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Currently submitted to: Journal of Medical Internet Research

Date Submitted: May 20, 2026
Open Peer Review Period: May 20, 2026 - Jul 15, 2026
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Can Digital Phenotyping Reveal Lifestyles That Reflect Mental Well-Being? Results From a Population-Matched Sample

  • Ningzhe Zhu; 
  • Ramona Schoedel; 
  • Larissa Sust; 
  • Markus Bühner; 
  • Yannik Terhorst

ABSTRACT

Background:

Digital phenotyping uses passively collected digital-sensing data to characterize real-world behavioral patterns. Such data may help identify everyday lifestyles that are relevant to mental well-being, but most prior approaches have used variable-centered methods that focus on single behaviors rather than person-centered combinations of behaviors across daily life.

Objective:

This study aimed to examine whether digitally captured behavioral and environmental data can be used to derive meaningful lifestyle profiles and whether these profiles are associated with mental well-being.

Methods:

The study used a two-week intensive longitudinal design with a German quota sample of 553 adults (Mage = 42.27, SD = 12.89; 44.4% female). Across the study period, participants contributed 7,635 person-days of smartphone-recorded data on social app use, mobility, physical activity, screen use, ambient loudness, and brightness, along with self-reported mental well-being and Big Five personality traits. We used an innovative two-level latent profile analysis to simultaneously identify day-level profiles at Level 1 and person-level profiles at Level 2. We then examined associations between person-level lifestyle profiles and mental well-being, including whether these associations were moderated by Big Five personality traits.

Results:

The analysis identified eight day-level profiles and seven person-level profiles. One person-level profile characterized by lighter phone usage combined with heavier physical activity reported greater positive functioning, an important aspect of mental well-being, than another profile characterized by extensive mobility combined with intensive social app use. Personality traits did not significantly moderate the associations between lifestyle profiles and mental well-being.

Conclusions:

These insights advance digital phenotyping by showing that interpretable, person-centered lifestyle profiles could reflect aspects of mental well-being. Potential clinical implications, including transparent monitoring and multi-behavior interventions are discussed.


 Citation

Please cite as:

Zhu N, Schoedel R, Sust L, Bühner M, Terhorst Y

Can Digital Phenotyping Reveal Lifestyles That Reflect Mental Well-Being? Results From a Population-Matched Sample

JMIR Preprints. 20/05/2026:101850

DOI: 10.2196/preprints.101850

URL: https://preprints.jmir.org/preprint/101850

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