Relationship between neuroleptic dosage and subjective cognitive dysfunction in schizophrenic patients treated with either conventional or atypical neuroleptic medication
Bibliographic record
Abstract
Previous research has suggested that high doses of conventional neuroleptics may induce neurocognitive deficits when assessed with standard tasks. However, little is known about the effects of high doses of neuroleptics (conventional or atypical) on subjective cognitive dysfunction. Recent research stresses the putative importance of self-reported cognitive deficits for both symptomatic outcome and medication compliance. The aim of the present study was to investigate the impact of neuroleptic medication on subjective cognition in patients treated with either conventional or atypical agents (clozapine, risperidone, olanzapine). Patients were asked to endorse the items of a questionnaire entitled 'Subjective Well-Being under Neuroleptic Treatment' prior to discharge. Subjective impairment, as assessed with the subscale 'mental functioning', was significantly correlated with greater conventional neuroleptic dosage after controlling for psychopathology (P<0.05). The difference between patients medicated with higher doses of conventional neuroleptics and those with lower doses was highly significant (P<0.001). In contrast, higher atypical neuroleptic doses were not associated with impairment.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".