Awareness of Tardive Dyskinesia in Asian Patients with Schizophrenia
Bibliographic record
Abstract
While ethnocultural differences in risk of tardive dyskinesia (TD) have been suggested, no previous studies have examined whether this factor also plays a role in lack of awareness of TD. This study examined this question in an Asian population with schizophrenia. Six hundred seven patients in a state mental hospital in Singapore were assessed using the Abnormal Involuntary Movement Scale (AIMS) and the Simpson-Angus Rating Scale. Of the 607 patients, 242 (39.9%) met criteria for TD, and 163 (67.4%) patients were not aware of the presence of TD. No significant differences in terms of age, gender, and duration of illness were found between those aware of their TD and those not aware. Daily neuroleptic doses and scores for the AIMS and Simpson-Angus Rating Scale were significantly different, although after logistic regression, only the Simpson-Angus Rating Scale scores remained significant. The finding that a large proportion of our patients lacked awareness of their TD is consistent with other reports in the West and provides evidence that this feature is characteristic of the illness rather than of a specific ethnocultural group. We found an association between lack of awareness and greater severity of extrapyramidal symptoms (EPS), suggesting that there may be a subtype of TD in which lack of awareness and greater vulnerability of developing EPS are features.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".