What is the role of smartphones on physical activity promotion? A systematic review and meta-analysis

Direct-to-consumer mHealth devices are a potential asset to behavioral research but rarely tested as intervention tools. This trial examined the accelerometer-based Fitbit tracker and website as a low-touch physical activity intervention. The purpose of this study is to evaluate, within an RCT, the feasibility and preliminary efficacy of integrating the Fitbit tracker and website into a physical activity intervention for postmenopausal women.

Background and aims: The primary objective of the present study was to investigate which cell-phone activities are associated with cell-phone addiction. No research to date has studied the full-range of cell-phone activities, and their relationship to cell-phone addiction, across male and female cell-phone users. Methods: College undergraduates (N = 164) participated in an online survey. Participants completed the questionnaire as part of their class requirements. The questionnaire took 10 and 15 minutes to complete and contained a measure of cell-phone addiction and questions that asked how much time participants spent daily on 24 cell-phone activities. Results: Findings revealed cell-phone activities that are associated significantly with cell-phone addiction (e.g., Instagram, Pinterest), as well as activities that one might logically assume would be associated with this form of addiction but are not (e.g., Internet use and Gaming). Cell-phone activities that drive cell-phone addiction (CPA) were found to vary considerably across male and female cell-phone users. Although a strong social component drove CPA for both males and females, the specific activities associated with CPA differed markedly. Conclusions: CPA amongst the total sample is largely driven by a desire to connect socially. The activities found to be associated with CPA, however, differed across the sexes. As the functionality of cell-phones continues to expand, addiction to this seemingly indispensable piece of technology becomes an increasingly realistic possibility. Future research must identify the activities that push cell-phone use beyond its “;tipping point” where it crosses the line from a helpful tool to one that undermines our personal well-being and that of others.

Background Regular physical activity has established physical and mental health benefits; however, merely one quarter of the U.S. adult population meets national physical activity recommendations. In an effort to engage individuals who do not meet these guidelines, researchers have utilized popular emerging technologies, including mobile devices (ie, personal digital assistants [PDAs], mobile phones). This study is the first to synthesize current research focused on the use of mobile devices for increasing physical activity. Objective To conduct a meta-analysis of research utilizing mobile devices to influence physical activity behavior. The aims of this review were to: (1) examine the efficacy of mobile devices in the physical activity setting, (2) explore and discuss implementation of device features across studies, and (3) make recommendations for future intervention development. Methods We searched electronic databases (PubMed, PsychINFO, SCOPUS) and identified publications through reference lists and requests to experts in the field of mobile health. Studies were included that provided original data and aimed to influence physical activity through dissemination or collection of intervention materials with a mobile device. Data were extracted to calculate effect sizes for individual studies, as were study descriptives. A random effects meta-analysis was conducted using the Comprehensive Meta-Analysis software suite. Study quality was assessed using the quality of execution portion of the Guide to Community Preventative Services data extraction form. Results Four studies were of “good” quality and seven of “fair” quality. In total, 1351 individuals participated in 11 unique studies from which 18 effects were extracted and synthesized, yielding an overall weight mean effect size of g = 0.54 (95% CI = 0.17 to 0.91, P = .01). Conclusions Research utilizing mobile devices is gaining in popularity, and this study suggests that this platform is an effective means for influencing physical activity behavior. Our focus must be on the best possible use of these tools to measure and understand behavior. Therefore, theoretically grounded behavior change interventions that recognize and act on the potential of smartphone technology could provide investigators with an effective tool for increasing physical activity.