A Social Media Group Cognitive Behavioral Therapy Intervention to Prevent Depression in Perinatal Youth: Stakeholder Interviews and Intervention Design
Notice bibliographique
Résumé
BACKGROUND: Adolescents and young adults aged <25 years (youth) are at a higher risk of perinatal depression than older adults, and they experience elevated barriers to in-person care. Digital platforms such as social media offer an accessible avenue to deliver group cognitive behavioral therapy (CBT) to perinatal youth. OBJECTIVE: We aim to develop the Interactive Maternal Group for Information and Emotional Support (IMAGINE) intervention, a facilitated social media group CBT intervention to prevent perinatal depression in youth in the United States, by adapting the Mothers and Babies (MB) course, an evidence-based in-person group CBT intervention. In this study, we report perspectives of youth and health care providers on perinatal youths' mental health needs and document how they informed IMAGINE design. METHODS: We conducted 21 semistructured in-depth individual interviews with 10 pregnant or postpartum youths aged 14-24 years and 6 health care workers. All interviews were recorded, transcribed, and analyzed using deductive and inductive approaches to characterize perceptions of challenges and facilitators of youth perinatal mental health. Using a human-centered design approach, stakeholder perspectives were incorporated into the IMAGINE design. We classified MB adaptations to develop IMAGINE according to the Framework for Modification and Adaptation, reporting the nature, timing, reason, and goal of the adaptations. RESULTS: Youth and health care workers described stigma associated with young pregnancy and parenting, social isolation, and lack of material resources as significant challenges to youth mental wellness. They identified nonjudgmental support, peer companionship, and access to step-by-step guidance as facilitators of youth mental wellness. They endorsed the use of a social media group to prevent perinatal depression and recommended that IMAGINE facilitate peer support, deliver content asynchronously to accommodate varied schedules, use a confidential platform, and facilitate the discussion of topics beyond the MB curriculum, such as navigating support resources or asking medical questions. IMAGINE was adapted from MB to accommodate stakeholder recommendations and facilitate the transition to web-based delivery. Content was tailored to be multimodal (text, images, and video), and the language was shortened and simplified. All content was designed for asynchronous engagement, and redundancy was added to accommodate intermittent access. The structure was loosened to allow the intervention facilitator to respond in real time to topics of interest for youth. A social media platform was selected that allows multiple conversation channels and conceals group member identity. All adaptations sought to preserve the fidelity of the MB core components. CONCLUSIONS: Our findings highlight the effect of stigmatization of young pregnancy and social determinants of health on youth perinatal mental health. Stakeholders supported the use of a social media group to create a supportive community and improve access to evidence-based depression prevention. This study demonstrates how a validated intervention can be tailored to this unique group.
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 | 0,010 | 0,007 |
| 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 | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».