Measuring Changes in Functional Status Among Patients With Schizophrenia: The Link With Cognitive Impairment
Bibliographic record
Abstract
Cognitive impairment associated with schizophrenia (CIAS) includes neuropsychological deficits in attention, working memory, verbal learning, and problem solving. These deficits have been shown to be linked to impairment in functional status (eg, social behavior, work performance, and activities of daily living) among patients with schizophrenia in cross-sectional studies. Less is known about the relationship between cognitive and functional change over time, such as potential functional implications of treatment-related improvement in CIAS. The purpose of this review is to summarize research on the association between change in CIAS and change in functional status, to discuss responsiveness of functional outcomes measures, and to provide recommendations for future research and measure development. Nine longitudinal studies were located on the link between CIAS and functional status, and 8 functional outcomes measures were used across these studies. The 9 studies offer initial support for a link between change in cognitive function and change in functional status. However, inconsistent findings across studies indicate that available research is preliminary, and substantial questions remain unanswered. Shortcomings of functional status measures are noted: most instruments were not developed for the target population, and none have demonstrated responsiveness to cognitive change among schizophrenic patients. It is recommended that new functional outcome measures be developed that are specifically designed to be responsive to change in cognition, with domains previously shown to be related to cognitive ability. When creating new functional outcomes measures for assessment of patients with schizophrenia, responsiveness to change in CIAS should be evaluated as part of the development and validation process.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".