A Cyberbullying Media-Based Prevention Intervention for Adolescents on Instagram: Pilot Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Between 15% and 70% of adolescents report experiencing cybervictimization. Cybervictimization is associated with multiple negative consequences, including depressed mood. Few validated, easily disseminated interventions exist to prevent cybervictimization and its consequences. With over 97% of adolescents using social media (such as YouTube, Facebook, Instagram, or Snapchat), recruiting and delivering a prevention intervention through social media and apps may improve accessibility of prevention tools for at-risk youth. OBJECTIVE: This study aims to evaluate the feasibility and acceptability of and obtain preliminary outcome data on IMPACT (Intervention Media to Prevent Adolescent Cyber-Conflict Through Technology), a brief, remote app-based intervention to prevent and reduce the effect of cyberbullying. METHODS: From January 30, 2020, to May 3, 2020, a national sample of 80 adolescents with a history of past-year cybervictimization was recruited through Instagram for a randomized control trial of IMPACT, a brief, remote research assistant-led intervention and a fully automated app-based program, versus enhanced web-based resources (control). Feasibility and acceptability were measured by consent, daily use, and validated surveys. Although not powered for efficacy, outcomes (victimization, bystander self-efficacy, and well-being) were measured using validated measures at 8 and 16 weeks and evaluated using a series of longitudinal mixed models. RESULTS: Regarding feasibility, 24.5% (121/494) of eligible participants provided contact information; of these, 69.4% (84/121) completed full enrollment procedures. Of the participants enrolled, 45% (36/80) were randomized into the IMPACT intervention and 55% (44/80) into the enhanced web-based resources groups. All participants randomized to the intervention condition completed the remote intervention session, and 89% (77/80) of the daily prompts were answered. The retention rate was 99% (79/80) at 8 weeks and 96% (77/80) at 16 weeks for all participants. Regarding acceptability, 100% (36/36) of the intervention participants were at least moderately satisfied with IMPACT overall, and 92% (33/36) of the participants were at least moderately satisfied with the app. At both 8 and 16 weeks, well-being was significantly higher (β=1.17, SE 0.87, P=.02 at 8 weeks and β=3.24, SE 0.95, P<.001 at 16 weeks) and psychological stress was lower (β=-.66, SE 0.08, P=.04 at 8 weeks and β=-.89, SE 0.09, P<.001 at 16 weeks) among IMPACT users than among control group users. Participants in the intervention group attempted significantly more bystander interventions than those in the control group at 8 weeks (β=.82, SE 0.42; P=.02). CONCLUSIONS: This remote app-based intervention for victims of cyberbullying was feasible and acceptable, increased overall well-being and bystander interventions, and decreased psychological stress. Our findings are especially noteworthy given that the trial took place during the COVID-19 pandemic. The use of Instagram to recruit adolescents can be a successful strategy for identifying and intervening with those at the highest risk of cybervictimization. TRIAL REGISTRATION: ClinicalTrials.gov NCT04259216; http://clinicaltrials.gov/ct2/show/NCT04259216.
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 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) | 0,001 | 0,001 |
| 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) | 0,001 | 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 ».