Dataset for "Can Digital Phenotyping Reveal Lifestyles That Reflect Mental Well-Being? Results From A Quota-Matched Sample"

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Authors: Ningzhe Zhu, Ramona Schoedel, Larissa N. N. Sust, Markus Bühner, Yannik Terhorst
Cited by: 0

Abstract

We present the dataset for the article "Can Digital Phenotyping Reveal Lifestyles That Reflect Mental Well-Being? Results From A Quota-Matched Sample." The data were collected as part of the Smartphone Sensing Panel Study and include 7,635 observations from N = 553 participants collected over 14 days of daily life using mobile sensing. Specifically, “Sensing_Variable’” is an aggregated mobile sensing dataset with 10 variables (including variables extracted from GPS, phone, app, activity logs, etc.). “Person_variable” contains the Mental Well-Being scale and Big Five Inventory scores. Demographic and technical variables (age, gender, education, manufacturer, and Android version of the smartphone) that were not used for the data analyses were removed for privacy reasons, but can be made available upon request. The datasets are documented by an accompanying codebook. Additional materials (e.g., analysis code) can also be found at https://osf.io/pzksa.

Fields of Study & Subjects

Human Mobility and Location-Based Analysis Mental Health Research Topics Digital Mental Health Interventions

Publication details

Publication date
4 February 2026
Language
EN
Document type
Dataset