Co-Designed Online Training Program for Worry Management: The Role of Young People With Lived Experience of Worry in Program Development
Bibliographic record
Abstract
Background: Many young people report high levels of worry, highlighting the need for interventions that teach strategies to help them shift focus away from worry. To maximize uptake by this population, interventions should be brief and accessible; to maximize dissemination, they should have potential for delivery at scale. We produced a multisession, online training program, Shift Focus, co-designed with young people with lived experience of worry. The online training program was accessed via a mobile app. In this paper, we describe how Lived Experience Advisory Panel (LEAP) members were involved in each stage of the process of developing the Shift Focus online training program, from refining session content through to designing and testing the online training program prototype. Objective: We aimed to engage with young people with lived experience of worry, to help refine, further develop, and tailor a new online training program designed to help shift focus away from worry. Methods: We recruited LEAP members (aged 16-25 y) with lived experience of worry from diverse backgrounds across the United Kingdom. We used a highly iterative participatory design process, such that LEAP members provided input during all 4 phases of program development: refining and further developing session content, piloting sessions, developing user experience design, and testing the online training program prototype. Results: Feedback from LEAP members during each phase of the online platform development informed key decisions regarding the platform content, functionality, and the interface design to ensure it suited our target population. In phase 1, we learned that the platform needed to be simple and aesthetically pleasing, personalized to individual needs and preferences, accessible to all, track progress, and provide individuals with a sense of community with others with similar lived experiences. In phase 2, we learned that the platform also needed to provide further guidance on how to apply the Shift Focus techniques to daily life, using personalized reminder settings. In phase 3, we additionally learned that ease of navigation and interactivity were key to maintaining user engagement. The importance of program tracking was reiterated, as well as the need for accessibility settings to support all learning styles. In phase 4, we identified that technical problems with the online platform were a barrier to engagement. The inclusion of future iterations (eg, reward systems) to help promote engagement was suggested by LEAP members in multiple phases. Conclusions: LEAP members brought unique expertise and made key contributions to the development of the Shift Focus online training program and were highly valued members of the team. A highly iterative participatory design process enabled continuous feedback from LEAP members throughout, ensuring that their input was meaningful and that their key messages and ideas were incorporated into the final program.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".