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大学生孤独与抑郁之间的关系:采集来自被动感应的数据
Malik Muhammad Qirtas1, Evi Zafeiridi1, Eleanor Bantry White2
1School of Computer Science and Information Technology, University College Cork, Cork, Ireland.
Digital health
|November 29, 2023
概括
过多的屏幕时间和手机使用与孤独相关,而较少的屏幕解锁和访问地点表明抑郁. 增加体力活动和睡眠减少了这两种疾病的风险,有助于针对学生的心理健康干预.
科学领域:
- 数字化表型化是指数字化表型化.
- 心理健康研究 心理健康研究
- 行为科学 行为科学
背景情况:
- 孤独和抑郁之间的关系是公认的,但不同的行为模式仍然不清楚.
- 了解这些差异对于有效的心理健康干预至关重要.
研究的目的:
- 在大学生中识别与孤独和抑郁相关的独特行为模式.
- 分析这些条件之间的相似性和相互关系.
- 评估行为指标在识别孤独和抑郁症方面的有效性.
主要方法:
- 利用学生生活数据集进行被动数据收集.
- 应用回归和调解分析来理解关联和关系.
- 使用机器学习模型 (XGBoost) 来预测孤独和抑郁.
主要成果:
- 晚上高屏幕时间和整体手机使用与孤独感增加有关.
- 更少的屏幕解锁和访问更少的与抑郁症相关的独特地点.
- 增加体力活动和睡眠时间与这两种疾病的风险较低相关.
- 孤独调解分析显示,抑郁症的可能性增加了48%.
- 机器学习模型在孤独预测方面达到82.43%的准确率,在抑郁预测方面达到79.43%.
结论:
- 清晰的数字行为模式区分孤独和抑郁.
- 结果支持针对学生福祉的有针对性的干预措施的发展.
- 被动数据收集为心理健康监测提供了一个有希望的途径.
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