Investigating the effect of exercise on clinical symptoms, cognitive performance, and quality of life in schizophrenia patients treated with clozapine
Bibliographic record
Abstract
Background This prospective study aims to investigate the effects of exercise on clinical symptoms, cognitive performance, and quality of life in schizophrenia patients treated with clozapine.Methods Fifty-six (n = 56) participants were completed as the physical exercise group (PEG) (n = 28) and control group (CG) (n = 28). The PEG participated in an exercise program lasting 30 min, three times a week, for 12 weeks, in addition to a routine ergotherapy programme. The CG did not receive any treatment other than ergotherapy programme. Sociodemographic characteristics, Positive and Negative Syndrome Scale (PANNS), Brief Psychiatric Rating Scale (BPRS), Montreal Cognitive Assessment (MOCA), and The World Health Organisation Quality of Life (WHQOL-BREF) evaluated at baseline and after 12 weeks for both groups.Results After intervention, a statistically significant increase was observed in the MOCA and the psychological health sub-parameter of WHQOL-BREF in the PEG (p ≤ 0.05). According to the intergroup change analysis, the changes in the cognitive performance and psychological health sub-parameter of quality-of-life scores were significantly higher in the PEG than in the CG (p ≤ 0.05).Conclusion The demonstrated improvement in cognitive performance and psychological health in patients with schizophrenia treated with Clozapine through physical exercise strongly advocates for the inclusion of structured exercise programs in comprehensive treatment plans.
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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 | 0.001 |
| 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".