Refining the Universal, School-Based OurFutures Mental Health Program to Be Trauma Informed, Gender and Sexuality Diversity Affirmative, and Adherent to Proportionate Universalism: Mixed Methods Participatory Design Process
Notice bibliographique
Résumé
BACKGROUND: Mental disorders are the leading cause of disease burden among youth. Effective prevention of mental disorders during adolescence is a critical public health strategy to reduce both individual and societal harms. Schools are an important setting for prevention; however, existing universal school-based mental health interventions have shown null, and occasionally iatrogenic, effects in preventing symptoms of common disorders, such as depression and anxiety. OBJECTIVE: This study aims to report the adaptation process of an established, universal, school-based prevention program for depression and anxiety, OurFutures Mental Health. Using a 4-stage process; triangulating quantitative, qualitative, and evidence syntheses; and centering the voices of young people, the revised program is trauma-informed; lesbian, gay, bisexual, transgender, nonbinary, queer, questioning, and otherwise gender and sexuality diverse (LGBTQA+) affirmative; relevant to contemporary youth; and designed to tailor intervention dosage to those who need it most (proportionate universalism). METHODS: Program adaptation occurred from April 2022 to July 2023 and involved 4 stages. Stage 1 comprised mixed methods analysis of student evaluation data (n=762; mean age 13.5, SD 0.62 y), collected immediately after delivering the OurFutures Mental Health program in a previous trial. Stage 2 consisted of 3 focus groups with high school students (n=39); regular meetings with a purpose-built, 8-member LGBTQA+ youth advisory committee; and 2 individual semistructured, in-depth interviews with LGBTQA+ young people via Zoom (Zoom Video Communications) or WhatsApp (Meta) text message. Stage 3 involved a clinical psychologist providing an in-depth review of all program materials with the view of enhancing readability, improving utility, and normalizing emotions while retaining key cognitive behavioral therapy elements. Finally, stage 4 involved fortnightly consultations among researchers and clinicians on the intervention adaptation, drawing on the latest evidence from existing literature in school-based prevention interventions, trauma-informed practice, and adolescent mental health. RESULTS: Drawing on feedback from youth, clinical psychologists, and expert youth mental health researchers, sourced from stages 1 to 4, a series of adaptations were made to the storylines, characters, and delivery of therapeutic content contained in the weekly manualized program content, classroom activities, and weekly student and teacher lesson summaries. CONCLUSIONS: The updated OurFutures Mental Health program is a trauma-informed, LBGTQA+ affirmative program aligned with the principles of proportionate universalism. The program adaptation responds to recent mixed findings on universal school-based mental health prevention programs, which include null, small beneficial, and small iatrogenic effects. The efficacy of the refined OurFutures Mental Health program is currently being tested through a cluster randomized controlled trial with up to 1400 students in 14 schools across Australia. It is hoped that the refined program will advance the current stalemate in universal school-based prevention of common mental disorders and ultimately improve the mental health and well-being of young people in schools.
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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 | 0,091 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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 ».