Reciprocal Reinforcement Between Wearable Activity Trackers and Social Network Services in Influencing Physical Activity Behaviors

Exploring the Experiences of Community-Dwelling Older Adults on Using Wearable Monitoring Devices With Regular Support From Community Health Workers, Nurses, and Social Workers: Qualitative Descriptive Study

BACKGROUND

The use of wearable monitoring devices (WMDs), such as smartwatches, is advancing support and care for community-dwelling older adults across the globe. Despite existing evidence of the importance of WMDs in preventing problems and promoting health, significant concerns remain about the decline in use after a period of time, which warrant an understanding of how older adults experience the devices.

OBJECTIVE

This study aims to explore and describe the experiences of community-dwelling older adults after receiving our interventional program, which included the use of a smartwatch with support from a community health workers, nurses, and social workers, including the challenges that they experienced while using the device, the perceived benefits, and strategies to promote their sustained use of the device.

METHODS

We used a qualitative descriptive approach in this study. Older adults who had taken part in an interventional study involving the use of smartwatches and who were receiving regular health and social support were invited to participate in focus group discussions at the end of the trial. Purposive sampling was used to recruit potential participants. Older adults who agreed to participate were assigned to focus groups based on their community. The focus group discussions were facilitated and moderated by 2 members of the research team. All discussions were recorded and transcribed verbatim. We used the constant comparison analytical approach to analyze the focus group data.

RESULTS

A total of 22 participants assigned to 6 focus groups participated in the study. The experiences of community-dwelling older adults emerged as (1) challenges associated with the use of WMDs, (2) the perceived benefits of using the WMDs, and (3) strategies to promote the use of WMDs. In addition, the findings also demonstrate a hierarchical pattern of health-seeking behaviors by older adults: seeking assistance first from older adult volunteers, then from social workers, and finally from nurses.

CONCLUSIONS

Ongoing use of the WMDs is potentially possible, but it is important to ensure the availability of technical support, maintain active professional follow-ups by nurses and social workers, and include older adult volunteers to support other older adults in such programs.

The Use of Digital Health Interventions for Cardiometabolic Diseases Among South Asian and Black Minority Ethnic Groups: Realist Review

BACKGROUND

Digital health interventions (DHIs) for the prevention and management of cardiometabolic diseases have become increasingly common. However, there is limited evidence for the suitability of these approaches in minority ethnic populations, who are at an increased risk of these diseases.

OBJECTIVE

This study aimed to investigate the use of DHIs for cardiovascular disease and type 2 diabetes among minority ethnic populations in countries with a majority of White, English-speaking populations, focusing on people who identified as South Asian, Black, or African American.

METHODS

A realist methodology framework was followed. A literature search was conducted to develop context-mechanism-outcome configurations, including the contexts in which DHIs work for the target minority ethnic groups, mechanisms that these contexts trigger, and resulting health outcomes. After systematic searches, a qualitative analysis of the included studies was conducted using deductive and inductive coding.

RESULTS

A total of 15 studies on the uptake of DHIs for cardiovascular disease or diabetes were identified, of which 13 (87%) focused on people with an African-American background. The review found evidence supporting the use of DHIs in minority ethnic populations when specific factors are considered in implementation and design, including patients' beliefs, health needs, education and literacy levels, material circumstances, culture, social networks, and wider community and the supporting health care systems.

CONCLUSIONS

Our context-mechanism-outcome configurations provide a useful guide for the future development of DHIs targeted at South Asian and Black minority ethnic populations, with specific recommendations for improving cultural competency and promoting accessibility and inclusivity of design.

The Impact of Wearable Devices on Physical Activity for Chronic Disease Patients: Findings from the 2019 Health Information National Trends Survey

BACKGROUND

Wearable devices are shown to be an advanced tool for chronic disease management, but their impacts on physical activity remain uninvestigated. This study aims to examine the effect of wearable devices on physical activity in general people and chronic patients.

METHODS

Our sample was from the third cycle of the fifth iteration of the Health Information National Trends Survey (HINTS), which includes a total of 5438 residents. Genetic matching was used to evaluate the effect of wearable devices on physical activity in different populations.

RESULTS

(1) Both using wearable devices and using them with high frequency will improve physical activity for the whole population. (2) Wearable devices may have greater positive effects on physical activity for chronic patients. (3) Especially in patients with hypertension, high-frequency use of wearable devices can significantly improve the duration and frequency of physical activity.

