Department of Psychiatry, New York State Psychiatric Institute, Columbia University Irving Medical Center.
Department of Psychiatry, University of Pittsburgh Medical Center.
J Psychopathol Clin Sci. 2024 Oct;133(7):577-597. doi: 10.1037/abn0000930. Epub 2024 Jul 18.
Intensive longitudinal research-including experience sampling and smartphone sensor monitoring-has potential for identifying proximal risk factors for psychopathology, including suicidal thoughts and behaviors (STB). Yet, missing data can complicate analysis and interpretation. This study aimed to address whether clinical and study design factors are associated with missing data and whether missingness predicts changes in symptom severity or STB. Adolescents ages 13- to 18 years old ( = 179) reporting depressive, anxiety, and/or substance use disorders were enrolled; 65% reported current suicidal ideation and 29% indicated a past-year attempt. Passively acquired smartphone sensor data (e.g., global positioning system, accelerometer, and keyboard inputs), daily mood surveys, and weekly suicidal ideation surveys were collected during the 6-month study period using the effortless assessment research system smartphone app. First, acquisition of passive smartphone sensor data (with data on ∼80% of days across the whole sample) was strongly associated with survey data acquisition on the same day (∼44% of days). Second, STB and psychiatric symptoms were largely not associated with missing data. Rather, temporal features (e.g., length of time in study, weekends, and summer) explained more missingness of survey and passive smartphone sensor data. Last, within-participant changes in missing data over time neither followed nor predicted subsequent change in suicidal ideation and psychiatric symptoms. Findings indicate that considering technical and study design factors impacting missingness is critical and highlight several factors that should be addressed to maximize the validity of clinical interpretations in intensive longitudinal research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
密集纵向研究——包括经验抽样和智能手机传感器监测——具有识别精神病理学的近端风险因素的潜力,包括自杀意念和行为(STB)。然而,缺失数据会使分析和解释变得复杂。本研究旨在确定临床和研究设计因素是否与缺失数据有关,以及缺失数据是否预测症状严重程度或 STB 的变化。招募了年龄在 13 至 18 岁(n = 179)、报告抑郁、焦虑和/或物质使用障碍的青少年;65%报告目前有自杀意念,29%表示过去一年有自杀企图。在 6 个月的研究期间,使用轻松评估研究系统智能手机应用程序收集了被动获取的智能手机传感器数据(例如,全球定位系统、加速度计和键盘输入)、每日情绪调查和每周自杀意念调查。首先,被动获取智能手机传感器数据(整个样本中约 80%的天数都有数据)与当天的调查数据获取(约 44%的天数)密切相关。其次,STB 和精神症状与缺失数据的关联性不大。相反,时间特征(例如,研究时间长短、周末和夏季)解释了更多的调查和被动智能手机传感器数据缺失。最后,参与者在时间上的缺失数据变化既没有遵循也没有预测随后自杀意念和精神症状的变化。研究结果表明,考虑影响缺失数据的技术和研究设计因素至关重要,并强调了应解决的几个因素,以最大限度地提高密集纵向研究中临床解释的有效性。(PsycInfo 数据库记录(c)2024 APA,保留所有权利)。