Application of Positive Psychology in Digital Interventions for Children, Adolescents, and Young Adults: Systematic Review and Meta-Analysis of Controlled Trials
Notice bibliographique
Résumé
BACKGROUND: The rising prevalence of mental health issues in children, adolescents, and young adults has become an escalating public health issue, impacting approximately 10%-20% of young people on a global scale. Positive psychology interventions (PPIs) can act as powerful mental health promotion tools to reach wide-ranging audiences that might otherwise be challenging to access. This increased access would enable prevention of mental disorders and promotion of widespread well-being by enhancing self-efficacy, thereby supporting the achievement of tangible objectives. OBJECTIVE: We aimed to conduct a comprehensive synthesis of all randomized controlled trials and controlled trials involving children, adolescents, and young adults, encompassing both clinical and nonclinical populations, to comprehensively evaluate the effectiveness of digital PPIs in this age group. METHODS: After a literature search in 9 electronic databases until January 12, 2023, and gray literature until April 2023, we carried out a systematic review of 35 articles, of which 18 (51%) provided data for the meta-analysis. We included randomized controlled trials and controlled trials mainly based on web-based, digital, or smartphone-based interventions using a positive psychology framework as the main component. Studies included participants with a mean age of <35 years. Outcomes of PPIs were classified into indicators of well-being (compassion, life satisfaction, optimism, happiness, resilience, emotion regulation and emotion awareness, hope, mindfulness, purpose, quality of life, gratitude, empathy, forgiveness, motivation, and kindness) and ill-being (depression, anxiety, stress, loneliness, and burnout). PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were used for the selection of studies and data extraction. Quality assessment was performed following the CONSORT (Consolidated Standards of Reporting Trials) guidelines. RESULTS: For well-being outcomes, meta-analytic results showed that PPIs augmented the feeling of purpose, gratitude, and hope (Hedges g=0.555), compassion (Hedges g=0.447), positive coping behaviors (Hedges g=0.421), body image-related outcomes (Hedges g=0.238), and positive mindset predisposition (Hedges g=0.304). For ill-being outcomes, PPIs reduced cognitive biases (Hedges g=-0.637), negative emotions and mood (Hedges g=-0.369), and stress levels (Hedges g=-0.342). Of note, larger effect sizes were found when a waiting list control group was considered versus a digital control group. A funnel plot showed no publication bias. Meta-regression analyses showed that PPIs tended to show a larger effect size on well-being outcomes in studies including young adults, whereas no specific effect was found for ill-being outcomes. CONCLUSIONS: Revised evidence suggests that PPIs benefit young people's well-being and mitigate ill-being symptoms. Digital platforms offer a unique way to address their mental health challenges, although not without limitations. Future research should explore how they work for the needs of the young population and further examine what specific PPIs or combination of interventions is most beneficial with respect to other digital control groups. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42023420092; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=420092.
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 | 0,017 | 0,054 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,020 | 0,026 |
| Bibliométrie | 0,007 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».