Predictors of Treatment Discontinuation and Medication Nonadherence in Patients Recovering From a First Episode of Schizophrenia, Schizophreniform Disorder, or Schizoaffective Disorder
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To evaluate predictors of treatment discontinuation against medical advice and poor medication adherence among first-episode patients treated with olanzapine, quetiapine, or risperidone. METHOD: First-episode patients with schizophrenia, schizophreniform disorder, or schizoaffective disorder (DSM-IV) were randomly assigned to olanzapine (2.5-20 mg/day), quetiapine (100-800 mg/day), or risperidone (0.5-4 mg/day) as part of a 52-week, randomized, double-blind, flexible-dose, multicenter study. Patients were enrolled from 2002 to 2004 at one of 26 sites in the United States and Canada. Survival analysis tested for predictors of treatment discontinuation against medical advice, while mixed models tested for predictors of poor medication adherence. Significant findings from the final models were replicated in sensitivity analyses. RESULTS: Of the 400 patients randomly assigned to treatment, 115 patients who discontinued treatment against medical advice and 119 study completers were compared in this analysis. Poor treatment response (p < .001) and low medication adherence (p = .02) were independent predictors of discontinuation against medical advice. Ongoing substance abuse, ongoing depression, and treatment response failure significantly predicted poor medication adherence (p < .01). Higher cognitive performance at baseline and ethnicity (black) were also associated with lower medication adherence (p < .05). An association between poor medication adherence and illness insight at study entry was found at trend level (p = .059). CONCLUSION: This study highlights the importance of treatment response in predicting discontinuation against medical advice and poor adherence to medication in first-episode patients. These results also support interventions to improve adherence behavior, particularly by targeting substance use disorders and depressive symptoms. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT00034892 (http://www.clinicaltrials.gov).
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it