Motivation and Social Cognition in Patients with Schizophrenia
Bibliographic record
Abstract
Social cognition, referring to one's ability to perceive and process social cues, is an important domain in schizophrenia. Numerous studies have demonstrated that patients with schizophrenia have poorer performance on tests assessing social cognition relative to healthy comparison participants. However, whether variables such as motivation are related to performance on these tests in patients with schizophrenia is unclear. One thousand three-hundred and seventy-eight patients with schizophrenia completed the Facial Emotion Discrimination Task as a measure of emotional processing, a key facet of social cognition. Level of motivation was also evaluated in these patients using a derived measure from the Quality of Life Scale. The relationship between motivation and task performance was examined using bivariate correlations and logistic regression modeling, controlling for the impact of age and overall severity of psychopathology, the latter evaluated using the Positive and Negative Syndrome Scale. Motivation was positively related to performance on the social cognition test, and this relationship remained significant after controlling for potential confounding variables such as age and illness severity. Social cognition was also related to functioning, and the relationship was mediated by level of motivation. The present study found a significant relationship between motivation and performance on a test of social cognition in a large sample of patients with schizophrenia. These findings suggest that amotivation undermines task performance, or alternatively that poor social cognitive ability impedes motivation. Future studies evaluating social cognition in patients with schizophrenia should concurrently assess for variables such as effort and motivation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".