Person-Specific Analyses of Smartphone Use and Mental Health: Intensive Longitudinal Study
BackgroundContrary to popular concerns about the harmful effects of media use on 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...
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JMIR Publications
2025-02-01
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| Series: | JMIR Formative Research |
| Online Access: | https://formative.jmir.org/2025/1/e59875 |
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| author | Merve Cerit Angela Y Lee Jeffrey Hancock Adam Miner Mu-Jung Cho Daniel Muise Anna-Angelina Garròn Torres Nick Haber Nilam Ram Thomas N Robinson Byron Reeves |
| author_facet | Merve Cerit Angela Y Lee Jeffrey Hancock Adam Miner Mu-Jung Cho Daniel Muise Anna-Angelina Garròn Torres Nick Haber Nilam Ram Thomas N Robinson Byron Reeves |
| author_sort | Merve Cerit |
| collection | DOAJ |
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BackgroundContrary to popular concerns about the harmful effects of media use on 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 been found null or have small associations, with the results often blamed on the use of cross-sectional study designs or imprecise measures of media use and mental health.
ObjectiveThis exploratory empirical demonstration aims to answer 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 over the course of 1 year, (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 media behaviors and mental health symptoms that may be more useful for studying media effects than single measures of dosage and affect or assessments of clinical symptoms related to specific disorders.
MethodsThe activity on individuals’ smartphone screens was recorded every 5 seconds when devices were in use over 1 year, resulting in a dataset of 6,744,013 screenshots and 123 fortnightly surveys from 5 adult participants. Each participant contributed between 0.8 and 2.7 million screens. Six media use metrics were derived from smartphone metadata. Fortnightly surveys captured symptoms of depression, attention-deficit/hyperactivity disorder, state anxiety, and positive affect. Idiographic filter models (p-technique canonical correlation analyses) were applied to explore person-specific associations.
ResultsCanonical correlations revealed substantial person-specific associations between media use and mental health, ranging from r=0.82 (P=.008) to r=0.92 (P=.03). The specific combinations of media use metrics and mental health dimensions were different for each person, reflecting significant individual variability. For instance, the media use canonical variate for 1 participant was characterized by higher loadings for app-switching, which, in combination with other behaviors, correlated strongly with a mental health variate emphasizing anxiety symptoms. For another, prolonged screen time, alongside other media use behaviors, contributed to a mental health variate weighted more heavily toward depression symptoms. These within-person correlations are among the strongest reported in this literature.
ConclusionsResults suggest that the relationships between media use and mental health are highly individualized, with implications for the development of personalized models and precision smartphone-informed interventions in mental health. We discuss how our approach can be extended generally, while still emphasizing the importance of idiographic approaches. 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. |
| format | Article |
| id | doaj-art-a16062aa24f34d079b935b758e86b30a |
| institution | DOAJ |
| issn | 2561-326X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Formative Research |
| spelling | doaj-art-a16062aa24f34d079b935b758e86b30a2025-08-20T03:11:16ZengJMIR PublicationsJMIR Formative Research2561-326X2025-02-019e5987510.2196/59875Person-Specific Analyses of Smartphone Use and Mental Health: Intensive Longitudinal StudyMerve Cerithttps://orcid.org/0009-0001-0560-4378Angela Y Leehttps://orcid.org/0000-0002-9527-5730Jeffrey Hancockhttps://orcid.org/0000-0001-5367-2677Adam Minerhttps://orcid.org/0000-0002-5125-4735Mu-Jung Chohttps://orcid.org/0000-0001-5500-6336Daniel Muisehttps://orcid.org/0000-0002-7137-0979Anna-Angelina Garròn Torreshttps://orcid.org/0009-0001-9687-5439Nick Haberhttps://orcid.org/0000-0001-8804-7804Nilam Ramhttps://orcid.org/0000-0003-1671-5257Thomas N Robinsonhttps://orcid.org/0000-0002-2367-0774Byron Reeveshttps://orcid.org/0000-0003-1546-8397 BackgroundContrary to popular concerns about the harmful effects of media use on 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 been found null or have small associations, with the results often blamed on the use of cross-sectional study designs or imprecise measures of media use and mental health. ObjectiveThis exploratory empirical demonstration aims to answer 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 over the course of 1 year, (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 media behaviors and mental health symptoms that may be more useful for studying media effects than single measures of dosage and affect or assessments of clinical symptoms related to specific disorders. MethodsThe activity on individuals’ smartphone screens was recorded every 5 seconds when devices were in use over 1 year, resulting in a dataset of 6,744,013 screenshots and 123 fortnightly surveys from 5 adult participants. Each participant contributed between 0.8 and 2.7 million screens. Six media use metrics were derived from smartphone metadata. Fortnightly surveys captured symptoms of depression, attention-deficit/hyperactivity disorder, state anxiety, and positive affect. Idiographic filter models (p-technique canonical correlation analyses) were applied to explore person-specific associations. ResultsCanonical correlations revealed substantial person-specific associations between media use and mental health, ranging from r=0.82 (P=.008) to r=0.92 (P=.03). The specific combinations of media use metrics and mental health dimensions were different for each person, reflecting significant individual variability. For instance, the media use canonical variate for 1 participant was characterized by higher loadings for app-switching, which, in combination with other behaviors, correlated strongly with a mental health variate emphasizing anxiety symptoms. For another, prolonged screen time, alongside other media use behaviors, contributed to a mental health variate weighted more heavily toward depression symptoms. These within-person correlations are among the strongest reported in this literature. ConclusionsResults suggest that the relationships between media use and mental health are highly individualized, with implications for the development of personalized models and precision smartphone-informed interventions in mental health. We discuss how our approach can be extended generally, while still emphasizing the importance of idiographic approaches. 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.https://formative.jmir.org/2025/1/e59875 |
| spellingShingle | Merve Cerit Angela Y Lee Jeffrey Hancock Adam Miner Mu-Jung Cho Daniel Muise Anna-Angelina Garròn Torres Nick Haber Nilam Ram Thomas N Robinson Byron Reeves Person-Specific Analyses of Smartphone Use and Mental Health: Intensive Longitudinal Study JMIR Formative Research |
| title | Person-Specific Analyses of Smartphone Use and Mental Health: Intensive Longitudinal Study |
| title_full | Person-Specific Analyses of Smartphone Use and Mental Health: Intensive Longitudinal Study |
| title_fullStr | Person-Specific Analyses of Smartphone Use and Mental Health: Intensive Longitudinal Study |
| title_full_unstemmed | Person-Specific Analyses of Smartphone Use and Mental Health: Intensive Longitudinal Study |
| title_short | Person-Specific Analyses of Smartphone Use and Mental Health: Intensive Longitudinal Study |
| title_sort | person specific analyses of smartphone use and mental health intensive longitudinal study |
| url | https://formative.jmir.org/2025/1/e59875 |
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