A Mobile App (MyPeer) Co-Designed With Immigrant Adolescents for Better Sexual and Reproductive Health: Usability Study
Bibliographic record
Abstract
BACKGROUND: Adolescents require comprehensive sexual and reproductive health (SRH) education to successfully transition from puberty into adulthood. However, they often experience barriers and challenges while trying to promote their SRH or access SRH services. Such challenges are amplified among youth from migrant backgrounds, who may further be constrained by societal stigmas and cultural taboos regarding SRH. Mobile health interventions have the potential to provide culturally relevant, accessible, and evidence-based SRH educational resources; however, few SRH mobile apps in Canada are co-designed with immigrant youth or meaningfully integrate their voices and lived experiences. OBJECTIVE: We aimed to co-design a culturally relevant and evidence-based mobile app with immigrant adolescents to provide accurate SRH resources. In this paper, we present the findings of the usability testing of our SRH mobile app-MyPeer. METHODS: Throughout our study, we used a community-based participatory research approach and implemented the principles of human-centered design to co-design our mobile app. For our usability study, we recruited immigrant adolescents and interest holders working with the target population. Adolescents participated in moderated focus group discussions (FGDs) and interest holders evaluated the app's quality using the standardized Mobile App Rating Scale (rating components on a scale of 1-5). All FGDs were audio-recorded and later analyzed to implement changes in the app. Mobile App Rating Scale (MARS) scores and responses were analyzed descriptively to evaluate the app's engagement, functionality, aesthetics, quality of information, and subjective app quality. RESULTS: Overall, 25 adolescents and 17 interest holders participated in this usability study. We analyzed the findings from the FGDs and categorized them into four categories: (1) navigation and interface, (2) SRH information quality and learning, (3) technical performance, and (4) accessibility and multimedia usability. Adolescents found the app visually appealing and the interface easy to navigate. They appreciated interactive features, such as quizzes, and the presentation of information through various media (eg, videos and infographics). However, they also identified technical issues, such as map glitches and navigation inconsistencies, and requested deeper content on SRH topics. The data from the MARS checklist completed by interest holders were analyzed descriptively. The app received the highest scores in the domains of functionality, with mean scores of 4.3 (performance and navigation); engagement, with mean scores of 3.7 (interest); and aesthetics, with mean scores of 4.1 (graphics) and 3.9 (visual appeal). The lowest rated items were customization, with a mean score of 2.5, and interactivity, with a mean score of 3.1. CONCLUSIONS: Our app-MyPeer-has promising usability and appeal for adolescents looking for SRH information. Incorporating feedback from youth and content experts helped identify both technical refinements and content requirements. Our findings support the app's potential as a scalable, youth-centered SRH digital tool and emphasize the value of participatory design in youth digital interventions.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".