The Implementation of an mHealth Intervention (ReZone) for the Self-Management of Overwhelming Feelings Among Young People
Bibliographic record
Abstract
BACKGROUND: The association between mental health difficulties and academic attainment is well established. There is increasing research on mobile health (mHealth) interventions to provide support for the mental health and education of young people. However, nonadoption and inadequate implementation of mHealth interventions are prevalent barriers to such trials. OBJECTIVE: The aim of this study was to bridge this gap and examine the implementation of an mHealth intervention, ReZone, for young people in schools. METHODS: Preliminary data for 79 students collected as part of a larger trial were analyzed. We additionally conducted postimplementation consultations with teachers. RESULTS: ReZone was used 1043 times by 36 students in the intervention arm during the study period. Postimplementation teacher consultations provided data on implementation strategies, barriers, and facilitators. CONCLUSIONS: Implementation strategies, barriers, and facilitators for digital interventions need to be considered to limit nonadoption and inadequate implementation in larger trials. Important considerations involve tailoring the characteristics of the intervention to the requirements of the intended user group, the technology itself, and the organization in which it is implemented. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number: 13425994; http://www.isrctn.com/ISRCTN13425994.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".