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Record W4412546288 · doi:10.7759/cureus.88476

Effectiveness of Adding Metacognitive Training to Occupational Therapy in Patients With Schizophrenia Under Long-Term Hospitalization: A Pilot Randomized Controlled Trial

2025· article· en· W4412546288 on OpenAlexaboutno aff
Rumi Sunohara, Ai Tayama, Mizuki Nakajima, Masayoshi Kobayashi

Bibliographic record

VenueCureus · 2025
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRandomized controlled trialPhysical therapySchizophrenia (object-oriented programming)Occupational therapyTerm (time)PsychiatrySurgery

Abstract

fetched live from OpenAlex

Objective This study investigated the effects of metacognitive training (MCT) on improving psychiatric symptoms and cognitive function in patients with schizophrenia who were hospitalized for long periods. Methods The participants were long-term inpatients with schizophrenia, hospitalized in a private psychiatric hospital in Japan. Participants were randomly assigned to either the occupational therapy (OT)+MCT group or the OT-alone group. The OT+MCT group received 16 weekly MCT sessions, each lasting 60 minutes, over a period of four months. The Japanese versions of the Montreal Cognitive Assessment (MoCA-J), Positive and Negative Syndrome Scale (PANSS), Beck Cognitive Insight Scale (BCIS), and Global Assessment of Functioning (GAF) scores were compared before and after the intervention using a two-way repeated measures analysis of variance. To examine age-related effects, a correlation analysis was performed between participants' age and their MoCA-J total score. Furthermore, the OT+MCT group was stratified by median age (68 years), and changes in each outcome measure were compared between the groups. Results The 41 participants had a mean age of 69.22 years, ranging from 37 to 79 years, with 21 assigned to the OT+MCT group and 20 to the OT-alone group. There were no dropouts during the study period. The mean MoCA-J Total score at baseline was 17.67 (SD = 5.37) in the OT+MCT group and 14.85 (SD = 5.95) in the OT-alone group, indicating mild cognitive impairment in both groups. Four months after the intervention, both groups demonstrated an upward trend in MoCA-J scores. Notable improvements were seen in visuospatial/executive and total scores over time in both groups. However, no significant between-subject effects or interaction effects were detected. Additionally, a significant negative correlation was observed between age and the MoCA-J total score. In the PANSS, scores decreased in both groups at the post-intervention assessment, and significant differences were observed in general psychopathology and total score categories due to within-subjects factors. Negative symptom scores significantly differed between groups; however, no interaction with time was observed. Participants aged 68 or older showed greater reductions in PANSS scores. While no significant differences were observed in positive symptoms, significant improvements were observed in negative symptoms, general psychopathology, and overall PANSS scores. No significant differences were observed between the two groups in either the BCIS or GAF scores. Conclusions These findings suggest that MCT is feasible for long-term hospitalized elderly patients with schizophrenia and may improve psychiatric symptoms when combined with OT. Although OT+MCT did not significantly improve cognitive function, the results suggest it may be particularly beneficial for older patients in managing persistent psychiatric symptoms. Future studies should investigate the cognitive effects of MCT in larger samples, determine optimal treatment duration and frequency, and explore potential interactions with medications.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.030
GPT teacher head0.334
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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