JMIR Publications

ABSTRACT

Background:

Contrary to popular concerns that media use is harmful to mental health, research on this relationship is ambiguous, stalling advances in theory, interventions, and policy. Scientific explorations of the relationship between media and mental health have mostly found null or small associations, with the lack of results often blamed on the use of cross-sectional study designs or imprecise measures of media use and mental health.

Objective:

This empirical demonstration aimed to answer the question of whether mental health effects are associated with media use experiences by (1) redirecting research investments to granular and intensive longitudinal recordings of digital experiences to build models of media use and mental health for single individuals, (2) using new metrics of fragmented media use to propose explanations of mental health effects that will advance person-specific theorizing in media psychology, and (3) identifying combinations of mental health symptoms that may be more useful for studying media effects than single measures of general well-being or assessments of clinical symptoms related to specific disorders.

Methods:

For one year, the activity occurring on individuals' smartphone screens was recorded every five seconds devices were in use, resulting in 0.8 to 2.7 million screens per person over the year. Using these moment-by-moment screen data, we explored how changes in frequency, duration, and fragmentation of smartphone use covary with changes in mental health. We applied idiographic filter models (p-technique canonical correlation analyses) to longitudinal data provided by five adult participants who exhibited at least one period of problematic mental health symptoms during the year. Fortnightly clinical surveys captured symptoms of depression and adult ADHD (hyperactivity and inattentiveness), as well as state anxiety and psychological well-being.

Results:

Results show person-specific associations between media use and mental health. Canonical correlations revealed substantial covariation, ranging from r=.82(P=.008) to .92(P=.031), over time, emphasizing smartphones’ significance. These within-person correlations are the strongest relationships observed in this literature. Simultaneously, the specific combinations of media use metrics and mental health dimensions were different for each person, thus accommodating substantial variance across individuals.

Conclusions:

Results suggest that the mechanisms driving the connection between media use and mental health are highly individualized, with implications for the development of precision smartphone-informed interventions in mental health. We discuss how our approach can be extended generally, while still emphasizing the importance of idiographic approaches in a field where the manifestation of extreme idiosyncrasy currently jeopardizes scientific progress. This study highlights the potential for granular, longitudinal data to reveal person-specific patterns that can inform theory development, personalized screening, diagnosis, and interventions in mental health. Clinical Trial: Not applicable.