Effects of Lee Silverman Voice Treatment‐BIG on Motor, Cognition, Mental Health, Occupational Performance, and Occupational Balance in Patients With Schizophrenia: A Single‐Subject Experimental Study
Why this work is in the frame
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Bibliographic record
Abstract
Introduction: In this study, we aim to apply BIG to patients with schizophrenia to confirm changes in mental symptoms, task performance, and occupational balance through motor and cognitive enhancement. Method: This study used a single‐subject A‐B‐A design. It consisted of a total of 22 sessions, with 4 sessions in the baseline period, 16 sessions in the intervention period (Lee Silverman Voice Treatment‐BIG), and 2 sessions in the follow‐up period. The subjects were three male patients diagnosed with chronic schizophrenia, all severe cases. During the 22 sessions, the timed up and go test (TUG) and functional reach test (FRT) and the Montreal Cognitive Assessment (MoCA) were used to determine changes in motor function and cognition, and the subjective cognitive and mental score (SS), Canadian Occupational Performance Measure (COPM), and Occupational Balance Questionnaire‐Korean (OBQ‐K) were used to determine changes in psychiatric symptoms, work performance, and work balance satisfaction before and after the intervention. Statistically significant changes were determined using the two standard deviation (2SD) band method. Results: The TUG, FRT, and MoCA showed significant results in the intervention period compared to the baseline period. The SS, COPM, and OBQ‐K also showed positive changes in scores from pre‐ to postintervention. Conclusion: In this study, BIG was found to promote improvement in motor and cognitive function in chronic schizophrenia patients, with positive effects on psychiatric symptoms, task performance, and occupational balance satisfaction.
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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 | 0.001 | 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 | 0.000 |
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 it