Literature DB >> 27868438

A standardized review of smartphone applications to promote balance for older adults.

Angelica Reyes1, Pei Qin1, Cary A Brown1.   

Abstract

BACKGROUND: Balance is one of the risk factors for falls in older adults. The use of smartphone applications (apps) related to health (mHealth) is increasing and, while there is potential for apps to be used as a self-managed balance intervention, many healthcare providers are concerned about the content and credibility of mHealth apps overall.
PURPOSE: This study evaluates the quality of balance promoting apps and identifies strengths and areas of concern to assist healthcare providers in recommending these resources.
MATERIALS AND METHODS: Balance apps for the general public, offered on the iPhone Operating System (iOS) and Android platforms, were evaluated using the Mobile Application Rating Scale (MARS).
RESULTS: Five iOS apps met the inclusion criteria. The mean scores for each of the domains in MARS were: Engagement (3.32), Information (3.7), Functionality (3.8), and Esthetics (3.8). Overall, one app (UStabilize) received a rating of 4.43 in MARS five-point scale, which was considered "good". Other apps in the review demonstrated acceptable quality.
CONCLUSIONS: The reviewed balance apps targeted to improve or maintain physical balance were of acceptable quality. Apps address many current issues older adults have to accessing rehabilitation services and, as such, may be particularly useful for this group. Future research should focus on assessing and comparing app efficacy. Development of balance apps for the Android platform is also necessary. Implications for Rehabilitation Given the availability and accessibility of various mHealth apps and the increasing mobile device usage among older adults, mobile apps are a promising avenue for delivering rehabilitation interventions, such as balance training, to older adults. Smartphone apps exist for balance training but overall confidence in health apps within the healthcare community is low and rigorous evaluation is required. A range of apps exist that demonstrate acceptable to good quality and stakeholders should work towards having these apps listed in credible mHealth clearinghouses.

Keywords:  app; applications; balance; mHealth; older adult; rehabilitation; smartphone

Mesh:

Year:  2016        PMID: 27868438     DOI: 10.1080/09638288.2016.1250124

Source DB:  PubMed          Journal:  Disabil Rehabil        ISSN: 0963-8288            Impact factor:   3.033


  12 in total

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Journal:  J Appl Gerontol       Date:  2018-07-26

Review 2.  What Works Best to Engage Participants in Mobile App Interventions and e-Health: A Scoping Review.

Authors:  Ingrid Oakley-Girvan; Reem Yunis; Michelle Longmire; Jessey Schwartz Ouillon
Journal:  Telemed J E Health       Date:  2021-10-11       Impact factor: 5.033

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Authors:  William B Hansen; Lawrence M Scheier
Journal:  JMIR Mhealth Uhealth       Date:  2019-07-29       Impact factor: 4.773

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Authors:  Yu Heng Kwan; Wei Jie Ong; Mengfei Xiong; Ying Ying Leung; Jie Kie Phang; Charmaine Tze May Wang; Warren Fong
Journal:  JMIR Mhealth Uhealth       Date:  2019-10-28       Impact factor: 4.773

5.  The Validity, Reliability, and Sensitivity of a Smartphone-Based Seated Postural Control Assessment in Wheelchair Users: A Pilot Study.

Authors:  Mikaela L Frechette; Libak Abou; Laura A Rice; Jacob J Sosnoff
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6.  Mobile Apps for Older Adults: Systematic Search and Evaluation Within Online Stores.

Authors:  Alexandra A Portenhauser; Yannik Terhorst; Dana Schultchen; Lasse B Sander; Michael D Denkinger; Michael Stach; Natalie Waldherr; Dhayana Dallmeier; Harald Baumeister; Eva-Maria Messner
Journal:  JMIR Aging       Date:  2021-02-19

7.  Selecting and Evaluating Mobile Health Apps for the Healthy Life Trajectories Initiative: Development of the eHealth Resource Checklist.

Authors:  Leigh M Vanderloo; Sarah Carsley; Payal Agarwal; Flavia Marini; Cindy-Lee Dennis; Catherine Birken
Journal:  JMIR Mhealth Uhealth       Date:  2021-12-02       Impact factor: 4.773

8.  Feasibility and Adoption of a Focused Digital Wellness Program in Older Adults.

Authors:  Eric Tam; Pedro Kondak Villas Boas; Fernando Ruaro; Juliane Flesch; Jennifer Wu; Amelia Thomas; James Li; Felipe Lopes
Journal:  Geriatrics (Basel)       Date:  2021-05-19

9.  Geriatric Helper: An mHealth Application to Support Comprehensive Geriatric Assessment.

Authors:  Samuel Silva; Rafael Felgueiras; Ilídio C Oliveira
Journal:  Sensors (Basel)       Date:  2018-04-22       Impact factor: 3.576

10.  The App Behavior Change Scale: Creation of a Scale to Assess the Potential of Apps to Promote Behavior Change.

Authors:  Fiona H McKay; Sarah Slykerman; Matthew Dunn
Journal:  JMIR Mhealth Uhealth       Date:  2019-01-25       Impact factor: 4.773

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