Evaluating the impact of physical activity apps and wearables: interdisciplinary review

Background: Although many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users’ interaction and usage behavior) and acceptability (ie, users’ subjective perceptions and experiences) to help explain how and why apps and wearables work. Objectives: This study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed. Method: An interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis. Results: A total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance). Conclusions: The rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines

Preventing weight gain in African American breast cancer survivors using smart scales and activity trackers: a randomized controlled pilot study

This study evaluated the feasibility and preliminary efficacy of two 6-month, self-regulation interventions that focused on daily self-weighing (DSW), and used objective monitoring and tailored feedback about weight (±activity), to prevent weight gain among African American breast cancer survivors

Examining adherence to activity monitoring devices to improve physical activity in adults with cardiovascular disease: A systematic review

Background Activity monitoring devices are currently being used to facilitate and monitor physical activity. No prior review has examined adherence to the use of activity monitoring devices amongst adults with cardiovascular disease. Methods Literature from June 2012 to October 2017 was evaluated to examine the extent of adherence to any activity monitoring device used to collect objective physical activity data. Randomized control trials comparing usual care against the use of an activity monitoring device, in a community intervention for adults from any cardiovascular diagnostic group, were included. A systematic search of databases and clinical trials registers was conducted using Joanna Briggs Institute methodology. Results Of 10 eligible studies, two studies reported pedometer use and eight accelerometer use. Six studies addressed the primary outcome. Mean adherence was 59.1% (range 39.6% to 85.7%) at last follow-up. Studies lacked equal representation by gender (28.6% female) and age (range 42 to 82 years). Conclusion This review indicates that current research on activity monitoring devices may be overstated due to the variability in adherence. Results showed that physical activity tracking in women and in young adults have been understudied

Evaluating Motivational Interviewing and Habit Formation to Enhance the Effect of Activity Trackers on Healthy Adults’ Activity Levels: Randomized Intervention

Background: While widely used and endorsed, there is limited evidence supporting the benefits of activity trackers for increasing physical activity; these devices may be more effective when combined with additional strategies that promote sustained behavior change like motivational interviewing (MI) and habit development. Objective: This study aims to determine the utility of wearable activity trackers alone or in combination with these behavior change strategies for promoting improvements in active and sedentary behaviors. Methods: A sample of 91 adults (48/91 female, 53%) was randomized to receive a Fitbit Charge alone or in combination with MI and habit education for 12 weeks. Active and sedentary behaviors were assessed pre and post using research-grade activity monitors (ActiGraph and activPAL), and the development of habits surrounding the use of the trackers was assessed postintervention with the Self-Reported Habit Index. During the intervention, Fitbit wear time and activity levels were monitored with the activity trackers. Linear regression analyses were used to determine the influence of the trial on outcomes of physical activity and sedentary time. The influence of habits was examined using correlation coefficients relating habits of tracker use (wearing the tracker and checking data on the tracker and associated app) to Fitbit wear time and activity levels during the intervention and at follow-up. Results: Regression analyses revealed no significant differences by group in any of the primary outcomes (all P\u3e.05). However, personal characteristics, including lower baseline activity levels (beta=–.49, P=.01) and lack of previous experience with pedometers (beta=–.23, P=.03) were predictive of greater improvements in moderate and vigorous physical activity. Furthermore, for individuals with higher activity levels at the baseline, MI and habit education were more effective for maintaining these activity levels when compared with receiving a Fitbit alone (eg, small increase of ~48 steps/day, d=0.01, vs large decrease of ~1830 steps/day, d=0.95). Finally, habit development was significantly related to steps/day during (r=.30, P=.004) and following the intervention (r=.27, P=.03). Conclusions: This study suggests that activity trackers may have beneficial effects on physical activity in healthy adults, but benefits vary based on individual factors. Furthermore, this study highlights the importance of habit development surrounding the wear and use of activity trackers and the associated software to promote increases in physical activity

Low-cost consumer-based trackers to measure physical activity and sleep duration among adults in free-living conditions : validation study

