Co-Designing a Digital Platform to Support a Culturally Adapted Family Intervention (CaFI:Digital) for Psychosis Among People of Sub-Saharan African and Caribbean Descent: Agile Co-Design Approach
Notice bibliographique
Résumé
Background: People of sub-Saharan African and Caribbean descent are significantly more likely to be diagnosed with psychotic disorders than other ethnic groups in the United Kingdom. The National Institute for Health and Care Excellence in the United Kingdom recommends family therapy as a clinically effective treatment for the management of psychosis. The National Institute for Health and Care Excellence also recommends that family interventions should be culturally informed to meet the needs of an increasingly ethnically diverse population. People from minoritized backgrounds are rarely offered family therapy; however, the rise in digital mental health worldwide offers unique opportunities to support culturally informed approaches at scale and at a low cost. Objective: The overarching aim of culturally adapted family intervention (CaFI):Digital was to help address inequalities in the provision of mental health care for people of sub-Saharan African and Caribbean descent, including those of Mixed heritage. A digital platform, CaFI:Digital, was built to support delivery of a CaFI. The purpose of developing CaFI:Digital was to provide an accessible, user-friendly, and engaging website for service users, their families, and therapists as an alternative or adjunct to in-person therapy. Methods: We used an iterative Agile co-design approach to develop a user-friendly and inclusive website. Co-design workshops (n=2), semistructured interviews (n=2), and collaborative research team meetings (n=3) were used to capture and prioritize end-user feedback on the clinician- and service-user-facing components of the platform. The software was developed using Agile sprints, with each sprint lasting 3 weeks, allowing feedback to be integrated rapidly and revised software prototypes to be shared with end users for review, revision, and approval. Results: Key software requirements, such as accessibility and diverse content, were identified in the co-design activities and were implemented to maximize accessibility and usability of the website. Following software development, we successfully beta-tested the software with our target end user population of service users and therapists to ensure it was defect-free and ready for use. Conclusions: A digital platform to support delivery of CaFI for psychosis was rapidly developed through a series of co-design activities. To our knowledge, this is the first bespoke digital therapy platform that has been co-designed with and for people of sub-Saharan African and Caribbean descent who experience psychosis. This is important given the disproportionate rates of diagnosis and lack of access to psychological therapies experienced by this population.
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 | 0,018 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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 ».