Reliability of the Glasgow Antipsychotic Side-effects Scale for Clozapine Japanese version (GASS-C-J)
Bibliographic record
Abstract
The purpose of this study was to develop the Glasgow Antipsychotic Side effects Scale for Clozapine Japanese version (GASS-C-J) and examine its reliability to assess clozapine-related side effects. We developed the GASS-C-J using forward and backward translation. Semantic equivalence of the GASS-C-J to the GASS-C was confirmed by the original author. We then administered the GASS-C-J twice to 109 patients on clozapine treatment at two psychiatric hospitals in Japan. We assessed the internal consistency and test-retest reliability of the GASS-C-J using Cronbach's alpha and weighted kappa coefficient, respectively. We also examined if discrepancies in each GASS-C-J item score between the first and second rating were correlated with items of the Brief Evaluation of Psychosis Symptom Domains (BE-PSD). The Cronbach's alpha coefficient of the GASS-C-J at the first and second rating was 0.78 (95% CI: 0.72 to 0.84) and 0.82 (95% CI: 0.76 to 0.88), respectively. The weighted kappa coefficient of individual and total GASS-C-J item scores ranged from 0.45 to 0.88. Some symptom domains were correlated with discrepancies in specific items of the GASS-C-J: psychotic symptoms and nausea/vomiting (rs = 0.27), thirst (rs = 0.31), and appetite/weight gain (rs = 0.27); disorganized thinking and urinary incontinence (rs = 0.26); depression/anxiety and myoclonus (rs = 0.25), hypersalivation (rs = -0.27), and blurred vision (rs = -0.22). These findings demonstrate that the GASS-C-J can be used in clinical and research settings as a reliable scale to assess clozapine-related side effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".