Background: Wearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are used not only by consumers to monitor their behavior but also by researchers to track the behavior of large samples and by health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high costs and accuracy concerns may be barriers to widespread adoption. Objective: This study aimed to investigate the concurrent validity of 6 low-cost activity trackers for measuring steps, moderate-to-vigorous physical activity (MVPA), and TST: Geonaut On Coach, iWown i5 Plus, MyKronoz ZeFit4, Nokia GO, VeryFit 2.0, and Xiaomi MiBand 2. Methods: A free-living protocol was used in which 20 adults engaged in their usual daily activities and sleep. For 3 days and 3 nights, they simultaneously wore a low-cost tracker and a high-cost tracker (Fitbit Charge HR) on the nondominant wrist. Participants wore an ActiGraph GT3X+ accelerometer on the hip at daytime and a BodyMedia SenseWear device on the nondominant upper arm at nighttime. Validity was assessed by comparing each tracker with the ActiGraph GT3X+ and BodyMedia SenseWear using mean absolute percentage error scores, correlations, and Bland-Altman plots in IBM SPSS 24.0. Results: Large variations were shown between trackers. Low-cost trackers showed moderate-to-strong correlations (Spearman r=0.53-0.91) and low-to-good agreement (intraclass correlation coefficient [ICC]=0.51-0.90) for measuring steps. Weak-to-moderate correlations (Spearman r=0.24-0.56) and low agreement (ICC=0.18-0.56) were shown for measuring MVPA. For measuring TST, the low-cost trackers showed weak-to-strong correlations (Spearman r=0.04-0.73) and low agreement (ICC=0.05-0.52). The Bland-Altman plot revealed a variation between overcounting and undercounting for measuring steps, MVPA, and TST, depending on the used low-cost tracker. None of the trackers, including Fitbit (a high-cost tracker), showed high validity to measure MVPA. Conclusions: This study was the first to examine the concurrent validity of low-cost trackers. Validity was strongest for the measurement of steps; there was evidence of validity for measurement of sleep in some trackers, and validity for measurement of MVPA time was weak throughout all devices. Validity ranged between devices, with Xiaomi having the highest validity for measurement of steps and VeryFit performing relatively strong across both sleep and steps domains Low-cost trackers hold promise for monitoring and measurement of movement and sleep behaviors, both for consumers and researchers

Effects of Consumer‑Wearable Activity Tracker‑Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School‑Aged Children: A Systematic Review and Meta‑analysis

Carolina Casado-Robles is supported by a research grant from the Spanish Ministry of Universities [Grant Number: FPU16/03314]. This publication is part of the WearFit project (Reference B-SEJ-029-UGR18), funded by the FEDER/Regional Government of Andalusia-Ministry of Economy and Knowledge. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Background: The popularity of consumer-wearable activity trackers has led the scientific community to conduct an increasing number of intervention studies integrating them to promote physical activity (PA) and to reduce sedentary behavior (SB) levels among school-aged children. Therefore, the aim of the present study was to estimate the effects of consumer-wearable activity tracker-based programs on daily objectively measured PA and SB among apparently healthy school-aged children, as well as to compare the influence of participants’ and programs’ characteristics. Methods: Eligibility criteria were: (1) participants: apparently healthy school-aged children (< 18 years old); (2) intervention: aimed to promote PA and/or to reduce SB incorporating consumer-wearable activity trackers; (3) comparator: baseline measurements and/or a control/traditional group; (4) outcomes: objectively measured daily PA and/or SB levels; (5) study design: pre-experimental, quasi-experimental, and true-experimental trials. Relevant studies were searched from eight databases up to December 2020, as well as from four alternative modes of searching. Based on the Cochrane Risk-of-bias tool 2, the risk of bias was assessed following four domains: (1) randomization process; (2) missing outcome data; (3) measurement of the outcomes; and (4) selection of the reported results. Based on a comprehensive systematic review, meta-analyses of the Cohen’s standardized mean difference (d) and 95% confidence interval (CI) with a random-effects model were conducted to estimate the overall effects, as well as the within- and between-study subgroups analyses effects, of the programs on daily total steps, moderate-to-vigorous PA (MVPA), total PA and SB. Results: Forty-four publications (i.e., 45 studies) were included in the systematic review (5,620 unique participants; mean age = 12.85 ± 2.84 years) and 40 publications (i.e., 41 studies) in the meta-analysis. Programs had a mean length of 11.78 ± 13.17 weeks and most used a waist-worn consumer-wearable activity tracker (77.78% waist-worn; 22.22% wrist-worn). Programs characteristics were: goal-setting strategies (64.06%); participants’ logbooks (56.25%); counseling sessions (62.50%); reminders (28.13%); motivational strategies (42.19%); and exercise routine (17.19%). Results showed a statistically significant moderate favorable effect on daily total steps (d = 0.612, 95% CI 0.477–0.746), small favorable effect on daily MVPA (d = 0.220, 95% CI 0.134–0.307), trivial favorable effect on daily total PA (d = 0.151, 95% CI 0.038–0.264) and trivial unfavorable effect on daily SB (d = 0.172, 95% CI 0.039–0.305). Subgroups analyses showed a higher effect for daily total steps and daily MVPA levels in females and the physically inactive for daily total steps (p = 0.003–0.044). Programs with educational counseling and/or goal-setting strategies, as well as a greater number of strategies, were more effective for improving children’s daily total steps, and wrist-worn activity trackers were more effective than waist-worn trackers for improving their daily MVPA levels (p = 0.001–0.021). Conclusions: Consumer-wearable activity tracker-based programs seem to be effective in promoting school-aged children’s daily total steps and MVPA levels, especially for females and those that are physically inactive. These programs should include specific goal-setting, educational counseling, and wrist-worn trackers as especially effective strategies. However, due to the certainty of evidence being from “low” to “moderate”, future well-designed primary research studies about the topic are needed.Spanish Government FPU16/03314FEDER/Regional Government of Andalusia-Ministry of Economy and Knowledge B-SEJ-029-UGR1