Habit Formation in Wearable Activity Tracker Use Among Older Adults: Qualitative Study

Effects of Peer- or Professional-Led Support in Enhancing Adherence to Wearable Monitoring Devices Among Community-Dwelling Older Adults: Systematic Review of Randomized Controlled Trials

BACKGROUND

Despite the well-documented health benefits associated with wearable monitoring devices (WMDs), adherence among community-dwelling older adults remains low. By providing guidance on the purpose and benefits of using WMDs, facilitating goal-setting aligned with the device's features, promoting comprehension of the health data captured by the device, and assisting in overcoming technological challenges, peers and health care professionals can potentially enhance older adults' adherence to WMDs. However, the effectiveness of such support mechanisms in promoting adherence to WMDs among older adults remains poorly understood.

OBJECTIVE

The aims of this systematic review were to examine the effects of peer- or professional-led intervention programs designed to improve adherence to WMDs among community-dwelling older adults and to identify the intervention components that may positively influence the effects of the intervention.

METHODS

We conducted a comprehensive search across 7 electronic databases (Cochrane Central Register of Controlled Trials [CENTRAL], PubMed, EMBASE, PsycINFO, British Nursing Index, Web of Science, and CINAHL) to identify articles published between January 1, 2010, and June 26, 2023. We specifically targeted randomized controlled trials that examined the impact of peer- or professional-led interventions on enhancing adherence to WMDs among individuals aged 60 years and older residing in the community. Two independent reviewers extracted data from the included studies and assessed the potential risk of bias in accordance with the Cochrane Risk of Bias tool for randomized trials, version 2.

RESULTS

A total of 10,511 studies were identified through the database search. Eventually, we included 3 randomized controlled trials involving 154 community-dwelling older adults. The participants had a mean age of 65 years. Our review revealed that increasing awareness of being monitored and implementing the SystemCHANGE approach, a habit change tool focusing on personal goals and feedback, were effective strategies for enhancing adherence to WMDs among older adults. All of the included studies exhibited a low risk of bias.

CONCLUSIONS

By collaboratively designing specific goals related to WMDs with health care professionals, including nurses and physicians, older adults exhibited a higher likelihood of adhering to the prescribed use of WMDs. These goal-setting tools provided a framework for structure and motivation, facilitating the seamless integration of WMDs into their daily routines. Researchers should prioritize interventions that target awareness and goal-setting as effective approaches to enhance adherence to WMDs among older adults, thereby maximizing the realization of associated health benefits.

Factors influencing smartwatch use and comfort with health data sharing: a sequential mixed-method study protocol

INTRODUCTION

Smartwatches have become ubiquitous for tracking health metrics. These data sets hold substantial potential for enhancing healthcare and public health initiatives; it may be used to track chronic health conditions, detect previously undiagnosed health conditions and better understand public health trends. By first understanding the factors influencing one's continuous use of the device, it will be advantageous to assess factors that may influence a person's willingness to share their individual data sets. This study seeks to comprehensively understand the factors influencing the continued use of these devices and people's willingness to share the health data they generate.

METHODS AND ANALYSIS

A two-section online survey of smartwatch users over the age of 18 will be conducted (n ≥200). The first section, based on the expectation-confirmation model, will assess factors influencing continued use of smartwatches while the second section will assess willingness to share the health data generated from these devices. Survey data will be analysed descriptively and based on structural equation modelling.Subsequently, six focus groups will be conducted to further understand the issues raised in the survey. Each focus group (n=6) will consist of three smartwatch users: a general practitioner, a public health specialist and an IT specialist. Young smartwatch users (aged 18-44) will be included in three of the focus groups and middle-aged smartwatch users (aged 45-64) will be included in the other three groups. This is to enhance comparison of opinions based on age groups. Data from the focus groups will be analysed using the microinterlocutor approach and an executive summary.After the focus group, participants will complete a brief survey to indicate any changes in their opinions resulting from the discussion.

ETHICS AND DISSEMINATION

The results of this study will be disseminated through publication in a peer-reviewed journal, and all associated data will be deposited in a relevant, publicly accessible data repository to ensure transparency and facilitate future research endeavours.This study was approved by the Social Research Ethic Committee (SREC), University College Cork-SREC/SOM/21062023/2.

Barriers and facilitators to smartwatch-based prehabilitation participation among frail surgery patients: a qualitative study

BACKGROUND

For older, frail adults, exercise before surgery through prehabilitation (prehab) may hasten return recovery and reduce postoperative complications. We developed a smartwatch-based prehab program (BeFitMe) for older adults that encourages and tracks at-home exercise. The objective of this study was to assess patient perceptions about facilitators and barriers to prehab generally and to using a smartwatch prehab program among older adult thoracic surgery patients to optimize future program implementation.

