An International Survey of Biomedical Researchers Knowledge, Perceptions, and Training on Peer Review
Bibliographic record
Abstract
Objective To provide an up-to-date perspective of biomedical researchers’ knowledge and perceptions of and engagement with peer review training. Previous studies, many done in consultation with editors and publishers, have reported researchers’ attitudes on peer review.1,2 This survey study is descriptive and does not have any a priori hypotheses. Design A cross-sectional online survey of biomedical researchers around the world was conducted. The CHERRIES (Checklist for Reporting Results of Internet E-Surveys) reporting guideline was used to inform the reporting of findings. A random sample of 2000 corresponding authors was collected from a Scopus source list of recently published articles in peer-reviewed biomedical journals. Authors from journals that exclusively published non-English articles were excluded. The closed survey was purpose built for this study, was administered using SurveyMonkey, and was available only to participants identified via the random sampling framework. Participants were invited through email; participation was voluntary, and all data were collected anonymously. Collected data included participants’ demographic characteristics as well as their experience with and opinions about peer review, with additional open-ended questions allowing participants to elaborate their responses. Data were analyzed from all surveys in which participants responded to 80% or more of the questions. Results Of the 2000 invited researchers, 186 (9.3%) responded. The average survey completion rate among these participants was 91%. Most participants (142 [76.3%]) reported having 6 or more years of experience in scholarly publishing. One hundred two of 180 participants (56.7%) reported being active as a manuscript peer reviewer for more than 6 years, and 171 of 185 participants (92.4%) reported having peer reviewed at least 1 article in the last 12 months. Despite the robust experience and activity in manuscript peer review reported by the participants, only 28 of 185 participants (15.1%) completed formal training in peer review. Twelve of 64 participants (18.8%) received training through in-person lecture, and 11 of 64 participants (17.2%) received training through online lecture. Thirteen of 36 participants (52.8%) received training in peer review provided by a university or college. Conclusions This study will provide a current international perspective on biomedical researchers’ knowledge, perceptions, and engagement regarding peer review training. The results of the survey may help identify gaps in peer review training experience and knowledge. Subsequently, the findings may guide the creation of future training options, inform the development of preferred training methods, and increase comprehensiveness of peer review training for biomedical researchers. References Mulligan A, Hall L, Raphael E. Peer review in a changing world: an international study measuring the attitudes of researchers. J Am Soc Inf Sci Tec. 2013;64:132-161. doi:10.1002/asi.22798 Publons. 2018 Global state of peer reviewy. 2018. Accessed July 2022. https://publons.com/static/Publons-Global-State- Of-Peer-Review-2018.pdf Conflict of Interest Disclosures David Moher is an associate director of the International Congress on Peer Review and Scientific Publication but was not involved in the review or decision for this abstract. No other disclosures reported. https://assets.underline.io/uploads/markdown_image/1/image/49348bfde8ee658b65c0fa925d323933.png
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".