Measuring neuropsychological change in schizophrenia with novel antipsychotic medications.
Bibliographic record
Abstract
The recent introduction of second-generation antipsychotic medications has stimulated considerable interest in cognitive changes to pharmacotherapeutic treatment. Cognitive impairment has been an integral consequence of schizophrenia since the inception of the diagnosis and has proven resistant to treatment with firstgeneration antipsychotic medication. This commentary summarizes the relevance of cognitive impairment to treatment outcome and reviews the research to date regarding the apparent cognitive efficacy of clozapine, olanzapine, risperidone and quetiapine. Emphasis is given to the value of comprehensive neuropsychological assessments that can provide information on the differential effects of the novel antipsychotic treatments on discrete domains of cognitive skill. Methodologic suggestions are also offered regarding secondary factors that may confound a cerebral interpretation of the changes, specific suggestions regarding the types of instruments that may be of value to this assessment, a general consideration of computerized testing, and the importance of translating cognitive improvement into changes in lifestyle. The novel interest in prospective alterations of cognitive skills to second-generation antipsychotic medications may provide an important stimulus to further research on traditional neuropsychological issues relating to a localization of cerebral pathology and a confident articulation of the onset and course of the dysfunction.
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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 | 0.000 | 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) | 0.001 | 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".