Desired Features of Smartphone Applications Promoting Physical Activity (original) (raw)
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Tailored Mobile Phone App Promoting Daily Physical Activity: A Randomized Trial
Journal of Sport and Health Research
Background/Objective: Do adults better adhere to daily physical activity when they were provided a personalized program an App delivered compared to single pedometer feedback? An experimental study including randomized parallel group with or without the personalized program aimed at assessing the effect of a PA App designed to enhance daily physical activity in healthy adults. Methods: The participants were 30 adults (12 men and 18 women), aged between 35 and 60 years (45.33 ± 7.6). They were randomly assigned to a control group (CG, N=15), or to an experimental group (EG, N=15). Participants from the EG received their program from an app linked to a web-platform and benefited from daily walking step-count feedback, individually adapted goals per week, behavioral advices and health information. Participants from the CG only benefited of daily walking step-count on their smartphones. Results: The primary outcomes measures were number of walking steps per week; they were collected at...
Personal and Ubiquitous Computing, 2017
Despite the well-known health benefits of physical activity, a large proportion of the population does not meet the guidelines. Hence, effective and widely accessible interventions to increase levels of physical activity are needed. Over the recent years, the number of health and fitness apps has grown rapidly, and they might form part of the solution to the widespread physical inactivity. However, it remains unclear to which extent they make use of the possibilities of mobile technology and form real e-coaching systems. This study aims to investigate the current landscape of smartphone apps that promote physical activity for healthy adults. Therefore, we present a framework to rate the extent to which such apps incorporate technological features. And, we show that the physical activity promotion apps included in the review implemented an average of approximately eight techniques and functions. The features that were implemented most often were user input, textual/numerical overviews of the user's behavior and progress, sharing achievements or workouts in social networks, and general advice on physical activity. The features that were present least often were adaptation, integration with external sources, and encouragement through gamification, some form of punishment or the possibility to contact an expert. Overall, the results indicate that apps can be improved substantially in terms of their utilization of the possibilities that current mobile technology offers.
The role of smartphones in encouraging physical activity in adults
International Journal of General Medicine, 2017
Lack of physical activity is a global public health issue. Behavioral change interventions utilizing smartphone applications (apps) are considered a potential solution. The purpose of this literature review was to: 1) determine whether smartphone-based interventions encourage the initiation of, and participation in, physical activity; 2) explore the success of interventions in different populations; and 3) examine the key factors of the interventions that successfully encouraged physical activity. Eight databases (Medline, Scopus, EBM Reviews-Cochrane Central Register of Controlled Trials, EBM Reviews-Cochrane Database of Systematic Reviews, PsycInfo, SportDISCUS, CINAHL, and EMBASE) were searched and studies reporting physical activity outcomes following interventions using smartphone apps in adults were included in the narrative review. Results were mixed with eight studies reporting increased physical activity and ten reporting no change. Interventions did not appear to be successful in specific populations defined by age, sex, country, or clinical diagnosis. There was no conclusive evidence that a specific behavioral theory or behavioral change technique was superior in eliciting behavioral change. The literature remains limited primarily to short-term studies, many of which are underpowered feasibility or pilot studies; therefore, many knowledge gaps regarding the effectiveness of smartphone apps in encouraging physical activity remain. Robust studies that can accommodate the fast pace of the technology industry are needed to examine outcomes in large populations.
PloS one, 2016
While there has been an explosion of mobile device applications (apps) promoting healthful behaviors, including physical activity and sedentary patterns, surprisingly few have been based explicitly on strategies drawn from behavioral theory and evidence. This study provided an initial 8-week evaluation of three different customized physical activity-sedentary behavior apps drawn from conceptually distinct motivational frames in comparison with a commercially available control app. Ninety-five underactive adults ages 45 years and older with no prior smartphone experience were randomized to use an analytically framed app, a socially framed app, an affectively framed app, or a diet-tracker control app. Daily physical activity and sedentary behavior were measured using the smartphone's built-in accelerometer and daily self-report measures. Mixed-effects models indicated that, over the 8-week period, the social app users showed significantly greater overall increases in weekly accele...
Mobile and Wearable Device Features that Matter in Promoting Physical Activity
Journal of Mobile Technology in Medicine, 2016
Background: As wearable sensors/devices become increasingly popular to promote physical activity (PA), research is needed to examine how and which components of these devices people use to increase their PA levels. Aims: (1) To assess usability and level of engagement with the Fitbit One and daily SMS-based prompts in a 6-week PA intervention, and (2) to examine whether use/ level of engagement with specific intervention components were associated with PA change. Methods: Data were analyzed from a randomized controlled trial that compared (1) a wearable sensor/ device (Fitbit One) plus SMS-based PA prompts, and (2) Fitbit One only, among overweight/ obese adults (N067). We calculated average scores from Likert-type response items that assessed usability and level of engagement with device features (e.g., tracker, website, mobile app, and SMS-based prompts), and assessed whether such factors were associated with change in steps/day (using Actigraph GT3X'). Results: Participants reported the Fitbit One was easy to use and the tracker helped to be more active. Those who used the Fitbit mobile app (36%) vs. those who did not (64%) had an increase in steps at 6-week follow-up, even after adjusting for previous web/app use: '545 steps/ day (SE 0 265) vs. (28 steps/ day (SE 0242) (p 0.04). Conclusions: Level of engagement with the Fitbit One, particularly the mobile app, was associated with increased steps. Mobile apps can instantly display summaries of PA performance and could optimize self-regulation to activate change. More research is needed to determine whether such modalities might be cost-effective in future intervention research and practice.
