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Record W4403880627 · doi:10.70135/seejph.vi.1788

Effectiveness of Social Skills Training on Quality of Life and Functional Performance in Patients with Schizophrenia

2024· article· en· W4403880627 on OpenAlexaboutno aff
Sonia Sonia, Senthil Vadivel, Arun Vijay Subbarayalu, Christopher Amalraj, G. R. Maruthi Sankar

Bibliographic record

VenueSouth Eastern European Journal of Public Health · 2024
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)PsychologyQuality of life (healthcare)Social skillsTraining (meteorology)PsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

The study aims to determine the effectiveness of social skills coaching on quality of life and functional performance in patients with schizophrenia. Methods: A quasi-experimental study design was chosen and sixty participants (N=60) aged 18 to 55 years were recruited using a convenience sampling approach. The participants were divided into two groups viz. experimental (n = 30) and control (n = 30). Participants in the experimental group received social skills coaching for eight weeks, while participants in the control group received traditional occupational therapy interventions. Two outcome measures, consisting of the Canadian Activity Performance Index (COPM) and a 36-item short survey (SF-36), were used to measure quality of life and functional performance. Results: There was a statistically significant difference between the pre- and post-test scores of the COPM and SF-36 survey in both the experimental and control groups. In addition, the quality of life and functional performance of the patients in the experimental group improved significantly compared to those in the control group. Conclusion: In schizophrenia patients, a social skills training intervention was more successful in improving quality of life and functional performance. Through social skills training exercises, participants' engagement increased, they showed more enthusiasm in completing their everyday tasks, and their role identity and integration into the community also improved.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.062
GPT teacher head0.328
Teacher spread0.266 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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