Cardiac Patients’ Walking Activity Determined by a Step Counter in Cardiac Telerehabilitation: Data From the Intervention Arm of a Randomized Controlled Trial

Thorup, Charlotte Brun; Hansen, John H. L.; Grønkjær, Mette; Andreasen, Jan Jesper; Nielsen, Gitte; Sørensen, Erik Elgaard; Dinesen, Birthe

doi:10.2196/jmir.5191

Cited by 75 publications

(72 citation statements)

References 49 publications

(86 reference statements)

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“…This study shows that of the 711 initial participants, approximately 50% still used their tracker after 6 months, and 12% continued to use their tracker even after 300 days. This rate of decay in usage confirms earlier findings [18]. This result also confirms the notion that wearable activity trackers are not subject to the rapid exponential decay of use we see in mobile phone apps, where usually 80% of users drop out in the first few days (eg, in [70]).…”

Section: Discussionsupporting

confidence: 89%

Determinants for Sustained Use of an Activity Tracker: Observational Study

Hermsen

Moons

Kerkhof

et al. 2017

JMIR Mhealth Uhealth

138

100

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BackgroundA 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.ObjectiveThe 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.MethodsA 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.ResultsThe 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.ConclusionsThis 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.

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Section: Discussionsupporting

confidence: 89%

Determinants for Sustained Use of an Activity Tracker: Observational Study

Hermsen

Moons

Kerkhof

et al. 2017

JMIR Mhealth Uhealth

138

100

View full text Add to dashboard Cite

show abstract

“…Meanwhile, better health-related quality of life and exercise capacity, less unplanned clinic visits, and cardiac-caused hospitalization were observed among patients in the regular PA group, compared with the irregular PA group ( P < .05). Substantial research has shown that walking (mild PA) can improve quality of life 25 and exercise capacity 26 among patients with CHD and decrease mortality compared with those who are inactive, in both the general population 27 , 28 and patients. 29 , 30 Wasfy and Baggish, 31 in their review of relevant epidemiologic literature on exercise, also found that the least active patients may benefit most from small increments in PA.…”

Section: Discussionmentioning

confidence: 99%

Physical Activity and Factors Affecting Its Maintenance Among Patients With Coronary Heart Disease Not Undergoing Cardiac Rehabilitation in China

et al. 2020

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Background The level of physical activity (PA) among patients with coronary heart disease (CHD) living in Chinese communities who do not participate in cardiac rehabilitation programs and the factors contributing to patient maintenance of PA are unclear. Objective This cross-sectional study, guided by the Transtheoretical Model, evaluated (1) the maintenance of PA in Chinese patients with CHD 12 months after hospital discharge and (2) the demographic, clinical, and psychological characteristics associated with maintenance of PA. Methods A total of 1162 patients completed 6 questionnaires at 12 months posthospitalization to assess their maintenance of PA, stage of change, symptoms of depression and anxiety, and health-related quality of life and sleep. Results Only 40% of patients with CHD maintained regular PA 12 months after hospital discharge. Walking was their primary PA. Thirty-seven percent of patients reported no intention of having regular PA. Male sex (odds ratio [OR], 1.69), awareness of PA's cardiac benefit (OR, 4.12), a history of regular PA before the cardiac event (OR, 6.08), history of chronic disease (OR, 1.43), mild depressive symptoms (OR, 1.40), moderate and severe depressive symptoms (OR, 0.41), smoking (OR, 0.54), and years of CHD (OR, 0.96) were related to maintenance of regular PA. Patients with CHD who maintained regular PA had better quality of life and sleep ( P < .001) and fewer unplanned clinic visits ( P = .001) and cardiac cause readmissions ( P = .012) and reported fewer declines in PA capacity ( P < .001). Conclusions Walking is the most common form of PA 12 months posthospitalization among patients with CHD in China. Patient education and counseling about the cardiac benefits of PA, taking into account stage of change, are important considerations to improve maintenance of PA.

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“…In contrast to most step counters used in clinical trials, 19,20 smartphones and smartwatches with built-in pedometers allow for more convenient and probably more accurate measurement of daily step count as marker of everyday PA. The observed compliance rate of >80% and mean wear time of 12.71 ± 1.13 h account for the validity of the measured step count.…”

Section: Validity Of Smart Device-based Measurement Of Health Datamentioning

confidence: 99%

Designing meaningful outcome parameters using mobile technology: a new mobile application for telemonitoring of patients with heart failure

et al. 2019

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Aims Health data captured by commercially available smart devices may represent meaningful patient‐reported outcome measures (PROMs) in heart failure (HF) patients. The purpose of this study was to test this hypothesis by evaluating the feasibility of a new telemonitoring concept for patients following initial HF hospitalization. Methods and results We designed a cardio patient monitoring platform (CPMP) that comprised mobile iOS‐based applications for patients' smartphone/smartwatch and the equivalent application on a physicians' tablet. It allowed for safe and continuous data transmission of self‐measured physiological parameters, activity data, and patient‐reported symptoms. In a prospective feasibility trial with 692 patient days from 10 patients hospitalized for newly diagnosed HF with reduced ejection fraction (mean left ventricular ejection fraction (LVEF) 26.5 ± 9.8%), we examined the CPMP during the first 2 months following discharge (69 ± 15 observation days per patient). The mean daily step count recorded by the mobile devices emerged as a promising new PROM. Its 14 day average increased over the study period (3612 ± 3311 steps/day at study inclusion and 7069 ± 5006 steps/day at end of study; P < 0.0001). It is unique for continuously reflecting real‐life activity and correlated significantly with traditional surrogate parameters of cardiac performance including LVEF ( r = 0.44; 95% CI 0.07–0.71; P = 0.0232), 6 min walk test ( r = 0.67; 95% CI 0.38–0.84; P = 0.0002), and scores in health‐related quality of life questionnaires. Conclusions We provide the first patient monitoring platform for HF patients that relies on commercially available iOS/watchOS‐based devices. Our study suggests it is ready for implementation as a tool for recording meaningful PROMs in future HF trials and telemonitoring.

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Cardiac Patients’ Walking Activity Determined by a Step Counter in Cardiac Telerehabilitation: Data From the Intervention Arm of a Randomized Controlled Trial

Cited by 75 publications

References 49 publications

Determinants for Sustained Use of an Activity Tracker: Observational Study

Determinants for Sustained Use of an Activity Tracker: Observational Study

Physical Activity and Factors Affecting Its Maintenance Among Patients With Coronary Heart Disease Not Undergoing Cardiac Rehabilitation in China

Designing meaningful outcome parameters using mobile technology: a new mobile application for telemonitoring of patients with heart failure

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