Problematic Social Media Use Among Italian Midadolescents: Protocol and Rationale of the SMART Project
Notice bibliographique
Résumé
BACKGROUND: Social media (SM) use constitutes a large portion of midadolescents' daily lives as a way of peer interaction. A significant percentage of adolescents experience intense or problematic social media use (PSMU), an etiologically complex behavior potentially associated with psychological distress. To date, studies longitudinally testing for risk or protective factors of PSMU, and collecting qualitative data are still scarce among midadolescents. Self-help interventions specifically targeting PSMU in this population and involving midadolescents in co-creation are needed. OBJECTIVE: The 2-year SMART multicenter project aims to (1) advance knowledge on PSMU; (2) co-design an unguided self-help app for promoting awareness and functional SM use; and (3) test feasibility and provide preliminary findings on its effectiveness to further improve and adapt the app. METHODS: The SMART project is organized in 3 phases: phase 1 will focus on knowledge advancement on PSMU and its risk and protective factors using a longitudinal design; phase 2 will explore adolescents perspectives using qualitative approach and will co-design an unguided self-help app for reducing PSMU, which will be evaluated and adapted in phase 3. Around 1500 midadolescents (aged 14-18 years) will be recruited in northern, central, and southern Italy to investigate the potential intra- and interpersonal psychological risk and protective factors for PSMU and define specific PSMU profiles and test for its association with psychological distress. Subjective (self-report) PSMU's psychosocial risk or protective factors will be assessed at 3 different time points and Ecological Momentary Assessment (EMA) will be used. Moreover, focus groups will be performed in a subsample of midadolescents to collect the adolescents' unique point of view on PSMU and experiences with SM. Those previous results will inform the self-help app, which will be co-designed through working groups with adolescents. Subsequently, the SMART app will be deployed and adapted, after testing its feasibility and potential effectiveness in a pilot study. RESULTS: The project is funded by the Italian Ministry of University and Research as part of a national grant (PRIN, "Progetti di Rilevante Interesse Nazionale"). The research team received an official notice of research funding approval in July 2023 (Project Code 2022LC4FT7). The project was preregistered on Open Science Framework, while the ethics approval was obtained in November 2023. We started the enrollments in December 2023, with the final follow-up data to be collected within May 2025. CONCLUSIONS: The innovative aspects of the SMART project will deepen the conceptualization of PSMU and of its biopsychosocial antecedents among midadolescents, with relevant scientific, technological, and socioeconomic impacts. The advancement of knowledge and the developed self-help app for PSMU will timely respond to midadolescents' increased loneliness and psychological burden due to COVID-19 pandemic and humanitarian crisis. TRIAL REGISTRATION: OSF Registries; https://osf.io/2ucnk/. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58739.
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 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,033 | 0,009 |
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 ».