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      A review and content analysis of engagement, functionality, aesthetics, information quality, and change techniques in the most popular commercial apps for weight management

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          Abstract

          Background

          There are thousands of apps promoting dietary improvement, increased physical activity (PA) and weight management. Despite a growing number of reviews in this area, popular apps have not been comprehensively analysed in terms of features related to engagement, functionality, aesthetics, information quality, and content, including the types of change techniques employed.

          Methods

          The databases containing information about all Health and Fitness apps on GP and iTunes (7,954 and 25,491 apps) were downloaded in April 2015. Database filters were applied to select the most popular apps available in both stores. Two researchers screened the descriptions selecting only weight management apps. Features, app quality and content were independently assessed using the Mobile App Rating Scale (MARS) and previously-defined categories of techniques relevant to behaviour change. Inter-coder reliabilities were calculated, and correlations between features explored.

          Results

          Of the 23 popular apps included in the review 16 were free (70 %), 15 (65 %) addressed weight control, diet and PA combined; 19 (83 %) allowed behavioural tracking. On 5-point MARS scales, apps were of average quality (Md = 3.2, IQR = 1.4); “functionality” (Md = 4.0, IQR = 1.1) was the highest and “information quality” (Md = 2.0, IQR = 1.1) was the lowest domain. On average, 10 techniques were identified per app (range: 1–17) and of the 34 categories applied, goal setting and self-monitoring techniques were most frequently identified. App quality was positively correlated with number of techniques included ( rho = .58, p < .01) and number of “technical” features ( rho = .48, p < .05), which was also associated with the number of techniques included ( rho = .61, p < .01). Apps that provided tracking used significantly more techniques than those that did not. Apps with automated tracking scored significantly higher in engagement, aesthetics, and overall MARS scores. Those that used change techniques previously associated with effectiveness (i.e., goal setting, self-monitoring and feedback) also had better “information quality”.

          Conclusions

          Popular apps assessed have overall moderate quality and include behavioural tracking features and a range of change techniques associated with behaviour change. These apps may influence behaviour, although more attention to information quality and evidence-based content are warranted to improve their quality.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12966-016-0359-9) contains supplementary material, which is available to authorized users.

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          Most cited references23

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          The role of exercise and physical activity in weight loss and maintenance.

          This review explores the role of physical activity (PA) and exercise training (ET) in the prevention of weight gain, initial weight loss, weight maintenance, and the obesity paradox. In particular, we will focus the discussion on the expected initial weight loss from different ET programs, and explore intensity/volume relationships. Based on the present literature, unless the overall volume of aerobic ET is very high, clinically significant weight loss is unlikely to occur. Also, ET also has an important role in weight regain after initial weight loss. Overall, aerobic ET programs consistent with public health recommendations may promote up to modest weight loss (~2 kg), however the weight loss on an individual level is highly heterogeneous. Clinicians should educate their patients on reasonable expectations of weight loss based on their physical activity program and emphasize that numerous health benefits occur from PA programs in the absence of weight loss. © 2014.
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            Behavior Change Techniques Implemented in Electronic Lifestyle Activity Monitors: A Systematic Content Analysis

            Background Electronic activity monitors (such as those manufactured by Fitbit, Jawbone, and Nike) improve on standard pedometers by providing automated feedback and interactive behavior change tools via mobile device or personal computer. These monitors are commercially popular and show promise for use in public health interventions. However, little is known about the content of their feedback applications and how individual monitors may differ from one another. Objective The purpose of this study was to describe the behavior change techniques implemented in commercially available electronic activity monitors. Methods Electronic activity monitors (N=13) were systematically identified and tested by 3 trained coders for at least 1 week each. All monitors measured lifestyle physical activity and provided feedback via an app (computer or mobile). Coding was based on a hierarchical list of 93 behavior change techniques. Further coding of potentially effective techniques and adherence to theory-based recommendations were based on findings from meta-analyses and meta-regressions in the research literature. Results All monitors provided tools for self-monitoring, feedback, and environmental change by definition. The next most prevalent techniques (13 out of 13 monitors) were goal-setting and emphasizing discrepancy between current and goal behavior. Review of behavioral goals, social support, social comparison, prompts/cues, rewards, and a focus on past success were found in more than half of the systems. The monitors included a range of 5-10 of 14 total techniques identified from the research literature as potentially effective. Most of the monitors included goal-setting, self-monitoring, and feedback content that closely matched recommendations from social cognitive theory. Conclusions Electronic activity monitors contain a wide range of behavior change techniques typically used in clinical behavioral interventions. Thus, the monitors may represent a medium by which these interventions could be translated for widespread use. This technology has broad applications for use in clinical, public health, and rehabilitation settings.
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              Apps to promote physical activity among adults: a review and content analysis

              Background In May 2013, the iTunes and Google Play stores contained 23,490 and 17,756 smartphone applications (apps) categorized as Health and Fitness, respectively. The quality of these apps, in terms of applying established health behavior change techniques, remains unclear. Methods The study sample was identified through systematic searches in iTunes and Google Play. Search terms were based on Boolean logic and included AND combinations for physical activity, healthy lifestyle, exercise, fitness, coach, assistant, motivation, and support. Sixty-four apps were downloaded, reviewed, and rated based on the taxonomy of behavior change techniques used in the interventions. Mean and ranges were calculated for the number of observed behavior change techniques. Using nonparametric tests, we compared the number of techniques observed in free and paid apps and in iTunes and Google Play. Results On average, the reviewed apps included 5 behavior change techniques (range 2–8). Techniques such as self-monitoring, providing feedback on performance, and goal-setting were used most frequently, whereas some techniques such as motivational interviewing, stress management, relapse prevention, self-talk, role models, and prompted barrier identification were not. No differences in the number of behavior change techniques between free and paid apps, or between the app stores were found. Conclusions The present study demonstrated that apps promoting physical activity applied an average of 5 out of 23 possible behavior change techniques. This number was not different for paid and free apps or between app stores. The most frequently used behavior change techniques in apps were similar to those most frequently used in other types of physical activity promotion interventions.
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                Author and article information

                Contributors
                marco.bardus@gmail.com
                s.b.vanbeurden@exeter.ac.uk
                jane.smith@exeter.ac.uk
                c.abraham@exeter.ac.uk
                Journal
                Int J Behav Nutr Phys Act
                Int J Behav Nutr Phys Act
                The International Journal of Behavioral Nutrition and Physical Activity
                BioMed Central (London )
                1479-5868
                10 March 2016
                10 March 2016
                2016
                : 13
                : 35
                Affiliations
                [ ]Department of Health Promotion and Community Health, American University of Beirut, Riad El Solh, Beirut, 1107 2020 Lebanon
                [ ]Psychology Applied to Health group, University of Exeter Medical School, St Luke’s Campus, Heavitree Road, Exeter, EX1 2LU United Kingdom
                Author information
                http://orcid.org/0000-0002-0707-7196
                Article
                359
                10.1186/s12966-016-0359-9
                4785735
                26964880
                883f87c1-b247-441a-91f6-8d2bd7c946ec
                © Bardus et al. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 3 November 2015
                : 4 March 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (CH);
                Award ID: 152290
                Award Recipient :
                Categories
                Review
                Custom metadata
                © The Author(s) 2016

                Nutrition & Dietetics
                smartphone,mobile apps,mobile health (mhealth),behaviour change techniques,weight loss,weight management

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