METHODS

We recruited patients, aged ≥50 years who had or were having surgery and were screened for frailty (Fried's Frailty Phenotype) at a thoracic surgery clinic at a single academic institution. Semi-structured interviews were conducted by telephone after obtaining informed consent. Participants were given a description of the BeFitMe program. The interview questions were informed by The Five "Rights" of Clinical Decision-Making framework (Information, Person, Time, Channel, and Format) and sought to identify the factors perceived to influence smartwatch prehab program participation. Interview transcripts were transcribed and independently coded to identify themes in for each of the Five "Rights" domains.

RESULTS

A total of 29 interviews were conducted. Participants were 52% men (n = 15), 48% Black (n = 14), and 59% pre-frail (n = 11) or frail (n = 6) with a mean age of 68 ± 9 years. Eleven total themes emerged. Facilitator themes included the importance of providers (right person) clearly explaining the significance of prehab (right information) during the preoperative visit (right time); providing written instructions and exercise prescriptions; and providing a preprogrammed and set-up (right format) Apple Watch (right channel). Barrier themes included pre-existing conditions and disinterest in exercise and/or technology. Participants provided suggestions to overcome the technology barrier, which included individualized training and support on usage and responsibilities.

CONCLUSIONS

This study reports the perceived facilitators and barriers to a smartwatch-based prehab program for pre-frail and frail thoracic surgery patients. The future BeFitMe implementation protocol must ensure surgical providers emphasize the beneficial impact of participating in prehab before surgery and provide a written prehab prescription; must include a thorough guide on smartwatch use along with the preprogrammed device to be successful. The findings are relevant to other smartwatch-based interventions for older adults.

The experiences of people with chronic obstructive pulmonary disease (COPD) using activity monitors in everyday life: an interpretative phenomenological study

PURPOSE

Understanding the experiences of people with Chronic Obstructive Pulmonary Disease (COPD) using activity monitors in daily life could support the utilisation of technology within healthcare to increase physical activity and support self-management. This qualitative study aimed to explore the experiences of people with COPD using activity monitors at home in everyday life.

METHODS

Semi-structured face-to-face or telephone interviews were conducted with seven people with COPD between August 2018 and June 2020. Participants had all used an activity monitor within the last year (Fitbit, Garmin, or Apple Watch). Interviews were analysed in-depth using Interpretative Phenomenological Analysis (IPA).

RESULTS

Four themes, developed using IPA, highlight participants' engagement with activity monitors and integrating them into their lives: (1) Motivational features to monitor activity, (2) Importance of setting achievable goals, (3) Developing knowledge and awareness, and (4) Integration into everyday life for self-management.

CONCLUSION

Activity monitors were perceived to be beneficial and useful to people with COPD, not just for monitoring their activity, but also helping to self-manage their condition. Activity monitors may be a useful tool within rehabilitation and healthcare services for COPD.

Electronic Wearable Device Use for Physical Activity in Older Adults: A Qualitative Study

Innovative solutions to help older adults increase physical activity are critically important. In this qualitative study, we explored older adults' acceptance, capability, and experiences of using three different types of electronic wearable devices over a period of 4-24 weeks for self-monitoring and promoting physical activity. We conducted 23 semistructured interviews with older adults who participated in three physical activity intervention studies. Two researchers analyzed the data using NVivo version 12, applying a directed content analysis that was partially guided by the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Six themes emerged: (1) device learning, (2) hedonic motivation, (3) habit and adherence, (4) facilitating conditions, (5) effort expectancy, and (6) performance expectancy. Although most older adults (95.8%) from this study were first-time users, they reflected positive experiences and generally enjoyed using electronic wearable devices. Participants reported issues related to electronic wearable device functionalities that can be improved to better enhance user experience and motivate increased physical activity. Future research should explore the role of electronic wearable devices in older adults' physical activity with an emphasis on behavioral change over time.

Haptic Nudging Using a Wearable Device to Promote Upper Limb Activity during Stroke Rehabilitation: Exploring Diurnal Variation, Repetition, and Duration of Effect

Haptic nudging via wearable devices promotes physical activity and may increase upper limb movement in stroke rehabilitation. This study investigated the optimal approach to haptic nudging by examining diurnal variation, duration of effect, and repeated nudging. The study analysed data from a multiple-period randomised crossover study. A 12 h inpatient rehabilitation day was divided into 72 intervals in which participants with stroke (n = 20) randomly received either a 'nudge' or 'no nudge'. Upper limb movement was observed, classified, and analysed using longitudinal mixed models. The odds of affected upper limb movement following a nudge compared with no nudge were significantly higher during active periods such as breakfast, lunch, and morning and afternoon activities (odds ratios (ORs) 2.01-4.63, 95% CIs [1.27-2.67, 3.17-8.01]), but not dinner (OR 1.36, 95% CI [0.86, 2.16]). The effect of nudging was no longer statistically significant at 50-60 s post-nudge. Consecutive delays in nudging significantly decreased the odds of moving when a nudge was eventually delivered. Contrary to expectations, people with stroke appear more responsive to haptic nudging during active periods rather than periods of inactivity. By understanding the optimal timing and frequency of haptic nudging, the design of wearable devices can be optimised to maximise their therapeutic benefits.

