Incidence of Antipsychotic-Associated Side Effects
Bibliographic record
Abstract
OBJECTIVE: This study aimed to compare (1) the detection rates of antipsychotic-associated side effects between clinician and patient ratings and (2) differences as a function of change and absolute score definitions. METHODS: Data from phase 1 of the Clinical Antipsychotic Trials of Intervention Effectiveness (N = 1460) were analyzed. In this trial, 18 adverse events were systematically and concurrently assessed by clinicians and patients using a 4-point severity scale ranging from 0 (absent) to 3 (severe). The incidence of antipsychotic-associated side effects was calculated according to 2 definitions: change score (ie, higher score on the scale versus baseline) and absolute score (a score of 2 or 3 on the scale). In addition, patient and clinician concurrent detection rates were examined. RESULTS: The differences in incidence of antipsychotic-associated side effects between clinician and patient ratings were as small as 5.7% across the 2 definitions. The incidence of all side effects across clinician and patient ratings was approximately 2 times higher when using the change versus absolute score definition. Among the side effects detected by patients, 11 side effects were identified more frequently by clinicians, with 14.3% to 30.2% differences when using the change versus absolute score definition. Conversely, there was no difference of 10% or greater in patient or clinician concurrent detection rate on any item when using the absolute versus change score definition. CONCLUSIONS: Our findings suggest that patient ratings are in line with clinician ratings and that the change score definition may be superior for the assessment of antipsychotic-associated side effects in clinical studies.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".