@Article{info:doi/10.2196/57512,
author="Zhang, Tianyi
and Camargo, Andres
and Schmaal, Lianne
and Kostakos, Vassilis
and D'Alfonso, Simon",
title="Nomophobia, Psychopathology, and Smartphone-Inferred Behaviors in Youth With Depression: Longitudinal Study",
journal="JMIR Form Res",
year="2025",
month="Feb",
day="19",
volume="9",
pages="e57512",
keywords="mobile sensing; nomophobia; digital phenotyping; depression; mental health; smartphone use; personal sensing; behavior analysis; machine learning; mobile health; mobile phone",
abstract="Background: Smartphones have become an indispensable part of people's lives, and the fear of being without them, what has been termed ``no mobile phone phobia'' (nomophobia), is a growing phenomenon. The rise of problematic smartphone use highlights the urgent need to explore the intricate relationship between smartphones and human behavior. However, the connections between nomophobia, mental health indicators, smartphone use patterns, and daily activities remain largely underexplored. Objective: This study aimed to explore the relationship between young adults with depression and smartphones and investigate nomophobia by analyzing data obtained from a pilot study of depression in a youth cohort. Exploring nomophobia can enhance our understanding of the dynamics between young adults and smartphone use, potentially empowering them to manage and regulate their smartphone use more effectively. Methods: During an 8-week period, data collected via smartphone sensors, such as locations and screen status, were gathered from a cohort of 41 individuals diagnosed with major depressive disorder. In addition to passive-sensing smartphone data, the study collected ecological momentary assessments and psychometric measures, including the Nomophobia Questionnaire, which formed the basis of our investigation. We explored statistical associations among smartphone-derived behavioral features, psychometric indicators, and nomophobia. In addition, we used behavioral and psychometric data to develop regression models demonstrating the prediction of nomophobia levels. Results: Our findings revealed that the level of nomophobia was positively associated with depression and negative affect, lower geolocation movements, and higher comfort with smartphone sensing. The exploratory predictive linear regression models demonstrated the feasibility of predicting an individual's Nomophobia Questionnaire score based on their smartphone sensing data. These models effectively used input features derived from both a combination of smartphone sensing data and psychometric measures and from smartphone sensing data alone. Conclusions: Our work is the first to explore the relationship between nomophobia and smartphone sensor data. It provides valuable insights into the predictors of nomophobia level, contributing to the understanding of the relationship between smartphones and human behavior and paving the way for future studies. ",
issn="2561-326X",
doi="10.2196/57512",
url="https://formative.jmir.org/2025/1/e57512",
url="https://doi.org/10.2196/57512",
url="http://www.ncbi.nlm.nih.gov/pubmed/39969982"
}