Feasibility and Acceptability of the Aboriginal and Islander Mental Health Initiative for Youth App: Nonrandomized Pilot With First Nations Young People
Notice bibliographique
Résumé
BACKGROUND: Despite young First Nations Australians being typically healthy, happy, and connected to family and culture, high rates of emotional distress, suicide, and self-harm are also observed. Differing worldviews of service providers and First Nations young people regarding illness and treatment practices, language differences, culturally inappropriate service models, geographical remoteness, and stigma can all inhibit access to appropriate mental health support. Mental health treatments delivered digitally (digital mental health; dMH) offer flexible access to evidence-based, nonstigmatizing, low-cost treatment and early intervention on a broad scale. There is a rapidly growing use and acceptance of these technologies among young First Nations people. OBJECTIVE: The objective was to assess the feasibility, acceptability, and use of the newly developed Aboriginal and Islander Mental Health Initiative for Youth (AIMhi-Y) app and determine the feasibility of study procedures in preparation for future assessments of effectiveness. METHODS: This was a nonrandomized pre-post study using mixed methods. First Nations young people aged 12-25 years who provided consent (with parental consent where appropriate) and possessed the ability to navigate a simple app with basic English literacy were included. Researchers conducted one face-to-face 20-minute session with participants to introduce and orient them to the AIMhi-Y app. The app integrates culturally adapted low-intensity cognitive behavioral therapy (CBT), psychoeducation, and mindfulness-based activities. Participants received supportive text messages weekly throughout the 4-week intervention period and completed assessments of psychological distress, depression, anxiety, substance misuse, help-seeking, service use, and parent-rated strengths and difficulties at baseline and 4 weeks. Qualitative interviews and rating scales were completed at 4 weeks to gain feedback on subjective experience, look and style, content, overall rating, check-ins, and involvement in the study. App use data were collected. RESULTS: Thirty young people (17 males and 13 females) aged between 12 and 18 (mean 14.0, SD 1.55) years were assessed at baseline and 4 weeks. Repeated measures 2-tailed t tests showed improvements in well-being measures that were statistically and clinically significant for psychological distress (Kessler Psychological Distress Scale, 10-item) and depressive symptoms (Patient Health Questionnaire, 2-item). Participants spent on average 37 minutes in the app. The app was rated positively, with mean ratings of 4 out of 5 points (on scales of 1-5). Participants reported that they found the app easy to use, culturally relevant, and useful. The feasibility of the study was demonstrated with a 62% recruitment rate, a 90% retention rate, and high study acceptability ratings. CONCLUSIONS: This study supports earlier research suggesting that dMH apps that are appropriately designed with and for the target populations are a feasible and acceptable means of lowering symptoms for mental health disorders among First Nations youth.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».