A systematic scoping review of adherence to reporting guidelines in health care literature
Bibliographic record
Abstract
Zainab Samaan,1–3 Lawrence Mbuagbaw,2 Daisy Kosa,2,4 Victoria Borg Debono,2,5 Rejane Dillenburg,6 Shiyuan Zhang2, Vincent Fruci,7 Brittany Dennis,2 Monica Bawor,8 Lehana Thabane2,5,91Department of Psychiatry and Behavioral Neurosciences, McMaster University, Hamilton, 2Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, 3Population Genomics Program, McMaster University, Hamilton, 4Department of Nephrology, Toronto General Hospital, Toronto, 5Department of Anesthesia, McMaster University, Hamilton, 6Department of Pediatrics, McMaster University, Hamilton, 7Michael G DeGroote School of Medicine, McMaster University, Hamilton, 8McMaster Integrative Neuroscience Discovery and Study (MiNDS) Program, McMaster University, Hamilton, 9Centre for Evaluation of Medicines, Hamilton, ON, CanadaBackground: Reporting guidelines have been available for the past 17 years since the inception of the Consolidated Standards of Reporting Trials statement in 1996. These guidelines were developed to improve the quality of reporting of studies in medical literature. Despite the widespread availability of these guidelines, the quality of reporting of medical literature remained suboptimal. In this study, we assess the current adherence practice to reporting guidelines; determine key factors associated with better adherence to these guidelines; and provide recommendations to enhance adherence to reporting guidelines for future studies.Methods: We undertook a systematic scoping review of systematic reviews of adherence to reporting guidelines across different clinical areas and study designs. We searched four electronic databases (Cumulative Index to Nursing and Allied Health Literature, Web of Science, Embase, and Medline) from January 1996 to September 2012. Studies were included if they addressed adherence to one of the following guidelines: Consolidated Standards of Reporting Trials (CONSORT), Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), Quality of Reporting of Meta-analysis (QUOROM), Transparent Reporting of Evaluations with Nonrandomized Designs (TREND), Meta-analysis Of Observational Studies in Epidemiology (MOOSE) and Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). A protocol for this study was devised. A literature search, data extraction, and quality assessment were performed independently by two authors in duplicate. This study reporting follows the PRISMA guidelines.Results: Our search retrieved 5159 titles, of which 50 were eligible. Overall, 86.0% of studies reported suboptimal levels of adherence to reporting guidelines. Factors associated with better adherence included journal impact factor and endorsement of guidelines, publication date, funding source, multisite studies, pharmacological interventions and larger studies.Conclusion: Reporting guidelines in the clinical literature are important to improve the standards of reporting of clinical studies; however, adherence to these guidelines remains suboptimal. Action is therefore needed to enhance the adherence to these standards. Strategies to enhance adherence include journal editorial policies endorsing these guidelines.Keywords: scoping, systematic, review, adherence, reporting, guidelines
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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 | 0.489 | 0.815 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.015 |
| Bibliometrics | 0.033 | 0.040 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.010 | 0.010 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".