Wearable Sensor/Device (Fitbit One) and SMS Text-Messaging Prompts to Increase Physical Activity in Overweight and Obese Adults: A Randomized Controlled Trial

Using Novel Technology within a School-Based Setting to Increase Physical Activity: A Pilot Study in School-Age Children from a Low-Income, Urban Community

Background

Less than half of American children meet national physical activity (PA) recommendations. This study tested the feasibility, acceptability, and preliminary effectiveness of using wearable PA monitors to increase PA in school-age children.

Methods

In Phase 1 of this study, conducted in 2014, 32 fifth-grade students enrolled in a low-resource middle school were given a waist-worn Fitbit Zip monitor for 4 weeks to test its feasibility (adherence) and acceptability. Adherence, wear time of ≥8 hours per day, was examined. Feedback was solicited from parents through structured interviews. In Phase 2, conducted in 2015, 42 sixth-grade students were assigned, by classroom, to one of three conditions (Fitbit + goal and incentive-based intervention, Fitbit only, or control) to test the feasibility of the wrist-worn Fitbit Charge and its preliminary effectiveness in increasing PA over 6 weeks.

Results

In Phase 1, average adherence was 64.1%. In Phase 2, it was 73.4% and 80.2% for participants in the Fitbit + intervention and Fitbit only groups, respectively (p = .07). After controlling for baseline values, weight status, and sex, there were no significant group differences in changes in MVPA or steps from baseline to follow-up.

Conclusions

While moderately acceptable, wearable PA monitors did not increase PA levels in this sample. They may be more effective within a coordinated school-based physical activity program.

Healthy lifestyle intervention for African American uterine cancer survivors: Study protocol

BACKGROUND

Cancer of the uterine corpus is the most common gynecologic malignancy and the fourth most common cancer in U.S. women. There is a racial disparity in the survival from endometrial cancer and this may be addressed by culturally-tailored lifestyle interventions to help African American (AA) endometrial cancer survivors lose weight or maintain a healthy weight.

OBJECTIVE

The overall purpose of this pilot study is to develop and evaluate a culturally-tailored lifestyle intervention to help AA uterine cancer survivors reduce their risk of cancer recurrence and improve their quality of life through healthy eating, physical activity, and weight management. While many interventions have been evaluated to assist cancer survivors through diet and physical activity, few have focused on AA women with a uterine cancer diagnosis.

METHODS

Community-engaged research principles are being followed. This study was developed with input from the Augusta University (AU) College of Nursing Community Advisory Board (CAB) and the Division of Gynecologic Oncology at the Georgia Cancer Center at AU. Weekly sessions throughout a 12-week intervention will include physical activity and lectures on improving nutritional status. The pre/post-test design includes baseline and 6-month follow-up, where participants will complete a questionnaire that assesses knowledge and attitudes about physical activity, nutrition, uterine cancer, social support, and quality of life.

CONCLUSIONS

From this pilot study, we will learn more about the feasibility and integration of healthy lifestyle interventions in this patient population, and the results can provide an opportunity for a larger-scale, multi-center study with a randomized controlled design.

Toward research-tested mobile health interventions to prevent diabetes and cardiovascular disease among persons with pre-diabetes

Background

About 35% of US adults have pre-diabetes and an increased risk of diabetes. Consumer-facing devices such as the Fitbit help users become more physically active and manage their weight which reduces risk of diabetes and cardiovascular disease.

Methods

In this commentary we provide a summary of healthy lifestyle intervention studies involving persons with pre-diabetes including those conducted in routine clinical practice. We also provide an account of how such interventions might be enhanced through the use of wearable devices linked to smartphone applications.

Results

In initial trials focusing on overweight and obesity, consumer wearable devices have been shown to increase physical activity and reduce weight. However, the acceptability and effectiveness of these mHealth interventions among persons with impaired glucose tolerance or impaired fasting glucose is unknown; studies involving persons with pre-diabetes have not yet been reported.

Conclusions

Research is needed to determine the feasibility and efficacy of wearable devices in improving physical activity and weight management in persons with pre-diabetes who are at-risk of diabetes and cardiovascular disease.

Wearables for Promoting Physical Activity

BACKGROUND

The rapid expansion and popularity of consumer-wearable physical activity monitors (WPAMs) has enabled the integration of technology into physical activity (PA) intervention, deployment, and evaluation. This brief review reports on the accuracy of consumer-WPAMs, considers the intervention effects of using consumer-WPAMs, and offers future considerations as the proliferation of this area of product development and consumer use continues to escalate.

CONTENT

The studies reviewed document the utility for consumer-WPAMs to objectively assess PA, with output metrics similar to research-grade activity monitors. Early intervention efficacy for the use of consumer-WPAMs to increase PA holds considerable promise. Substantial increases in moderate- to vigorous-intensity PA (MVPA) have been reported across different research study designs and populations in which consumer-WPAMs have been used in isolation or in conjunction with other behavioral change strategies. The utility of consumer-WPAMs is currently being investigated in clinical populations, notably showing increases in PA in individuals at risk for cancer or post cancer survivors, in those with chronic obstructive pulmonary disease, and in postsurgical patients. There has been a proliferation of registered trials at clinicaltrials.gov, and an increase of disseminated works regarding the use of consumer-WPAMs is expected.

SUMMARY

There are many research studies documenting the validity and intervention effectiveness of consumer-WPAMs; evidence is emerging on the health benefits linked to use of such devices. Future work on the long-term effects of consumer-WPAMs on behavior and health is warranted, and prospects appear exciting as wearable technology advances and adoption increases.

Acceptability of the Fitbit in behavioural activation therapy for depression: a qualitative study

INTRODUCTION

Major depressive disorder is characterised by low mood and poor motivation. Literature suggests that increased physical activity has positive effects on alleviating depression. Fitness-tracking devices may complement behavioural activation (BA) therapy to improve physical activity and mental health in patients with depression.

OBJECTIVES

To understand patients' perceived benefit from the Fitbit and explore themes associated with patient experiences. To compare perceived benefit, patient factors, Fitbit usage and Beck's Depression Inventory (BDI) scores.

METHODS

Semistructured interviews were conducted with patients (n=36) who completed a 28-week BA group programme in a mood disorders outpatient clinic. All patients were asked to carry a Fitbit One device. We conducted thematic analyses on the interviews and exploratory quantitative analyses on patient characteristics, Fitbit usage, steps recorded, perceived benefit and BDI scores.

FINDINGS

Twenty-three patients found the Fitbit helpful for their physical activity. Themes of positive experiences included self-awareness, peer motivation and goal-setting opportunities. Negative themes included inconvenience, inaccuracies and disinterest. Age, baseline and change in BDI scores, prior physical activity goals and familiarity with technology were not associated with perceived benefit from the Fitbit or usage. Perceived benefit was significantly (p<0.01) associated with usage.

