Reducing the Stigma of Depression Among Asian Students
Bibliographic record
Abstract
In North America, Asians reliably report higher levels of stigma toward people with depression than do Europeans. Possible methods of reducing this discrepancy have rarely been explored. Asian undergraduate students ( n = 132) were presented with one of four antistigma videos with two actresses: one portraying a student with depression and the other a professor. The videos used the concept of social proof, presenting either positive or negative descriptive norms, to effect change in stigma, measured by social distance. It was hypothesized that the positive descriptive norms intervention would show significantly greater positive change in social distance compared with the negative descriptive norms intervention. All videos were effective in reducing preferred social distance toward people with depression relative to the control condition. The effectiveness of the positive descriptive norm video was mediated through descriptive norms and self-efficacy. The effectiveness of the negative descriptive norm video was mediated through injunctive norms and perceived value of support. The findings can help guide interventions that aim to encourage social engagement with people with depression among Asian student populations. Manipulating social norms and increasing self-efficacy may be especially effective.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".