Cognitive Performance and Functional Competence as Predictors of Community Independence in Schizophrenia
Bibliographic record
Abstract
Measures of functional competence have been introduced to supplement standard cognitive and neuropsychological evaluations in schizophrenia research and practice. Functional competence comprises skills and abilities that are more relevant to daily life and community adjustment. However, it is unclear whether relevance translates into significantly enhanced prediction of real-world outcomes. The aim of this study was to assess the specific contribution of functional competence in predicting a key aspect of real-world outcome in schizophrenia: community independence. Demographic, clinical, cognitive, and functional competence data were obtained from 127 patients with schizophrenia or schizoaffective disorder and used to predict community independence concurrently and longitudinally after 10 months. Hierarchical regression analyses indicated that demographic, clinical, and cognitive predictors accounted jointly for 35%-38% of the variance in community independence across assessment points. Functional competence data failed to add significantly to this validity. Considered separately from demographic and clinical predictors, cognitive and functional competence data accounted for significant amounts of outcome variance. However, the addition of functional competence to standard cognitive test data yielded a significant increase in validity only for concurrent and not for longitudinal prediction of community independence. The specific real-world validity of functional competence is modest, yielding information that is largely redundant with standard cognitive performance.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".