Evaluation of a Healthy Relationship Smartphone App With Indigenous Young People: Protocol for a Co-designed Stepped Wedge Randomized Trial
Bibliographic record
Abstract
BACKGROUND: We co-designed a smartphone app, Harmonised, with taitamariki (young people aged 13-17 years) to promote healthy intimate partner relationships. The app also provides a pathway for friends and family, or whānau (indigenous Māori extended family networks), to learn how to offer better support to taitamariki. OBJECTIVE: The aim of our taitamariki- and Māori-centered study is to evaluate the implementation of the app in secondary schools. The study tests the effectiveness of the app in promoting taitamariki partner relationship self-efficacy (primary outcome). METHODS: We co-designed a pragmatic, randomized, stepped wedge trial (retrospectively registered on September 12, 2019) for 8 Aotearoa, New Zealand, secondary schools (years 9 through 13). The schools were randomly assigned to implement the app in 1 of the 2 school terms. A well-established evaluation framework (RE-AIM [Reach, Effectiveness, Adoption, Implementation, Maintenance]) guided the selection of mixed data collection methods. Our target sample size is 600 taitamariki enrolled across the 8 schools. Taitamariki will participate by completing 5 web-based surveys over a 15-month trial period. Taitamariki partner relationship self-efficacy (primary outcome) and well-being, general health, cybersafety management, and connectedness (secondary outcomes) will be assessed with each survey. The general effectiveness hypotheses will be tested by using a linear mixed model with nested participant, year-group, and school random effects. The primary analysis will also include testing effectiveness in the Māori subgroup. RESULTS: The study was funded by the New Zealand Ministry of Business, Innovation, and Employment in October 2015 and approved by the Auckland University of Technology Ethics Committee on May 3, 2017 (application number: 17/71). CONCLUSIONS: This study will generate robust evidence evaluating the impact of introducing a healthy relationship app in secondary schools on taitamariki partner relationship self-efficacy, well-being, general health, cybersafety management, and connectedness. This taitamariki- and indigenous Māori-centered research fills an important gap in developing and testing strengths-based mobile health interventions in secondary schools. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12619001262190; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377584. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/24792.
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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 | 0.051 | 0.050 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.061 | 0.012 |
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".