How Intersectional Are Mental Health Interventions for Sexual Minority People? A Systematic Review
Bibliographic record
Abstract
Purpose: Complex and widespread stigma exposes sexual minority people to disproportionate risks for adverse mental health. Intersectionality theory calls for consideration of the unique experiences of living with multiple forms of inequality. Yet, concerns remain regarding the extent to which intersectionality theory has been integrated into mental health interventions for sexual minority populations. This systematic review aims to assess the degree to which available mental health interventions account for intersecting forms of marginalization and to identify methods that facilitate the application of intersectionality. Methods: A search for peer-reviewed English language journal articles was conducted using PsycINFO and PubMed to locate reports of mental health interventions for sexual minority groups. A coding framework was designed to evaluate how interventions incorporated intersectionality theory. Results: Of 1877 potentially eligible articles, forty-three were included in the analysis. They were each classified as low, medium, or high with regard to intersectionality. Thirteen (30.2%) were rated as low on intersectionality for only recruiting a homogeneous group of participants in the interventions; 23 (53.4%) were classified as medium for including additional identities in recruitment without responding to possible intersectional disadvantages; 7 (16.3%) were rated as high with adequate consideration of the complex effects of intersecting positions. In addition, the review identified community-based participatory research as a common and instrumental method to ensure intersectionality. Conclusions: This review highlights the limitations of interventions for sexual minority people in addressing intersectionality. Guidelines are needed for clinical practice and evaluation to adequately incorporate intersectionality theory.
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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 | 0.021 | 0.108 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".