Promoting mental health and wellbeing among post-secondary students with the JoyPop™ app: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Technology use may be one strategy to promote mental health and wellbeing among young adults in post-secondary education settings experiencing increasing distress and mental health difficulties. The JoyPop™ app is mobile mental health tool with a growing evidence base. The objectives of this research are to (1) evaluate the effectiveness of the JoyPop™ app in improving emotion regulation skills (primary outcome), as well as mental health, wellbeing, and resilience (secondary outcomes); (2) evaluate sustained app use once users are no longer reminded and determine whether sustained use is associated with maintained improvements in primary and secondary outcomes; (3) determine whether those in the intervention condition have lower mental health service usage and associated costs compared to those in the control condition; and (4) assess users' perspectives on the quality of the JoyPop™ app. METHODS: A pragmatic, parallel arm randomized controlled trial will be used. Participants will be randomly allocated using stratified block randomization in a 1:1 ratio to the intervention (JoyPop™) or control (no intervention) condition. Participants allocated to the intervention condition will be asked to use the JoyPop™ app at least twice daily for 4 weeks. Participants will complete outcome measures at four assessment time-points (first [baseline], second [after 2 weeks], third [after 4 weeks], fourth [after 8 weeks; follow-up]). Participants in the control condition will be offered access to the app after the fourth assessment time-point. DISCUSSION: Results will determine the effectiveness of the JoyPop™ app for promoting mental health and wellbeing among post-secondary students. If effective, this may encourage more widespread adoption of the JoyPop™ app by post-secondary institutions as part of their response to student mental health needs. TRIAL REGISTRATION: ClinicalTrials.gov NCT06154369 . Registered on November 23, 2023.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
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 | 0.052 | 0.051 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.008 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.095 | 0.017 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".