Identifying Factors Impacting Missingness within Smartphone-based Research: Implications for Intensive Longitudinal Studies of Adolescent Suicidal Thoughts and Behaviors

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 13-18-years-old (N=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., GPS, accelerometer, keyboard inputs), daily mood surveys, and weekly suicidal ideation surveys were collected during the 6-month study period using the Effortless Assessment Research System (EARS) 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 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, 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.