Views and experiences of healthcare practitioners supporting people with COPD who have used activity monitors: "More than just steps"

INTRODUCTION

Activity monitors (apps and wearables) are increasingly used by the general population, including people with Chronic Obstructive Pulmonary Disease (COPD). There is potential for activity monitors to support increases in physical activity for people with COPD and healthcare practitioners (HCPs) are likely to be key in supporting their use, but little is currently known about HCPs' views or experiences. This qualitative research aimed to explore HCPs' views and experiences of supporting people with COPD who have used activity monitors.

METHODS

Seventeen semi-structured telephone or online interviews were conducted with HCPs between September 2020 and May 2021. HCPs included two nurses, an occupational therapist, a physician, and 13 physiotherapists. Participants were recruited via social media advertisements. They all had experience of supporting people with COPD who had used activity monitors. Interviews were analysed using reflexive thematic analysis.

FINDINGS

Four themes were developed highlighting the challenges and benefits of HCPs supporting patients with using activity monitors and utilising patient-collected activity data; 1) Skills and experience are needed to increase accessibility and engagement, 2) Objectively monitored physical activity can support exercise prescription, 3) Applications of activity monitors vary across different settings, and 4) Support is needed for future use of activity monitors.

DISCUSSION

HCPs recognised the potential for activity monitors to impact patients' ability to self-manage their COPD. However, there is a lack of guidance and information to support integration within practice. Future research is needed to co-develop information and guidelines for people with COPD and HCPs.

The Importance of Activating Factors in Physical Activity Interventions for Older Adults Using Information and Communication Technologies: Systematic Review

Background

In an aging population, it is important to activate older adults in taking care of their own health. Increasing physical activity is one way to avoid or lessen age-related physical and mental impairments. Interest in the use of information and communication technology (ICT) tools to promote physical activity among older adults is growing considerably. Such tools are suitable for communicating activation factors-skills, knowledge, and motivation-by integrating a variety of behavior change techniques (BCTs) to enhance physical activity. Although activation factors have been incorporated into physical activity interventions using ICT, little is known about the actual integration methods used in such interventions or about the effects of activation factors on influencing behavior change.

Objective

The first aim of this study was to identify which of the activation factors were covered in physical activity-promoting ICT interventions for older adults and which BCTs were used to address them. The second objective was to classify the user interaction interfaces and delivery modes that were used to promote these activation factors.

Methods

The search engines of PubMed, Web of Science, and ScienceDirect were used to search for and identify articles examining the effectiveness of ICT interventions for promoting physical activity in older adults. References and related data were selected, extracted, and reviewed independently by 2 reviewers. The risk of bias was assessed, and any conflict was addressed by a third separate reviewer. Selected articles included older adults aged ≥55 years without pre-existing medical diseases and other physical or mental conditions that could hinder movement.

Results

In total, 368 records were retrieved, and 13 studies met all inclusion criteria. Articles differed in terms of themes, timescales, user interaction interfaces, and outcome measures; therefore, a quantitative data synthesis was not feasible. Motivation was the most promoted activation factor among all trials (33 times). An app and a smartwatch were used in the majority of intervention groups (7/20, 35%) for tracking physical activity and receiving personalized feedback based on the individual goals. Skills (25 times) and knowledge (17 times) were the next most commonly addressed activation factors. Face-to-face interaction was the most used approach to targeting users' skills, including providing instructions on how to perform a behavior and exchanging knowledge via education on the health consequences of insufficient physical activity. Overall, integrating all 3 activation factors and using multiple user interaction interfaces with a variety of delivery modes proved the most effective in improving physical activity.

Conclusions

This study highlights commonly used BCTs and preferred modes of their delivery. So far, only a limited number of available BCTs (21/99, 21%) have been integrated. Considering their effectiveness, a larger variety of BCTs that address skills, knowledge, and motivation should be exploited in future ICT interventions.

