Evidence map›Paper›PMID 41985075›Full record

ArticleJMIR rehabilitation and assistive technologies2026

Effects of an Exercise-Assisting Mobile App (Osteoarthritis-Rehabilitation Assistant [O-RA]) on Rehabilitation Outcomes in Older Adults: Randomized Controlled Parallel Clinical Trial.

Pajaree Sornmayura, Sintip Pattanakuhar, Napaschol Intapan, Krittipat Tragoolpua, Kaewkla Sroykabkaew, Rungkan Wangboon, Krittipong Wachirangkul, Sartita Wannarat, Jakkrit Klaphajone

Abstract read
In one paragraph

Article in JMIR rehabilitation and assistive technologies, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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.

Pajaree SornmayuraDepartment of Rehabilitation Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID http://orcid.org/0009-0006-8327-7196
Sintip PattanakuharDepartment of Rehabilitation Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID http://orcid.org/0000-0003-2568-5897
Napaschol IntapanDepartment of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand.ORCID http://orcid.org/0009-0008-1367-8423
Krittipat TragoolpuaDepartment of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand.ORCID http://orcid.org/0009-0006-4180-789X
Kaewkla SroykabkaewDepartment of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand.ORCID http://orcid.org/0009-00018640-5740
Rungkan WangboonThe Prince Royal's College, Chiang Mai, Thailand.ORCID http://orcid.org/0009-0001-6378-897
Krittipong WachirangkulThe Prince Royal's College, Chiang Mai, Thailand.ORCID http://orcid.org/0009-0000-3203-3649
Sartita WannaratThe Prince Royal's College, Chiang Mai, Thailand.ORCID http://orcid.org/0009-0002-5626-9853
Jakkrit KlaphajoneDepartment of Rehabilitation Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID http://orcid.org/0000-0001-6545-6437

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mobile apps and biofeedback using motion analysis have both been used separately to increase compliance with exercise programs. We developed a mobile app, Osteoarthritis-Rehabilitation Assistant (O-RA), that uses motion analysis technology in the mobile app to assist older adults with performing a knee exercise program. Objective: This study aimed to evaluate the effects of the O-RA app on the compliance and correctness of the exercise program by older adults. Methods: We conducted an assessor-blind, parallel-design, randomized controlled trial with 40 older adults (aged 60 years or older) who had no symptoms and no diagnosis of knee osteoarthritis. Participants were divided into 2 groups: O-RA app (intervention) group and standard treatment (control) group. Both groups were taught 4 types of exercise programs by a physical therapist for 15 minutes and were instructed to do exercises at home every day for 1 week. The number of exercises, the percentage between observed and prescribed exercises, the correctness of exercises, and overall pain during the program were assessed in both groups. Results: The control group had significantly higher compliance with the exercise program than the intervention group (t38=3.5044, P=.001). There was no statistically significant difference in the correctness of the exercise program between the intervention and control groups. The difficulty of use and satisfaction were 47 and 59, respectively, out of the full score of 100. The main problems were the instability and the difficulty using the app. Conclusions: In older adults without knee osteoarthritis symptoms or diagnosis, the O-RA app was not a facilitator but a barrier to the lower extremity exercise program. An updated version, aiming to increase the stability and make it more user-friendly, should be developed; however, more comprehensive data, including qualitative user feedback and standardized usability metrics, will be needed to effectively guide its design.

Indexed as

compliancekneemobile appmotion analysisosteoarthritisrehabilitation

Identifiers

PMID41985075
PMCPMC13082571

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LicenceCC BY
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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.