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Using consumer wearables to estimate physical activity of nursing home residents with dementia
Daniela Gawehns, Suzanne Portegijs, Adriana Petronella Anna van Beek, Matthijs van Leeuwen. Exploration of Digital Health Technologies, 2025-01-16
Topic: Risk, prevention and care in population studies
We showed that consumer wearables are a valid tool for long-term data collection in this vulnerable patient population. Regarding the movement intensity, the data collected by fitness trackers is overall in accordance with the data collected with the observational tool. Regarding the type of movement, we concluded that the automatic activity classification on the wearables is not yet ready for use with a mostly sedentary patient population.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Gawehns, D., Portegijs, S., van Beek, A. P. A., & van Leeuwen, M. (2025). Using consumer wearables to estimate physical activity of nursing home residents with dementia. Exploration of Digital Health Technologies. https://doi.org/10.37349/edht.2025.101137
Vancouver
Gawehns D, Portegijs S, van Beek APA, van Leeuwen M. Using consumer wearables to estimate physical activity of nursing home residents with dementia. Exploration of Digital Health Technologies. 2025. doi:10.37349/edht.2025.101137.
BibTeX
@article{gawehns2025-94962c8b,
author = {Gawehns, Daniela and Portegijs, Suzanne and van Beek, Adriana Petronella Anna and van Leeuwen, Matthijs},
title = {{Using consumer wearables to estimate physical activity of nursing home residents with dementia}},
journal = {Exploration of Digital Health Technologies},
year = {2025},
doi = {10.37349/edht.2025.101137},
url = {https://doi.org/10.37349/edht.2025.101137}
}
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
Key findings
- We showed that consumer wearables are a valid tool for long-term data collection in this vulnerable patient population.
- Regarding the movement intensity, the data collected by fitness trackers is overall in accordance with the data collected with the observational tool.
- Regarding the type of movement, we concluded that the automatic activity classification on the wearables is not yet ready for use with a mostly sedentary patient population.
Why it matters
Consumer wearables were found valid for long-term collection of movement intensity data in nursing home residents with dementia, but automatic classification of movement type was not yet ready for this mostly sedentary group. This concerns monitoring activity, not treating, curing or preventing Alzheimer's disease.
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Study details
- Participants16
- Evidence strengthLow
How this study scored 39/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Exploration of Digital Health Technologies) |
| Journal's citation record | 0 / 4 | Exploration of Digital Health Technologies: journal h-index 10 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 1 / 4 | 16 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 3 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.0 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 2 / 6 | Cited 1.1× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 3 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Matthijs van Leeuwen: h-index 26 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Leiden University: institution h-index 926 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 4 institution(s) in 3 countries |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 2 / 2 | Free to read |
| Total | 39 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.37349/edht.2025.101137
- Original source →
- Free full text: Exploration of Digital Health Technologies →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
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