A Digital Intervention for Adolescent Depression (MoodHwb): Mixed Methods Feasibility Evaluation
Notice bibliographique
Résumé
BACKGROUND: Treatment and prevention guidelines highlight the key role of health information and evidence-based psychosocial interventions for adolescent depression. Digital health technologies and psychoeducational interventions have been recommended to help engage young people and to provide accurate health information, enhance self-management skills, and promote social support. However, few digital psychoeducational interventions for adolescent depression have been robustly developed and evaluated in line with research guidance. OBJECTIVE: We aimed to evaluate the feasibility, acceptability, and potential impact of a theory-informed, co-designed digital intervention program, MoodHwb. METHODS: We used a mixed methods (quantitative and qualitative) approach to evaluate the program and the assessment process. Adolescents with or at elevated risk of depression and their parents and carers were recruited from mental health services, school counselors and nurses, and participants from a previous study. They completed a range of questionnaires before and after the program (related to the feasibility and acceptability of the program and evaluation process, and changes in mood, knowledge, attitudes, and behavior), and their Web usage was monitored. A subsample was also interviewed. A focus group was conducted with professionals from health, education, social, and youth services and charities. Interview and focus group transcripts were analyzed using thematic analysis with NVivo 10 (QSR International Pty Ltd). RESULTS: A total of 44 young people and 31 parents or carers were recruited, of which 36 (82%) young people and 21 (68%) parents or carers completed follow-up questionnaires. In all, 19 young people and 12 parents or carers were interviewed. Overall, 13 professionals from a range of disciplines participated in the focus group. The key themes from the interviews and groups related to the design features, sections and content, and integration and context of the program in the young person's life. Overall, the participants found the intervention engaging, clear, user-friendly, and comprehensive, and stated that it could be integrated into existing services. Young people found the "Self help" section and "Mood monitor" particularly helpful. The findings provided initial support for the intervention program theory, for example, depression literacy improved after using the intervention (difference in mean literacy score: 1.7, 95% CI 0.8 to 2.6; P<.001 for young people; 1.3, 95% CI 0.4 to 2.2; P=.006 for parents and carers). CONCLUSIONS: Findings from this early stage evaluation suggest that MoodHwb and the assessment process were feasible and acceptable, and that the intervention has the potential to be helpful for young people, families and carers as an early intervention program in health, education, social, and youth services and charities. A randomized controlled trial is needed to further evaluate the digital program.
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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 | 0,002 | 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 | 0,000 | 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 ».