Acceptability of physical activity signposting for pre-frail older adults: a qualitative study to inform intervention development

Frailty is a medical condition common in older adults characterised by diminished strength and reduced physiologic function in which individuals are more vulnerable to multiple adverse health outcomes. Pre-frailty is an intermediate stage associated with some minor health outcomes. However, the main risk is progression toward moderate/severe frailty. Evidence shows physical activity interventions to be effective in slowing or modifying the progression of frailty. Researchers at the University of Manchester are developing a behaviour change intervention targeting pre-frail older adults, signposting them to group-based physical activity classes known to be effective for delaying/slowing frailty. This paper reports on the initial intervention development work with key stakeholders exploring the practicality of taking forward this intervention and identifying uncertainties to be explored in the feasibility stage. These included issues around physical activity messaging, the use of the term 'frail', identification/recruitment of pre-frail older adults, and the acceptability of behaviour change techniques. There was overwhelming support for a proactive approach to addressing pre-frailty issues. Given that a large proportion of older adults are estimated to be pre-frail, interventions aimed at this group have the potential to support healthy ageing, positively impacting on frailty outcomes and providing wider population health benefits.

Wearable-Technology-Assisted Interventions for Breast-Cancer Survivors: A Meta-Analysis and Meta-Regression

OBJECTIVES

This review, meta-analysis, and meta-regression aimed to (1) evaluate the effect of wearable-technology-assisted interventions on the physical activity and weight of breast cancer survivors, (2) identify the essential features of wearable-technology-assisted interventions, and (3) explore the covariates of the treatment effect.

DATA SOURCES

Randomized controlled trials were obtained from 10 databases and trial registries from inception until December 21, 2021. Trials that examined the effects of wearable-technology-assisted interventions for individuals with breast cancer were included. The mean and standard deviation scores were used to compute the effect sizes.

CONCLUSION

The meta-analyses revealed significantly improved in moderate-to-vigorous activity, total physical activity, and weight control. The findings from this review suggest that wearable-technology-assisted interventions may be a potential solution to improve physical activity and weight in breast cancer survivors. Future studies should include high-quality trials with large sample sizes.

IMPLICATIONS FOR NURSING PRACTICE

Wearable technology has promising effects on physical activity and could be incorporated into routine care for breast cancer survivors.

Predicting Habitual Use of Wearable Health Devices Among Middle-aged Individuals With Metabolic Syndrome Risk Factors in South Korea: Cross-sectional Study

BACKGROUND

Prevention of the risk factors for metabolic syndrome (MetS) in middle-aged individuals is an important public health issue. Technology-mediated interventions, such as wearable health devices, can aid in lifestyle modification, but they require habitual use to sustain healthy behavior. However, the underlying mechanisms and predictors of habitual use of wearable health devices among middle-aged individuals remain unclear.

OBJECTIVE

We investigated the predictors of habitual use of wearable health devices among middle-aged individuals with risk factors for MetS.

METHODS

We proposed a combined theoretical model based on the health belief model, the Unified Technology of Acceptance and Use of Technology 2, and perceived risk. We conducted a web-based survey of 300 middle-aged individuals with MetS between September 3 and 7, 2021. We validated the model using structural equation modeling.

RESULTS

The model explained 86.6% of the variance in the habitual use of wearable health devices. The goodness-of-fit indices revealed that the proposed model has a desirable fit with the data. Performance expectancy was the core variable explaining the habitual use of wearable devices. The direct effect of the performance expectancy on habitual use of wearable devices was greater (β=.537, P<.001) than that of intention to continue use (β=.439, P<.001), and the total effect estimate of the performance expectancy was 0.909 (P<.001), including the indirect effect (β=.372, P=.03) on habitual use of wearable devices via intention to continue use. Furthermore, performance expectancy was influenced by health motivation (β=.497, P<.001), effort expectancy (β=.558, P<.001), and risk perception (β=.137, P=.02). Perceived vulnerability (β=.562, P<.001) and perceived severity (β=.243, P=.008) contributed to health motivation.

CONCLUSIONS

The results suggest the importance of the users' performance expectations for wearable health devices for the intention of continued use for self-health management and habituation. Based on our results, developers and health care practitioners should find better ways to meet the performance expectations of middle-aged individuals with MetS risk factors. They also should generate device use easier and find a way to encourage users' health motivation, thereby reducing users' effort expectancy and resulting in a reasonable performance expectancy of the wearable health device, to induce users' habitual use behaviors.

Establishing Healthy Eating 'Habits': A Pilot Randomised Controlled Trial of a Habit-Based Dietary Intervention following Oral Rehabilitation for Older Adults

