Adaptation and validation of the Glasgow Antipsychotic Side-Effect Scale in Bangladesh
Bibliographic record
Abstract
OBJECTIVE: This study aimed to adapt and validate the Glasgow Antipsychotic Side-Effect Scale (GASS) in Bangla. METHODS: Patients aged ≥18 years with a psychiatric disorder who were currently taking antipsychotics were recruited from a tertiary care psychiatric hospital using convenience sampling. Additionally, patients aged ≥18 years with a psychiatric disorder who had not received any antipsychotic medications in the past 6 months were recruited as controls. Participants were assessed using the newly adapted GASS Bangla. Internal consistency was assessed using McDonald's omega. Principal component analysis with varimax rotation was used to determine the factor structure. Discriminant validity was examined. RESULTS: In total, 153 male and 67 female patients (mean age, 27.8 years) who were receiving antipsychotic medications were included. The most common diagnoses were schizophrenia spectrum disorders (49.1%) and bipolar disorders (46.8%). The median duration of illness was 36 months, and the median duration of antipsychotic medication was 4 months. Additionally, 29 male and 21 female controls (mean age, 30.2 years) were included. The mean GASS Bangla score of the patients was 13.3 ± 8.4. Among the 220 patients, 181 (82.3%) reported absent or mild adverse effects, 34 (15.5%) reported moderate adverse effects, and five (2.3%) reported severe adverse effects. In contrast, all controls reported either absent or mild adverse effects. Patients taking antipsychotic medication had higher median GASS Bangla scores than controls (12 vs 2, p < 0.001), supporting the scale's discriminant validity. Internal consistency of the GASS Bangla was moderate (McDonald's omega = 0.604). Factor loadings ranged from 0.040 to 0.573, with most items loading above the conventional threshold of 0.30. Principal component analysis revealed a seven-factor structure that explained 58.9% of the total variance. CONCLUSION: The GASS Bangla is a user-friendly instrument for use as a screening tool. Despite moderate internal consistency, its clinical relevance and strong discriminant validity support its application in clinical practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".