TY - JOUR AU - Perski, Olga AU - Lumsden, Jim AU - Garnett, Claire AU - Blandford, Ann AU - West, Robert AU - Michie, Susan PY - 2019 DA - 2019/11/20 TI -评估App用户数字行为改变干预参与量表的心理测量特性:评估研究JO - J Med Internet Res SP - e16197 VL - 21 IS - 11 KW -参与KW -数字行为改变干预KW -移动健康KW -自我报告量表KW -智能手机应用KW -过度饮酒AB -背景:参与数字行为改变干预(dbci)的水平和类型可能会影响其有效性，但缺乏有效的参与自我报告措施。DBCI参与量表旨在评估行为(即使用的数量、深度)和体验(即注意力、兴趣、享受)维度的参与。目的:我们旨在评估DBCI参与量表在减少酒精消费的智能手机应用程序用户中的心理测量特性。方法:参与者(N=147)是通过在线研究平台招募的英国成年酗酒者。参与者下载了“少喝”应用程序，并在第一次登录后立即完成秤，以换取经济奖励。标准变量包括客观记录的使用量、使用深度和随后的登录。五种类型的效度(即结构，标准，预测，增量，发散)在探索性因素，相关和回归分析中进行了检验。计算Cronbach alpha来评估量表的内部信度。协变量包括减少饮酒的动机。 Results: Responses on the DBCI Engagement Scale could be characterized in terms of two largely independent subscales related to experience and behavior. The experiential and behavioral subscales showed high (α=.78) and moderate (α=.45) internal reliability, respectively. Total scale scores predicted future behavioral engagement (ie, subsequent login) with and without adjusting for users’ motivation to reduce alcohol consumption (adjusted odds ratio [ORadj]=1.14; 95% CI 1.03-1.27; P=.01), which was driven by the experiential (ORadj=1.19; 95% CI 1.05-1.34; P=.006) but not the behavioral subscale. Conclusions: The DBCI Engagement Scale assesses behavioral and experiential aspects of engagement. The behavioral subscale may not be a valid indicator of behavioral engagement. The experiential subscale can predict subsequent behavioral engagement with an app for reducing alcohol consumption. Further refinements and validation of the scale in larger samples and across different DBCIs are needed. SN - 1438-8871 UR - //www.mybigtv.com/2019/11/e16197/ UR - https://doi.org/10.2196/16197 UR - http://www.ncbi.nlm.nih.gov/pubmed/31746771 DO - 10.2196/16197 ID - info:doi/10.2196/16197 ER -