Desired Features of a Digital Technology Tool for Self-Management of Well-Being in a Nonclinical Sample of Young People: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Adaptive coping behaviors can improve well-being for young people experiencing life stressors, while maladaptive coping can increase vulnerability to mental health problems in youth and into adulthood. Young people could potentially benefit from the use of digital technology tools to enhance their coping skills and overcome barriers in help-seeking behaviors. However, little is known about the desired digital technology use for self-management of well-being among young people in the general population. OBJECTIVE: This is a small, qualitative study aimed at exploring what young people desire from digital technology tools for the self-management of their well-being. METHODS: Young people aged 12-18 years were recruited from the general community to take part in semistructured interviews. Recorded data from the interviews were transcribed and analyzed using inductive thematic analysis. RESULTS: In total, 14 participants were recruited and completed the study, with a mean age of 14.6 years (female n=3). None of the participants reported using any digital tools specifically designed to manage well-being. However, as indicated through the emerged themes, young people used digital technology to reduce their stress levels and manage their mood, mainly through games, music, and videos. Overall, identified themes showed that young people were keen on using such tools and desired certain facets and features of an ideal tool for self-management of well-being. Themes related to these facets indicated what young people felt a tool should do to improve well-being, including being immersed in a stress-free environment, being uplifting, and that such a tool would direct them to resources based on their needs. The feature-based themes suggested that young people wanted the tool to be flexible and enable engagement with others while also being sensitive to privacy. CONCLUSIONS: The young people interviewed in this study did not report engaging with digital technology specialized to improving well-being but instead used media already accessed in their daily lives in order to self-manage their psychological states. As a result, the variety of coping strategies reported and digital tools used was limited to the resources that were already being used for recreational and social purposes. These findings contribute to the scarce research into young people's preferred use of digital technology tools for the self-management of their well-being. However, this was a small-scale study and the current participant sample is not representative of the general youth population. Therefore, the results are only tentative and warrant further investigation.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".