Community member attitudes and understanding of “serious mental illness”: A mixed-method study.
Bibliographic record
Abstract
OBJECTIVE: "Serious mental illness" (SMI) is a priority population within mental health treatment and policy. However, there is no standard operational definition across research, clinical, and policy contexts. The use of the label has also not been evaluated regarding its association with stigma among the general public. This mixed-method study compared community members' stigma toward "SMI" with other psychiatric labels and examined community understanding and perceptions of the SMI label. METHOD: Two hundred forty-six participants recruited via Prolific read randomly manipulated vignettes describing an individual diagnosed with depression, schizophrenia, or "SMI" and completed measures of stigma and qualitative questions regarding familiarity, understanding, and perceived utility of SMI. Quantitative analyses evaluated stigma across vignettes, and qualitative analyses identified common themes across responses. RESULTS: Stigma was relatively high across vignettes, with more negative views reported toward SMI and schizophrenia compared with depression. Quantitative differences in stigma by vignette were not significant after controlling for participants' age and gender. Qualitative responses were split regarding the perceived utility of the SMI term, with noted concerns including its broadness and potential for stigma. Most participants described functional impairment or disability as characteristic of "SMI," and approximately 70% associated schizophrenia and psychotic disorders with "SMI" compared with 45% for depression. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Person-level factors were more strongly associated with stigma than psychiatric labels. However, our sample described concerns that the SMI term is vague and may exacerbate stigma. Community education and antistigma efforts should move beyond diagnostic labels in characterizing mental illness to facilitate change in attitudes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".