<p>Adolescent problematic gaming may be better understood by integrating what youth play with why they play. Using the 2023 Taiwan Communication Survey Youth Wave (<i>N</i> = 1171; ages 12–18), we estimated a joint latent class model on 16 game genres and 11 gaming motivations, identifying four gamer profiles—Competitive–Social (35.8%), Low-Involvement (29.0%), Omni–Core (11.9%), and Creative–Exploration (11.4%)—plus Non-Players (11.9%). Gender and personality predicted profile membership: females were less likely than males to be classified into gamer profiles rather than the Non-Player group (ORs = 0.08–0.50), higher Conscientiousness predicted lower odds of gamer-profile membership (OR = 0.57), and lower Agreeableness was uniquely associated with Omni–Core membership (OR = 0.60). Among gamers (<i>n</i> = 1032), profiles differed in problematic-gaming scores after adjusting for gender, age, stratum, Big Five traits, and weekly gaming hours (<i>F</i>(3, 1021) = 61.42, partial <i>η</i><sup>2</sup> = 0.153): adjusted means were highest for Omni–Core (3.40), followed by Creative–Exploration (3.16) and Competitive–Social (3.04), with Low-Involvement lowest (2.44). Weekly hours independently predicted greater problematic gaming (<i>B</i> = 0.011, <i>p</i> &lt; 0.001), and the hours × profile interaction indicated steeper exposure-to-risk slopes for Competitive–Social and Creative–Exploration. Findings support profile-based screening and prevention beyond screen time alone in school and primary-care programs worldwide.</p>

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Adolescent Gaming Profiles and Problematic Gaming Symptoms: A Joint Genre–Motivation Latent Class Analysis

  • Rong-Kou Liu

摘要

Adolescent problematic gaming may be better understood by integrating what youth play with why they play. Using the 2023 Taiwan Communication Survey Youth Wave (N = 1171; ages 12–18), we estimated a joint latent class model on 16 game genres and 11 gaming motivations, identifying four gamer profiles—Competitive–Social (35.8%), Low-Involvement (29.0%), Omni–Core (11.9%), and Creative–Exploration (11.4%)—plus Non-Players (11.9%). Gender and personality predicted profile membership: females were less likely than males to be classified into gamer profiles rather than the Non-Player group (ORs = 0.08–0.50), higher Conscientiousness predicted lower odds of gamer-profile membership (OR = 0.57), and lower Agreeableness was uniquely associated with Omni–Core membership (OR = 0.60). Among gamers (n = 1032), profiles differed in problematic-gaming scores after adjusting for gender, age, stratum, Big Five traits, and weekly gaming hours (F(3, 1021) = 61.42, partial η2 = 0.153): adjusted means were highest for Omni–Core (3.40), followed by Creative–Exploration (3.16) and Competitive–Social (3.04), with Low-Involvement lowest (2.44). Weekly hours independently predicted greater problematic gaming (B = 0.011, p < 0.001), and the hours × profile interaction indicated steeper exposure-to-risk slopes for Competitive–Social and Creative–Exploration. Findings support profile-based screening and prevention beyond screen time alone in school and primary-care programs worldwide.