Stigma towards borderline personality disorder: effectiveness and generalizability of an anti-stigma program for healthcare providers using a pre-post randomized design
Bibliographic record
Abstract
BACKGROUND: Stigmatization among healthcare providers towards mental illnesses can present obstacles to effective caregiving. This may be especially the case for borderline personality disorder (BPD). Our study measured the impact of a three hour workshop on BPD and dialectical behavior therapy (DBT) on attitudes and behavioral intentions of healthcare providers towards persons with BPD as well as mental illness more generally. The intervention involved educational and social contact elements, all focused on BPD. METHODS: The study employed a pre-post design. We adopted the approach of measuring stigmatization towards persons with BPD in one half of the attendees and stigmatization towards persons with a mental illness in the other half. The stigma-assessment tool was the Opening Minds Scale for Healthcare Providers (OMS-HC). Two versions of the scale were employed - the original version and a 'BPD-specific' version. A 2x2 mixed model factorial analysis of variance (ANOVA) was conducted on the dependent variable, stigma score. The between-subject factor was survey type. The within-subject factor was time. RESULTS: The mixed-model ANOVA produced a significant between-subject main effect for survey type, with stigma towards persons with BPD being greater than that towards persons with a mental illness more generally. A significant within-subject main effect for time was also observed, with participants showing significant improvement in stigma scores at Time 2. The main effects were subsumed by a significant interaction between time and survey type. Bonferroni post hoc tests indicated significant improvement in attitudes towards BPD and mental illness more generally, although there was a greater improvement in attitudes towards BPD. CONCLUSIONS: Although effectiveness cannot be conclusively demonstrated with the current research design, results are encouraging that the intervention was successful at improving healthcare provider attitudes and behavioral intentions towards persons with BPD. The results further suggest that anti stigma interventions effective at combating stigma against a specific disorder may also have positive generalizable effects towards a broader set of mental illnesses, albeit to a lessened degree.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".