Guidelines for the Primary Care of Lesbian, Gay, and Bisexual People: A Systematic Review
Bibliographic record
Abstract
PURPOSE: We assessed whether existing guidelines for the primary care of lesbian, gay, and bisexual (LGB) people meet appropriate standards of developmental rigor, and whether they provide consistent recommendations useful for primary care clinicians. METHODS: We performed a systematic review of such guidelines using the Cochrane Collaboration method. The countries searched were Australia, Canada, Ireland, New Zealand, the United Kingdom, and the United States. For sources, we used electronic databases, guidelines databases, primary care professional organizations, government departments of public health, LGB health care textbooks, and national LGB organizations. We assessed the quality of existing guidelines using the validated Appraisal of Guidelines for Research and Evaluation (AGREE) instrument and compared the recommendations from all fully appraised guidelines. RESULTS: Our search did not identify any previous systematic reviews on primary care of LGB people. Of 2,421 documents identified, we initially reviewed 30 and fully appraised 11, none of which completely satisfied the AGREE criteria for quality and only 2 of which were specifically designed for primary care. Developmental rigor was poor. Particular gaps were a lack of explicit inclusion criteria, independent reviewers, and updating procedures. Nonetheless, we did identify several consistent recommendations pertinent to primary care settings: guidance on inclusive clinical environments, standards for clinician-patient communication, sensitive documentation of sexual orientation, knowledge for cultural awareness, staff training, and addressing population health issues. CONCLUSIONS: Currently available guidelines for LGB care are philosophically and practically consistent, and provide a degree of evidence-based clinical and systems support to primary care clinicians. There is a need, however, for evidence-based LGB guidelines that are more rigorously developed, disseminated, and evaluated specifically for the primary care setting.
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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 | 0.048 | 0.219 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".