Evidence map›Paper›PMID 41004250›Full record

ArticleJournal of medical Internet research2025

Data Donation as a Method to Measure Physical Activity in Older Adults: Cross-Sectional Web Survey Assessing Consent Rates, Donation Success, and Bias.

Florian Keusch, Bella Struminskaya, Joris Mulder, Stein Jongerius

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. 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
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0citing papers in PubMed
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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

4 authors.

Florian KeuschDepartment of Sociology, School of Social Sciences, University of Mannheim, Mannheim, Germany.ORCID https://orcid.org/0000-0003-1002-4092
Bella StruminskayaDepartment of Methodology & Statistics, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht, The Netherlands.ORCID https://orcid.org/0000-0002-5944-8163
Joris MulderCenterdata, Tilburg University, Tilburg, The Netherlands.ORCID https://orcid.org/0000-0003-4863-0936
Stein JongeriusCenterdata, Tilburg University, Tilburg, The Netherlands.ORCID https://orcid.org/0009-0000-8019-9571

Funding

Network for Advancing Methodological Research in Longitudinal Studies of AgingU24AG077012 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sung-Hee Lee, Brady T West · 2024 to 2026
$1.2M
NIMLAS Admin SupplementR24AG077012 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LEE, SUNG-HEE, WEST, BRADY T · 2022 to 2023
$863k
NIA NIH HHS R24 AG077012NIA NIH HHS U24 AG077012
6 · The paper itself

Abstract

backgroundAccurate measurement of physical activity (PA) is key to identifying determinants of health and developing appropriate interventions. Self-reports of PA (eg, in surveys or diary studies) often suffer from measurement error. Providing study participants with wearable devices that passively track PA reduces reactivity and recall error but participants' noncompliance and high device costs are problematic. Many older adults now have smartphones that track PA. Based on legal requirements, data controllers (eg, health apps) must provide users with access to their data, and individuals can request and donate these data for research. This user-centric approach provides researchers with access to individual-level data, and it gives users control over what data are shared.

objectiveWe conduct a first test of the data donation approach for PA data among older adults. We study (1) how willing and successful older adults are to donate their PA data from different smartphone apps, (2) what drives donation of PA data at the different stages of participation, and (3) what biases arise from selective data donation.

methodsTo answer our research questions, we use cross-sectional observational data from a probability-based online panel of the Dutch general population. A total of 2086 members of the Longitudinal Internet Studies for the Social Sciences panel aged 50 years and older completed a web survey in 2024. All iPhone and Android smartphone owners were asked to download passively collected PA data from their devices (Apple Health, Google Location History, or Samsung Health) and donate them via the Port platform.

resultsOut of the 2086 survey participants, 1889 (91%) reported owning an iPhone or Android phone compatible for data donation, 606 (29%) reported willingness to donate PA data, 354 (17%) started the data donation, and 256 (12%) successfully provided a data package. Gender, age, educational attainment, monthly personal net income, smartphone usage behavior, privacy- and trust-related attitudes, and type of health app from which the data were requested correlated with behavior at the different stages of study participation. Self-reported reasons for nonwillingness to donate related mainly to expected technical issues, privacy concerns, and perceived usefulness. Compared with the entire sample, data donors reported better health, fewer health-related limitations, fewer difficulties performing tasks, and more PA.

conclusionsOur study shows that data donation from smartphones as part of a probability-based web survey of older adults is a feasible alternative for the measurement of PA, especially for iPhone owners younger than 70 years. Limitations relate to nonparticipation which correlates strongly with characteristics of smartphone ownership and comfort with device use. Substantive bias in health and PA outcomes persists for those who donated in comparison with all survey respondents.

Indexed as

ExerciseInformed ConsentAgedBiasCross-Sectional StudiesFemaleHumansInternetMaleMiddle AgedMobile ApplicationsSmartphoneSurveys and Questionnairesconsentdata donationhealth appsself-reportsmartphones

Identifiers

PMID41004250
PMCPMC12514404

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Registered trials

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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.