PLoS ONE, 2013
Mobile devices are a promising channel for delivering just-in-time guidance and support for improving key daily health behaviors. Despite an explosion of mobile phone applications aimed at physical activity and other health behaviors, few have been based on theoretically derived constructs and empirical evidence. Eighty adults ages 45 years and older who were insufficiently physically active, engaged in prolonged daily sitting, and were new to smartphone technology, participated in iterative design development and feasibility testing of three daily activity smartphone applications based on motivational frames drawn from behavioral science theory and evidence. An ''analytically'' framed custom application focused on personalized goal setting, self-monitoring, and active problem solving around barriers to behavior change. A ''socially'' framed custom application focused on social comparisons, norms, and support. An ''affectively'' framed custom application focused on operant conditioning principles of reinforcement scheduling and emotional transference to an avatar, whose movements and behaviors reflected the physical activity and sedentary levels of the user. To explore the applications' initial efficacy in changing regular physical activity and leisure-time sitting, behavioral changes were assessed across eight weeks in 68 participants using the CHAMPS physical activity questionnaire and the Australian sedentary behavior questionnaire. User acceptability of and satisfaction with the applications was explored via a post-intervention user survey. The results indicated that the three applications were sufficiently robust to significantly improve regular moderate-to-vigorous intensity physical activity and decrease leisure-time sitting during the 8-week behavioral adoption period. Acceptability of the applications was confirmed in the post-intervention surveys for this sample of midlife and older adults new to smartphone technology. Preliminary data exploring sustained use of the applications across a longer time period yielded promising results. The results support further systematic investigation of the efficacy of the applications for changing these key health-promoting behaviors.
BACKGROUND: Physical activity apps are commonly used to increase levels of activity and health status. To date, the focus of research has been to determine the potential of apps to influence behavior, to ascertain the efficacy of a limited number of apps to change behavior, and to identify the characteristics of apps that users prefer. OBJECTIVE: The purpose of this study was to identify the mechanisms by which the use of physical activity apps may influence the users' physical activity behavior. METHODS: This study used a cross-sectional survey of users of health-related physical activity apps during the past 6 months. An electronic survey was created in Qualtrics' Web-based survey software and deployed on Amazon Mechanical Turk. Individuals who had used at least one physical activity app in the past 6 months were eligible to respond. The final sample comprised 207 adults living in the United States. 86.0% (178/207) of respondents were between the ages of 26 and 54 years, with 51.2% (106/207) of respondents being female. Behavior change theory informed the creation of 20 survey items relating to the mechanisms of behavior change. Respondents also reported about engagement with the apps, app likeability, and physical activity behavior. RESULTS: Respondents reported that using a physical activity app in the past 6 months resulted in a change in their attitudes, beliefs, perceptions, and motivation. Engagement with the app (P<.001), frequency of app use (P=.03), and app price (P=.01) were related to the reported impact of the behavior change theory or mechanisms of change. The mechanisms of change were associated with self-reported physical activity behaviors (P<.001). CONCLUSIONS: The findings from this study provide an overview of the mechanisms by which apps may impact behavior. App developers may wish to incorporate these mechanisms in an effort to increase impact. Practitioners should consider the extent to which behavior change theory is integrated into a particular app when they consider making recommendations to others wishing to increase levels of physical activity.
Background: Smartphones are ideal for promoting physical activity in those with little intrinsic motivation for exercise. This study tested three hypotheses: H1 – receipt of social feedback generates higher step-counts than receipt of no feedback; H2 – receipt of social feedback generates higher step-counts than only receiving feedback on one's own walking; H3 – receipt of feedback on one's own walking generates higher step-counts than no feedback (H3). Methods: A parallel group randomised controlled trial measured the impact of feedback on steps-counts. Healthy male participants (n = 165) aged 18–40 were given phones pre-installed with an app that recorded steps continuously, without the need for user activation. Participants carried these with them as their main phones for a two-week run-in and six-week trial. Randomisation was to three groups: no feedback (control); personal feedback on step-counts; group feedback comparing step-counts against those taken by others in their group. The primary outcome measure, steps per day, was assessed using longitudinal multilevel regression analysis. Control variables included attitude to physical activity and perceived barriers to physical activity. Results: Fifty-five participants were allocated to each group; 152 completed the study and were included in the analysis: n = 49, no feedback; n = 53, individual feedback; n = 50, individual and social feedback. The study provided support for H1 and H3 but not H2. Receipt of either form of feedback explained 7.7% of between-subject variability in step-count (F = 6.626, p < 0.0005). Compared to the control, the expected step-count for the individual feedback group was 60 % higher (effect on log step-count = 0.474, 95% CI = 0.166–0.782) and that for the social feedback group, 69% higher (effect on log step-count = 0.526, 95 % CI = 0.212–0.840). The difference between the two feedback groups (individual vs social feedback) was not statistically significant. Conclusions: Always-on smartphone apps that provide step-counts can increase physical activity in young to early-middle-aged men but the provision of social feedback has no apparent incremental impact. This approach may be particularly suitable for inactive people with low levels of physical activity; it should now be tested with this population.