OBJECTIVE To determine whether psychiatric and gaming pattern variables are associated with gaming disorder in a school-based sample. METHODS We analyzed data from the Brazilian High-Risk Cohort for Psychiatric Disorders, a community sample aged 10 to 18, using questionnaires on gaming use patterns. We applied the Gaming Addiction Scale to diagnose gaming disorder and the Development and Well-Being Behavior Assessment for other diagnoses. RESULTS Out of 407 subjects, 83 (20.4%) fulfilled the criteria for gaming disorder. More role-playing game players were diagnosed with gaming disorder that any other genre. Gaming disorder rates increased proportionally to the number of genres played. Playing online, being diagnosed with a mental disorder, and more hours of non-stop gaming were associated with higher rates of gaming disorder. When all variables (including age and gender) were considered in a logistic regression model, the number of genres played, the number of non-stop hours, the proportion of online games, and having a diagnosed mental disorder emerged as significant predictors of gaming disorder. CONCLUSION Each variable seems to add further risk of gaming disorder among children and adolescents. Monitoring the length of gaming sessions, the number and type of genres played, time spent gaming online, and behavior changes may help parents or guardians identify unhealthy patterns of gaming behavior.

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儿童和青少年游戏障碍的预测因素：一项基于学校的研究

目的 确定精神病学和游戏模式变量是否与学校样本中的游戏障碍相关。方法我们使用关于游戏使用模式的问卷分析了来自巴西精神疾病高危队列的数据，该队列是一个 10 至 18 岁的社区样本。我们应用游戏成瘾量表来诊断游戏障碍，并应用发展和幸福行为评估来进行其他诊断。结果 在 407 名受试者中，83 名 (20.4%) 符合游戏障碍的标准。与任何其他类型的游戏相比，更多的角色扮演游戏玩家被诊断出患有游戏障碍。游戏障碍率与游戏类型的数量成正比。在线玩游戏、被诊断出患有精神障碍以及不间断游戏的时间越长，游戏障碍的发生率越高。当在逻辑回归模型中考虑所有变量（包括年龄和性别）时，游戏类型的数量、不间断的小时数、网络游戏的比例和被诊断出的精神障碍成为游戏障碍的重要预测因素. 结论 每个变量似乎都会进一步增加儿童和青少年游戏障碍的风险。监控游戏时间长度、游戏类型的数量和类型、在线游戏时间以及行为变化可以帮助父母或监护人识别不健康的游戏行为模式。结论 每个变量似乎都会进一步增加儿童和青少年游戏障碍的风险。监控游戏时间长度、游戏类型的数量和类型、在线游戏时间以及行为变化可以帮助父母或监护人识别不健康的游戏行为模式。结论 每个变量似乎都会进一步增加儿童和青少年游戏障碍的风险。监控游戏时间长度、游戏类型的数量和类型、在线游戏时间以及行为变化可以帮助父母或监护人识别不健康的游戏行为模式。