CONCLUSIONS

Overall, the Fitbit is an acceptable tool to complement BA therapy for patients with depression. Many positive themes were concordant with current literature; however, patients also reported negative aspects that may affect use.

CLINICAL IMPLICATIONS

Clinicians and researchers should consider both strengths and limitations of activity trackers when implementing them to motivate patients with depression.

TRIAL REGISTRATION NUMBER

NCT02045771; Pre-results.

Determinants for Sustained Use of an Activity Tracker: Observational Study

BACKGROUND

A lack of physical activity is considered to cause 6% of deaths globally. Feedback from wearables such as activity trackers has the potential to encourage daily physical activity. To date, little research is available on the natural development of adherence to activity trackers or on potential factors that predict which users manage to keep using their activity tracker during the first year (and thereby increasing the chance of healthy behavior change) and which users discontinue using their trackers after a short time.

OBJECTIVE

The aim of this study was to identify the determinants for sustained use in the first year after purchase. Specifically, we look at the relative importance of demographic and socioeconomic, psychological, health-related, goal-related, technological, user experience-related, and social predictors of feedback device use. Furthermore, this study tests the effect of these predictors on physical activity.

METHODS

A total of 711 participants from four urban areas in France received an activity tracker (Fitbit Zip) and gave permission to use their logged data. Participants filled out three Web-based questionnaires: at start, after 98 days, and after 232 days to measure the aforementioned determinants. Furthermore, for each participant, we collected activity data tracked by their Fitbit tracker for 320 days. We determined the relative importance of all included predictors by using Random Forest, a machine learning analysis technique.

RESULTS

The data showed a slow exponential decay in Fitbit use, with 73.9% (526/711) of participants still tracking after 100 days and 16.0% (114/711) of participants tracking after 320 days. On average, participants used the tracker for 129 days. Most important reasons to quit tracking were technical issues such as empty batteries and broken trackers or lost trackers (21.5% of all Q3 respondents, 130/601). Random Forest analysis of predictors revealed that the most influential determinants were age, user experience-related factors, mobile phone type, household type, perceived effect of the Fitbit tracker, and goal-related factors. We explore the role of those predictors that show meaningful differences in the number of days the tracker was worn.

CONCLUSIONS

This study offers an overview of the natural development of the use of an activity tracker, as well as the relative importance of a range of determinants from literature. Decay is exponential but slower than may be expected from existing literature. Many factors have a small contribution to sustained use. The most important determinants are technical condition, age, user experience, and goal-related factors. This finding suggests that activity tracking is potentially beneficial for a broad range of target groups, but more attention should be paid to technical and user experience-related aspects of activity trackers.

Effect of personal activity trackers on weight loss in families enrolled in a comprehensive behavioral family-lifestyle intervention program in the Federally Qualified Health Center setting: a randomized controlled trial

BACKGROUND

Childhood obesity continues to be a substantial problem despite major public health efforts, and disproportionately impacts children from low-income families. Digital health tools and consumer technology offer promising opportunities for interventions, but few studies have evaluated how they might be incorporated into existing interventions or used to create new types of interventions. It remains unclear which approaches would be most beneficial for underserved pediatric populations.

PURPOSE

To describe the design and rationale of a single-center randomized, controlled trial evaluating the effects of personal activity tracker (PAT) use by parents on weight-status improvement in both parents and overweight children enrolled in BodyWorks (BW), a comprehensive behavioral family-lifestyle intervention program (CBFLI), in a primary-care clinic serving a predominantly low-income Latino population.

METHODS

This study is being conducted in the AltaMed general pediatrics clinic at Children's Hospital Los Angeles. Eligible participants are families (child and adult caregiver) in which the child is between 7-18 years of age, has a BMI ≥85th percentile for age and sex, and has been referred to BW by their AltaMed pediatrician. BW consists of one weekly, two-hour session for 7 weeks. In a given cycle, the program is offered on two separate nights: Monday (Spanish) and Wednesday (English). Families self sort into one of two groups based on language preference. To ensure balanced allocation of language preference groups and prevent in-group cross contamination, block randomization is used to assign whole groups to either the intervention or control arms of the study. The control arm consists of usual care, while the intervention arm adds assigning a Fitbit PAT to the parents and training them in its proper use. Study personnel are blinded to group assignment during the analysis phase. Study outcomes include attendance rate, program completion rate, and changes in weight-status improvement, defined as change in weight and BMI for adults and change in BMI z-score for children. We hypothesize that the intervention arm will have better weight-related outcomes than the control arm. Study completion is anticipated in 2017, after the enrollment of approximately 150 families.

CONCLUSIONS

The study aim is to evaluate the effects of PATs on weight-related outcomes in overweight children and parents participating in a CBFLI. The results will be important for determining whether wearable devices are an effective addition to weight loss interventions for overweight and obese children.

Promise of Wearable Physical Activity Monitors in Oncology Practice

Commercially available physical activity monitors provide clinicians an opportunity to obtain oncology patient health measures to an unprecedented degree. These devices can provide objective and quantifiable measures of physical activity, which are not subject to errors or bias of self-reporting or shorter duration of formal testing. Prior work on so-called quantified-self data was based on older-generation, research-grade accelerometers, which laid the foundation for consumer-based physical activity monitoring devices to be validated as a feasible and reliable tool in patients with cancer. Physical activity monitors are being used in chronic conditions including chronic obstructive pulmonary disease, congestive heart failure, diabetes mellitus, and obesity. Differing demographics, compounded with higher symptom and treatment burdens in patients with cancer, imply that additional work is needed to understand the unique strengths and weaknesses of physical activity monitors in this population. Oncology programs can systematically implement these tools into their workflows in an adaptable and iterative manner. Translating large amounts of data collected from an individual physical activity monitoring device into clinically relevant information requires sophisticated data compilation and reduction. In this article, we summarize the characteristics of older- and newer-generation physical activity monitors, review the validation of physical activity monitors with respect to health-related quality-of-life assessments, and describe the current role of these devices for the practicing oncologist. We also highlight the challenges and next steps needed for physical activity monitors to provide relevant information that can change the current state of oncology practice.

How Accurate Is Your Activity Tracker? A Comparative Study of Step Counts in Low-Intensity Physical Activities

Background

As commercially available activity trackers are being utilized in clinical trials, the research community remains uncertain about reliability of the trackers, particularly in studies that involve walking aids and low-intensity activities. While these trackers have been tested for reliability during walking and running activities, there has been limited research on validating them during low-intensity activities and walking with assistive tools.

Objective

The aim of this study was to (1) determine the accuracy of 3 Fitbit devices (ie, Zip, One, and Flex) at different wearing positions (ie, pants pocket, chest, and wrist) during walking at 3 different speeds, 2.5, 5, and 8 km/h, performed by healthy adults on a treadmill; (2) determine the accuracy of the mentioned trackers worn at different sites during activities of daily living; and (3) examine whether intensity of physical activity (PA) impacts the choice of optimal wearing site of the tracker.

