The relationship between stigma sentiments and self-identity of individuals with schizophrenia.
Bibliographic record
Abstract
OBJECTIVE: Stigma sentiments are the attitudes held toward a culturally devalued label or group. The present study measures schizophrenia stigma sentiments and self-identity to assess self-stigma experienced by people with schizophrenia. METHOD: Ninety individuals with schizophrenia and 23 controls with no history of psychosis rated the evaluation, potency, and activity of "A person with schizophrenia or schizoaffective disorder," (stigma sentiments) and of "Myself as I really am" (self-identity). t tests, correlations, and regression analysis were used to (a) test relationships among stigma sentiments and self-identity in the groups separately; (b) test a model for predicting self-identity in the schizophrenia group, using stigma sentiments, current symptoms, and current functioning; and (c) compare the participant groups' stigma sentiments and self-identities. RESULTS: The evaluation category of self-identity and of stigma sentiment were correlated in the schizophrenia group, r(88) = .44, p < .001, but not in the control group. Current symptoms and the evaluation category of stigma sentiments were significant predictors of the evaluation category of self-identity in the schizophrenia group. The evaluation and potency stigma sentiments reported by the 2 groups did not differ; the control group rated itself more favorably on evaluation and potency than did the schizophrenia group. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Self-evaluation of individuals with schizophrenia was less favorable than self-evaluation of individuals with no psychosis history, and evaluation attitudes held by individuals with schizophrenia regarding the schizophrenia label were associated with their self-identity. Results suggest preliminary utility of this simple measure in identifying self-stigma experienced by individuals with schizophrenia.
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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".