Reporting of sex and gender in randomized controlled trials in Canada: a cross-sectional methods study
Bibliographic record
Abstract
BACKGROUND: Accurate reporting on sex and gender in health research is integral to ensuring that health interventions are safe and effective. In Canada and internationally, governments, research organizations, journal editors, and health agencies have called for more inclusive research, provision of sex-disaggregated data, and the integration of sex and gender analysis throughout the research process. Sex and gender analysis is generally defined as an approach for considering how and why different subpopulations (e.g., of diverse genders, ages, and social locations) may experience health conditions and interventions in different or similar ways.The objective of this study was to assess the extent and nature of reporting about sex and/or gender, including whether sex and gender analysis (SGA) was carried out in a sample of Canadian randomized controlled trials (RCTs) with human participants. METHODS: We searched MEDLINE from 01 January 2013 to 23 July 2014 using a validated filter for identification of RCTs, combined with terms related to Canada. Two reviewers screened the search results to identify the first 100 RCTs that were either identified in the trial publication as funded by a Canadian organization or which had a first or last author based in Canada. Data were independently extracted by two people from 10% of the RCTs during an initial training period; once agreement was reached on this sample, the remainder of the data extraction was completed by one person and verified by a second. RESULTS: The search yielded 1433 records. We screened 256 records to identify 100 RCTs which met our eligibility criteria. The median sample size of the RCTs was 107 participants (range 12-6085). While 98% of studies described the demographic composition of their participants by sex, only 6% conducted a subgroup analysis across sex and 4% reported sex-disaggregated data. No article defined "sex" and/or "gender." No publication carried out a comprehensive sex and gender analysis. CONCLUSIONS: Findings highlight poor uptake of sex and gender considerations in the Canadian RCT context and underscore the need for better articulated guidance on sex and gender analysis to improve reporting of evidence, inform policy development, and guide future research.
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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 | 0.426 | 0.739 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.023 | 0.048 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| 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".