Effects of Pilates-Based Exercises on Functional Capacity and Mental Health in Individuals with Schizophrenia: A Pilot Study
Bibliographic record
Abstract
Background Although there is considerable evidence that exercise improves the physical and mental health of individuals with schizophrenia, the most useful exercise technique for this population is still the subject of research.Purpose The aim of this study was to investigate the effects of Pilates exercises on functional capacity and mental health in individuals with schizophrenia.Methods Twenty-three participants were not randomly assigned to either Pilates exercise group (PEG) or nonspecific exercise group (NSEG). Ten participants from each group completed the study (87% response rate). The PEG participated in a 6-week Pilates exercise training twice per week, while the NSEG participated in a nonspecific activity program. 6-Minute Walk Distance (6-MWD) was assessed for functional capacity. Mental health was evaluated using Calgary Depression Scale for Schizophrenia (CDSS), and Brief Psychiatric Rating Scale (BPRS).Results 6-MWD significantly increased (p = .025), CDSS (p = .023) and BPRS (p = .012) scores significantly decreased in the PEG compared to baseline. Inter-group comparison showed that PEG had significantly better scores than NSEG in terms of the final 6-MWD (p = .005), CDSS (p = .008) and BPRS (p = .008).Conclusion Results showed that Pilates may help improve the functional capacity and mental health of individuals with schizophrenia, but the small sample size and methodological limitations limit the interpretability of this study.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".