Alimenté par : Claudia (ADFI Alsace)
Cet outil s'appuie sur PubMind
Un accès direct à la littérature scientifique via la base PubMed permettant de faciliter la veille sur les enjeux complexes de la santé mentale et du fait religieux : de la neuroscience des croyances à l'étude des abus spirituels, en passant par la prise en charge des traumatismes et des processus de déconversion.
Dernière synchronisation le 06/06/2026
JMIR Serious Games . 2026;14 :e81407
BACKGROUND: Gaming disorder (GD) is an emerging issue that leads to significant impairment, yet existing tools for measuring withdrawal symptoms in GD are limited and often fail to capture its multidimensional nature. Most current measures rely on single-item assessments or adapted tools from substance use disorders, overlooking cognitive, behavioral, and physiological components. A comprehensive, multidimensional questionnaire is needed to more accurately assess withdrawal in GD, aiding in early detection and intervention.OBJECTIVE: The objective of this study was to develop and psychometrically validate a comprehensive measurement tool, the Gaming Withdrawal Symptoms Questionnaire (GWSQ), capturing the multidimensional nature of withdrawal symptoms in GD, including affective, cognitive, behavioral, and physiological components.METHODS: A multistage psychometric approach was used, starting with item generation from a scoping literature review. Exploratory factor analysis and confirmatory factor analysis were conducted to refine the questionnaire. Reliability and validity were assessed using 2 cross-sectional studies. Data were collected anonymously via an online survey platform. Participants were recruited from gaming-related platforms and social media (eg, Discord, Reddit, and Facebook) and restricted to actively engaged adult gamers who passed attention check questions to ensure data quality.RESULTS: Study 1 involved 480 adults (mean age 23, SD 4.96 years; n=327, 68.1% male). Study 2 included 565 adults (mean age 25, SD 5.55 years; n=245, 43% male). Exploratory factor analysis revealed a 3-factor model of withdrawal symptoms: (1) motivational and cognitive symptoms, (2) affective symptoms, and (3) physical symptoms, explaining 54% of the variance. Confirmatory factor analysis confirmed adequate model fit (χ=887.8; P