An ageing population presents significant nutritional challenges, particularly for partially dentate adults. This two-armed pilot randomised controlled trial (RCT) compared habit formation (automaticity) for healthy eating behaviours between control and intervention groups after participation in a habit-based dietary intervention for older adults, following oral rehabilitation in the United Kingdom (UK). n = 54 participants were randomised to receive a habit-based dietary intervention (intervention group n = 27, IG) or standard dietary advice in a leaflet (control group n = 27, CG). The IG attended three sessions over six weeks, which focused on habit formation for three healthy eating behaviours (increasing fruit and vegetables, wholegrains, and healthy proteins). Participants were assessed for habit strength (using the Self-Report Behavioural Automaticity Index (SRBAI)) alongside health and nutrition outcomes at six weeks, four months and eight months. Forty-nine participants completed all follow-up visits. The IG compared to the CG had significant increases in automaticity at six weeks, four months (primary outcome) and eight months for eating ≥3 portions of fruit and vegetables; choosing wholegrain sources over white alternatives, and choosing healthy protein sources over red/processed meat. The mean change in the Mini Nutritional Assessment total score was greater in the IG compared with the CG at six weeks only (p = 0.03). A habit-based dietary intervention following oral rehabilitation increased automaticity for healthy dietary behaviours, which could translate into clinically meaningful benefits in this cohort of older adults.

Technology-assisted behavioral intervention to encourage prehabilitation in frail older adults undergoing surgery: Development and design of the BeFitMe™ Apple Watch app

Objective

Increasing the physical activity of frail, older patients before surgery through prehabilitation (prehab) can hasten return to autonomy and reduce complications postoperatively. However, prehab participation is low in the clinical setting. In this study, we re-design an existing prehab smartphone application (BeFitMe™) using a novel standalone Apple Watch platform to increase accessibility and usability for vulnerable patients.

Methods

Design Science Research Methodology was used to (1) develop an approach to clinical research using standalone Apple Watches, (2) re-design BeFitMe™ for the Apple Watch platform, and (3) incorporate user feedback into app design. In phase 3, beta and user testers gave feedback via a follow-up phone call. Exercise data was extracted from the watch after testing. Descriptive statistics were used to summarize accessibility and usability.

Results

BeFitMe™ was redesigned for the Apple Watch with full functionality without requiring patients to have an iPhone or internet connectivity and the ability to passively collect exercise data without patient interaction. Three study staff participated in beta testing over 3 weeks. Six randomly chosen thoracic surgery patients participated in user testing over 12 weeks. Feedback from beta and user testers was addressed with updated software (versions 1.0-1.10), improved interface and notification schemes, and the development of educational materials used during enrollment. The majority of users (5/6, 83%) participated by responding to at least one notification and data was able to be collected for 54/82 (68%) of the days users had the watches. The amount of data collected in BeFitMe™ Watch app increased from 2/11 (16%) days with the first patient tester to 13/13 (100%) days with the final patient tester.

Conclusions

The BeFitMe™ Watch app is accessible and usable. The BeFitMe™ Watch app may help older patients, particularly those from vulnerable backgrounds with fewer resources, participate in prehab prior to surgery.

Acceptable, useful, and ineffective? Recent retirees’ experiences of a 12-month activity tracker-based physical activity intervention

Objective

Activity trackers appear cost-effective and acceptable intervention tools for promoting physical activity among older adults, particularly in the short-term. However, long-term studies focused on participants’ experiences continue to be scarce. This study evaluated participants’ experiences of a 12-month activity tracker-driven physical activity intervention.

Methods

Participants’ experiences were assessed qualitatively using open-ended questionnaire items ( n = 113) and semi-structured interviews conducted after the 12-month intervention ( n = 27). Quantitative items assessed the perceived ease-of-use and usefulness of the activity tracker during the intervention. Qualitative data was analyzed using thematic analysis and Wilcoxon signed-rank tests were used to examine changes in the perceived ease-of-use and usefulness over time.

Results

The 113 participants completing the 12-month intervention were on average 65.2 ( SD 1.0) years old and 81.4% women with 92.3% providing activity tracker data on at least 2 weeks per each intervention month. In the qualitative analysis, four main themes with 20 subthemes were identified: (a) burdens of participation, (b) affective attitudes of using the activity tracker, (c) perceived effects of using the activity tracker, and (d) no perceived behavioral effects. At 12 months, the participants found activity trackers mainly easy to use (mean 4.6, SD 0.6), reliable (mean 3.6, SD 1.2), motivating (mean 3.9, SD 1.0), and helpful in reducing sitting (mean 3.7, SD 1.0) with no changes observed during the intervention.

Conclusions

The participants’ experiences were highly varied suggesting that tailored intervention designs are likely to be required for effectively using activity trackers to promote long-term changes in daily activity among older adults.

Associations of Demographic, Socioeconomic, and Cognitive Characteristics With Mobile Health Access: MESA (Multi-Ethnic Study of Atherosclerosis)

Background

Mobile health (mHealth) has an emerging role in the prevention of cardiovascular disease. This study evaluated possible inequities in mHealth access in older adults.

