Evidence map›Paper›PMID 38277195›Full record

ArticleJMIR mHealth and uHealth2024

Mobile and Computer-Based Applications for Rehabilitation Monitoring and Self-Management After Knee Arthroplasty: Scoping Review.

Sabhya Pritwani, Purnima Shrivastava, Shruti Pandey, Ajit Kumar, Rajesh Malhotra, Ralph Maddison, Niveditha Devasenapathy

Open access · goldAbstract readScoping Review
In one paragraph

Article in JMIR mHealth and uHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
12.0field-weighted citation impact, top 1% of its field
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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Review
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  8. [Research progress in application of intelligent remote follow-up mode in hip and knee arthroplasty].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2025
    Review
  9. Implementation of +PERTOHealthcare (Basel, Switzerland) · 2025
    Article
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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

7 authors at 3 institutions in 2 countries.

Sabhya PritwaniDepartment of Research & Development, The George Institute for Global Health India, Delhi, India.ORCID 0000-0002-3797-2829
Purnima ShrivastavaDepartment of Research & Development, The George Institute for Global Health India, Delhi, India.ORCID 0000-0002-6370-1774
Shruti PandeyDepartment of Research & Development, The George Institute for Global Health India, Delhi, India.ORCID 0000-0002-3173-8038
Ajit KumarDepartment of Orthopaedics, All India Institute of Medical Sciences, Delhi, India.ORCID 0000-0003-4252-0576
Rajesh MalhotraDepartment of Orthopaedics, All India Institute of Medical Sciences, Delhi, India.ORCID 0000-0001-5971-003X
Ralph MaddisonDepartment of School of Exercise & Nutrition, Institute for Physical Activity and Nutrition, Deakin University, Geelong, Australia.ORCID 0000-0001-8564-5518
Niveditha DevasenapathyDepartment of Research & Development, The George Institute for Global Health India, Delhi, India.ORCID 0000-0003-3044-0560
George Institute for Global Health · INAll India Institute of Medical Sciences · INDeakin University · AU

Funding

DBT-Wellcome Trust India Alliance IA/CPHI/20/1/505224Wellcome Trust
6 · The paper itself

Abstract

backgroundSuccessful post-knee replacement rehabilitation requires adequate access to health information, social support, and periodic monitoring by a health professional. Mobile health (mHealth) and computer-based technologies are used for rehabilitation and remote monitoring. The extent of technology use and its function in post-knee replacement rehabilitation care in low and middle-income settings are unknown.

objectiveTo inform future mHealth intervention development, we conducted a scoping review to map the features and functionality of existing technologies and determine users' perspectives on telerehabilitation and technology for self-management.

methodsWe followed the Joanna Briggs Institute methodology for scoping reviews. We searched the Embase, Medline, PsycINFO via OVID, and Cochrane Central Register of Controlled Trials databases for manuscripts published from 2001 onward. We included original research articles reporting the use of mobile or computer-based technologies by patients, health care providers, researchers, or family members. Studies were divided into the following 3 categories based on the purpose: validation studies, clinical evaluation, and end user feedback. We extracted general information on study design, technology features, proposed function, and perspectives of health care providers and patients. The protocol for this review is accessible in the Open Science Framework.

resultsOf the 5960 articles, 158 that reported from high-income settings contributed to the qualitative summary (64 studies on mHealth or telerehabilitation programs, 28 validation studies, 38 studies describing users' perceptions). The highest numbers of studies were from Europe or the United Kingdom and North America regarding the use of a mobile app with or without wearables and reported mainly in the last decade. No studies were from low and middle-income settings. The primary functions of technology for remote rehabilitation were education to aid recovery and enable regular, appropriate exercises; monitoring progress of pain (n=19), activity (n=20), and exercise adherence (n=30); 1 or 2-way communication with health care professionals to facilitate the continuum of care (n=51); and goal setting (n=23). Assessment of range of motion (n=16) and gait analysis (n=10) were the commonly validated technologies developed to incorporate into a future rehabilitation program. Few studies (n=14) reported end user involvement during the development stage. We summarized the reasons for satisfaction and dissatisfaction among users across various technologies.

conclusionsSeveral existing mobile and computer-based technologies facilitate post-knee replacement rehabilitation care for patients and health care providers. However, they are limited to high-income settings and may not be extrapolated to low-income settings. A systematic needs assessment of patients undergoing knee replacement and health care providers involved in rehabilitation, involving end users at all stages of development and evaluation, with clear reporting of the development and clinical evaluation can make post-knee replacement rehabilitation care in resource-poor settings accessible and cost-effective.

Indexed as

Arthroplasty, Replacement, KneeMobile ApplicationsSelf-ManagementTelemedicineTelerehabilitationHumansarthroplastydevelopmentkneeknee arthroplastyknee replacementmHealthmHealth interventionmonitoringrehabilitationscoping reviewself-managementsocial supporttelerehabilitation

Identifiers

PMID38277195
PMCPMC10858429
OpenAlexW4391263713

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.