Factors shaping the decision-making process to continue or discontinue antipsychotics: exploratory qualitative study of 12 individuals in remission from first-episode psychosis
Bibliographic record
Abstract
BACKGROUND: The decision-making process regarding antipsychotic continuation or discontinuation following remission from first-episode psychosis (FEP) remains complex and underresearched. While discontinuation increases the risk of relapse, concerns over long-term side-effects such as metabolic disturbances and extrapyramidal symptoms also exist. Current guidelines recommend maintaining antipsychotics for 1-5 years, emphasising shared decision-making (SDM) between clinicians and patients. AIMS: This study aimed to explore the decision-making process and describe the factors influencing the decision to discontinue or continue antipsychotic treatment following remission from FEP, from the patients' perspective. METHOD: A descriptive qualitative study was conducted with 12 individuals in remission from FEP who received care at early intervention services in Quebec, Canada. Data were collected through online semi-structured interviews and analysed thematically to identify key factors influencing treatment decisions. RESULTS: The decision-making process was activated by treatment reflection triggers and shaped by various perceptions (of illness, treatment and stigma) and relationships (with friends, family and the clinical team), ultimately leading to decisions to either discontinue, continue (at standard or reduced dose) or remain ambivalent. This dynamic process was guided by participants' motivators, such as well-being and societal contribution. Most participants felt that discontinuation discussions were not initiated by the clinical team. CONCLUSIONS: The decision-making process is driven by motivators that were found to be linked to the concept of personal recovery. This study highlights the need for proactive, personalised discussions between clinicians and patients. Future research should focus on decision aids tailored to the FEP population to support SDM and improve treatment outcomes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".