether you are a history buff, nature enthusiast, or simply curious about different cultures, Elektrostal is sure to captivate you.

This article will provide you with 40 fascinating facts about Elektrostal, giving you a better understanding of why this city is worth exploring. From its origins as an industrial hub to its modern-day charm, we will delve into the various aspects that make Elektrostal a unique and must-visit destination.

So, join us as we uncover the hidden treasures of Elektrostal and discover what makes this city a true gem in the heart of Russia.

Key Takeaways:

• Elektrostal, known as the “Motor City of Russia,” is a vibrant and growing city with a rich industrial history, offering diverse cultural experiences and a strong commitment to environmental sustainability.
• With its convenient location near Moscow, Elektrostal provides a picturesque landscape, vibrant nightlife, and a range of recreational activities, making it an ideal destination for residents and visitors alike.

Known as the “Motor City of Russia.”

Elektrostal, a city located in the Moscow Oblast region of Russia, earned the nickname “Motor City” due to its significant involvement in the automotive industry.

Home to the Elektrostal Metallurgical Plant.

Elektrostal is renowned for its metallurgical plant, which has been producing high-quality steel and alloys since its establishment in 1916.

Boasts a rich industrial heritage.

Elektrostal has a long history of industrial development, contributing to the growth and progress of the region.

Founded in 1916.

The city of Elektrostal was founded in 1916 as a result of the construction of the Elektrostal Metallurgical Plant.

Located approximately 50 kilometers east of Moscow.

Elektrostal is situated in close proximity to the Russian capital, making it easily accessible for both residents and visitors.

Known for its vibrant cultural scene.

Elektrostal is home to several cultural institutions, including museums, theaters, and art galleries that showcase the city’s rich artistic heritage.

A popular destination for nature lovers.

Surrounded by picturesque landscapes and forests, Elektrostal offers ample opportunities for outdoor activities such as hiking, camping, and birdwatching.

Hosts the annual Elektrostal City Day celebrations.

Every year, Elektrostal organizes festive events and activities to celebrate its founding, bringing together residents and visitors in a spirit of unity and joy.

Has a population of approximately 160,000 people.

Elektrostal is home to a diverse and vibrant community of around 160,000 residents, contributing to its dynamic atmosphere.

Boasts excellent education facilities.

The city is known for its well-established educational institutions, providing quality education to students of all ages.

A center for scientific research and innovation.

Elektrostal serves as an important hub for scientific research, particularly in the fields of metallurgy , materials science, and engineering.

Surrounded by picturesque lakes.

The city is blessed with numerous beautiful lakes , offering scenic views and recreational opportunities for locals and visitors alike.

Well-connected transportation system.

Elektrostal benefits from an efficient transportation network, including highways, railways, and public transportation options, ensuring convenient travel within and beyond the city.

Famous for its traditional Russian cuisine.

Food enthusiasts can indulge in authentic Russian dishes at numerous restaurants and cafes scattered throughout Elektrostal.

Home to notable architectural landmarks.

Elektrostal boasts impressive architecture, including the Church of the Transfiguration of the Lord and the Elektrostal Palace of Culture.

Offers a wide range of recreational facilities.

Residents and visitors can enjoy various recreational activities, such as sports complexes, swimming pools, and fitness centers, enhancing the overall quality of life.

Provides a high standard of healthcare.

Elektrostal is equipped with modern medical facilities, ensuring residents have access to quality healthcare services.

Home to the Elektrostal History Museum.

The Elektrostal History Museum showcases the city’s fascinating past through exhibitions and displays.

A hub for sports enthusiasts.

Elektrostal is passionate about sports, with numerous stadiums, arenas, and sports clubs offering opportunities for athletes and spectators.

Celebrates diverse cultural festivals.

Throughout the year, Elektrostal hosts a variety of cultural festivals, celebrating different ethnicities, traditions, and art forms.

Electric power played a significant role in its early development.

Elektrostal owes its name and initial growth to the establishment of electric power stations and the utilization of electricity in the industrial sector.

Boasts a thriving economy.

The city’s strong industrial base, coupled with its strategic location near Moscow, has contributed to Elektrostal’s prosperous economic status.

Houses the Elektrostal Drama Theater.

The Elektrostal Drama Theater is a cultural centerpiece, attracting theater enthusiasts from far and wide.

Popular destination for winter sports.

Elektrostal’s proximity to ski resorts and winter sport facilities makes it a favorite destination for skiing, snowboarding, and other winter activities.

