Health care providers and people with mental illness: An integrative review on anti-stigma interventions
Bibliographic record
Abstract
BACKGROUND: Health care providers are an important target group for anti-stigma interventions because they have the potential to convey stigmatizing attitudes towards people with mental illness. This can have a detrimental impact on the quality and effectiveness of care provided to those affected by mental illness. AIMS AND METHODS: Whittemore & Knafl's integrative review method (2005) was used to analyze 16 studies investigating anti-stigma interventions targeting health care providers. RESULTS: The interventions predominantly involved contact-based educational approaches which ranged from training on mental health (typically short-term), showing videos or films (indirect social contact) to involving people with lived experiences of mental illness (direct social contact). A few studies focused on interventions involving educational strategies without social contact, such as mental health training (courses/modules), distance learning via the Internet, lectures, discussion groups, and simulations. One study investigated an online anti-stigma awareness-raising campaign that aimed to reduce stigmatizing attitudes among health care providers. CONCLUSION: Anti-stigma interventions that involve social contact between health care providers and people with mental illness, target specific mental illnesses and include long-term follow-up strategies seem to be the most promising at reducing stigma towards mental illness among health care providers.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".