The Relationship Between Predominant Negative Symptoms and Self-Stigmatization in Clinically Stable Schizophrenia Patients
Bibliographic record
Abstract
Objective: Internalized stigma and negative symptoms have deteriorating effects on prognosis and treatment adherence. Therefore, it is important to recognize the interaction between internalized stigma and negative symptoms in patients with schizophrenia. However, the relationships between negative symptom dimensions and internalized stigma are unclear. In this study, we examined the relationship between self-stigmatization and negative symptoms in a homogeneous subgroup of patients with predominant negative symptoms (PNS). At the same time, the relationships between depression severity and perceived social support and self-stigmatization were evaluated. Methods: Clinically stable schizophrenia patients who were being followed up in a Community Mental Health Center were included in this cross-sectional study. The Positive and Negative Symptom Scale (PANSS), the Brief Negative Symptom Scale (BNSS), the Calgary Depression Scale for Schizophrenia (CDSS) were applied by the clinician to the patients. In addition, the Internalized Stigma of Mental Illness Inventory (ISMI) and Multidimensional Scale of Perceived Social Support (MSPS), which are self-report scales, were given. Scale scores were compared between PNS and non-PNS (NPNS) groups. Correlations between the ISMI scale scores (perceived discrimination, alienation, stereotype endorsement, social withdrawal, and resistance to stigma) and demographic and clinical variables and other scale scores were evaluated. ANCOVA analysis was used to assess the effect of years of education, employment status, and insight level in intergroup comparisons. Results: The study included 117 patients [mean age = 43.4 (SD = 11.8); 35 females], with 88.9% experiencing self-stigma. The PNS group (n=58) had lower levels of insight, perceived discrimination, and ISMI total score, but higher negative symptoms and BNSS scores, whereas the NPNS group had higher scores on the positive and general subscales of the PANSS. Correlation analysis revealed negative relationships between alienation and perceived discrimination scores, years of education, and all negative symptom scores. ANCOVA results indicated that, after adjusting for education, employment status, and insight level, the difference in perceived discrimination between PNS and NPNS groups remained significant, while the difference in ISMI total score did not. Insight level was the only significant variable affecting ISMI total score in the model. Conclusion: Patients with PNS have a unique profile in terms of the relationships between self-stigma and negative symptom dimensions. At the same time, an increase in self-stigma was found as the level of insight increased.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".