CONCLUSIONS

Wearable devices lead to more physical activity, and the benefit is more noticeable for chronic patients, particularly those with hypertension.

Research on User Experience of Sports Smart Bracelet Based on Fuzzy Comprehensive Appraisal and SSA-BP Neural Network

Due to the marked increase in the prevalence of overweight and obesity worldwide and an environment leading to a series of chronic diseases, physical exercise is an important way to prevent chronic diseases. Additionally, a good exercise smart bracelet can bring convenience to physical exercise. Quick and accurate evaluation of smart sports bracelets has become a hot topic and draws attention from both academic researchers and public society. In the literature, the analytic hierarchy process (AHP) and entropy weight method (EWM) were used to obtain the weights from both subjective and objective perspectives, which were integrated by the comprehensive weighting method, and furthermore the performance of sports smart bracelet was evaluated through fuzzy comprehensive evaluation. Also, to avoid complex weight calculations caused by the comprehensive weighting method, machine learning methods are used to model the structure and contribute to the comprehensive evaluation process. However, few studies have investigated all previous elements in the comprehensive evaluation process. In this study, we consider all previous parts when evaluating smart sports bracelets. In particular, we use the sparrow search algorithm (SSA) to optimize the backpropagation (BP) neural network for constructing the comprehensive score prediction model of the sports smart bracelet. Results show that the sparrow search algorithm-optimized backpropagation (SSA-BP) neural network model has good predictive ability and can quickly obtain evaluation results on the premise of effectively ensuring the accuracy of the evaluation results.

Self-efficacy and trust in consumers' use of health-technologies devices for sports

The commercial market for wearable health technology is growing but the value these technologies provide for consumers is debatable, as many technologies lack formal validation and are being abandoned at a high rate. The enabling of self-efficacy mechanisms in the design of health technologies, through the factors identified by self-determination theory and the Technology Acceptance Model, could increase the uptake and continued use of these devices. The aim of this research was to investigate how and why people use wearable health technology, and to evaluate their experiences from the perspective of perceptions of autonomy, safety, information security, information accuracy and willingness for continued use. Forty-eight sport enthusiasts or athletes, age range 18–65 and over, completed an online survey with 46 questions. A statistical analysis that included a Mann-Whitney U Test and a Person's Correlation analysis indicated that participants who were confident in their use of a health technology showed satisfaction with previous uses and a sense of autonomy leading to an overall positive experience. Issues around data and personal information security were identified, aligning with extant literature. Findings suggest that: (i) past experience play a role in people's perception of self-efficacy, (ii) the tracking of activities enables of autonomy and confidence, (iii) autonomy influences personal willingness to use health technologies, (iv) strong interest in personal health technologies motivates sustained engagement, and that (v) reliability and validity of data impacts on confidence in health technologies. A conceptual model is proposed for consideration when designing and evaluating health technologies, based on the factors supporting self-efficacy and trust in health technologies. Further research is required to develop this model with the aim of informing designers and developers about how to translate these factors into design features for the development of more effective personal health technology.

The Combined Effects of Sports Smart Bracelet and Multi-Component Exercise Program on Exercise Motivation among the Elderly in Macau

Background and objectives: Faced with the serious problem of an aging population, exercise is one of the most effective ways to maintain the health of the elderly. In recent years, with the popularization of smartphones, the elderly have increasingly accepted technological products that incorporate artificial intelligence (AI). However, there is not much research on using artificial intelligence bracelets to enhance elders' motivation and participation in exercise. Therefore, the purpose of this study is to evaluate the effectiveness of the combination of sports smart bracelets and multi-sport training programs on the motivation of the elderly in Macau. Materials and Methods: The study was conducted with a randomized trial design in a 12 week multi-sport exercise training intervention. According to the evaluation, a total of sixty elders' pre- and post-test data were included in this study. Results: After 12 weeks of multi-sport exercise training, the evaluation scores on the exercise motivation scale (EMS) increased significantly in the group wearing exercise bracelets and those taking part in the multi-component exercise program, and the degree of progress reached a statistically significant level, but the control group did not show any statistically significant difference. The influence of the combination of sports smart bracelets and multi-sport training programs on elders' motivation is clearer. Conclusions: The use of sports smart bracelets by elderly people in conjunction with diverse exercise training can effectively enhance elders' motivation and increase their participation in regular exercise. The combination of sports smart bracelets and multi-sport training programs is worth promoting in the elderly population.

