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对有问题的互联网游戏障碍发生的风险因素分析和预测模型开发
Andrian Fajar Kusumadewi1, Raihan Hananto2, Arrum Putri Amalia3
1Department of Psychiatry, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Sleman, Indonesia.
概括
问题性互联网游戏障碍 (PIGD) 与男性,学生,经历抑郁,焦虑,压力,高神经症,良心低,和专制的育儿有关. 一个预测模型准确地识别出有风险的个体.
科学领域:
- 心理学 心理学 心理学
- 公共卫生 公共卫生
- 行为科学 行为科学
背景情况:
- 问题性互联网游戏障碍 (PIGD) 是一个越来越令人担忧的多方面的起源.
- 了解各种风险因素对于开发有效干预措施至关重要.
研究的目的:
- 确定与印度尼西亚雅加达市PIGD相关的社会人口统计学,心理,人格和育儿因素.
- 开发和验证一个预测模型,用于识别高风险的个人.
主要方法:
- 一项涉及350名15-25岁参与者的横截面研究,在Yogyakarta.
- 通过调查问卷收集的数据,包括互联网游戏障碍缩短表格 (IGDS9-SF),DASS-21,大五大库存 (BFI) 和育儿风格调查问卷.
- 多重物流回归分析用于识别风险因素并构建预测模型.
主要成果:
- 男性性别,学生身份,抑郁症,焦虑,压力,高神经症,良心低,和专制的育儿是PIGD的重要预测因素.
- 开发的风险预测模型显示出强大的预测性能,AUC为0.85 (95%CI为0.80-0.90).
结论:
- 猪病受到各种风险因素的复杂相互作用的影响.
- 经过验证的风险预测模型有效地识别了容易感染猪猪病的个体.
- 早期识别可以为猪猪病制定有针对性的预防和治疗策略.
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