Methods and Results

mHealth access was assessed from 2019 to 2020 in MESA (Multi‐Ethnic Study of Atherosclerosis) telephone surveys of 2796 participants aged 62 to 102 years. A multivariable logistic regression model adjusted for general health status assessed associations of mHealth access measures with relevant demographic, socioeconomic, and cognitive characteristics. There were lower odds of all access measures with older age (odds ratios [ORs], 0.37–0.59 per 10 years) and annual income <$50 000 (versus ≥$50 000 ORs, 0.55–0.62), and higher odds with higher Cognitive Abilities Screening Instrument Score (ORs, 1.22–1.29 per 5 points). Men (versus women) had higher odds of internet access (OR, 1.32 [95% CI,1.05–1.66]) and computing device ownership (OR, 1.31 [95% CI, 1.05–1.63]) but lower fitness tracker ownership odds (OR, 0.70 [95% CI, 0.49–0.89]). For internet access and computing device ownership, we saw lower odds for Hispanic participants (versus White participants OR, 0.61 [95% CI, 0.44–0.85]; OR, 0.69 [95% CI, 0.50–0.95]) and less than a high school education (versus bachelor's degree or higher OR, 0.27 [95% CI, 0.18–0.40]; OR, 0.32 [95% CI, 0.28–0.62]). For internet access, lower odds were seen for Black participants (versus White participants OR, 0.64 [95% CI, 0.47–0.86]) and other health insurance (versus health maintenance organization/private OR, 0.59 [95% CI, 0.47–0.74]). Chinese participants (versus White participants) had lower internet access odds (OR, 0.63 [95% CI, 0.44–0.91]) but higher computing device ownership odds (OR, 1.87 [95% CI, 1.28–2.77]).

Conclusions

Among older‐age adults, mHealth access varied by major demographic, socioeconomic, and cognitive characteristics, suggesting a digital divide. Novel mHealth interventions should consider individual access barriers.

Registration

URL: https://www.clinicaltrials.gov/; Unique identifier: NCT00005487.

Leveraging Mobile-Based Sensors for Clinical Research to Obtain Activity and Health Measures for Disease Monitoring, Prevention, and Treatment

Clinical researchers are using mobile-based sensors to obtain detailed and objective measures of the activity and health of research participants, but many investigators lack expertise in integrating wearables and sensor technologies effectively into their studies. Here, we describe the steps taken to design a study using sensors for disease monitoring in older adults and explore the benefits and drawbacks of our approach. In this study, the Geriatric Acute and Post-acute Fall Prevention Intervention (GAPcare), we created an iOS app to collect data from the Apple Watch's gyroscope, accelerometer, and other sensors; results of cognitive and fitness tests; and participant-entered survey data. We created the study app using ResearchKit, an open-source framework developed by Apple for medical research that includes neuropsychological tests (e.g., of executive function and memory), gait speed, balance, and other health assessments. Data is transmitted via an Application Programming Interface (API) from the app to REDCap for researchers to monitor and analyze in real-time. Employing the lessons learned from GAPcare could help researchers create study-tailored research apps and access timely information about their research participants from wearables and smartphone devices for disease prevention, monitoring, and treatment.

Exploring Families' Acceptance of Wearable Activity Trackers: A Mixed-Methods Study

Background: The family environment plays a crucial role in child physical activity (PA). Wearable activity trackers (wearables) show potential for increasing children’s PA; however, few studies have explored families’ acceptance of wearables. This study investigated the acceptability of using wearables in a family setting, aligning experiences with components of the Technology Acceptance Model and Theoretical Domains Framework. Methods: Twenty-four families, with children aged 5–9 years, took part in a 5-week study, where all members were provided with a Fitbit Alta HR for 4 weeks. Acceptability was measured using weekly surveys and pre-post-questionnaires. Nineteen families participated in a focus group. Quantitative and qualitative data were integrated using the Pillar Integration Process technique. Results: Pillars reflected (1) external variables impacting wearable use and PA and (2) wearable use, (3) ease of use, (4) usefulness for increasing PA and other health outcomes, (5) attitudes, and (6) intention to use a wearable, including future intervention suggestions. Conclusions: Families found the Fitbit easy to use and acceptable, but use varied, and perceived impact on PA were mixed, with external variables contributing towards this. This study provides insights into how wearables may be integrated into family-based PA interventions and highlights barriers and facilitators of family wearable use.

Supporting Behavior Change in Sedentary Adults via Real-time Multidimensional Physical Activity Feedback: Mixed Methods Randomized Controlled Trial

BACKGROUND

Increasing physical activity (PA) behavior remains a public health priority, and wearable technology is increasingly being used to support behavior change efforts. Using wearables to capture and provide comprehensive, visually persuasive, multidimensional feedback with real-time support may be a promising way of increasing PA in inactive individuals.

OBJECTIVE

This study aims to explore whether a 6-week self-monitoring intervention using composite web-based multidimensional PA feedback with real-time daily feedback supports increased PA in adults.