Methods

We recruited 15 healthy young adults to perform 6 PAs while wearing 3 Fitbit devices (ie, Zip, One, and Flex) on their chest, pants pocket, and wrist. The activities include walking at 2.5, 5, and 8 km/h, pushing a shopping cart, walking with aid of a walker, and eating while sitting. We compared the number of steps counted by each tracker with gold standard numbers. We performed multiple statistical analyses to compute descriptive statistics (ie, ANOVA test), intraclass correlation coefficient (ICC), mean absolute error rate, and correlation by comparing the tracker-recorded data with that of the gold standard.

Results

All the 3 trackers demonstrated good-to-excellent (ICC>0.75) correlation with the gold standard step counts during treadmill experiments. The correlation was poor (ICC<0.60), and the error rate was significantly higher in walker experiment compared to other activities. There was no significant difference between the trackers and the gold standard in the shopping cart experiment. The wrist worn tracker, Flex, counted several steps when eating (P<.01). The chest tracker was identified as the most promising site to capture steps in more intense activities, while the wrist was the optimal wearing site in less intense activities.

Conclusions

This feasibility study focused on 6 PAs and demonstrated that Fitbit trackers were most accurate when walking on a treadmill and least accurate during walking with a walking aid and for low-intensity activities. This may suggest excluding participants with assistive devices from studies that focus on PA interventions using commercially available trackers. This study also indicates that the wearing site of the tracker is an important factor impacting the accuracy performance. A larger scale study with a more diverse population, various activity tracker vendors, and a larger activity set are warranted to generalize our results.

Key Components in eHealth Interventions Combining Self-Tracking and Persuasive eCoaching to Promote a Healthier Lifestyle: A Scoping Review

BACKGROUND

The combination of self-tracking and persuasive eCoaching in automated interventions is a new and promising approach for healthy lifestyle management.

OBJECTIVE

The aim of this study was to identify key components of self-tracking and persuasive eCoaching in automated healthy lifestyle interventions that contribute to their effectiveness on health outcomes, usability, and adherence. A secondary aim was to identify the way in which these key components should be designed to contribute to improved health outcomes, usability, and adherence.

METHODS

The scoping review methodology proposed by Arskey and O'Malley was applied. Scopus, EMBASE, PsycINFO, and PubMed were searched for publications dated from January 1, 2013 to January 31, 2016 that included (1) self-tracking, (2) persuasive eCoaching, and (3) healthy lifestyle intervention.

RESULTS

The search resulted in 32 publications, 17 of which provided results regarding the effect on health outcomes, 27 of which provided results regarding usability, and 13 of which provided results regarding adherence. Among the 32 publications, 27 described an intervention. The most commonly applied persuasive eCoaching components in the described interventions were personalization (n=24), suggestion (n=19), goal-setting (n=17), simulation (n=17), and reminders (n=15). As for self-tracking components, most interventions utilized an accelerometer to measure steps (n=11). Furthermore, the medium through which the user could access the intervention was usually a mobile phone (n=10). The following key components and their specific design seem to influence both health outcomes and usability in a positive way: reduction by setting short-term goals to eventually reach long-term goals, personalization of goals, praise messages, reminders to input self-tracking data into the technology, use of validity-tested devices, integration of self-tracking and persuasive eCoaching, and provision of face-to-face instructions during implementation. In addition, health outcomes or usability were not negatively affected when more effort was requested from participants to input data into the technology. The data extracted from the included publications provided limited ability to identify key components for adherence. However, one key component was identified for both usability and adherence, namely the provision of personalized content.

CONCLUSIONS

This scoping review provides a first overview of the key components in automated healthy lifestyle interventions combining self-tracking and persuasive eCoaching that can be utilized during the development of such interventions. Future studies should focus on the identification of key components for effects on adherence, as adherence is a prerequisite for an intervention to be effective.

Youth Oriented Activity Trackers: Comprehensive Laboratory- and Field-Based Validation

BACKGROUND

Commercial activity trackers are growing in popularity among adults and some are beginning to be marketed to children. There is, however, a paucity of independent research examining the validity of these devices to detect physical activity of different intensity levels.

OBJECTIVES

The purpose of this study was to determine the validity of the output from 3 commercial youth-oriented activity trackers in 3 phases: (1) orbital shaker, (2) structured indoor activities, and (3) 4 days of free-living activity.

METHODS

Four units of each activity tracker (Movband [MB], Sqord [SQ], and Zamzee [ZZ]) were tested in an orbital shaker for 5-minutes at three frequencies (1.3, 1.9, and 2.5 Hz). Participants for Phase 2 (N=14) and Phase 3 (N=16) were 6-12 year old children (50% male). For Phase 2, participants completed 9 structured activities while wearing each tracker, the ActiGraph GT3X+ (AG) research accelerometer, and a portable indirect calorimetry system to assess energy expenditure (EE). For Phase 3, participants wore all 4 devices for 4 consecutive days. Correlation coefficients, linear models, and non-parametric statistics evaluated the criterion and construct validity of the activity tracker output.

RESULTS

Output from all devices was significantly associated with oscillation frequency (r=.92-.99). During Phase 2, MB and ZZ only differentiated sedentary from light intensity (P<.01), whereas the SQ significantly differentiated among all intensity categories (all comparisons P<.01), similar to AG and EE. During Phase 3, AG counts were significantly associated with activity tracker output (r=.76, .86, and .59 for the MB, SQ, and ZZ, respectively).

CONCLUSIONS

Across study phases, the SQ demonstrated stronger validity than the MB and ZZ. The validity of youth-oriented activity trackers may directly impact their effectiveness as behavior modification tools, demonstrating a need for more research on such devices.

The Effects of an Activity Promotion System on active living in overweight subjects with metabolic abnormalities

OBJECTIVES

The aim of this study is to examine the effects of Activity Promotion System (APs) on promoting physical activity (PA) for overweight subjects with metabolic abnormalities.

METHODS

We designed a six-month randomised controlled trial with a cross-over design, and recruited 53 subjects. Subjects in group A used APs with a wearable device measuring whole-day PA, including sleep time, sedentary, light, moderate and vigorous PA and a web-based feedback system in the first three months and followed by usual care with traditional health education in the next three months. Subjects in group B received the above programs in a reverse order. PA and metabolic profiles were measured prior to the intervention (T1), three months after the first intervention (T2), and six months after the other intervention (T3), respectively. An independent t test was used to test the differences between periods with and without Aps.

RESULTS

This study found that the APs had short-term effects on decreasing sedentary time and increasing mild PA, total PA, daily step counts, and calories burnt. With regard to the secondary outcome measures of metabolic abnormalities, the results showed that APs had had no effect on metabolic abnormalities, except a borderline decreasing of waist circumference.

