Validation of a patient interview for assessing reasons for antipsychotic discontinuation and continuation
Bibliographic record
Abstract
INTRODUCTION: The Reasons for Antipsychotic Discontinuation Interview (RAD-I) was developed to assess patients' perceptions of reasons for discontinuing or continuing an antipsychotic. The current study examined reliability and validity of domain scores representing three factors contributing to these treatment decisions: treatment benefits, adverse events, and distal reasons other than direct effects of the medication. METHODS: Data were collected from patients with schizophrenia or schizoaffective disorder and their treating clinicians. For approximately 25% of patients, a second rater completed the RAD-I for assessment of inter-rater reliability. RESULTS: All patients (n = 121; 81 discontinuation, 40 continuation) reported at least one reason for discontinuation or continuation (mean = 2.8 reasons for discontinuation; 3.4 for continuation). Inter-rater reliability was supported (kappas = 0.63-1.0). Validity of the discontinuation domain scores was supported by associations with symptom measures (the Positive and Negative Syndrome Scale for Schizophrenia, the Clinical Global Impression - Schizophrenia Scale; r = 0.30 to 0.51; all P < 0.01), patients' primary reasons for discontinuation, and adverse events. However, the continuation domain scores were not significantly associated with these other indicators. DISCUSSION: Results support the reliability, convergent validity, and known-groups validity of the RAD-I for assessing patients' reasons for antipsychotic discontinuation. Further research is needed to examine validity of the RAD-I continuation section.
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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 | 0.023 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".