METHODS

A 6-week, mixed methods, 2-armed exploratory randomized controlled trial with 6-week follow-up was used, whereby low to moderately active (PA level [PAL] <2.0) adults (mean age 51.3 years, SD 8.4 years; women 28/51, 55%) were randomly assigned to receive the self-monitoring intervention (36/51, 71%) or waiting list control (15/51, 29%). Assessment of PA across multiple health-harnessing PA dimensions (eg, PAL, weekly moderate to vigorous intensity PA, sedentary time, and steps), psychosocial cognitions (eg, behavioral regulation, barrier self-efficacy, and habit strength), and health were made at the prerandomization baseline at 6 and 12 weeks. An exploratory analysis of the mean difference and CIs was conducted using the analysis of covariance model. After the 12-week assessment, intervention participants were interviewed to explore their views on the program.

RESULTS

There were no notable differences in any PA outcome immediately after the intervention; however, at 12 weeks, moderate-to-large effects were observed with a mean difference in PAL of 0.09 (95% CI 0.02-0.15; effect size [Hedges g] 0.8), daily moderate-intensity PA of 24 (95% CI 0-45; Hedges g=0.6) minutes, weekly moderate-to-vigorous intensity PA of 195 (95% CI 58-331; Hedges g=0.8) minutes, and steps of 1545 (95% CI 581-2553; Hedges g=0.7). Descriptive analyses suggested that the differences in PA at 12 weeks were more pronounced in women and participants with lower baseline PA levels. Immediately after the intervention, there were favorable differences in autonomous motivation, controlled motivation, perceived competence for PA, and barrier self-efficacy, with the latter sustained at follow-up. Qualitative data implied that the intervention was highly informative for participants and that the real-time feedback element was particularly useful in providing tangible, day-to-day behavioral support.

CONCLUSIONS

Using wearable trackers to capture and present sophisticated multidimensional PA feedback combined with discrete real-time support may be a useful way of facilitating changes in behavior. Further investigation into the ways of optimizing the use of wearables in inactive participants and testing the efficacy of this approach via a robust study design is warranted.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02432924; https://clinicaltrials.gov/ct2/show/NCT02432924.

A Digital Platform to Support Self-management of Multiple Chronic Conditions (ProACT): Findings in Relation to Engagement During a One-Year Proof-of-Concept Trial

Background

Populations globally are ageing, resulting in higher incidence rates of chronic diseases. Digital health platforms, designed to support those with chronic conditions to self-manage at home, offer a promising solution to help people monitor their conditions and lifestyle, maintain good health, and reduce unscheduled clinical visits. However, despite high prevalence rates of multimorbidity or multiple chronic conditions, most platforms tend to focus on a single disease. A further challenge is that despite the importance of users actively engaging with such systems, little research has explored engagement.

Objective

The objectives of this study are to design and develop a digital health platform, ProACT, for facilitating older adults self-managing multimorbidity, with support from their care network, and evaluate end user engagement and experiences with this platform through a 12-month trial.

Methods

The ProACT digital health platform is presented in this paper. The platform was evaluated in a year-long proof-of-concept action research trial with 120 older persons with multimorbidity in Ireland and Belgium. Alongside the technology, participants had access to a clinical triage service responding to symptom alerts and a technical helpdesk. Interactions with the platform during the trial were logged to determine engagement. Semistructured interviews were conducted with participants and analyzed using inductive thematic analysis, whereas usability and user burden were examined using validated questionnaires.

Results

This paper presents the ProACT platform and its components, along with findings on engagement with the platform and its usability. Of the 120 participants who participated, 24 (20%) withdrew before the end of the study, whereas 3 (2.5%) died. The remaining 93 participants actively used the platform until the end of the trial, on average, taking 2 or 3 health readings daily over the course of the trial in Ireland and Belgium, respectively. The participants reported ProACT to be usable and of low burden. Findings from interviews revealed that participants experienced multiple benefits as a result of using ProACT, including improved self-management, health, and well-being and support from the triage service. For those who withdrew, barriers to engagement were poor health and frustration when technology, in particular sensing devices, did not work as expected.

Conclusions

This is the first study to present findings from a longitudinal study of older adults using digital health technology to self-manage multimorbidity. Our findings show that older adults sustained engagement with the technology and found it usable. Potential reasons for these results include a strong focus on user-centered design and engagement throughout the project lifecycle, resulting in a platform that meets user needs, as well as the integration of behavior change techniques and personal analytics into the platform. The provision of triage and technical support services alongside the platform during the trial were also important facilitators of engagement.

