Cognitive Mechanisms Between Psychosocial Resources and the Behavioral Intention of Professional Help-Seeking for Internet Gaming Disorder Among Chinese Adolescent Gamers: Cross-Sectional Mediation Study
Notice bibliographique
Résumé
Background: Internet gaming disorder (IGD) is a global public health concern for adolescents due to its potential severe negative consequences. Professional help-seeking is important for early screening, diagnosis, and treatment of IGD. However, research on the factors associated with professional help-seeking for IGD as well as relevant mediation mechanisms among adolescents is limited. Objective: Based on the stress coping theory, the conservation of resource theory, and behavioral change theories, this study investigated the prevalence and factors influencing the behavioral intention of professional help-seeking for internet gaming disorder (BI-PHSIGD). The research also explored the underlying mechanisms, including psychosocial resources like resilience and social support, perceived resource loss due to reduced gaming time, and self-efficacy, in professional help-seeking among adolescent internet gamers. Methods: A cross-sectional survey was conducted among secondary school students who were internet gamers in 2 Chinese cities from October 2019 to January 2020. Data from the full sample (N=1526) and a subsample of 256 IGD cases (according to the 9-item DSM-5 [Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition] IGD Checklist) were analyzed. Multivariate logistic regression analysis was conducted to examine the factors of BI-PHSIGD, while structural equation modeling was performed to test the proposed mediation mechanisms. Results: The prevalence of BI-PHSIGD was 54.3% (829/1526) in the full sample and 40.6% (104/256) in the IGD subsample (vs 708/1239, 57.1% among non-IGD cases). In the full sample, psychosocial resources of resilience (adjusted odds ratio [aOR] 1.03, 95% CI 1.02-1.05) and social support (aOR 1.03, 95% CI 1.02-1.04) as well as self-efficacy in professional help-seeking (aOR 1.64, 95% CI 1.49-1.81) were positively associated with BI-PHSIGD, while perceived resource loss due to reduced gaming time was negatively associated with BI-PHSIGD (aOR 0.97, 95% CI 0.96-0.98); the positive association between psychosocial resources and BI-PHSIGD was fully mediated via 2 single-mediator indirect paths (via self-efficacy in professional help-seeking alone: effect size=53.4%; indirect effect/total effect=0.10/0.19 and via perceived resource loss due to reduced gaming time alone: effect size=17.8%; indirect effect/total effect=0.03/0.19) and one 2-mediator serial indirect path (first via perceived resource loss due to reduced gaming time then via self-efficacy in professional help-seeking: effect size=4.7%; indirect effect/total effect=0.009/0.19). In the IGD subgroup, a full mediation via self-efficacy in professional help-seeking alone but not the other 2 indirect paths was statistically significant. Conclusions: Many adolescent internet gamers, especially those with IGD, were unwilling to seek professional help; as a result, early treatment is often difficult to achieve. To increase BI-PHSIGD, enhancing psychosocial resources such as resilience and social support, perceived resource loss due to reduced gaming time, and self-efficacy in professional help-seeking may be effective. Future longitudinal and intervention studies are needed to confirm and extend the findings.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».