Promotes environmental sustainability.

Elektrostal prioritizes environmental protection and sustainability, implementing initiatives to reduce pollution and preserve natural resources.

Home to renowned educational institutions.

Elektrostal is known for its prestigious schools and universities, offering a wide range of academic programs to students.

Committed to cultural preservation.

The city values its cultural heritage and takes active steps to preserve and promote traditional customs, crafts, and arts.

Hosts an annual International Film Festival.

The Elektrostal International Film Festival attracts filmmakers and cinema enthusiasts from around the world, showcasing a diverse range of films.

Encourages entrepreneurship and innovation.

Elektrostal supports aspiring entrepreneurs and fosters a culture of innovation, providing opportunities for startups and business development .

Offers a range of housing options.

Elektrostal provides diverse housing options, including apartments, houses, and residential complexes, catering to different lifestyles and budgets.

Home to notable sports teams.

Elektrostal is proud of its sports legacy , with several successful sports teams competing at regional and national levels.

Boasts a vibrant nightlife scene.

Residents and visitors can enjoy a lively nightlife in Elektrostal, with numerous bars, clubs, and entertainment venues.

Promotes cultural exchange and international relations.

Elektrostal actively engages in international partnerships, cultural exchanges, and diplomatic collaborations to foster global connections.

Surrounded by beautiful nature reserves.

Nearby nature reserves, such as the Barybino Forest and Luchinskoye Lake, offer opportunities for nature enthusiasts to explore and appreciate the region’s biodiversity.

Commemorates historical events.

The city pays tribute to significant historical events through memorials, monuments, and exhibitions, ensuring the preservation of collective memory.

Promotes sports and youth development.

Elektrostal invests in sports infrastructure and programs to encourage youth participation, health, and physical fitness.

Hosts annual cultural and artistic festivals.

Throughout the year, Elektrostal celebrates its cultural diversity through festivals dedicated to music, dance, art, and theater.

Provides a picturesque landscape for photography enthusiasts.

The city’s scenic beauty, architectural landmarks, and natural surroundings make it a paradise for photographers.

Connects to Moscow via a direct train line.

The convenient train connection between Elektrostal and Moscow makes commuting between the two cities effortless.

A city with a bright future.

Elektrostal continues to grow and develop, aiming to become a model city in terms of infrastructure, sustainability, and quality of life for its residents.

In conclusion, Elektrostal is a fascinating city with a rich history and a vibrant present. From its origins as a center of steel production to its modern-day status as a hub for education and industry, Elektrostal has plenty to offer both residents and visitors. With its beautiful parks, cultural attractions, and proximity to Moscow, there is no shortage of things to see and do in this dynamic city. Whether you’re interested in exploring its historical landmarks, enjoying outdoor activities, or immersing yourself in the local culture, Elektrostal has something for everyone. So, next time you find yourself in the Moscow region, don’t miss the opportunity to discover the hidden gems of Elektrostal.

Q: What is the population of Elektrostal?

A: As of the latest data, the population of Elektrostal is approximately XXXX.

Q: How far is Elektrostal from Moscow?

A: Elektrostal is located approximately XX kilometers away from Moscow.

Q: Are there any famous landmarks in Elektrostal?

A: Yes, Elektrostal is home to several notable landmarks, including XXXX and XXXX.

Q: What industries are prominent in Elektrostal?

A: Elektrostal is known for its steel production industry and is also a center for engineering and manufacturing.

Q: Are there any universities or educational institutions in Elektrostal?

A: Yes, Elektrostal is home to XXXX University and several other educational institutions.

Q: What are some popular outdoor activities in Elektrostal?

A: Elektrostal offers several outdoor activities, such as hiking, cycling, and picnicking in its beautiful parks.

Q: Is Elektrostal well-connected in terms of transportation?

A: Yes, Elektrostal has good transportation links, including trains and buses, making it easily accessible from nearby cities.

Q: Are there any annual events or festivals in Elektrostal?

A: Yes, Elektrostal hosts various events and festivals throughout the year, including XXXX and XXXX.

Elektrostal's fascinating history, vibrant culture, and promising future make it a city worth exploring. For more captivating facts about cities around the world, discover the unique characteristics that define each city . Uncover the hidden gems of Moscow Oblast through our in-depth look at Kolomna. Lastly, dive into the rich industrial heritage of Teesside, a thriving industrial center with its own story to tell.

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