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Showing content from https://pubmed.ncbi.nlm.nih.gov/30368438/ below:

Features, Behavioral Change Techniques, and Quality of the Most Popular Mobile Apps to Measure Physical Activity: Systematic Search in App Stores

Affiliations

• ¹ School of Health Sciences, University of Aveiro, Aveiro, Portugal.
• ² Center for Health Technology and Services Research, University of Aveiro, Aveiro, Portugal.
• ³ School of Technology and Management at Águeda, University of Aveiro, Aveiro, Portugal.
• ⁴ Institute of Electronics and Telematics Engineering of Aveiro, University of Aveiro, Águeda, Portugal.
• ⁵ Department of Medical Sciences, University of Aveiro, Aveiro, Portugal.

• PMID: 30368438
• PMCID: PMC6229520
• DOI: 10.2196/11281

Item in Clipboard

Patrícia Simões et al. JMIR Mhealth Uhealth. 2018.

• ¹ School of Health Sciences, University of Aveiro, Aveiro, Portugal.
• ² Center for Health Technology and Services Research, University of Aveiro, Aveiro, Portugal.
• ³ School of Technology and Management at Águeda, University of Aveiro, Aveiro, Portugal.
• ⁴ Institute of Electronics and Telematics Engineering of Aveiro, University of Aveiro, Águeda, Portugal.
• ⁵ Department of Medical Sciences, University of Aveiro, Aveiro, Portugal.

• PMID: 30368438
• PMCID: PMC6229520
• DOI: 10.2196/11281

Item in Clipboard

Background: It is estimated that 23% of adults and 55% of older adults do not meet the recommended levels of physical activity. Thus, improving the levels of physical activity is of paramount importance, but it requires the use of low-cost resources that facilitate universal access without depleting the health system. The high number of apps available constitutes an opportunity, but it also makes it quite difficult for the layperson to select the most appropriate app. Furthermore, the information available in the app stores is often insufficient, lacks quality, and is not evidence based, and the systematic reviews fail to assess app quality using standardized and validated instruments.

Objective: The objective of this study was to systematically assess the features, content, and quality of the most popular apps that can be used to measure and, potentially, promote physical activity.

Methods: Systematic searches were conducted on Apple App Store, Google Play, and Windows Phone Store between December 2017 and January 2018. Apps were included if their primary objective was to assess the aspects of physical activity, if they had a user rating of at least 4, if their number of ratings was ≥100, and if they were free. Apps meeting these criteria were independently assessed by two reviewers regarding their general and technical information, aspects of physical activity, presence of behavioral change techniques, and quality. Data were analyzed using means and SDs or frequencies and percentages.

Results: Of 51 apps included, none specified the age of the target group and only one mentioned the involvement of health professionals. Most apps offered the possibility to work in background (n=50) and allowed data sharing (n=40). Regarding physical activity, most apps measured steps and distance (n=11) or steps, distance, and time (n=17). Only 18 apps, all of which measured number of steps, followed the guidelines on recommendations for physical activity. On average, 5.5 (SD 1.8) behavioral change techniques were identified per app; the most frequently used techniques were "provide feedback on performance" (n=50) and "prompt self-monitoring of behavior" (n=50). The overall quality score was 3.88 (SD 0.34).

Conclusions: Although the overall quality of the apps was moderate, the quality of their content, particularly the use of international guidelines on physical activity, should be improved. Additionally, a more in-depth assessment of apps should be performed before releasing them for public use, particularly regarding their reliability and validity.

Keywords: behavioral change techniques; mobile phone; mobile phone app; physical activity; quality; technical features.

©Patrícia Simões, Anabela G Silva, João Amaral, Alexandra Queirós, Nelson P Rocha, Mário Rodrigues. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 26.10.2018.

PubMed Disclaimer

Conflicts of Interest: None declared.

Flowchart of the selection process…

Flowchart of the selection process for apps included in the study. PA: physical…

Flowchart of the selection process for apps included in the study. PA: physical activity.

Frequencies of the 23 behavioral…

Frequencies of the 23 behavioral change techniques presented in the included apps (N=51).

Frequencies of the 23 behavioral change techniques presented in the included apps (N=51).

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