CONCLUSION

Using this APs might be an effective approach to decrease sedentary time and increase PA for an overweight non-elderly adult population with only metabolic abnormalities. However, long-term studies with APs are needed to further confirm the effectiveness of this innovative Activity Promotion System.

A Bit of Fit: Minimalist Intervention in Adolescents Based on a Physical Activity Tracker

Background

Only 5% of Canadian youth meet the recommended 60 minutes of moderate to vigorous physical activity (MVPA) per day, with leisure time being increasingly allocated to technology usage. Direct-to-consumer mHealth devices that promote physical activity, such as wrist-worn physical activity trackers, have features with potential appeal to youth.

Objective

The primary purpose of this study was to determine whether a minimalist physical activity tracker-based intervention would lead to an increase in physical activity in young adolescents. A secondary aim of this study was to assess change in physical activity across a 7-week intervention, as measured by the tracker.

Methods

Using a quasi-experimental crossover design, two groups of 23 young adolescents (aged 13-14 years) were randomly assigned to immediate intervention or delayed intervention. The intervention consisted of wearing a Fitbit-Charge-HR physical activity tracker over a 7-week period. Actical accelerometers were used to measure participants’ levels of MVPA before and at the end of intervention periods for each group. Covariates such as age, sex, stage of change for physical activity behavior, and goal commitment were also measured.

Results

There was an increase in physical activity over the course of the study period, though it was not related to overall physical activity tracker use. An intervention response did, however, occur in a subset of participants. Specifically, exposure to the physical activity tracker was associated with an average daily increase in MVPA by more than 15 minutes (P=.01) among participants who reported being in the action and maintenance stages of behavior change in relation to participation in physical activity. Participants in the precontemplation, contemplation, and preparation stages of behavior change had no change in their level of MVPA (P=.81).

Conclusions

These results suggest that physical activity trackers may elicit improved physical activity related behavior in young adolescents demonstrating a readiness to be active. Future studies should seek to investigate if integrating physical activity trackers as part of more intensive interventions leads to greater increases in physical activity across different levels of stages of behavior change and if these changes can be sustained over longer periods of time.

Apps to improve diet, physical activity and sedentary behaviour in children and adolescents: a review of quality, features and behaviour change techniques

Background

The number of commercial apps to improve health behaviours in children is growing rapidly. While this provides opportunities for promoting health, the content and quality of apps targeting children and adolescents is largely unexplored. This review systematically evaluated the content and quality of apps to improve diet, physical activity and sedentary behaviour in children and adolescents, and examined relationships of app quality ratings with number of app features and behaviour change techniques (BCTs) used.

Methods

Systematic literature searches were conducted in iTunes and Google Play stores between May–November 2016. Apps were included if they targeted children or adolescents, focused on improving diet, physical activity and/or sedentary behaviour, had a user rating of at least 4+ based on at least 20 ratings, and were available in English. App inclusion, downloading and user-testing for quality assessment and content analysis were conducted independently by two reviewers. Spearman correlations were used to examine relationships between app quality, and number of technical app features and BCTs included.

Results

Twenty-five apps were included targeting diet (n = 12), physical activity (n = 18) and sedentary behaviour (n = 7). On a 5-point Mobile App Rating Scale (MARS), overall app quality was moderate (total MARS score: 3.6). Functionality was the highest scoring domain (mean: 4.1, SD: 0.6), followed by aesthetics (mean: 3.8, SD: 0.8), and lower scoring for engagement (mean: 3.6, SD: 0.7) and information quality (mean: 2.8, SD: 0.8). On average, 6 BCTs were identified per app (range: 1–14); the most frequently used BCTs were providing ‘instructions’ (n = 19), ‘general encouragement’ (n = 18), ‘contingent rewards’ (n = 17), and ‘feedback on performance’ (n = 13). App quality ratings correlated positively with numbers of technical app features (rho = 0.42, p < 0.05) and BCTs included (rho = 0.54, p < 0.01).

Conclusions

Popular commercial apps to improve diet, physical activity and sedentary behaviour in children and adolescents had moderate quality overall, scored higher in terms of functionality. Most apps incorporated some BCTs and higher quality apps included more app features and BCTs. Future app development should identify factors that promote users’ app engagement, be tailored to specific population groups, and be informed by health behaviour theories.

Electronic supplementary material

The online version of this article (doi:10.1186/s12966-017-0538-3) contains supplementary material, which is available to authorized users.

A qualitative evaluation of breast cancer survivors' acceptance of and preferences for consumer wearable technology activity trackers

BACKGROUND

Physical inactivity and sedentary behaviour are common amongst breast cancer survivors. These behaviours are associated with an increased risk of comorbidities such as heart disease, diabetes and other cancers. Commercially available, wearable activity trackers (WATs) have potential utility as behavioural interventions to increase physical activity and reduce sedentary behaviour within this population.

PURPOSE

The purpose of the study is to explore the acceptability and usability of consumer WAT amongst postmenopausal breast cancer survivors.

METHODS

Fourteen participants tested two to three randomly assigned trackers from six available models (Fitbit One, Jawbone Up 24, Garmin Vivofit 2, Garmin Vivosmart, Garmin Vivoactive and Polar A300). Participants wore each device for 2 weeks, followed by a 1-week washout period before wearing the next device. Four focus groups employing a semi-structured interview guide explored user perceptions and experiences. We used a thematic analysis approach to analyse focus group transcripts.

RESULTS

Five themes emerged from our data: (1) trackers' increased self-awareness and motivation, (2) breast cancer survivors' confidence and comfort with wearable technology, (3) preferred and disliked features of WAT, (4) concerns related to the disease and (5) peer support and doctor monitoring were possible strategies for WAT application.

CONCLUSIONS

WATs are perceived as useful and acceptable interventions by postmenopausal breast cancer survivors. Effective WAT interventions may benefit from taking advantage of the simple features of the trackers paired with other behavioural change techniques, such as specialist counselling, doctor monitoring and peer support, along with simple manual instructions.

Breast cancer survivors' preferences for technology-supported exercise interventions

PURPOSE

The purpose of this study was to explore breast cancer survivors' interest in and preferences for technology-supported exercise interventions.

METHODS

Post-treatment survivors [n = 279; M _age = 60.7 (SD = 9.7)] completed a battery of online questionnaires in August 2015. Descriptive statistics were calculated for all data. Logistic regression analyses were conducted to examine relationships between survivors' interest in a technology-supported exercise interventions and demographic, disease, and behavioral factors. These same factors were examined in relation to perceived effectiveness of such interventions using multiple regression analyses.