International Registered Report Identifier (IRRID)

RR2-10.2196/22125

Predicting Decisional Determinants of Physical Activity Among Older Adults: An Integrated Behavior Approach

The present study applied the Integrated Behavior Change Model to investigate how behavioral decisions are predicted, namely, intention, planning, and habits, with respect to physical activity. Methods: Participants were older adults (ages 65+) residing in the U.S. (N = 667) who completed online measures of behavioral determinants (autonomous motivation, perceived behavioral control, subjective norms, attitudes, intention, habit, and consistency), in addition to past behavior. Results: A structural equation model revealed that intention was predicted by past behavior and social-cognitive determinants. Social cognitive determinants mediated between past behavior and habit, as well as between autonomous motivation and habit. Intention mediated between past behavior and planning. Discussion: This study highlights the importance of multiple processes (social cognitive, habit/automatic, and post-intentional/planning) that formulate physical activity intentions. Mediation pathways revealed the importance of autonomous motivation for establishing intentions and habit. Facilitating these processes among older adults could be effective for promoting physical activity.

Protocol for a randomized controlled trial of sitting reduction to improve cardiometabolic health in older adults

Older adults with obesity spend the majority of their waking hours sedentary. Given substantial barriers to regular physical activity in this population, approaches to reduce sedentary time could be an effective health promotion strategy. We present the protocol of a randomized controlled trial to reduce sitting time in older adults with a body mass index of 30 kg/m² or above. Participants (N = 284) will be randomized to receive a sitting reduction intervention (termed I-STAND) or a healthy living focused attention control condition. I-STAND includes 10 contacts with a health coach (10 sessions total) and participants receive a wrist-worn prompting device and portable standing desk. The healthy living condition includes 10 sessions with a health coach to set goals around various topics relating to healthy aging. Participants receive their assigned intervention for 6 months. After 6 months, those receiving the I-STAND condition are re-randomized to receive five booster health coaching sessions by 'phone or no further contact; healthy living participants receive no further contact and those in both conditions are followed for an additional 6 months. Measurements initially included wearing an activPAL device and completing several biometric tests (e.g., blood pressure, HbA1c), at baseline, 3 months, 6 months, and 12 months; however, during the COVID-19 pandemic we shifted to remote assessments and were unable to collect all of these measures. The primary outcomes remained activPAL-assessed sitting time and blood pressure. Recruitment is anticipated to be completed in 2022.

Analysis of Older Adults in Spanish Care Facilities, Risk of Falling and Daily Activity Using Xiaomi Mi Band 2

BACKGROUND

Presently the use of technological devices such as wearable devices has emerged. Physical activity monitoring with wearable sensors is an easy and non-intrusive approach to encourage preventive care for older adults. It may be useful to follow a continuous assessment of the risk of falling. The objective is to explore the relationship between the daily activity measured by Xiaomi Mi Band 2 and the risk of falling of older adults residing in or attending care facilities.

METHODS

A cross-sectional study was conducted on three different institutions located in Galicia (autonomous community) (Spain).

RESULTS

A total of 31 older adults were included in the study, with a mean age of 84 ± 8.71 years old. The main findings obtained were that a greater number of steps and distance could be related to a lower probability of falling, of dependency in basic activities of daily living, or of mobility problems.

CONCLUSIONS

The importance of focusing on daily steps, intrinsically related to the objective assessment of daily physical activity, is that it is a modifiable factor that impacts different aspects of health and quality of life.

"I shy away from them because they are very identifiable": A qualitative study exploring user and non-user's perceptions of wearable activity trackers

OBJECTIVE

Wearable activity trackers hold potential as a research tool to increase physical activity. However, long-term wearable adherence is low among users, which may be due to the limited understanding of the factors related to use and relation to health behavior theory. The purpose of this study was to qualitatively explore the perceptions of wearables among active adult users and non-users. Findings will inform potential barriers and facilitators for the adherence and adoption of wearables through the application of the Self-Determination Theory.

METHODS

Six focus groups were conducted and equally stratified to wearable users (n = 10) and non-users (n = 10). Data were audio recorded, transcribed, and analyzed using an iterative approach creating first-level codes. This was followed by developing second-level codes that allowed for generating themes.

RESULTS

For users, the wearables' feedback provided them with validation, a sense of achievement, and other-determined motivation. Users appreciated the functionality of wearables, particularly with simpler and newer models. They also reported improvements in health behaviors. While both users and non-users had a general positive feeling towards wearables, they held similar concerns about cost, guilt, dependency, and accuracy. Non-users were unique in their concerns for materialism and functionality (i.e. ease of use and charge) associated with wearables. They also seemed to be more intrinsically motivated to be physically active by relying less on external sources of motivation as potentially provided by wearables.

CONCLUSIONS

Findings show that while both adult users and non-users held positive perceptions of wearables and concerns for feelings of guilt and dependency, widespread adoption and adherence may be prevented by differences in motivation for physical activity and concerns for cost, materialism, and functionality.