School of Psychological Sciences, University of Northern Colorado.
Applied Statistics and Research Methods, University of Northern Colorado.
Psychol Assess. 2014 Sep;26(3):947-57. doi: 10.1037/a0036612. Epub 2014 Apr 21.
Measuring self-reported substance use behavior is challenging due to issues related to memory recall and patterns of bias in estimating behavior. Limited research has focused on the use of ecological momentary assessment (EMA) to evaluate marijuana use. This study assessed the feasibility of using short message service (SMS) texting as a method of EMA with college-age marijuana users. Our goals were to evaluate overall response/compliance rates and trends of data missingness, response time, baseline measures (e.g., problematic use) associated with compliance rates and response times, and differences between EMA responses of marijuana use compared to timeline followback (TLFB) recall. Nine questions were texted to participants on their personal cell phones 3 times a day over a 2-week period. Overall response rate was high (89%). When examining predictors of the probability of data missingness with a hierarchical logistic regression model, we found evidence of a higher propensity for missingness for Week 2 of the study compared to Week 1. Self-regulated learning was significantly associated with an increase in mean response time. A model fit at the participant level to explore response time found that more time spent smoking marijuana related to higher response times, while more time spent studying and greater "in the moment" academic motivation and craving were associated with lower response times. Significant differences were found between the TLFB and EMA, with greater reports of marijuana use reported through EMA. Overall, results support the feasibility of using SMS text messaging as an EMA method for college-age marijuana users.
由于与记忆召回和行为估计偏差模式相关的问题,自我报告的物质使用行为的测量具有挑战性。有限的研究集中在使用生态瞬时评估(EMA)来评估大麻使用情况。本研究评估了使用短消息服务(SMS)短信作为大学生大麻使用者 EMA 方法的可行性。我们的目标是评估总体响应/合规率以及数据缺失、响应时间、与合规率和响应时间相关的基线测量(例如,问题使用)的趋势,以及与 TLFB 回忆相比,EMA 对大麻使用的响应之间的差异。在两周的时间里,每天通过个人手机向参与者发送 3 次共 9 个问题。总体响应率很高(89%)。当使用分层逻辑回归模型检查数据缺失概率的预测因子时,我们发现与第 1 周相比,第 2 周研究中数据缺失的可能性更高。自我调节学习与平均响应时间的增加显著相关。探索响应时间的参与者水平模型拟合发现,吸烟大麻的时间与更高的响应时间有关,而花更多的时间学习、更高的“当下”学术动机和渴望与更低的响应时间有关。在 TLFB 和 EMA 之间发现了显著差异,通过 EMA 报告了更多的大麻使用情况。总体而言,结果支持使用 SMS 短信作为大学生大麻使用者 EMA 方法的可行性。