JMIR Publications

ABSTRACT

Background:

Smartphones have become an indispensable part of people's lives, and the fear of being without them, what has been termed 'nomophobia', is a growing phenomenon. The connections among nomophobia, mental health measures, smartphone usage, and daily activities remains largely unexplored. Exploring nomophobia can enhance our understanding of the dynamics between young adults and smartphone usage, potentially empowering them to manage and regulate their smartphone usage more effectively.

Objective:

This paper aims to explore the relationship between young depressive adults and smartphones, and investigate nomophobia by analysing data obtained from a pilot study of depression in a youth cohort. In addition to passive sensing smartphone data, the study collected ecological momentary assessments and psychometric measures, including the Nomophobia Questionnaire (NMP-Q), which forms the basis of our investigation. Thus, we here examine associations between smartphone use, various clinical psychometric measures and nomophobia.

Methods:

During an 8-week period, data collected by smartphone sensors, self-reported Ecological Momentary Assessments, and psychometric evaluations were gathered from a cohort of 41 individuals diagnosed with major depressive disorder. We explored statistical associations between smartphone-derived behavioral features, psychometric indicators, and nomophobia. Additionally, we utilized behavioral and psychometric data to develop a regression model demonstrating the prediction of nomophobia levels.

Results:

Our findings reveal that nomophobia is positively associated with depression and negative affect, lower geolocation movements, and higher comfort with smartphone sensing. We also have developed exploratory predictive linear regression models that demonstrates the feasibility of predicting an individual's NMP-Q score based on their smartphone sensing data.

Conclusions:

Our work is the first paper to explore the relationship between NMP-Q and smartphone sensor data. It provides valuable insights of the predictors of nomophobia level, contributing to how individuals behave and engage with their smartphones, and paving the way for future studies.