Population-level mental health literacy: A vignette-based study on prejudice, sexism, and recognition in prevention strategies for social anxiety in Ghana
Bibliographic record
Abstract
Mental Health Literacy (MHL) evidence on promoting mental health prevention at the population level in Ghana is limited. We explored factors, including, sociodemographic variables, prejudice, sexist attitudes, and previous experience of mental disorders, related to the endorsement of prevention strategies for social anxiety in Ghana. A total of 601 individuals participated in an online vignette-based experimental study. Participants were randomly assigned to read two clinical vignettes, each presenting symptoms of social anxiety for a hypothetical person, one being male and the other female. Participants provided their impressions of the hypothetical person and completed self-reported measures, encompassing assessments related to ambivalent sexism, MHL, prejudice, and demographic factors. We found that recognition of the social anxiety in the vignettes directly associated with psychotherapeutic prevention strategies and indirectly predicted substance-related prevention strategies for social anxiety among the participants. Prejudice towards social anxiety was linked to increased recommendation of substance-related prevention strategies for social anxiety and less frequent endorsement of psychotherapeutic prevention strategies. Benevolence towards women was positively associated with stress-reduction preventive strategies for social anxiety, while benevolence towards men negatively impacted such strategies. Findings underscore the significant role of Western views of mental health, and the harmful impact of prejudice on mental health, including the potential impact of cultural and contextual elements in shaping preventive approaches to mental disorders. Efforts to enhance MHL aimed at improving population-level mental health outcomes should prioritize the development of compassionate and culturally inclusive responses to mental health distress while also working to reduce stigma.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".