Bias in the diagnosis of borderline personality disorder among sexual and gender minority persons: Results from a vignette-based experiment
Bibliographic record
Abstract
Sexual and gender minority (SGM) individuals are diagnosed with borderline personality disorder (BPD) more than cisgender heterosexuals. Using a large sample of mental health practitioners in the U.S. and Canada (N=426) we examined bias in the diagnosis of BPD. Mental health practitioners were randomly assigned to receive one of three clinical vignettes (cisgender heterosexual man, cisgender gay man, or transgender woman) and asked to provide psychiatric diagnoses based on the vignette. Mental health practitioners demonstrated a predilection to diagnose BPD when presented with the transgender (OR=1.99, p=.01), not the cisgender gay condition (OR=1.34, p=0.29), vignette when compared with those presented the cisgender heterosexual vignette. Psychiatrists, mental health counselors, and clinical social workers were significantly more inclined to diagnose BPD than psychologists, though reasons for underdiagnosis differed across groups. These findings bear important implications for future training given the nature of the mental health workforce in the U.S.
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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 | 0.026 | 0.089 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".