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JMIR Aging. 2021 Feb 19;4(1):e23313. doi: 10.2196/23313.

Mobile Apps for Older Adults: Systematic Search and Evaluation Within Online Stores.

JMIR aging

Alexandra A Portenhauser, Yannik Terhorst, Dana Schultchen, Lasse B Sander, Michael D Denkinger, Michael Stach, Natalie Waldherr, Dhayana Dallmeier, Harald Baumeister, Eva-Maria Messner

Affiliations

  1. Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University of Ulm, Ulm, Germany.
  2. Department of Psychological Research Methods, Institute of Psychology and Education, University of Ulm, Ulm, Germany.
  3. Department of Clinical and Health Psychology, Institute of Psychology and Education, University of Ulm, Ulm, Germany.
  4. Department of Rehabilitation Psychology and Psychotherapy, Institute of Psychology, University of Freiburg, Freiburg im Breisgau, Germany.
  5. Agaplesion Bethesda Clinic, Geriatric Research, University of Ulm, Ulm, Germany.
  6. Institute of Databases and Information Systems, University of Ulm, Ulm, Germany.
  7. Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States.

PMID: 33605884 PMCID: PMC8081158 DOI: 10.2196/23313

Abstract

BACKGROUND: Through the increasingly aging population, the health care system is confronted with various challenges such as expanding health care costs. To manage these challenges, mobile apps may represent a cost-effective and low-threshold approach to support older adults.

OBJECTIVE: This systematic review aimed to evaluate the quality, characteristics, as well as privacy and security measures of mobile apps for older adults in the European commercial app stores.

METHODS: In the European Google Play and App Store, a web crawler systematically searched for mobile apps for older adults. The identified mobile apps were evaluated by two independent reviewers using the German version of the Mobile Application Rating Scale. A correlation between the user star rating and overall rating was calculated. An exploratory regression analysis was conducted to determine whether the obligation to pay fees predicted overall quality.

RESULTS: In total, 83 of 1217 identified mobile apps were included in the analysis. Generally, the mobile apps for older adults were of moderate quality (mean 3.22 [SD 0.68]). Four mobile apps (5%) were evidence-based; 49% (41/83) had no security measures. The user star rating correlated significantly positively with the overall rating (r=.30, P=.01). Obligation to pay fees could not predict overall quality.

CONCLUSIONS: There is an extensive quality range within mobile apps for older adults, indicating deficits in terms of information quality, data protection, and security precautions, as well as a lack of evidence-based approaches. Central databases are needed to identify high-quality mobile apps.

©Alexandra A Portenhauser, Yannik Terhorst, Dana Schultchen, Lasse B Sander, Michael D Denkinger, Michael Stach, Natalie Waldherr, Dhayana Dallmeier, Harald Baumeister, Eva-Maria Messner. Originally published in JMIR Aging (http://aging.jmir.org), 19.02.2021.

Keywords: MARS; MARS-G; aging; apps; mHealth; mobile apps; older adults

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