Evidence map›Paper›PMID 40990372›Full record

ArticleJournal of medical Internet research2025

How Well Do Older Adult Fitness Technologies Match User Needs and Preferences? Scoping Review of 2014-2024 Literature.

Christopher Tacca, Arturo Vazquez Galvez, Isobel Margaret Thompson, Alexander Dawid Bincalar, Christoph Tremmel, Richard Gomer, Martin Warner, Chris Freeman, M C Schraefel

Abstract readScoping Review
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
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

9 authors.

Christopher TaccaSchool of Electronics and Computer Science, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, United Kingdom.ORCID https://orcid.org/0000-0002-8715-9166
Arturo Vazquez GalvezSchool of Electronics and Computer Science, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, United Kingdom.ORCID https://orcid.org/0009-0002-7957-990X
Isobel Margaret ThompsonSchool of Health Sciences, University of Southampton, Southampton, United Kingdom.ORCID https://orcid.org/0000-0002-2788-1675
Alexander Dawid BincalarSchool of Electronics and Computer Science, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, United Kingdom.ORCID https://orcid.org/0009-0003-4038-0503
Christoph TremmelSchool of Electronics and Computer Science, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, United Kingdom.ORCID https://orcid.org/0000-0002-0324-6626
Richard GomerSchool of Electronics and Computer Science, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, United Kingdom.ORCID https://orcid.org/0000-0001-8866-3738
Martin WarnerSchool of Health Sciences, University of Southampton, Southampton, United Kingdom.ORCID https://orcid.org/0000-0002-1483-0561
Chris FreemanSchool of Electronics and Computer Science, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, United Kingdom.ORCID https://orcid.org/0000-0003-0305-9246
M C SchraefelSchool of Electronics and Computer Science, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, United Kingdom.ORCID https://orcid.org/0000-0002-9061-7957

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe population is aging, and research on maintaining older adult independent living is growing in interest. Digital technologies have been developed to support older adults' independent living through fitness. However, reviews of current fitness technologies for older adults indicate that the success is considerably limited.

objectiveThis scoping review investigates older adult fitness by comparing current interventions to known needs and preferences of older adults from older adult-specific technology acceptance research, barriers and enablers to physical activity, and qualitative research on fitness technologies. The review questions are (1) How well do current older adult fitness technologies align with known preferences? (2) How well do current research methodologies evaluate the known needs and preferences?

methodsResearch papers from the last 10 years were searched in the ACM Digital Library, IEEE Xplore, Medline, and PsycINFO databases using keywords related to older adults, technology, and exercise. Papers were only included if they specifically evaluated fitness technologies, focused on older adults, and mentioned a specific technology used in the intervention. To evaluate the fitness interventions, an assessment tool, the Older Adult Fitness Technology Translation Assessment tool, was synthesized through literature on technology acceptance, barriers and enablers to physical activity, and qualitative research on fitness technologies. Interventions were scored by 5 reviewers using a dual-review approach.

resultsA total of 43 research papers were selected:16 from medical journals, 15 from engineering journals, 7 from human-computer interaction journals, 3 from public health, and 2 from combined computing and engineering journals. The Older Adult Fitness Technology Translation Assessment tool contained six assessment factors: (1) compatibility with lifestyle, (2) similarity with experience, (3) dignity and independence, (4) privacy concerns, (5) social support, and (6) emotion. The average scores of the 6 factors were 2.93 (SD 0.86) on compatibility with lifestyle, 3.10 (SD 0.74) on similarity to experience, 3.49 (SD 0.64) on dignity and independence, 3.17 (SD 0.86) on privacy concerns, 3.74 (SD 0.81) on short-term outcomes, 2.75 (SD 1.21) on long-term outcomes, 2.79 (SD 0.88) on social support, and 3.17 (SD 1.19) on emotion. No research paper scored a 3 or above on all 6 factors.

conclusionsThe results show a lack of alignment between the known preferences of older adults and the design and assessment of current older adult fitness technologies. Areas for growth include (1) alignment between the needs of older adults and fitness technology intervention design, (2) translation of findings from older adult design work to designs in practice, and (3) explicit usage of older adult-specific factors in research. We hypothesize that the proposed Older Adult Fitness Technology Translation Assessment tool can help bridge the gap between technological capability and real-world applicability, ultimately fostering greater acceptance, respect, and long-term success.

Indexed as

Patient PreferencePhysical FitnessAgedExerciseHumansIndependent Livingdigital healthelder physical fitnessfitness technologiesmobile phoneolder adultsphysical activity promotion

Identifiers

PMID40990372
PMCPMC12508674

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.