A Mobile Social Networking App for Weight Management and Physical Activity Promotion: Results From an Experimental Mixed Methods Study

BACKGROUND

Smartphone apps, fitness trackers, and online social networks have shown promise in weight management and physical activity interventions. However, there are knowledge gaps in identifying the most effective and engaging interventions and intervention features preferred by their users.

OBJECTIVE

This 6-month pilot study on a social networking mobile app connected to wireless weight and activity tracking devices has 2 main aims: to evaluate changes in BMI, weight, and physical activity levels in users from different BMI categories and to assess user perspectives on the intervention, particularly on social comparison and automated self-monitoring and feedback features.

METHODS

This was a mixed methods study involving a one-arm, pre-post quasi-experimental pilot with postintervention interviews and focus groups. Healthy young adults used a social networking mobile app intervention integrated with wireless tracking devices (a weight scale and a physical activity tracker) for 6 months. Quantitative results were analyzed separately for 2 groups-underweight-normal and overweight-obese BMI-using t tests and Wilcoxon sum rank, Wilcoxon signed rank, and chi-square tests. Weekly BMI change in participants was explored using linear mixed effects analysis. Interviews and focus groups were analyzed inductively using thematic analysis.

RESULTS

In total, 55 participants were recruited (mean age of 23.6, SD 4.6 years; 28 women) and 45 returned for the final session (n=45, 82% retention rate). There were no differences in BMI from baseline to postintervention (6 months) and between the 2 BMI groups. However, at 4 weeks, participants' BMI decreased by 0.34 kg/m² (P<.001), with a loss of 0.86 kg/m² in the overweight-obese group (P=.01). Participants in the overweight-obese group used the app significantly less compared with individuals in the underweight-normal BMI group, as they mentioned negative feelings and demotivation from social comparison, particularly from upward comparison with fitter people. Participants in the underweight-normal BMI group were avid users of the app's self-monitoring and feedback (P=.02) and social (P=.04) features compared with those in the overweight-obese group, and they significantly increased their daily step count over the 6-month study duration by an average of 2292 steps (95% CI 898-3370; P<.001). Most participants mentioned a desire for a more personalized intervention.

CONCLUSIONS

This study shows the effects of different interventions on participants from higher and lower BMI groups and different perspectives regarding the intervention, particularly with respect to its social features. Participants in the overweight-obese group did not sustain a short-term decrease in their BMI and mentioned negative emotions from app use, while participants in the underweight-normal BMI group used the app more frequently and significantly increased their daily step count. These differences highlight the importance of intervention personalization. Future research should explore the role of personalized features to help overcome personal barriers and better match individual preferences and needs.

Use of a Smartphone App to Increase Physical Activity Levels in Insufficiently Active Adults: Feasibility Sequential Multiple Assignment Randomized Trial (SMART)

Background

The sequential multiple assignment randomized trial (SMART) design allows for changes in the intervention during the trial period. Despite its potential and feasibility for defining the best sequence of interventions, so far, it has not been utilized in a smartphone/gamified intervention for physical activity.

Objective

We aimed to investigate the feasibility of the SMART design for assessing the effects of a smartphone app intervention to improve physical activity in adults. We also aimed to describe the participants’ perception regarding the protocol and the use of the app for physical activity qualitatively.

Methods

We conducted a feasibility 24-week/two-stage SMART in which 18 insufficiently active participants (<10,000 steps/day) were first randomized to group 1 (smartphone app only), group 2 (smartphone app + tailored messages), and a control group (usual routine during the protocol). Participants were motivated to increase their step count by at least 2000 steps/day each week. Based on the 12-week intermediate outcome, responders continued the intervention and nonresponders were rerandomized to subsequent treatment, including a new group 3 (smartphone app + tailored messages + gamification) in which they were instructed to form groups to use several game elements available in the chosen app (Pacer). We considered responders as those with any positive slope in the linear relationship between weeks and steps per day at the end of the first stage of the intervention. We compared the accelerometer-based steps per day before and after the intervention, as well as the slopes of the app-based steps per day between the first and second stages of the intervention.

