A Retrospective Study on the Relationship Between Cognitive Function and Social Function in Patients With Schizophrenia
Bibliographic record
Abstract
Background: Social dysfunction is associated with decreased activity, employment difficulties, and poor prognosis in patients with schizophrenia. Cognitive functions, such as attention and processing speed, have been implicated in the social functions of schizophrenia patients; however, the relationship between cognitive functions and social functions remains unclear. Thus, understanding the factors that influence social functioning can aid the development of therapeutic strategies for schizophrenia. Herein, we retrospectively analyzed factors that influence social functioning in patients with schizophrenia. Methods: Patient background, intelligence quotient (IQ) scores, Japanese version of the Brief Assessment of Cognition in Schizophrenia (BACS-J) scores, the dose of antipsychotic drugs, Positive and Negative Syndrome Scale (PANSS) scores, and the factors influencing each subscale of the Japanese version of the Social Functioning Scale (SFS-J) were evaluated using univariate and multivariate analyses. The Bonferroni correction was applied to evaluate the correlation between each factor in the univariate analysis. In multivariate analysis, independent variables were selected using a stepwise method. In each model, considering the sample size, the maximum number of variables extracted using the stepwise method was set to three. We then calculated the standard partial regression coefficient (standard β) between the SFS-J subscale scores and each factor. Results: Data from 36 patients were analyzed. The average age, illness duration, and total length of hospitalization were 57.8 years, 34.8 years, and 196.7 months, respectively. Of the seven significant correlations with the SFS-J subscale in the univariate analysis, only three were significant in the multivariate analysis model. According to the multivariable model, BACS-J verbal fluency positively correlated with SFS-J withdrawal, interpersonal communication, and employment/occupation. Moreover, BACS-J token motor and educational history were positively correlated with SFS-J recreation and SFS-J employment/occupation, respectively. PANSS scores, IQ scores, and doses of antipsychotic drugs did not show clear associations with SFS-J scores. Conclusions: In conclusion, there were significant correlations between BACS-J subscale scores for cognitive functioning and SFS-J subscale scores for social functioning in patients with schizophrenia.
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 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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".