Establishing a Global Standard for Wearable Devices in Sport and Exercise Medicine: Perspectives from Academic and Industry Stakeholders.

Millions of consumer sport and fitness wearables (CSFWs) are used worldwide, and millions of datapoints are generated by each device. Moreover, these numbers are rapidly growing, and they contain a heterogeneity of devices, data types, and contexts for data collection. Companies and consumers would benefit from guiding standards on device quality and data formats. To address this growing need, we convened a virtual panel of industry and academic stakeholders, and this manuscript summarizes the outcomes of the discussion. Our objectives were to identify (1) key facilitators of and barriers to participation by CSFW manufacturers in guiding standards and (2) stakeholder priorities. The venues were the Yale Center for Biomedical Data Science Digital Health Monthly Seminar Series (62 participants) and the New England Chapter of the American College of Sports Medicine Annual Meeting (59 participants). In the discussion, stakeholders outlined both facilitators of (e.g., commercial return on investment in device quality, lucrative research partnerships, and transparent and multilevel evaluation of device quality) and barriers (e.g., competitive advantage conflict, lack of flexibility in previously developed devices) to participation in guiding standards. There was general agreement to adopt Keadle et al.'s standard pathway for testing devices (i.e., benchtop, laboratory, field-based, implementation) without consensus on the prioritization of these steps. Overall, there was enthusiasm not to add prescriptive or regulatory steps, but instead create a networking hub that connects companies to consumers and researchers for flexible guidance navigating the heterogeneity, multi-tiered development, dynamicity, and nebulousness of the CSFW field.

Effects of Three Motivationally Targeted Mobile Device Applications on Initial Physical Activity and Sedentary Behavior Change in Midlife and Older Adults: A Randomized Trial.

BACKGROUND: 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. OBJECTIVE: 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. STUDY DESIGN AND METHODS: 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. RESULTS: Mixed-effects models indicated that, over the 8-week period, the social app users showed significantly greater overall increases in weekly accelerometry-derived moderate to vigorous physical activity relative to the other three arms (P values for between-arm differences = .04-.005; Social vs. Control app: d = 1.05, CI = 0.44,1.67; Social vs. Affect app: d = 0.89, CI = 0.27,1.51; Social vs. Analytic app: d = 0.89, CI = 0.27,1.51), while more variable responses were observed among users of the other two motivationally framed apps. Social app users also had significantly lower overall amounts of accelerometry-derived sedentary behavior relative to the other three arms (P values for between-arm differences = .02-.001; Social vs. Control app: d = 1.10,CI = 0.48,1.72; Social vs. Affect app: d = 0.94, CI = 0.32,1.56; Social vs. Analytic app: d = 1.24, CI = 0.59,1.89). Additionally, Social and Affect app users reported lower overall sitting time compared to the other two arms (P values for between-arm differences < .001; Social vs. Control app: d = 1.59,CI = 0.92, 2.25; Social vs. Analytic app: d = 1.89,CI = 1.17, 2.61; Affect vs. Control app: d = 1.19,CI = 0.56, 1.81; Affect vs. Analytic app: d = 1.41,CI = 0.74, 2.07). CONCLUSION: The results provide initial support for the use of a smartphone-delivered social frame in the early induction of both physical activity and sedentary behavior changes. The information obtained also sets the stage for further investigation of subgroups that might particularly benefit from different motivationally framed apps in these two key health promotion areas. TRIAL REGISTRATION: ClinicalTrials.gov NCT01516411.

Physically active vs. sedentary academic lessons: A dose response study for elementary student time on task.

BACKGROUND: Physically active academic lessons are an effective intervention to reduce sedentary time and increase student physical activity. They have also been shown to enhance task engagement, as indicated by observations of attention and behavior control, time on task (TOT). However, it is not clear if the improved TOT stems from the physical activity or if it is the result of an enjoyable break from traditional instruction. If it is due to physical activity, what dose of intensity is required for the effect? This study was designed to test these questions. METHODS: Participants were 320 children (7-9years) recruited from school districts in Central Texas in 2012. They were assigned by classroom (n=20) to one of four conditions: 1) sedentary, standard lesson (n=72); 2) sedentary academic game (n=87); 3) low to moderate intensity PA (LMPA), academic game (n=81); and 4) moderate to vigorous intensity PA (MVPA), academic game (n=76). Measures included PA via accelerometer and TOT. RESULTS: Mixed-method RMANOVA indicated TOT decreased following the standard lesson (p<0.001), showed no change following the sedentary academic game (p=0.68), and increased following the LMPA (p<0.01) and MVPA (p<0.001) academic games. CONCLUSIONS: While the sedentary, academic game prevented the reduction in TOT observed in the standard lesson, PA resulted in increased TOT. Future research should be designed to examine the potential academic benefits of the change in TOT.

Harnessing different motivational frames via mobile phones to promote daily physical activity and reduce sedentary behavior in aging adults.

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.

The Stanford Healthy Neighborhood Discovery Tool: a computerized tool to assess active living environments.

BACKGROUND: The built environment can influence physical activity, particularly among older populations with impaired mobility. Existing tools to assess environmental features associated with walkability are often cumbersome, require extensive training, and are not readily available for use by community residents. PURPOSE: This project aimed to develop and evaluate the utility of a computerized, tablet-based participatory tool designed to engage older residents in identifying neighborhood elements that affect active living opportunities. METHODS: Following formative testing, the tool was used by older adults (aged ≥65 years, in 2011) to record common walking routes (tracked using built-in GPS) and geocoded audio narratives and photographs of the local neighborhood environment. Residents (N=27; 73% women; 77% with some college education; 42% used assistive devices) from three low-income communal senior housing sites used the tool while navigating their usual walking route in their neighborhood. Data were analyzed in 2012. RESULTS: Elements (from 464 audio narratives and photographs) identified as affecting active living were commensurate with the existing literature (e.g., sidewalk features, aesthetics, parks/playgrounds, crosswalks). However, within each housing site, the profile of environmental elements identified was distinct, reflecting the importance of granular-level information collected by the tool. Additionally, consensus among residents was reached regarding which elements affected active living opportunities. CONCLUSIONS: This tool serves to complement other assessments and assist decision makers in consensus-building processes for environmental change.

Physically active academic lessons and time on task: the moderating effect of body mass index.

UNLABELLED: Physically active classroom lessons have been found to increase on-task behavior in children. Given that physical activity has been associated with an increased time on task (TOT) and that overweight children take fewer steps than normal weight children do, it was expected that benefits of the physical activity would differentially impact those children of higher weight status. PURPOSE: To examine the effects of a physically active classroom lesson and body mass index (BMI) category on TOT in a sample of elementary-aged children (N = 97). METHODS: Behavior was assessed through direct observations before and after a physically active classroom lesson and before and after a traditional inactive classroom lesson. TOT was calculated through momentary time sampling for each student by dividing the number of on-task observations by the total number of observations per student (interrater reliability = 94%). RESULTS: TOT decreased significantly from before to after the lesson for all BMI categories in the inactive control condition, with no change for the active condition. Post hoc analyses found a significant linear effect for the reduction in TOT with each level of BMI in the inactive condition, with the greatest magnitude of effect for the overweight group. CONCLUSIONS: Physically active classroom lessons provide a buffer to prevent the steep reduction in TOT experienced after a period of inactivity in all children, especially those who are overweight.