How do and could clinical guidelines support patient-centred care for women: Content analysis of guidelines
Bibliographic record
Abstract
OBJECTIVES: Patient-centred care (PCC) improves multiple patient and health system outcomes. However, many patients do not experience PCC, particularly women, who are faced with disparities in care and outcomes globally. The purpose of this study was to identify if and how guidelines address PCC for women (PCCW). METHODS: We searched MEDLINE, EMBASE, National Guideline Clearing House, and guideline developer websites for publicly-available, English-language guidelines on depression and cardiac rehabilitation, conditions with known gendered inequities. We used summary statistics to report guideline characteristics, clinical topic, mention of PCC according to McCormack's framework, and mention of women's health considerations. We appraised guideline quality with the AGREE II instrument. RESULTS: A total of 27 guidelines (18 depression, 9 cardiac rehabilitation) were included. All 27 guidelines mentioned at least one PCC domain (median 3, range 1 to 6), most frequently exchanging information (20, 74.1%), making decisions (20, 74.1%), and enabling patient self-management (21, 77.8%). No guidelines fully addressed PCC: 9 (50.0%) of 18 depression guidelines and 3 (33.3%) of 9 cardiac rehabilitation guidelines addressed 4 or more PCC domains. Even when addressed, guidance was minimal and vague. Among 14 (51.9%) guidelines that mentioned women's health, most referred to social determinants of health; none offered guidance on how to support women impacted by these factors, engage women, or tailor care for women. These findings pertained even to women-specific guidelines. Reported use or type of guideline development process/system did not appear to be linked with PCCW content. Based on quality appraisal with AGREE II, guidelines were either not recommended or recommended with modifications. In particular, the stakeholder involvement AGREE II domain was least addressed, but guidelines that scored higher for stakeholder involvement also appeared to better address PCCW. IMPLICATIONS: This research identified opportunities to generate guidelines that achieve PCCW. Strategies include employing a PCC framework, considering gender issues, engaging women on guideline-writing panels, and including patient-oriented tools in guidelines. Primary research is needed to establish what constitutes PCCW.
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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 | 0.046 | 0.243 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".