A Trauma Support App for Young People: Co-design and Usability Study
Bibliographic record
Abstract
BACKGROUND: One of the most common reasons young people with mental health issues, such as posttraumatic stress disorder, do not seek help is stigma, which digital support tools could help address. However, there is a lack of trauma support apps specifically designed for young people. Involving the target group in such projects has been shown to produce more engaging and effective results. OBJECTIVE: This study aimed to apply a child rights-based participatory approach to develop a trauma support app with young people. METHODS: Seven young people (aged 14-19 years; 3 males and 4 females) with experiences of trauma were recruited as coresearchers. A child rights-based framework guided the working process. The app was developed through a series of Design Studio workshops and home assignments, using the manualized intervention Teaching Recovery Techniques as the foundation for its content. The coresearchers were trained in research methodology and conducted usability testing with other young people (n=11) using the think-aloud method, the System Usability Scale (SUS), and qualitative follow-up questions. RESULTS: A functional app prototype was developed using a no-code platform, incorporating various trauma symptom management techniques. These techniques covered psychoeducation, normalization, relaxation, and cognitive shifting, presented in multiple formats, including text, audio, and video. The contributions of the coresearchers to the design can be categorized into 3 areas: mechanics (rules and interactions shaping the app's structure), dynamics (user-visible elements, such as the outcome when pressing a button), and aesthetics (the emotional responses the app aimed to evoke in users during interaction). Beyond influencing basic aesthetics, the coresearchers placed significant emphasis on user experience and the emotional responses the app could evoke. SUS scores ranged from 67.5 to 97.5, with the vast majority exceeding 77.5, indicating good usability. However, usability testing revealed several issues, generally of lower severity. For instance, video content required improvements, such as reducing light flickering in some recordings and adding rewind and subtitle selection options. Notably, the feature for listening to others' stories was removed to minimize emotional burden, shifting the focus to text formats with more context. CONCLUSIONS: Young people who have experienced trauma can actively participate in the cocreation of a mental health intervention, offering valuable insights into the needs and preferences of their peers. Applying a child rights-based framework to their involvement in a research project supported the fulfillment of the Convention on the Rights of the Child Article 12.
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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 | 0.017 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".