Results

Twelve participants, including five controls, finished the intervention. We identified two responders in group 1. We did not observe relevant changes in the steps per day either throughout the intervention or compared with the control group. However, the rerandomization of five nonresponders led to a change in the slope of the steps per day (median −198 steps/day [IQR −279 to −103] to 20 steps/day [IQR −204 to 145]; P=.08). Finally, in three participants from group 2, we observed an increase in the number of steps per day up to the sixth week, followed by an inflection to baseline values or even lower (ie, a quadratic relationship). The qualitative analysis showed that participants’ reports could be classified into the following: (1) difficulty in managing the app and technology or problems with the device, (2) suitable response to the app, and (3) difficulties to achieve the goals.

Conclusions

The SMART design was feasible and changed the behavior of steps per day after rerandomization. Rerandomization should be implemented earlier to take advantage of tailored messages. Additionally, difficulties with technology and realistic and individualized goals should be considered in interventions for physical activity using smartphones.

Trial Registration

Brazilian Registry of Clinical Trials RBR-8xtc9c; http://www.ensaiosclinicos.gov.br/rg/RBR-8xtc9c/.

What matters the adherence with BP 24-hr self-monitoring wearable device among hypertensive patients? A population-based survey

Wearable mobile health (mHealth) technologies are a convenient and cost-effective community-based intervention to improve management of hypertension in resource-limited populations. This study was designed to evaluate user characteristics of blood pressure (BP) wearable technology among a community-based population in a rural area of China. During the period of April through July 2018, a self-monitoring intervention program for hypertension control was implemented in a remote area of central China. Participants completed a cross-sectional survey which included demographic characteristics, Technology Fluency, the Compliance of Hypertensive Patients' Scale, and the Health-related Quality of Life Survey. Participants were given a wearable BP-monitoring device which wirelessly uploaded data and monitored for 1 month. Participants (n = 317) were 64.57 years (SD = 11.68), 53.94% were male. During the 30-day monitoring, 52.68% of the sample uploaded BP wristband data daily were identified as "BP device users." No differences existed between device users and nonusers related to cardiovascular health measurements, technology fluency, and health-related quality of life. Device users were more likely to report a higher level of hypertension compliance. Individuals reporting a higher level of compliance in hypertension management are more likely to interact with a wearable BP-monitoring device than persons with lower levels of compliance. Further evaluation of mobile health systems involving a wearable device as part of a hypertension management program is needed in a resource-limited community-based setting.

Adherence with blood pressure monitoring wearable device among the elderly with hypertension: The case of rural China

INTRODUCTION

Wearable blood pressure (BP) monitor devices are increasingly adopted owing to the promotion of hypertension management program. However, little is known about the adherence and its associated factors in older adults (OAs) with hypertension.

METHODS

The aim of this study was to determine factors associated with adherence to wearable BP monitor. In total, 212 OAs with hypertension in a remote rural area in China were asked to wear a BP monitor over 1-month period. The following information on associated factors for adherence was collected, including demographic characteristics, cardiovascular health measurements, technology fluency, the Compliance of Hypertensive Patients' Scale, and the Health-related Quality of Life Survey. As a result, the mean age of the 212 hypertension participants was 71.32 years (SD = 6.81).

RESULTS

During the 30-day survey, 50.94% of the participants with daily recoded BP wristband data were assigned as "BP device users." The binary logistic regression model revealed that lower lifestyle compliance, lower medication compliance and higher total hypertension compliance were significant predictors for adherence. However, there were no differences concerning cardiovascular health factors, technology fluency, and health-related quality of life between device users and nonusers.

CONCLUSION

Individuals reporting a higher level of total compliance in hypertension management were more likely to wear a BP monitor device among OAs with hypertension. In addition, further research is needed to determine how wearable mHealth technology can be used to develop better hypertension self-management education programs for this population.

Who Uses Wearable Activity Trackers and Why? A Comparison of Former and Current Users in the United States

BACKGROUND

There has been an explosion in the use of wearable activity trackers (WATs), but we do not fully understand who wears them and why. This study's purpose was to describe the characteristics of WAT users and to compare current and former users.

