Reflections of Foster Youth Engaging in the Co-Design of Digital Mental Health Technology: Duoethnography Study
Notice bibliographique
Résumé
BACKGROUND: Current research on digital applications to support the mental health and well-being of foster youth is limited to theoretical applications for transition-aged foster youth and support platforms developed without intentional input from foster youth themselves. Centering the lived expertise of foster youth in digital solutions is crucial to dismantling barriers to care, leading to an increase in service access and improving mental health outcomes. Co-design centers the intended end users during the design process, creating a direct relationship between potential users and developers. This methodology holds promise for creating tools centered on foster youth, yet little is known about the co-design experience for foster youth. Understanding foster youth's experience with co-design is crucial to identifying best practices, knowledge of which is currently limited. OBJECTIVE: The aim of this paper is to reflect on the experiences of 4 foster youth involved in the co-design of FostrSpace, a mobile app designed through a collaboration among foster youth in the San Francisco Bay Area; clinicians and academics from the Juvenile Justice Behavioral Health research team at the University of California, San Francisco; and Chorus Innovations, a rapid technology development platform specializing in participatory design practices. Key recommendations for co-designing with foster youth were generated with reference to these reflections. METHODS: A duoethnography study was conducted over a 1-month period with the 4 transition-aged former foster youth co-designers of FostrSpace via written reflections and a single in-person roundtable discussion. Reflections were coded and analyzed via reflexive thematic analysis. RESULTS: In total, 4 main themes were identified from coding of the duoethnography reflections: power and control, resource navigation, building community and safe spaces, and identity. Themes of power and control and resource navigation highlighted the challenges FostrSpace co-designers experienced trying to access basic needs, support from caregivers, and mental health resources as foster youth and former foster youth. Discussions pertaining to building community and safe spaces highlighted the positive effect of foster youth communities on co-designers, and discussions related to identity revealed the complexities associated with understanding and embracing foster youth identity. CONCLUSIONS: This duoethnography study highlights the importance of centering the lived expertise of co-designers throughout the app development process. As the digital health field increasingly shifts toward using co-design methods to develop digital mental health technologies for underserved youth populations, we offer recommendations for researchers seeking to ethically and effectively engage youth co-designers. Actively reflecting throughout the co-design process, finding creative ways to engage in power-sharing practices to build community, and ensuring mutual benefit among co-designers are some of the recommended core components to address when co-designing behavioral health technologies for youth.
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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 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,016 | 0,010 |
| Communication savante | 0,007 | 0,004 |
| Science ouverte | 0,002 | 0,013 |
| Intégrité de la recherche | 0,004 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».