Public attitudes toward mental illness in Africa and North America
Bibliographic record
Abstract
OBJECTIVE: Public attitudes toward mental illness in two widely disparate cultures, Canada and Cameroon, were compared using an experimental version of a survey instrument, the Public Opinion Survey of Human Attributes-Mental Illness or POSHA-MI(e). METHOD: 120 respondents rated POSHA-MI(e) items relating to mental illness on 1-9 equal appearing interval scales: 30 in English and 30 in French in both Cameroon and Canada. Additionally, 30 matched, monolingual English, American respondents were included as a comparison group. RESULT: In Canada (and in the USA), attitudes were generally more positive and less socially stigmatizing toward mental illness than in Cameroon. Differences between countries were much larger than differences between language groups. CONCLUSION: Consistent with other research, beliefs and reactions of the public regarding mental illness reflect stigma, especially in Cameroon. Cultural influences on these public attitudes are more likely important than language influences. Results of this field test of the POSHA-MI(e), documenting differences in public attitudes toward mental illness in two divergent cultures, support its further development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.000 |
| 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".