Prevalence of Depression in Schizophrenic Remission Patients and its Impact on their QoL: A Cross-sectional Study
Bibliographic record
Abstract
Introduction: Schizophrenia is a major mental illness and a significant contributor to the global burden of disease. Around one-fifth of patients with Schizophrenia have signific ant depression during the phase of clinical remission. Aim: To evaluate the prevalence of depression in patients with Schizophrenia, the Quality of Life (QoL) of patients with depression in Schizophrenia, and to study the relationship between the two. Materials and Methods: This cross-sectional study was conducted at the Department of Psychiatry, Chettinad Hospital and Research Institute, Chennai, Tamil Nadu, India. One hundred patients aged 18 to 59 years diagnosed with Schizophrenia as per International Classification of Diseases (ICD-11), operationally in remission for a minimum of one month, were included. The Calgary Depression Scale for Schizophrenia (CDSS) and the World Health Organisation Quality of Life Brief version (WHOQoL-BREF) scale were used to measure the presence of depression and QoL in patients with Schizophrenia. Data were analysed with t-test, Chi-square tests, and Pearson correlation using Statistical Package for Social Sciences (SPSS) software version 21.0. Results: The mean age of the study participants was 31.6±5.1 years. Of the total study population, 72% were male, 31% had a high school level education, 20% were unemployed, 64% were married, 46% were from a semi-urban background, and 45% belonged to a lower-middle socio-economic background. Twenty-two percent of patients with Schizophrenia in remission were found to have depression. A longer duration of untreated psychosis (mean=9.14±2.83 years) was significantly associated with the development of depression in patients with Schizophrenia. Patients with Schizophrenia and depression had significantly poorer QoL in all domains (physical, psychological, social, environmental; p<0.001). Conclusion: This study helps us understand the importance of monitoring for depression in at-risk patients with Schizophrenia in remission. Doing so can pave the way for early intervention, thus improving their overall QoL.
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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 | 0.005 | 0.003 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".