MATERIALS AND METHODS

A variety of internet-based resources (eg, Craigslist, Facebook) were used to recruit current and former WAT users. Respondents completed a web-based survey, where they provided information on sociodemographic characteristics, health, physical activity behavior, and about their WAT use.

RESULTS

Of the 2826 respondents who gave informed consent, 70.8% (n = 2002) met inclusion criteria for this analysis. Respondents ranged from 18 to 81 years old (mean 32.9 ± 12.2 standard deviation) with 73.8% women. Most were current WAT users (68.7%), and the average length of WAT use overall was 9.3 ± 9.7 months. On average, current users wore the device for 3.7 months longer than former users. Compared to current users, former users had a lower body mass index (1.2 kg/m² less), reported fewer medical conditions, shared data from their device less often, and received the device as a gift more frequently.

CONCLUSIONS

Current and former users varied in their reasons for using a WAT and how they used their device. Differences identified between these groups support further exploration of associations between WAT users' profiles and their physical activity behavior.

Using a Mobile Social Networking App to Promote Physical Activity: A Qualitative Study of Users' Perspectives

Background

Despite many health benefits of physical activity, nearly a third of the world’s adult population is insufficiently active. Technological interventions, such as mobile apps, wearable trackers, and Web-based social networks, offer great promise in promoting physical activity, but little is known about users’ acceptability and long-term engagement with these interventions.

Objective

The aim of this study was to understand users’ perspectives regarding a mobile social networking intervention to promote physical activity.

Methods

Participants, mostly university students and staff, were recruited using purposive sampling techniques. Participants were enrolled in a 6-month feasibility study where they were provided with a wearable physical activity tracker (Fitbit Flex 2) and a wireless scale (Fitbit Aria) integrated with a social networking mobile app (named “fit.healthy.me”). We conducted semistructured, in-depth qualitative interviews and focus groups pre- and postintervention, which were recorded and transcribed verbatim. The data were analyzed in Nvivo 11 using thematic analysis techniques.

Results

In this study, 55 participants were enrolled; 51% (28/55) were females, and the mean age was 23.6 (SD 4.6) years. The following 3 types of factors emerged from the data as influencing engagement with the intervention and physical activity: individual (self-monitoring of behavior, goal setting, and feedback on behavior), social (social comparison, similarity and familiarity between users, and participation from other users in the network), and technological. In addition, automation and personalization were observed as enhancing the delivery of both individual and social aspects. Technological limitations were mentioned as potential barriers to long-term usage.

Conclusions

Self-regulatory techniques and social factors are important to consider when designing a physical activity intervention, but a one-size-fits-all approach is unlikely to satisfy different users’ preferences. Future research should adopt innovative research designs to test interventions that can adapt and respond to users’ needs and preferences throughout time.

Activity Monitors as Support for Older Persons' Physical Activity in Daily Life: Qualitative Study of the Users' Experiences

Background

Falls are a major threat to the health and independence of seniors. Regular physical activity (PA) can prevent 40% of all fall injuries. The challenge is to motivate and support seniors to be physically active. Persuasive systems can constitute valuable support for persons aiming at establishing and maintaining healthy habits. However, these systems need to support effective behavior change techniques (BCTs) for increasing older adults’ PA and meet the senior users’ requirements and preferences. Therefore, involving users as codesigners of new systems can be fruitful. Prestudies of the user’s experience with similar solutions can facilitate future user-centered design of novel persuasive systems.

Objective

The aim of this study was to investigate how seniors experience using activity monitors (AMs) as support for PA in daily life. The addressed research questions are as follows: (1) What are the overall experiences of senior persons, of different age and balance function, in using wearable AMs in daily life?; (2) Which aspects did the users perceive relevant to make the measurements as meaningful and useful in the long-term perspective?; and (3) What needs and requirements did the users perceive as more relevant for the activity monitors to be useful in a long-term perspective?

Methods

This qualitative interview study included 8 community-dwelling older adults (median age: 83 years). The participants’ experiences in using two commercial AMs together with tablet-based apps for 9 days were investigated. Activity diaries during the usage and interviews after the usage were exploited to gather user experience. Comments in diaries were summarized, and interviews were analyzed by inductive content analysis.

