Evidence map›Paper›PMID 42416806›Full record

ArticleFrontiers in digital health2026

User acceptance and continuance intention of the BeSt age mHealth application for physical activity promotion and fall prevention in nursing homes.

Jonathan Diener, Jelena Krafft, Kerem Doğan, Iris Ten Klooster, Janina Krell-Roesch, Lisette van Gemert-Pijnen, Alexander Woll, Kathrin Wunsch

Abstract read
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Jonathan DienerInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.
Jelena KrafftInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.
Kerem DoğanDepartment of Psychology, Health and Technology, Centre for EHealth and Wellbeing Research, TechMed Centre, Faculty of Behavioural, Management and Social Sciences, University of Twente, Enschede, Netherlands.
Iris Ten KloosterDepartment of Psychology, Health and Technology, Centre for EHealth and Wellbeing Research, TechMed Centre, Faculty of Behavioural, Management and Social Sciences, University of Twente, Enschede, Netherlands.
Janina Krell-RoeschInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.
Lisette van Gemert-PijnenDepartment of Psychology, Health and Technology, Centre for EHealth and Wellbeing Research, TechMed Centre, Faculty of Behavioural, Management and Social Sciences, University of Twente, Enschede, Netherlands.
Alexander WollInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.
Kathrin WunschInstitute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Falls pose a major threat to nursing home residents, highlighting urgent prevention needs. Mobile health applications offer promising solutions, but their effectiveness depends on acceptance and sustained use. Despite increasing attention to digital care technologies, adherence remains low and integration into care practice limited. This study aimed to examine acceptance of the BeSt Age App, a fall prevention mobile application for nursing homes, and to analyze the influence of perceived usefulness and usability on continuance intention. Methods: A cluster-randomized controlled trial was conducted in nursing homes in Southern Germany. Over 12 weeks, trained nursing home employees used the BeSt Age App to provide individualized exercise sessions to nursing home residents. User acceptance data and related usage constructs were collected from nursing home employees (adherence, usability, user experience, perceived usefulness, engagement, continuance intention) and residents (continuance intention, motivation). Multiple regression was conducted to examine factors influencing continuance intention. Results: Eleven nursing homes with 37 employees and 137 residents participated. Residents (mean age 85.0 ± 7.6 years, 81% female) showed moderate cognitive impairment and low digital competence (1.9 ± 1.1; scale: 1-5). Employees (mean age 51.7 ± 11.5 years, 84% female, digital competence 3.54 ± 0.8) rated usability with 87.1 ± 15 points and reported positive continuance intention (4.03 ± 1.22; scale: 1-5). Employee adherence was 85.6%, resident adherence 75.1%. Perceived usefulness ( Discussion: Nursing home employees evaluated the BeSt Age App positively, particularly with respect to usability, which, alongside perceived usefulness, predicted continuance intention. The digital divide between employees and residents emphasizes the critical role of employee-mediated technology interventions for successful implementation in long-term care. Future research should examine longer-term adoption patterns and investigate the relationship between sustained app usage and clinical outcomes in nursing home settings.

Indexed as

continuance intentionfall preventionmHealthnursing homeuser acceptance

Identifiers

PMID42416806
PMCPMC13337713

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LicenceCC BY
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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.