8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The use of social features in mobile health interventions to promote physical activity: a systematic review

      review-article
      ,
      NPJ Digital Medicine
      Nature Publishing Group UK
      Public health, Lifestyle modification

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Mobile health (mHealth) technologies have increasingly been used in interventions to promote physical activity (PA), yet, they often have high attrition rates. Integrating social features into mHealth has the potential to engage users; however, little is known about the efficacy and user engagement of such interventions. Thus, the aim of this systematic review was to characterize and evaluate the impact of interventions integrating social features in mHealth interventions to promote PA. During database screening, studies were included if they involved people who were exposed to a mHealth intervention with social features, to promote PA. We conducted a narrative synthesis of included studies and a meta-analysis of randomized controlled trials (RCTs). Nineteen studies were included: 4 RCTs, 10 quasi-experimental, and 5 non-experimental studies. Most experimental studies had retention rates above 80%, except two. Social features were often used to provide social support or comparison. The meta-analysis found a non-significant effect on PA outcomes [standardized difference in means = 0.957, 95% confidence interval −1.09 to 3.00]. Users’ preferences of social features were mixed: some felt more motivated by social support and competition, while others expressed concerns about comparison, indicating that a one-size-fits-all approach is insufficient. In summary, this is an emerging area of research, with limited evidence suggesting that social features may increase user engagement. However, due to the quasi-experimental and multi-component nature of most studies, it is difficult to determine the specific impact of social features, suggesting the need for more robust studies to assess the impact of different intervention components.

          Related collections

          Most cited references25

          • Record: found
          • Abstract: found
          • Article: not found

          Dose response between physical activity and risk of coronary heart disease: a meta-analysis.

          No reviews have quantified the specific amounts of physical activity required for lower risks of coronary heart disease when assessing the dose-response relation. Instead, previous reviews have used qualitative estimates such as low, moderate, and high physical activity. We performed an aggregate data meta-analysis of epidemiological studies investigating physical activity and primary prevention of CHD. We included prospective cohort studies published in English since 1995. After reviewing 3194 abstracts, we included 33 studies. We used random-effects generalized least squares spline models for trend estimation to derive pooled dose-response estimates. Among the 33 studies, 9 allowed quantitative estimates of leisure-time physical activity. Individuals who engaged in the equivalent of 150 min/wk of moderate-intensity leisure-time physical activity (minimum amount, 2008 U.S. federal guidelines) had a 14% lower coronary heart disease risk (relative risk, 0.86; 95% confidence interval, 0.77 to 0.96) compared with those reporting no leisure-time physical activity. Those engaging in the equivalent of 300 min/wk of moderate-intensity leisure-time physical activity (2008 U.S. federal guidelines for additional benefits) had a 20% (relative risk, 0.80; 95% confidence interval, 0.74 to 0.88) lower risk. At higher levels of physical activity, relative risks were modestly lower. People who were physically active at levels lower than the minimum recommended amount also had significantly lower risk of coronary heart disease. There was a significant interaction by sex (P=0.03); the association was stronger among women than men. These findings provide quantitative data supporting US physical activity guidelines that stipulate that "some physical activity is better than none" and "additional benefits occur with more physical activity."
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            When and Why Incentives (Don't) Work to Modify Behavior

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              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.
                Bookmark

                Author and article information

                Contributors
                (+61) 2 9850 2475 , huong-ly.tong@students.mq.edu.au
                Journal
                NPJ Digit Med
                NPJ Digit Med
                NPJ Digital Medicine
                Nature Publishing Group UK (London )
                2398-6352
                4 September 2018
                4 September 2018
                2018
                : 1
                : 43
                Affiliations
                ISNI 0000 0001 2158 5405, GRID grid.1004.5, Centre for Health Informatics, , Australian Institute of Health Innovation, Macquarie University, ; Sydney, NSW Australia
                Article
                51
                10.1038/s41746-018-0051-3
                6550193
                31304323
                215dfa10-e90f-4d75-9f2b-0ac78315b742
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 April 2018
                : 11 August 2018
                : 13 August 2018
                Funding
                Funded by: International Macquarie University Research Training Pathway Master of Research (iMQRTPMRES) Scholarship (2016302).
                Categories
                Review Article
                Custom metadata
                © The Author(s) 2018

                public health,lifestyle modification
                public health, lifestyle modification

                Comments

                Comment on this article