Insight, self-stigma and depressive symptoms among patients with schizophrenia
Bibliographic record
Abstract
Depressive symptoms are rather prevalent among patients with schizophrenia and various factors can influence them. Insight and self-stigma shows complex and contradictory relationship, both are among most important features of schizophrenia with strong impact on depressive symptoms. We wanted to test hypothesis that preserved insight is related to depressive symptoms only when self-stigma is also high. Our cross-sectional research comprised 149 patients with diagnosis of schizophrenia, both gender, age span 25-45 years. Rating scales used were Calgary Depression Scale (CDS), Scale to assess Unawareness of Mental Disorder (SUMD) and Internalized Stigma in Mental Illness (ISMI) which are specifically designed for patients with schizophrenia. Majority of patients were male (72%), single or separated (85%). Relation between selfstigma and depressive symptoms was statistically significant ( b =0.12, 95% CI=[0.06, 0.19], β=0.32, t (135)=3.89, P b =–0.01, 95% CI=[–0.02,–0.001], β=–0.17, t (135)=–2.20, P =0.029). Post-hoc analysis showed that among patients with extremely high selfstigma (more than 90 centile), higher insight was related to more depressive symptoms (b=–0.22, 95% CI=[–0.42,–0.02], β=–0.34, t =–2.23, P =0.028). These results are important for tailoring specific antistigma programs for patients with high level of insight in order to prevent deleterious impact of depressive symptoms on course of 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".