Beliefs about Schizophrenia in Italy: A Comparative Nationwide Survey of the General Public, Mental Health Professionals, and Patients' Relatives
Bibliographic record
Abstract
OBJECTIVE: This study compared beliefs about the causes, treatments, and psychosocial consequences of schizophrenia in a sample of 714 lay respondents, 465 mental health professionals, and 709 key relatives of patients with this disorder. METHOD: We conducted the survey in 30 Italian geographic areas that we randomly selected after considering location and population density. We used the Questionnaire on the Opinions About Mental Illness (QO) to collect data. RESULTS: Of those surveyed, 34% of the lay respondents, 20% of the professionals, and 68% of the relatives stated that schizophrenia is exclusively caused by psychosocial factors. Lay respondents' opinions on patients' civil rights and social competence tended to be more similar to those expressed by professionals then to those reported by relatives. Lay respondents differed from the other 2 groups in their beliefs regarding the effectiveness of psychological treatments, patients' unpredictability, and whether patients should be admitted to asylums. CONCLUSIONS: These results suggest that the general public needs to be better informed about schizophrenia's main characteristics, available treatments, and risk for dangerous behaviours. The existing gap among the study's target populations could be reduced through campaigns aimed at increasing public awareness of the affective and civil rights of patients.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".