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- to 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., 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).

Study Preregistration: Testing a Digital Suicide Risk Reduction Platform for Adolescents: A Pragmatic Randomized Controlled Trial.

Suicide is the second leading cause of death among adolescents, and rates of suicidal thoughts and behaviors (STBs) are climbing.1 Promising interventions such as dialectical behavior therapy (DBT) are available to treat suicidal youth, and new approaches may facilitate greater intervention engagement, adherence, and effectiveness.2 Digital tools (eg, personal smartphones) are a particularly promising avenue and could enhance existing, evidence-based interventions by providing new opportunities for assessment and intervention between sessions.

Detecting adolescent depression through passive monitoring of linguistic markers in smartphone communication.

BACKGROUND: Cross sectional studies have identified linguistic correlates of major depressive disorder (MDD) in smartphone communication. However, it is unclear whether monitoring these linguistic characteristics can detect when an individual is experiencing MDD, which would facilitate timely intervention. METHODS: Approximately 1.2 million messages typed into smartphone social communication apps (e.g. texting, social media) were passively collected from 90 adolescents with a range of depression severity over a 12-month period. Sentiment (i.e. positive vs. negative valence of text), proportions of first-person singular pronouns (e.g. 'I'), and proportions of absolutist words (e.g. 'all') were computed for each message and converted to weekly aggregates temporally aligned with weekly MDD statuses obtained from retrospective interviews. Idiographic, multilevel logistic regression models tested whether within-person deviations in these linguistic features were associated with the probability of concurrently meeting threshold for MDD. RESULTS: Using more first-person singular pronouns in smartphone communication relative to one's own average was associated with higher odds of meeting threshold for MDD in the concurrent week (OR = 1.29; p = .007). Sentiment (OR = 1.07; p = .54) and use of absolutist words (OR = 0.99; p = .90) were not related to weekly MDD. CONCLUSIONS: Passively monitoring use of first-person singular pronouns in adolescents' smartphone communication may help detect MDD, providing novel opportunities for early intervention.