Analyzing GPS Data for Psychological Research: A Tutorial

Müller, Sandrine R.; Bayer, Joseph B.; Ross, Morgan Quinn; Mount, Jerry; Stachl, Clemens; Harari, Gabriella M.; Chang, Yi‐Jun; Le, Huyen

doi:10.1177/25152459221082680

Cited by 17 publications

(9 citation statements)

References 41 publications

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“…While using passive smartphone measures in research, researchers must make other decisions that are not directly related to time but can still introduce researchers’ degrees of freedom. For example, there are various algorithms and methods for clustering location data (examples described in Müller et al, 2022; Zheng et al, 2009), and researchers must decide which one to use to cluster the staypoints.…”

Section: Discussionmentioning

confidence: 99%

It’s All About Timing: Exploring Different Temporal Resolutions for Analyzing Digital-Phenotyping Data

Langener,

Stulp,

Jacobson

et al. 2024

Advances in Methods and Practices in Psychological Science

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The use of smartphones and wearable sensors to passively collect data on behavior has great potential for better understanding psychological well-being and mental disorders with minimal burden. However, there are important methodological challenges that may hinder the widespread adoption of these passive measures. A crucial one is the issue of timescale: The chosen temporal resolution for summarizing and analyzing the data may affect how results are interpreted. Despite its importance, the choice of temporal resolution is rarely justified. In this study, we aim to improve current standards for analyzing digital-phenotyping data by addressing the time-related decisions faced by researchers. For illustrative purposes, we use data from 10 students whose behavior (e.g., GPS, app usage) was recorded for 28 days through the Behapp application on their mobile phones. In parallel, the participants actively answered questionnaires on their phones about their mood several times a day. We provide a walk-through on how to study different timescales by doing individualized correlation analyses and random-forest prediction models. By doing so, we demonstrate how choosing different resolutions can lead to different conclusions. Therefore, we propose conducting a multiverse analysis to investigate the consequences of choosing different temporal resolutions. This will improve current standards for analyzing digital-phenotyping data and may help combat the replications crisis caused in part by researchers making implicit decisions.

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Section: Discussionmentioning

confidence: 99%

It’s All About Timing: Exploring Different Temporal Resolutions for Analyzing Digital-Phenotyping Data

Langener,

Stulp,

Jacobson

et al. 2024

Advances in Methods and Practices in Psychological Science

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“…For each 15-min interval, we labeled a user’s geometric median location with the corresponding environmental context and sub-context. We further registered whether participants were moving or staying during each 15-min interval using the unsupervised machine-learning DBSCAN algorithm utilized in previous studies on human mobility (Cuttone et al, 2014; Müller et al, 2022).…”

Section: Methodsmentioning

confidence: 99%

Nature Exposure is Associated With Reduced Smartphone Use

Minor

Glavind

Schwartz

et al. 2023

Environment and Behavior

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Evidence links greenspace exposure with restorative benefits to cognition and well-being, yet nature contact is declining for younger demographics. Although natural settings have been shown to restore the capacity to inhibit distracting stimuli, it remains unknown whether smartphone attention capture disrupts nature contact. Here, we analyzed ~2.5 million observations of logged smartphone use, texting, calling, and environmental exposures for 701 young adults over 2 years. Participants’ weekly smartphone screen-time was over double their green-time. The relationship between greenspace exposure and smartphone activity differed by exposure dose, type, and mobility state. Calling and texting increased during short recreational greenspace visits while all smartphone use declined over the first 3 hr in nature areas, suggesting that nature exposure may support digital impulse inhibition. Those with elevated baseline screen-time or green-time significantly reduced device use in nature, indicating that parts of the biosphere may provide a reprieve from the cybersphere for highly connected youth.

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“…Passive monitoring used collected GPS data to measure mobility and activity level of users. GPS mobility indicators measured on the smartphone, including home time, distance travelled, and location clusters, will be extracted following the procedures by Müller et al [ 62 ]. Briefly, locations will be clustered as “unique” if a person spent at least 30 minutes within a 200-meter radius.…”

Section: Methodsmentioning

confidence: 99%

A Digital System (YouXin) to Facilitate Self-Management by People With Psychosis in China: Protocol for a Nonrandomized Validity and Feasibility Study With a Mixed Methods Design

Zhang¹,

Lewis²,

Carter³

et al. 2023

JMIR Res Protoc

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Background Psychosis is one of the most disabling mental health conditions and causes significant personal, social, and economic burden. Accurate and timely symptom monitoring is critical to offering prompt and time-sensitive clinical services. Digital health is a promising solution for the barriers encountered by conventional symptom monitoring approaches, including accessibility, the ecological validity of assessments, and recall bias. However, to date, there has been no digital health technology developed to support self-management for people with psychosis in China. Objective We report the study protocol to evaluate the validity, feasibility, acceptability, usability, and safety of a symptom self-monitoring smartphone app (YouXin; Chinese name 佑心) for people with psychosis in China. Methods This is a nonrandomized validity and feasibility study with a mixed methods design. The study was approved by the University of Manchester and Beijing Anding Hospital Research Ethics Committee. YouXin is a smartphone app designed to facilitate symptom self-monitoring for people with psychosis. YouXin has 2 core functions: active monitoring of symptoms (ie, smartphone survey) and passive monitoring of behavioral activity (ie, passive data collection via embedded smartphone sensors). The development process of YouXin utilized a systematic coproduction approach. A series of coproduction consultation meetings was conducted by the principal researcher with service users and clinicians to maximize the usability and acceptability of the app for end users. Participants with psychosis aged 16 years to 65 years were recruited from Beijing Anding Hospital, Beijing, China. All participants were invited to use the YouXin app to self-monitor symptoms for 4 weeks. At the end of the 4-week follow-up, we invited participants to take part in a qualitative interview to explore the acceptability of the app and trial procedures postintervention. Results Recruitment to the study was initiated in August 2022. Of the 47 participants who were approached for the study from August 2022 to October 2022, 41 participants agreed to take part in the study. We excluded 1 of the 41 participants for not meeting the inclusion criteria, leaving a total of 40 participants who began the study. As of December 2022, 40 participants had completed the study, and the recruitment was complete. Conclusions This study is the first to develop and test a symptom self-monitoring app specifically designed for people with psychosis in China. If the study shows the feasibility of YouXin, a potential future direction is to integrate the app into clinical workflows to facilitate digital mental health care for people with psychosis in China. This study will inform improvements to the app, trial procedures, and implementation strategies with this population. Moreover, the findings of this trial could lead to optimization of digital health technologies designed for people with psychosis in China. International Registered Report Identifier (IRRID) DERR1-10.2196/45170

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Analyzing GPS Data for Psychological Research: A Tutorial

Cited by 17 publications

References 41 publications

It’s All About Timing: Exploring Different Temporal Resolutions for Analyzing Digital-Phenotyping Data

It’s All About Timing: Exploring Different Temporal Resolutions for Analyzing Digital-Phenotyping Data

Nature Exposure is Associated With Reduced Smartphone Use

A Digital System (YouXin) to Facilitate Self-Management by People With Psychosis in China: Protocol for a Nonrandomized Validity and Feasibility Study With a Mixed Methods Design

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