High School Students’ Preferences and Design Recommendations for a Mobile Phone–Based Intervention to Improve Psychological Well-Being: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Young adults' mental health is characterized by relatively high rates of stress and anxiety and low levels of help-seeking behavior. Mobile health (mHealth) interventions could offer a cost-effective and readily available avenue to provide personalized support to young adults. More research needs to be directed at the development of mHealth interventions targeting youths specifically, as well as at determining how to reach young people and how to effectively intervene to improve psychological well-being. OBJECTIVE: The objective was to gather perceptions from high school students to inform the development of a prototype mHealth intervention aiming to promote psychological well-being. METHODS: A mixed methods design was used to (1) investigate high school students' perceptions about stress and its consequences in daily life, as well as their ability to cope with stress, and (2) explore their preferences and design recommendations for an mHealth intervention to improve psychological well-being. Students from two high schools in the southeast of Sweden were invited to take part in the study. Recruitment of high school students was completed over a 6-week period, between October 25 and December 7, 2018. Recruitment entailed inviting students to complete a stress test (ie, screening and feedback) on their mobile phones. After completing the stress test, all participants were invited to complete a follow-up questionnaire and take part in telephone interviews. RESULTS: A total of 149 high school students completed the stress test, of which 68 completed the questionnaire. There were 67 free-text comments distributed across the items. The majority of participants (55/68, 81%) stated that they coped with stress better or in the same way after engaging in the stress test, due to time management, dialogue with others, and self-refection. A total of 4 out of 68 participants (6%)-3 female students (75%) and 1 male student (25%)-took part in telephone interviews. Three main themes were identified from the interview data: perceptions about stress, design features, and intervention features. CONCLUSIONS: Stress was described by the students as a condition caused by high demands set by oneself and the social environment that impacted their physical health, personal relationships, school performance, and emotional well-being. Participants claimed that mHealth interventions need to be clearly tailored to a young age group, be evidence based, and offer varied types of support, such as information about stress, exercises to help organize tasks, self-assessment, coping tools, and recommendations of other useful websites, literature, blogs, self-help books, or role models. Mobile phones seemed to be a feasible and acceptable platform for the delivery of an intervention.
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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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".