Youth, Caregiver, and Prescriber Experiences of Antipsychotic-Related Weight Gain
Bibliographic record
Abstract
Objectives. To explore the lived experience of youth, caregivers, and prescribers with antipsychotic medications. Design. We conducted a qualitative interpretive phenomenology study. Youth aged 11 to 25 with recent experience taking antipsychotics, the caregivers of youth taking antipsychotics, and the prescribers of antipsychotics were recruited. Subjects. Eighteen youth, 10 caregivers (parents), and 11 prescribers participated. Results. Eleven of 18 youth, six of ten parents, and all prescribers discussed antipsychotic-related weight gain. Participants were attuned to the numeric weight changes usually measured in pounds. Significant discussions occurred around weight changes in the context of body image, adherence and persistence, managing weight increases, and metabolic effects. These concepts were often inextricably linked but maintained the significance as separate issues. Participants discussed tradeoffs regarding the perceived benefits and risks of weight gain, often with uncertainty and inadequate information regarding the short- and long-term consequences. Conclusion. Antipsychotic-related weight gain in youth influences body image and weight management strategies and impacts treatment courses with respect to adherence and persistence. In our study, the experience of monitoring for weight and metabolic changes was primarily reactive in nature. Participants expressed ambiguity regarding the short- and long-term consequences of weight and metabolic changes.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".