Results

The users (n=8) perceived that, by using the AMs, their awareness of own PA had increased. However, the AMs’ impact on the users’ motivation for PA and activity behavior varied between participants. The diaries showed that self-estimated physical effort varied between participants and varied for each individual over time. Additionally, participants reported different types of accomplished activities; talking walks was most frequently reported. To be meaningful, measurements need to provide the user with a reliable receipt of whether his or her current activity behavior is sufficient for reaching an activity goal. Moreover, praise when reaching a goal was described as motivating feedback. To be useful, the devices must be easy to handle. In this study, the users perceived wearables as easy to handle, whereas tablets were perceived difficult to maneuver. Users reported in the diaries that the devices had been functional 78% (58/74) of the total test days.

Conclusions

Activity monitors can be valuable for supporting seniors’ PA. However, the potential of the solutions for a broader group of seniors can significantly be increased. Areas of improvement include reliability, usability, and content supporting effective BCTs with respect to increasing older adults’ PA.

Adherence with physical activity monitoring wearable devices in a community-based population: observations from the Washington, D.C., Cardiovascular Health and Needs Assessment

Wearable mobile health (mHealth) technologies offer approaches for targeting physical activity (PA) in resource-limited, community-based interventions. We sought to explore user characteristics of PA tracking, wearable technology among a community-based population within a health and needs assessment. In 2014-2015, we conducted the Washington, D.C., Cardiovascular Health and Needs Assessment in predominantly African-American churches among communities with higher obesity rates and lower household incomes. Participants received a mHealth PA monitor and wirelessly uploaded PA data weekly to church data collection hubs. Participants (n = 99) were 59 ± 12 years, 79% female, and 99% African-American, with a mean body mass index of 33 ± 7 kg/m2. Eighty-one percent of participants uploaded PA data to the hub and were termed "PA device users." Though PA device users were more likely to report lower household incomes, no differences existed between device users and non-users for device ownership or technology fluency. Findings suggest that mHealth systems with a wearable device and data collection hub may feasibly target PA in resource-limited communities.

Users' experiences of wearable activity trackers: a cross-sectional study

Background

Wearable activity trackers offer considerable promise for helping users to adopt healthier lifestyles. This study aimed to explore users’ experience of activity trackers, including usage patterns, sharing of data to social media, perceived behaviour change (physical activity, diet and sleep), and technical issues/barriers to use.

Methods

A cross-sectional online survey was developed and administered to Australian adults who were current or former activity tracker users. Results were analysed descriptively, with differences between current and former users and wearable brands explored using independent samples t-tests, Mann-Whitney, and chi square tests.

Results

Participants included 200 current and 37 former activity tracker users (total N = 237) with a mean age of 33.1 years (SD 12.4, range 18–74 years). Fitbit (67.5%) and Garmin devices (16.5%) were most commonly reported. Participants typically used their trackers for sustained periods (5–7 months) and most intended to continue usage. Participants reported they had improved their physical activity (51–81%) more commonly than they had their diet (14–40%) or sleep (11–24%), and slightly more participants reported to value the real time feedback (89%) compared to the long-term monitoring (78%). Most users (70%) reported they had experienced functionality issues with their devices, most commonly related to battery life and technical difficulties.

Conclusions

Results suggest users find activity trackers appealing and useful tools for increasing perceived physical activity levels over a sustained period.

Electronic supplementary material

The online version of this article (10.1186/s12889-017-4888-1) contains supplementary material, which is available to authorized users.

Brief Report: Active Ingredients for Adherence to a Tracker-Based Physical Activity Intervention in Older Adults

OBJECTIVES

To identify factors associated with weekly adherence to a 12-week tracker-based activity intervention in older adults.

METHOD

Using generalized linear mixed models in a secondary analysis ( N = 35), we examined factors associated with weekly adherence (defined as wore the Jawbone Up24 tracker for ≥5 days and completed weekly calls). Factors examined included individual characteristics, gave and received virtual support, achieved step goals, barrier and task self-efficacy, and self-comment.

RESULTS

Participants' ( M_age = 61.7, SD_age = 5.7) adherence changed from 86% (Week 1) to 74% (Week 12). Achieved the previous week's goal (β = 1.13, p = .01) and received virtual support (β = 0.01, p = .02) significantly increased the odds of weekly adherence.

DISCUSSION

Achieved step goals and received virtual support were associated with improved adherence to our tracker-based activity intervention, which has promising potential to be translated into the clinical setting to promote active lifestyles.