Sex and gender considerations in reporting guidelines for health research: a systematic review
Bibliographic record
Abstract
BACKGROUND: Despite growing recognition of the importance of sex and gender considerations in health research, they are rarely integrated into research design and reporting. We sought to assess the integration of sex, as a biological attribute, and gender, as a socially constructed identity, in published reporting guidelines. METHODS: We conducted a systematic review of published reporting guidelines listed on the EQUATOR website ( www.equator-nework.org ) from inception until December 2018. We selected all reporting guidelines (original and extensions) listed in the EQUATOR library. We used EndNote Citation Software to build a database of the statements of each guideline identified as a "full bibliographic reference" and retrieved the full texts. Reviewers independently extracted the data on use of sex and gender terms from the checklist/abstract/main text of guidelines. Data were analyzed using descriptive statistics and narrative synthesis. RESULTS: A total of 407 reporting guidelines were included; they were published between 1995 and 2018. Of the 407 guidelines, 235 (57.7%) mentioned at least one of the sex- and gender-related words. In the checklist of the reporting guidelines (n = 363), "sex" and "gender" were mentioned in 50 (13.8%) and 40 (11%), respectively. Only one reporting guideline met our criteria (nonbinary, appropriate categorization, and non-interchangeability) for correct use of sex and gender concepts. Trends in the use of "sex" and "gender" in the checklists showed that the use of "sex" only started in 2003, while "gender" has been in use since 1996. CONCLUSIONS: We assessed the integration of sex and gender in reporting guidelines based on the use of sex- and gender-related words. Our findings showed a low use and integration of sex and gender concepts and their incorrect use. Authors of reporting guidelines should reduce this gap for a better use of research knowledge. Trial registration PROSPERO no. CRD42019136491.
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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 | 0.497 | 0.789 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.036 | 0.044 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.014 | 0.027 |
| Open science | 0.009 | 0.008 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".