长期密集的纵向数据协议中的合规性和响应一致性
Alexander W Sokolovsky1, Rachel L Gunn1, Andrea M Wycoff1
1Center for Alcohol and Addiction Studies, Brown University.
Psychological assessment
|August 5, 2024
概括
随着时间的推移,密集纵向数据 (ILD) 收集的遵守程度会下降,尤其是在较长的研究中. 药物使用可能会影响酒精和大麻研究中的调查答案一致性和不合规性.
科学领域:
- 心理学 心理学 心理学
- 成研究 研究成研究
- 数据科学数据科学数据科学
背景情况:
- 密集的纵向数据 (ILD) 收集对于了解现实世界物质使用模式至关重要.
- 在ILD研究中,长时间的评估窗口对参与者合规性和响应一致性构成挑战.
- 关于影响ILD遵守和一致性的因素的先前研究是有限的.
研究的目的:
- 调查如何在漫长的ILD协议中随着时间的推移保持合规性和响应一致性.
- 检查事件和个人层面对大学生报告酒精和大麻联合使用的合规性和响应一致性的影响.
- 评估时间和测量冲击对违规和响应一致性的影响.
主要方法:
- 在多层次中断时间序列框架内利用线性混合效应模型.
- 分析了316名大学生参与两次28天的ILD爆发的数据,每次每天进行5次调查.
- 评估了不合规性 (错过的调查) 和响应的一致性 (饮酒报告中的差异).
主要成果:
- 时间与不遵守积极相关,这表明在研究持续时间内遵守程度下降.
- 不合规率在第二次测量爆发时增加.
- 时间和测量爆发都没有显著影响响应的一致性;然而,当天使用物质似乎影响了非响应和一致性.
结论:
- 在漫长的ILD协议中,参与者的服从性普遍下降,而响应的一致性保持稳定.
- 较短的评估窗口或适应性提示策略可能会提高研究合规性.
- 对日常负担和背景的进一步研究是必要的,以优化未来的ILD设计用于物质使用研究.
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