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      What features do Dutch university students prefer in a smartphone application for promotion of physical activity? A qualitative approach

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          Abstract

          Background

          The transition from adolescence to early adulthood is a critical period in which there is a decline in physical activity (PA). College and university students make up a large segment of this age group. Smartphones may be used to promote and support PA. The purpose of this qualitative study was to explore Dutch students’ preferences regarding a PA application (PA app) for smartphones.

          Methods

          Thirty Dutch students (aged 18–25 years) used a PA app for three weeks and subsequently attended a focus group discussion (k = 5). To streamline the discussion, a discussion guide was developed covering seven main topics, including general app usage, usage and appreciation of the PA app, appreciation of and preferences for its features and the sharing of PA accomplishments through social media. The discussions were audio and video recorded, transcribed and analysed according to conventional content analysis.

          Results

          The participants, aged 21 ± 2 years, were primarily female (67%). Several themes emerged: app usage, technical aspects, PA assessment, coaching aspects and sharing through social media. Participants most often used social networking apps (e.g., Facebook or Twitter), communication apps (e.g., WhatsApp) and content apps (e.g., news reports or weather forecasts). They preferred a simple and structured layout without unnecessary features. Ideally, the PA app should enable users to tailor it to their personal preferences by including the ability to hide features. Participants preferred a companion website for detailed information about their accomplishments and progress, and they liked tracking their workout using GPS. They preferred PA apps that coached and motivated them and provided tailored feedback toward personally set goals. They appreciated PA apps that enabled competition with friends by ranking or earning rewards, but only if the reward system was transparent. They were not willing to share their regular PA accomplishments through social media unless they were exceptionally positive.

          Conclusions

          Participants prefer PA apps that coach and motivate them, that provide tailored feedback toward personally set goals and that allow competition with friends.

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          Most cited references17

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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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            A social media-based physical activity intervention: a randomized controlled trial.

            Online social networks, such as Facebook™, have extensive reach, and they use technology that could enhance social support, an established determinant of physical activity. This combination of reach and functionality makes online social networks a promising intervention platform for increasing physical activity. To test the efficacy of a physical activity intervention that combined education, physical activity monitoring, and online social networking to increase social support for physical activity compared to an education-only control. RCT. Students (n=134) were randomized to two groups: education-only controls receiving access to a physical activity-focused website (n=67) and intervention participants receiving access to the same website with physical activity self-monitoring and enrollment in a Facebook group (n=67). Recruitment and data collection occurred in 2010 and 2011; data analyses were performed in 2011. Female undergraduate students at a large southeastern public university. Intervention participants were encouraged through e-mails, website instructions, and moderator communications to solicit and provide social support related to increasing physical activity through a physical activity-themed Facebook group. Participants received access to a dedicated website with educational materials and a physical activity self-monitoring tool. The primary outcome was perceived social support for physical activity; secondary outcomes included self-reported physical activity. Participants experienced increases in social support and physical activity over time but there were no differences in perceived social support or physical activity between groups over time. Facebook participants posted 259 times to the group. Two thirds (66%) of intervention participants completing a post-study survey indicated that they would recommend the program to friends. Use of an online social networking group plus self-monitoring did not produce greater perceptions of social support or physical activity as compared to education-only controls. Given their promising features and potential reach, efforts to further understand how online social networks can be used in health promotion should be pursued. This study is registered at clinicaltrials.govNCT01421758. Copyright © 2012 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
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              Apps of steel: are exercise apps providing consumers with realistic expectations?: a content analysis of exercise apps for presence of behavior change theory.

              To quantify the presence of health behavior theory constructs in iPhone apps targeting physical activity. This study used a content analysis of 127 apps from Apple's (App Store) Health & Fitness category. Coders downloaded the apps and then used an established theory-based instrument to rate each app's inclusion of theoretical constructs from prominent behavior change theories. Five common items were used to measure 20 theoretical constructs, for a total of 100 items. A theory score was calculated for each app. Multiple regression analysis was used to identify factors associated with higher theory scores. Apps were generally observed to be lacking in theoretical content. Theory scores ranged from 1 to 28 on a 100-point scale. The health belief model was the most prevalent theory, accounting for 32% of all constructs. Regression analyses indicated that higher priced apps and apps that addressed a broader activity spectrum were associated with higher total theory scores. It is not unexpected that apps contained only minimal theoretical content, given that app developers come from a variety of backgrounds and many are not trained in the application of health behavior theory. The relationship between price and theory score corroborates research indicating that higher quality apps are more expensive. There is an opportunity for health and behavior change experts to partner with app developers to incorporate behavior change theories into the development of apps. These future collaborations between health behavior change experts and app developers could foster apps superior in both theory and programming possibly resulting in better health outcomes.
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                Author and article information

                Contributors
                a.middelweerd@vumc.nl
                d.vanderlaan1@vumc.nl
                maartje.van.stralen@vu.nl
                j.s.mollee@vu.nl
                maartje.van.stralen@vu.nl
                s.tevelde@vumc.nl
                j.brug@vumc.nl
                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
                1 March 2015
                1 March 2015
                2015
                : 12
                : 31
                Affiliations
                [ ]Department of Epidemiology & Biostatistics and the EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
                [ ]Department of Earth and Life Science and the EMGO Institute for Health and Care Research, VU University Amsterdam, Amsterdam, The Netherlands
                [ ]Department of Computer Science, VU University Amsterdam, Amsterdam, The Netherlands
                [ ]Department of Medical Humanities and the EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
                [ ]Mulier Institute, Utrecht, the Netherlands
                Article
                189
                10.1186/s12966-015-0189-1
                4359580
                25889577
                c0a6be37-78a7-4760-8f6e-f9fccf61f62d
                © Middelweerd et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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
                : 23 July 2014
                : 16 February 2015
                Categories
                Research
                Custom metadata
                © The Author(s) 2015

                Nutrition & Dietetics
                Nutrition & Dietetics

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