Co-Designed Online Training Program for Worry Management: The Role of Young People With Lived Experience of Worry in Program Development
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».