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The effects of a mobile application-based dementia care intelligent recommender system on caregivers of people with dementia: a randomized controlled trial
Yue Sun, Mengmeng Ji, Minmin Leng, Baoyu Chen, Shuai Liu, Zhiwen Wang. Age and Ageing, 2026-01-22
Topic: Risk, prevention and care in population studies
The caregivers in intervention group showed significant reductions in distress scores for dressing, personal hygiene, communication, and behavioural and psychological care problems at both the 6th and 12th week assessments. Caregiver burden scores in the intervention group showed a continuous decline from baseline to week 6 (MD = -1.61) and further to week 12 (MD = -3.43) (P < .05). Within-group analyses showed that depressive symptom scores remained largely stable from baseline to week 6 and week 12 in both the intervention and control groups, with no significant pre-post changes detected. A significant between-group difference was found in the total number of safety-related events (P = .037). In summary, this RCT showed that the DCIRS may reduce caregivers' distress related to care problems and lessen caregiver burden. Although depressive symptoms did not improve significantly, further research is needed to assess long-term effects and clarify the mechanisms underlying remote, personalized interventions such as the DCIRS. REGISTRATION: The trial was registered at the Chinese Clinical Trials Registry (ChiCTR2200066087).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Sun, Y., Ji, M., Leng, M., Chen, B., Liu, S., & Wang, Z. (2026). The effects of a mobile application-based dementia care intelligent recommender system on caregivers of people with dementia: a randomized controlled trial. Age and Ageing. https://doi.org/10.1093/ageing/afag021
Vancouver
Sun Y, Ji M, Leng M, Chen B, Liu S, Wang Z. The effects of a mobile application-based dementia care intelligent recommender system on caregivers of people with dementia: a randomized controlled trial. Age and Ageing. 2026. doi:10.1093/ageing/afag021. PMID: 41642176.
BibTeX
@article{sun2026-41642176,
author = {Sun, Yue and Ji, Mengmeng and Leng, Minmin and Chen, Baoyu and Liu, Shuai and Wang, Zhiwen},
title = {{The effects of a mobile application-based dementia care intelligent recommender system on caregivers of people with dementia: a randomized controlled trial}},
journal = {Age and Ageing},
year = {2026},
doi = {10.1093/ageing/afag021},
pmid = {41642176},
url = {https://doi.org/10.1093/ageing/afag021}
}
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
- The caregivers in intervention group showed significant reductions in distress scores for dressing, personal hygiene, communication, and behavioural and psychological care problems at both the 6th and 12th week assessments.
- Caregiver burden scores in the intervention group showed a continuous decline from baseline to week 6 (MD = -1.61) and further to week 12 (MD = -3.43) (P < .05).
- Within-group analyses showed that depressive symptom scores remained largely stable from baseline to week 6 and week 12 in both the intervention and control groups, with no significant pre-post changes detected.
- A significant between-group difference was found in the total number of safety-related events (P = .037).
- In summary, this RCT showed that the DCIRS may reduce caregivers' distress related to care problems and lessen caregiver burden.
Why it matters
In this randomized controlled trial, a mobile app-based recommender system reduced caregivers' distress over care problems and lessened caregiver burden at 6 and 12 weeks. Depressive symptoms did not improve significantly, and the authors say further research is needed on long-term effects and mechanisms.
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Study details
- Participants125
- Evidence strengthLow
How this study scored 44/100
Published in a peer-reviewed journal. Scored zero for study design and effect reported because the record does not state it. We have no data on senior author's track record, so that was left out: it earned 42 of the 96 points we could judge it on, which is 44 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Age and Ageing) |
| Journal's citation record | 2 / 4 | Age and Ageing: journal h-index 231 (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 | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 2 / 4 | 125 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 | 1 / 2 | Randomised (as stated in the record) |
| Times cited | 1 / 7 | Cited 2 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.0 citations a year over 2 year(s) since 2026 |
| Impact for its field and year | 4 / 6 | Cited 9.5× 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 | 0 / 4 | Cited 2 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | — / 4 | OpenAlex's profile for last-listed author Zhiwen Wang holds only 2 work(s), too few to judge a track record — left out of this score |
| Institution's track record | 1 / 3 | Peking University: institution h-index 1,098 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 6 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41642176) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 42 / 96 | Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 42 of the 96 points we could judge it on is 44 out of 100. |
| Total | 44 / 100 | — |
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