RESULTS

About half (53.4%) of survivors self-reported meeting public health recommendations for physical activity. Fewer than half reported using an exercise or diet mobile app (41.2%) or owning an activity tracker (40.5%). The majority were interested in receiving remotely delivered exercise counseling (84.6%), participating in a remotely delivered exercise intervention (79.5%), and using an exercise app or website (68%). Survivors reported that the most helpful technology-supported intervention components would be an activity tracker (89.5%), personalized feedback (81.2%), and feedback on how exercise is influencing mood, fatigue, etc. (73.6%). Components rated as least helpful were social networking integration (31.2%), group competitions (33.9%), and ability to see others' progress (35.1%).

CONCLUSIONS

Preferences for technology-supported exercise interventions varied among breast cancer survivors. Nonetheless, data indicate that technology-supported interventions may be feasible and acceptable. Engaging stakeholders may be important in developing and testing potential intervention components.

Feasibility and Acceptability of a Wearable Technology Physical Activity Intervention With Telephone Counseling for Mid-Aged and Older Adults: A Randomized Controlled Pilot Trial

BACKGROUND

As adults age, their physical activity decreases and sedentary behavior increases, leading to increased risk of negative health outcomes. Wearable electronic activity monitors have shown promise for delivering effective behavior change techniques. However, little is known about the feasibility and acceptability of non-Fitbit wearables (Fitbit, Inc, San Francisco, California) combined with telephone counseling among adults aged more than 55 years.

OBJECTIVE

The purpose of our study was to determine the feasibility, acceptability, and effect on physical activity of an intervention combining a wearable physical activity monitor, tablet device, and telephone counseling among adults aged 55-79 years.

METHODS

Adults (N=40, aged 55-79 years, body mass index=25-35, <60 min of activity per week) were randomized to receive a 12-week intervention or to a wait list control. Intervention participants received a Jawbone Up24 monitor, a tablet with the Jawbone Up app installed, and brief weekly telephone counseling. Participants set daily and weekly step goals and used the monitor's idle alert to notify them when they were sedentary for more than 1 h. Interventionists provided brief counseling once per week by telephone. Feasibility was measured using observation and study records, and acceptability was measured by self-report using validated items. Physical activity and sedentary time were measured using ActivPAL monitors following standard protocols. Body composition was measured using dual-energy x-ray absorptiometry scans, and fitness was measured using a 6-min walk test.

RESULTS

Participants were 61.48 years old (SD 5.60), 85% (34/40) female, 65% (26/40) white. Average activity monitor wear time was 81.85 (SD 3.73) of 90 days. Of the 20 Up24 monitors, 5 were reported broken and 1 lost. No related adverse events were reported. Acceptability items were rated at least 4 on a scale of 1-5. Effect sizes for most outcomes were small, including stepping time per day (d=0.35), steps per day (d=0.26), sitting time per day (d=0.21), body fat (d=0.17), and weight (d=0.33).

CONCLUSIONS

The intervention was feasible and acceptable in this population. Effect sizes were similar to the sizes found using other wearable electronic activity monitors, indicating that when combined with telephone counseling, wearable activity monitors are a potentially effective tool for increasing physical activity and decreasing sedentary behavior.

TRIAL REGISTRATION

Clinicaltrials.gov NCT01869348; https://clinicaltrials.gov/ct2/show/NCT01869348 (Archived by WebCite at http://www.webcitation.org/6odlIolqy).

Personal Activity Trackers and the Quantified Self

Personal activity trackers are an inexpensive and easy way for people to record their physical activity and simple biometric data. As these devices have increased in availability and sophistication, their use in daily life and in medicine has grown. This column will briefly explore what these devices are, what types of data they can track, and how that data can be used. It will also discuss potential problems with trackers and how librarians can help patients and physicians manage and protect activity data. A brief list of currently available activity trackers is also included.

Behavior Change with Fitness Technology in Sedentary Adults: A Review of the Evidence for Increasing Physical Activity

Physical activity is closely linked with health and well-being; however, many Americans do not engage in regular exercise. Older adults and those with low socioeconomic status are especially at risk for poor health, largely due to their sedentary lifestyles. Fitness technology, including trackers and smartphone applications (apps), has become increasingly popular for measuring and encouraging physical activity in recent years. However, many questions remain regarding the effectiveness of this technology for promoting behavior change. Behavior change techniques such as goal setting, feedback, rewards, and social factors are often included in fitness technology. However, it is not clear which components are most effective and which are actually being used by consumers. We discuss additional strategies not typically included in fitness technology devices or apps that are promising for engaging inactive, vulnerable populations. These include action planning, restructuring negative attitudes, enhancing environmental conditions, and identifying other barriers to regular physical activity. We consider which strategies are most conducive to motivating behavior change among sedentary adults. Overall, fitness technology has the potential to significantly impact public health, research, and policies. We suggest ways in which app developers and behavior change experts can collaborate to develop successful apps. Advances are still needed to help inactive individuals determine how, when, where, and with whom they can increase their physical activity.

How Gamification Affects Physical Activity: Large-scale Analysis of Walking Challenges in a Mobile Application

Gamification represents an effective way to incentivize user behavior across a number of computing applications. However, despite the fact that physical activity is essential for a healthy lifestyle, surprisingly little is known about how gamification and in particular competitions shape human physical activity.

Here we study how competitions affect physical activity. We focus on walking challenges in a mobile activity tracking application where multiple users compete over who takes the most steps over a predefined number of days. We synthesize our findings in a series of game and app design implications. In particular, we analyze nearly 2,500 physical activity competitions over a period of one year capturing more than 800,000 person days of activity tracking. We observe that during walking competitions, the average user increases physical activity by 23%. Furthermore, there are large increases in activity for both men and women across all ages, and weight status, and even for users that were previously fairly inactive. We also find that the composition of participants greatly affects the dynamics of the game. In particular, if highly unequal participants get matched to each other, then competition suffers and the overall effect on the physical activity drops significantly. Furthermore, competitions with an equal mix of both men and women are more effective in increasing the level of activities. We leverage these insights to develop a statistical model to predict whether or not a competition will be particularly engaging with significant accuracy. Our models can serve as a guideline to help design more engaging competitions that lead to most beneficial behavioral changes.

Development of the Physical activity and Your Nutrition for Cancer (PYNC) smartphone app for preventing breast cancer in women

BACKGROUND

In the U.S., breast cancer accounts for more cancer deaths in women than any site other than lung cancer. Based upon attributable risks, about 30-35% of breast cancers could potentially be prevented by addressing obesity, physical inactivity, increased alcohol consumption, and carcinogenic exposures such as hormone replacement therapy (HRT). We need methods of reducing women's risks of this disease that are attractive and easy to use, widely accessible to diverse women, and able to be easily amended to account for new research.

