Reducing stigma toward people with bipolar disorder: Impact of a filmed theatrical intervention based on a personal narrative
Bibliographic record
Abstract
BACKGROUND: Stigma toward people with bipolar disorder (BD) is pervasive and can have many negative repercussions. Common approaches to stigma reduction include education and intergroup contact. From this perspective, the Collaborative RESearch Team to study psychosocial issues in Bipolar Disorder (CREST.BD) and Canadian Network for Mood and Anxiety Treatments (CANMAT) partnered to develop an intervention to combat stigma. The result is a personal narrative intervention that combines contact, education and drama to educate audiences and dispel the myths that drive stigma. AIM: This study reports on the impact of the CREST.BD-CANMAT stigma-reduction intervention in filmed format. METHODS: A sample of 137 participants was recruited to view the film, including health-care service providers, university students in a health-care-related course, people with BD and their friends and family members and the general public. Participants were evaluated for stigmatizing attitudes and the desire for social distance before and after the intervention and 1 month later. RESULTS: For health-care service providers, the intervention was associated with statistically significant improvements in several categories of stigmatizing attitudes, with maintenance 1 month later. The impact was more modest for the other subsamples. Students demonstrated progressive, significant improvements in the desire for (less) social distance. Some improvements were observed among members of the BD community and the general public, but these were limited and eroded over time. CONCLUSION: This study demonstrated that a filmed dramatic intervention based on the lived experience of BD has statistically significant, sustainable stigma-reduction impacts for health-care service providers and more limited impacts for other target groups. This intervention can be considered an effective tool for use in stigma-reduction campaigns specifically targeting members of the health-care sector. Results are discussed in the context of multi-component stigma-reduction campaigns and the potential needs of target groups.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".