A Brief, Affordable, Broad-Access Transdiagnostic Intervention (Project RE-THINK) for Adolescents: Quasi-Experimental Study
Notice bibliographique
Résumé
Background: Adolescence is a crucial developmental period characterized by elevated stress and significant mental health challenges, including depression and anxiety. With barriers, such as stigma, accessibility, and cost hindering effective treatment, leveraging school systems for mental health interventions offers a strategic advantage due to their reach and potential for scalability. Objective: This study aimed to investigate the immediate impact of "Project RE-THINK," a single-session, digital thought record intervention delivered in a school setting, on negative cognitions and overall emotional valence among adolescents. Methods: Project RE-THINK helps adolescents to identify, examine, and challenge negative cognitions to improve their mental health, as demonstrated through changes in negative cognition and overall emotional valence. Adolescents (N=1052) in grades 10-12 enrolled in high school during the 2023-2024 school year completed the digital thought record intervention activity. Using a quasi-experimental pre/post design, participants read through an example thought record and completed their own thought record, which involved identifying and describing a recent upsetting situation, answering a series of questions to challenge their negative cognition, and learning and using emotion regulation skills regarding the upsetting situation. Measures of pre- and postintervention overall emotional valence and negative cognition were collected to determine the intervention effect on participants' mental health. Results: Descriptive statistics confirmed that smaller proportions of adolescents endorsed feeling negative emotions, such as anger, shame, anxiety, disgust, guilt, sadness, and fear, after the intervention. Paired samples t tests showed that adolescents experienced a significant reduction in their belief in their negative cognition from pre- to postintervention (t1051=27.71; P<.001; d=0.85, 95% CI 0.78-0.93), which demonstrates that the intervention helped them challenge their negative thoughts about their upsetting situation, as well as significant improvements to their overall emotional valence (t1051=-31.85; P<.001; d=-0.98, 95% CI -1.06 to -0.91), which demonstrates that the intervention helped them feel better about their upsetting situation. Findings also showed a significant correlation between change in negative cognition and change in overall emotional valence (r=0.25; P<.001), supporting our hypothesis that reducing the strength of belief in negative cognitions can help improve one's emotions. Finally, analysis of covariance (ANCOVAs) confirmed that there were no significant differences in intervention efficacy by gender, race and ethnicity, or socioeconomic status, suggesting broad intervention efficacy across adolescents from different backgrounds and experiences. Conclusions: Project RE-THINK effectively improved both cognitive and emotional outcomes among adolescents, demonstrating its potential as a scalable, low-cost intervention within school settings. Future studies should explore the longitudinal effects and potential integration of such interventions into regular school curricula to help adolescents learn effective emotions and coping skills as well as to help protect and sustain adolescent mental health.
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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 | 0,005 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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 ».