METHODS

The overall objective of this 12-month project is to develop and test a smartphone app to provide women with information about how they can reduce their risk of breast cancer through healthy behaviors such as physical activity, weight management, restricting caloric intake, consuming a healthy diet and proper nutrition, engaging in regular physical activity, and avoiding carcinogenic exposures such as HRT and alcohol. The specific aims are: (I) to develop a smartphone app for breast cancer prevention using a behavioral framework; (II) to ensure interconnectivity with commercially available products (Fitbit device for monitoring physical activity and the LoseIt! smartphone app for monitoring and tracking diet and nutrition); and (III) to ensure that the mHealth intervention is suitable for women with varying levels of health literacy and eHealth literacy.

RESULTS

The app, referred to as Physical activity and Your Nutrition for Cancer (PYNC), is being coded on an iOS platform. Users will be able to access the breast cancer prevention app using their smartphone or tablet. The app's design will ensure interconnectivity with commercially available products for monitoring and tracking physical activity, caloric intake, diet and nutrition. Using the app, it will be feasible for users to connect and sync their Fitbit and LoseIt! accounts so that information collected about physical activity, caloric intake, diet, and nutrition can be conveniently assessed from one portal. The Fitbit device and app provides reminders and allows users to set physical activity goals. Users will be able to access health education information about breast cancer risk-reduction with attractive graphics and visual displays.

CONCLUSIONS

Future directions will include testing the efficacy of the mHealth intervention in increasing physical activity, improving diet and nutrition, and weight management through a randomized controlled trial, and widespread dissemination and implementation research.

THE FUTURE OF MOBILE HEALTH APPLICATIONS AND DEVICES IN CARDIOVASCULAR HEALTH

Mobile health (mHealth) is the utilisation of mobile technologies in healthcare and has particular relevance in improving lifestyle behaviours which may ultimately reduce cardiovascular disease risk. Various intervention studies for example integrate self-monitoring of diet and physical activity with text messaging systems to improve intermediate outcomes. Currently the future progress of mHealth technologies in formal diagnostic and therapeutic roles is pending and includes the need to validate and standardise accelerometer and heart rate data from various devices. Data also needs to be integrated from such devices into the medical record system to facilitate communication between providers and patients. Although short-term behaviour changes have been found with technologies such as Fitbit® (Fitbit, Inc., San Francisco, California, USA), whether such technologies/interventions lead to sustained behaviour change and reduced risk of myocardial infarction and death remains to be seen.

Healthy lifestyle intervention for adult clinic patients with type 2 diabetes mellitus

BACKGROUND

Diet and exercise therapy have been reported to be effective in improving blood glucose control and are an important part of treatment of type 2 diabetes mellitus.

OBJECTIVE

The goal of this study is to examine the efficacy of a healthy lifestyle intervention for adult clinic patients with type 2 diabetes mellitus, as measured by Hgb-A1c, cardiovascular indicators, physical activity, weight, and BMI. Also of interest are optimal strategies for subject recruitment, the number of intervention sessions attended, and participant use of the Fitbit watch to monitor their physical activity and track food and beverage consumption.

METHODS

A pre/post-test design will be used in this pilot study. Non-institutionalized adult patients (n=50) aged 18-65 years who have been seen at the Augusta Health outpatient clinics (General Internal Medicine or Family Medicine) for type 2 diabetes in the past 12 months, and who are interested in reducing their risk of disease recurrence through healthy lifestyle behaviors, will be eligible to participate. At orientation visit, eligible individuals will be asked to provide written informed consent. Consenting volunteers (n=50) will be asked to complete the baseline and 6-month follow-up questionnaire and to participate in 12 weekly group sessions of 90 min duration, involving physical activity and to meet with a dietitian (baseline, one month, 90 days) to receive individualized advice on diet and nutrition. The technology-based intervention will use wrist-worn Fitbit Blaze physical activity monitoring devices.

CONCLUSIONS

This pilot study will provide important information about the feasibility and preliminary efficacy of a healthy lifestyle intervention for adult clinic patients with type 2 diabetes mellitus. The use of consumer-facing devices such as the Fitbit watch has the potential advantage over the use of research accelerometers, pedometers, or actigraphs in increasing the likelihood that the intervention will be sustainable after the study ends.

Assessing the Correlation Between Physical Activity and Quality of Life in Advanced Lung Cancer

BACKGROUND AND OBJECTIVE

Increasing physical activity (PA) is safe and beneficial in lung cancer (LC) patients. Advanced-stage LC patients are under-studied and have worse symptoms and quality of life (QoL). We evaluated the feasibility of monitoring step count in advanced LC as well as potential correlations between PA and QoL.

METHODS

This is a prospective, observational study of 39 consecutive patients with advanced-stage LC. Daily step count over 1 week (via Fitbit Zip), QoL, dyspnea, and depression scores were collected. Spearman rank testing was used to assess correlations. Correlation coefficients (ρ) >0.3 or <-0.3 (more and less correlated, respectively) were considered potentially clinically significant.

RESULTS

Most (83%) of the patients were interested in participating, and 67% of those enrolled were adherent with the device. Of those using the device (n = 30), the average daily step count was 4877 (range = 504-12 118) steps/d. Higher average daily step count correlated with higher QoL (ρ = 0.46), physical (ρ = 0.61), role (ρ = 0.48), and emotional functioning (ρ = 0.40) scores as well as lower depression (ρ = -0.40), dyspnea (ρ = -0.54), and pain (ρ = -0.37) scores.

CONCLUSION

Remote PA monitoring (Fitbit Zip) is feasible in advanced-stage LC patients. Interest in participating in this PA study was high with comparable adherence to other PA studies. In those utilizing the device, higher step count correlates with higher QoL as well as lower dyspnea, pain, and depression scores. PA monitoring with wearable devices in advanced-stage LC deserves further study.

An Open Platform for Seamless Sensor Support in Healthcare for the Internet of Things

Population aging and increasing pressure on health systems are two issues that demand solutions. Involving and empowering citizens as active managers of their health represents a desirable shift from the current culture mainly focused on treatment of disease, to one also focused on continuous health management and well-being. Current developments in technological areas such as the Internet of Things (IoT), lead to new technological solutions that can aid this shift in the healthcare sector. This study presents the design, development, implementation and evaluation of a platform called Common Recognition and Identification Platform (CRIP), a part of the CareStore project, which aims at supporting caregivers and citizens to manage health routines in a seamless way. Specifically, the CRIP offers sensor-based support for seamless identification of users and health devices. A set of initial requirements was defined with a focus on usability limitations and current sensor technologies. The CRIP was designed and implemented using several technologies that enable seamless integration and interaction of sensors and people, namely Near Field Communication and fingerprint biometrics for identification and authentication, Bluetooth for communication with health devices and web services for wider integration with other platforms. Two CRIP prototypes were implemented and evaluated in laboratory during a period of eight months. The evaluations consisted of identifying users and devices, as well as seamlessly configure and acquire vital data from the last. Also, the entire Carestore platform was deployed in a nursing home where its usability was evaluated with caregivers. The evaluations helped assess that seamless identification of users and seamless configuration and communication with health devices is feasible and can help enable the IoT on healthcare applications. Therefore, the CRIP and similar platforms could be transformed into a valuable enabling technology for secure and reliable IoT deployments on the healthcare sector.

Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review

BACKGROUND

Health and fitness applications (apps) have gained popularity in interventions to improve diet, physical activity and sedentary behaviours but their efficacy is unclear. This systematic review examined the efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour in children and adults.

METHODS

Systematic literature searches were conducted in five databases to identify papers published between 2006 and 2016. Studies were included if they used a smartphone app in an intervention to improve diet, physical activity and/or sedentary behaviour for prevention. Interventions could be stand-alone interventions using an app only, or multi-component interventions including an app as one of several intervention components. Outcomes measured were changes in the health behaviours and related health outcomes (i.e., fitness, body weight, blood pressure, glucose, cholesterol, quality of life). Study inclusion and methodological quality were independently assessed by two reviewers.

RESULTS

Twenty-seven studies were included, most were randomised controlled trials (n = 19; 70%). Twenty-three studies targeted adults (17 showed significant health improvements) and four studies targeted children (two demonstrated significant health improvements). Twenty-one studies targeted physical activity (14 showed significant health improvements), 13 studies targeted diet (seven showed significant health improvements) and five studies targeted sedentary behaviour (two showed significant health improvements). More studies (n = 12; 63%) of those reporting significant effects detected between-group improvements in the health behaviour or related health outcomes, whilst fewer studies (n = 8; 42%) reported significant within-group improvements. A larger proportion of multi-component interventions (8 out of 13; 62%) showed significant between-group improvements compared to stand-alone app interventions (5 out of 14; 36%). Eleven studies reported app usage statistics, and three of them demonstrated that higher app usage was associated with improved health outcomes.

CONCLUSIONS

This review provided modest evidence that app-based interventions to improve diet, physical activity and sedentary behaviours can be effective. Multi-component interventions appear to be more effective than stand-alone app interventions, however, this remains to be confirmed in controlled trials. Future research is needed on the optimal number and combination of app features, behaviour change techniques, and level of participant contact needed to maximise user engagement and intervention efficacy.

Influence of Pokémon Go on Physical Activity: Study and Implications

Background

Physical activity helps people maintain a healthy weight and reduces the risk for several chronic diseases. Although this knowledge is widely recognized, adults and children in many countries around the world do not get recommended amounts of physical activity. Although many interventions are found to be ineffective at increasing physical activity or reaching inactive populations, there have been anecdotal reports of increased physical activity due to novel mobile games that embed game play in the physical world. The most recent and salient example of such a game is Pokémon Go, which has reportedly reached tens of millions of users in the United States and worldwide.

Objective

The objective of this study was to quantify the impact of Pokémon Go on physical activity.

Methods

We study the effect of Pokémon Go on physical activity through a combination of signals from large-scale corpora of wearable sensor data and search engine logs for 32,000 Microsoft Band users over a period of 3 months. Pokémon Go players are identified through search engine queries and physical activity is measured through accelerometers.

Results

We find that Pokémon Go leads to significant increases in physical activity over a period of 30 days, with particularly engaged users (ie, those making multiple search queries for details about game usage) increasing their activity by 1473 steps a day on average, a more than 25% increase compared with their prior activity level (P<.001). In the short time span of the study, we estimate that Pokémon Go has added a total of 144 billion steps to US physical activity. Furthermore, Pokémon Go has been able to increase physical activity across men and women of all ages, weight status, and prior activity levels showing this form of game leads to increases in physical activity with significant implications for public health. In particular, we find that Pokémon Go is able to reach low activity populations, whereas all 4 leading mobile health apps studied in this work largely draw from an already very active population.

Conclusions

Mobile apps combining game play with physical activity lead to substantial short-term activity increases and, in contrast to many existing interventions and mobile health apps, have the potential to reach activity-poor populations. Future studies are needed to investigate potential long-term effects of these applications.

Use of Consumer Wearable Devices to Promote Physical Activity: A Review of Health Intervention Studies

BACKGROUND

Although many wearable devices for monitoring and tracking physical activity are available to consumers, relatively few research studies have been conducted to determine their efficacy in promoting health.

METHODS

In this article, data on the use of consumer wearable devices in promoting healthy behaviors are summarized based upon bibliographic searches in PubMed and Psychology and Behavioral Sciences Collection with relevant search terms through September 2016.

RESULTS

A total of 274 articles were identified in the bibliographic searches. By screening abstracts or full-text articles, six pre/post test trials and seven randomized controlled trials were identified. In initial trials, consumer wearable devices have been shown to increase physical activity and help users lose weight. However, the number of studies completed to date is small and limited by small sample sizes, short study durations, and uncertain generalizability of the findings.

CONCLUSIONS

Future studies should utilize randomized controlled trial research designs, larger sample sizes, and longer study periods to better establish the efficacy of wearable devices in promoting physical activity. Additional research is needed to determine the feasibility and effectiveness of wearable devices in promoting physical activity and weight loss in community settings including communities affected by health disparities. Studies focusing on children and adolescents are also needed.

Use of a Wearable Activity Device in Rural Older Obese Adults: A Pilot Study

Objective: Assess the feasibility and acceptability of Fitbit for supporting behavioral change in rural, older adults with obesity. Method: Eight adults aged ≥65 with a body mass index (BMI) ≥30kg/m² were recruited from a rural practice and provided a Fitbit Zip device for 30 days. Participants completed validated questionnaires/interviews. Results: Mean age was 73.4 ± 4.0 years (50% female) with a mean BMI of 34.5 ± 4.5kg/m². We observed reductions in exercise confidence (sticking to it: 34.5 ± 3.3 to 30.9 ± 4.3, p = .04; making time: 18.9 ± 1.3 to 17.0 ± 2.6, p = .03) but no changes in patient activation (45.4 ± 4.3 vs. 45.0 ± 3.9). All reported high satisfaction, seven (87.5%) found Fitbit easy to use, and five (62.5%) found the feedback useful. The majority (n = 6 [75.0%]) were mostly/very satisfied with the intervention. Consistent themes emerged regarding the benefit of self-monitoring and participant motivation. Common concerns included finding time to exercise and lack of a peer group. Conclusion: Use of Fitbit is feasible/acceptable for use among older rural obese adults but may lead to reduced confidence.

Person-generated Data in Self-quantification. A Health Informatics Research Program

OBJECTIVES

The availability of internet-connected mobile, wearable and ambient consumer technologies, direct-to-consumer e-services and peer-to-peer social media sites far outstrips evidence about the efficiency, effectiveness and efficacy of using them in healthcare applications. The aim of this paper is to describe one approach to build a program of health informatics research, so as to generate rich and robust evidence about health data and information processing in self-quantification and associated healthcare and health outcomes.

