Motivational and neurocognitive deficits are central to the prediction of longitudinal functional outcome in schizophrenia
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Functional impairment is characteristic of most individuals with schizophrenia; however, the key variables that undermine community functioning are not well understood. This study evaluated the association between selected clinical variables and one-year longitudinal functional outcomes in patients with schizophrenia. METHOD: The sample included 754 patients with schizophrenia who completed both baseline and one-year follow-up visits in the CATIE study. Patients were evaluated with a comprehensive battery of assessments capturing symptom severity and cognitive performance among other variables. The primary outcome variable was functional status one-year postbaseline measured using the Heinrichs-Carpenter Quality of Life Scale. RESULTS: Factor analysis of negative symptom items revealed two factors reflecting diminished expression and amotivation. Multivariate regression modeling revealed several significant independent predictors of longitudinal functioning scores. The strongest predictors were baseline amotivation and neurocognition. Both amotivation and neurocognition also had independent predictive value for each of the domains of functioning assessed (e.g., vocational). CONCLUSION: Both motivational and neurocognitive deficits independently contribute to longitudinal functional outcomes assessed 1 year later among patients with schizophrenia. Both of these domains of psychopathology impede functional recovery; hence, it follows that treatments ameliorating each of these symptoms should promote community functioning among individuals with schizophrenia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it