Technology‐enabled collaborative care for youth with early psychosis: Results of a feasibility study to improve physical health behaviours
Bibliographic record
Abstract
AIM: Psychotic disorders are associated with excess morbidity and premature mortality. Contributing factors include tobacco smoking, low physical activity, and poor nutrition. This study tested a Technology-Enabled Collaborative Care model to improve health behaviours among youth with early psychosis. METHODS: A feasibility study among youth (ages 16-29) with early psychosis in Ontario, Canada. Participants were randomized to either a health coach supervised by a virtual care team (high intensity, n = 29), or self-directed learning (low intensity, n = 23) for 12 weeks. The primary outcome was participant engagement, defined as self-perceived benefit of changing health behaviours. Secondary outcomes were measures of health behaviours and programme-use metrics. RESULTS: Engagement was higher for high intensity participants for physical activity (adjusted group difference in change at 24 weeks = 3.4, CI95% = 1.9-4.9, p < .001) and nutrition (adjusted difference = 2.9, CI95% = 1.2-4.6, p = .001). No change was observed in health behaviours. Sixty two percent of participants completed 6 or more of the 12 weekly remote individualized health coaching sessions. Nine (39%) low intensity and 12 (41%) high intensity participants completed the final follow-up. CONCLUSIONS: Personalized health coaching for youth with psychosis is feasible and may have sustained benefits. However, retention with this population for 12 weeks is challenging.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".