METHODS

The paper summarises relevant health informatics research approaches in the literature and presents an example of developing a program of research in the Health and Biomedical Informatics Centre (HaBIC) at the University of Melbourne. The paper describes this program in terms of research infrastructure, conceptual models, research design, research reporting and knowledge sharing.

RESULTS

The paper identifies key outcomes from integrative and multiple-angle approaches to investigating the management of information and data generated by use of this Centre's collection of wearable, mobiles and other devices in health self-monitoring experiments. These research results offer lessons for consumers, developers, clinical practitioners and biomedical and health informatics researchers.

CONCLUSIONS

Health informatics is increasingly called upon to make sense of emerging self-quantification and other digital health phenomena that are well beyond the conventions of healthcare in which the field of informatics originated and consolidated. To make a substantial contribution to optimise the aims, processes and outcomes of health self-quantification needs further work at scale in multi-centre collaborations for this Centre and for health informatics researchers generally.

Estimating Physical Activity and Sedentary Behavior in a Free-Living Context: A Pragmatic Comparison of Consumer-Based Activity Trackers and ActiGraph Accelerometry

BACKGROUND

Activity trackers are increasingly popular with both consumers and researchers for monitoring activity and for promoting positive behavior change. However, there is a lack of research investigating the performance of these devices in free-living contexts, for which findings are likely to vary from studies conducted in well-controlled laboratory settings.

OBJECTIVE

The aim was to compare Fitbit One and Jawbone UP estimates of steps, moderate-to-vigorous physical activity (MVPA), and sedentary behavior with data from the ActiGraph GT3X+ accelerometer in a free-living context.

METHODS

Thirty-two participants were recruited using convenience sampling; 29 provided valid data for this study (female: 90%, 26/29; age: mean 39.6, SD 11.0 years). On two occasions for 7 days each, participants wore an ActiGraph GT3X+ accelerometer on their right hip and either a hip-worn Fitbit One (n=14) or wrist-worn Jawbone UP (n=15) activity tracker. Daily estimates of steps and very active minutes were derived from the Fitbit One (n=135 days) and steps, active time, and longest idle time from the Jawbone UP (n=154 days). Daily estimates of steps, MVPA, and longest sedentary bout were derived from the corresponding days of ActiGraph data. Correlation coefficients and Bland-Altman plots with examination of systematic bias were used to assess convergent validity and agreement between the devices and the ActiGraph. Cohen's kappa was used to assess the agreement between each device and the ActiGraph for classification of active versus inactive (≥10,000 steps per day and ≥30 min/day of MVPA) comparable with public health guidelines.

RESULTS

Correlations with ActiGraph estimates of steps and MVPA ranged between .72 and .90 for Fitbit One and .56 and .75 for Jawbone UP. Compared with ActiGraph estimates, both devices overestimated daily steps by 8% (Fitbit One) and 14% (Jawbone UP). However, mean differences were larger for daily MVPA (Fitbit One: underestimated by 46%; Jawbone UP: overestimated by 50%). There was systematic bias across all outcomes for both devices. Correlations with ActiGraph data for longest idle time (Jawbone UP) ranged from .08 to .19. Agreement for classifying days as active or inactive using the ≥10,000 steps/day criterion was substantial (Fitbit One: κ=.68; Jawbone UP: κ=.52) and slight-fair using the criterion of ≥30 min/day of MVPA (Fitbit One: κ=.40; Jawbone UP: κ=.14).

CONCLUSIONS

There was moderate-strong agreement between the ActiGraph and both Fitbit One and Jawbone UP for the estimation of daily steps. However, due to modest accuracy and systematic bias, they are better suited for consumer-based self-monitoring (eg, for the public consumer or in behavior change interventions) rather than to evaluate research outcomes. The outcomes that relate to health-enhancing MVPA (eg, "very active minutes" for Fitbit One or "active time" for Jawbone UP) and sedentary behavior ("idle time" for Jawbone UP) should be used with caution by consumers and researchers alike.

Mobile and Wearable Device Features that Matter in Promoting Physical Activity

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 (N = 67). 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 = 265) vs. -28 steps/ day (SE = 242) (p = .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.

Interrogation of Patient Smartphone Activity Tracker to Assist Arrhythmia Management

A 42-year-old man presented to the emergency department (ED) with newly diagnosed atrial fibrillation of unknown duration. Interrogation of the patient's wrist-worn activity tracker and smartphone application identified the onset of the arrhythmia as within the previous 3 hours, permitting electrocardioversion and discharge of the patient from the ED.

Systematic review of the validity and reliability of consumer-wearable activity trackers

BACKGROUND

Consumer-wearable activity trackers are electronic devices used for monitoring fitness- and other health-related metrics. The purpose of this systematic review was to summarize the evidence for validity and reliability of popular consumer-wearable activity trackers (Fitbit and Jawbone) and their ability to estimate steps, distance, physical activity, energy expenditure, and sleep.

METHODS

Searches included only full-length English language studies published in PubMed, Embase, SPORTDiscus, and Google Scholar through July 31, 2015. Two people reviewed and abstracted each included study.

RESULTS

In total, 22 studies were included in the review (20 on adults, 2 on youth). For laboratory-based studies using step counting or accelerometer steps, the correlation with tracker-assessed steps was high for both Fitbit and Jawbone (Pearson or intraclass correlation coefficients (CC) > =0.80). Only one study assessed distance for the Fitbit, finding an over-estimate at slower speeds and under-estimate at faster speeds. Two field-based studies compared accelerometry-assessed physical activity to the trackers, with one study finding higher correlation (Spearman CC 0.86, Fitbit) while another study found a wide range in correlation (intraclass CC 0.36-0.70, Fitbit and Jawbone). Using several different comparison measures (indirect and direct calorimetry, accelerometry, self-report), energy expenditure was more often under-estimated by either tracker. Total sleep time and sleep efficiency were over-estimated and wake after sleep onset was under-estimated comparing metrics from polysomnography to either tracker using a normal mode setting. No studies of intradevice reliability were found. Interdevice reliability was reported on seven studies using the Fitbit, but none for the Jawbone. Walking- and running-based Fitbit trials indicated consistently high interdevice reliability for steps (Pearson and intraclass CC 0.76-1.00), distance (intraclass CC 0.90-0.99), and energy expenditure (Pearson and intraclass CC 0.71-0.97). When wearing two Fitbits while sleeping, consistency between the devices was high.

CONCLUSION

This systematic review indicated higher validity of steps, few studies on distance and physical activity, and lower validity for energy expenditure and sleep. The evidence reviewed indicated high interdevice reliability for steps, distance, energy expenditure, and sleep for certain Fitbit models. As new activity trackers and features are introduced to the market, documentation of the measurement properties can guide their use in research settings.