Evidence map›Paper›PMID 42766793›Full record

ArticleJMIR formative research2026

Objectively Measured Life Space Using Participants' Mobile Phones: Cross-Sectional Study.

Michelle C Odden, Annabel X Tan, Sylvie Dobrota Lai, J David Rhodes, Suzanne Judd, Kyle Sargent, Sheila Mwanda, Sage Rowe, Jiajun Wu, Abby C King and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JMIR formative research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Michelle C OddenDepartment of Epidemiology and Population Health, Stanford University, 1701 Page Mill Road, Stanford, CA, 94305, United States, 1 (650) 721-0230.ORCID http://orcid.org/0000-0002-5974-3648
Annabel X TanDepartment of Epidemiology and Population Health, Stanford University, 1701 Page Mill Road, Stanford, CA, 94305, United States, 1 (650) 721-0230.ORCID http://orcid.org/0000-0001-8368-0301
Sylvie Dobrota LaiDepartment of Epidemiology and Population Health, Stanford University, 1701 Page Mill Road, Stanford, CA, 94305, United States, 1 (650) 721-0230.ORCID http://orcid.org/0000-0001-5134-2105
J David RhodesDepartment of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID http://orcid.org/0000-0002-2307-0904
Suzanne JuddDepartment of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID http://orcid.org/0000-0001-7594-6587
Kyle SargentDepartment of Computer Science, Stanford University, Stanford, CA, United States.ORCID http://orcid.org/0009-0009-8609-6894
Sheila MwandaDepartment of Epidemiology and Population Health, Stanford University, 1701 Page Mill Road, Stanford, CA, 94305, United States, 1 (650) 721-0230.ORCID http://orcid.org/0009-0009-6917-2701
Sage RoweDepartment of Epidemiology and Population Health, Stanford University, 1701 Page Mill Road, Stanford, CA, 94305, United States, 1 (650) 721-0230.ORCID http://orcid.org/0009-0008-1430-4108
Jiajun WuDepartment of Computer Science, Stanford University, Stanford, CA, United States.ORCID http://orcid.org/0000-0002-4176-343X
Abby C KingDepartment of Epidemiology and Population Health, Stanford University, 1701 Page Mill Road, Stanford, CA, 94305, United States, 1 (650) 721-0230.ORCID http://orcid.org/0000-0002-7949-8811
Vishnu RaviByers Center for Biodesign, Stanford University, Stanford, CA, United States.ORCID http://orcid.org/0000-0003-0359-1275

Funding

VCID and Stroke in a Bi-racial National CohortU01NS041588 · NINDS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI CUSHMAN, MARY, HOWARD, GEORGE · 2002 to 2022
$96.0M
NINDS NIH HHS U01 NS041588
6 · The paper itself

Abstract

Background: Measurement of life space characterizes people's engagement with their environment. Several studies have used GPS devices to capture life space. A challenge with device-based measures is that participants may forget to bring the device with them. Life-space measures that leverage the GPS data from participants' mobile phones may address this challenge, but few studies have leveraged this approach to date. Objective: Our objective was to assess the feasibility of implementing a mobile phone life-space assessment and characterize life space using Google Street View (GSV) imagery. We then aimed to evaluate the association of demographic data with life-space size and environmental features. Methods: We developed a mobile phone app to passively capture life space in older adults and sampled GSV images from participants' life space to characterize the environments where they spent their time. For this cross-sectional study, we recruited 82 participants (n=34, 41.5% men) aged 65 years and older (mean 74.5, SD 6.5 years) in 2023 to 2024 from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study. They were followed for 2 weeks and invited to complete nightly questionnaires on their phones. We measured features of the built environment that captured walkability (sidewalks, benches, and streetlights), neighborhoods (houses), and green space based on an image segmentation algorithm. Differences in life-space size and environmental features across participant characteristics were tested using the Wilcoxon rank sum test. Results: Among 82 participants, 76 (92.7%) completed all 14 days of data collection. Median daily maximum distance from home was 6.6 (IQR 1.3-15.5) km. Median distance traveled over 2 weeks was 477.1 (IQR 234.4-817.13) km. Adults younger than 70 years, women, Black participants, and those with income more than US $75,000 per year had larger life space than those aged 70 years and older, men, White participants, and those with income less than US $75,000 (154.5 vs 58.1 km Conclusions: In this feasibility study, we demonstrated that personal mobile phones could be used to passively track older adults' life space based on a digital health app developed on an open-source platform. There was wide variation in objectively measured life space, and we found sociodemographic patterning of life-space movement. Objective measurement of life space with participants' mobile phones is feasible and should be evaluated in larger samples to better capture the relationship between health and time spent in different environments. Integration of a life-space assessment into older adults' daily lives may allow for the use of life space as a health measure.

Indexed as

Cell PhoneAgedAged, 80 and overCross-Sectional StudiesFemaleGeographic Information SystemsHumansMaleMobile ApplicationsSurveys and Questionnairesagingbuilt environmentGPS trackinglife spacemHealthmobile health

Identifiers

PMID42766793
PMCPMC13592664

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.