Accurate physical activity monitoring is important for cardiac patients. Novel activity monitoring devices may enable precise measurement of physical activity. This study aimed to validate ...Fitbit-Flex against Actigraph accelerometer for monitoring physical activity.
A validation study with a comparative design.
Cardiac patients and family members participating in community-based exercise programs wore Fitbit-Flex and Actigraph simultaneously over four days to monitor daily step counts and minutes of moderate to vigorous physical activity (MVPA).
Participants (N = 48) comprised 52.1% males, with a mean age of 65.6 ± 6.9 years and 58.9% had a cardiac diagnosis. Fitbit-Flex and Actigraph were significantly correlated in males, females, total participants and cardiac patients for step counts (r = .96; r = .95; r = .95; r = .95), though less so for MVPA (r = .81; r = .65, r = .74; r = .71). As step counts increased the differences between Fitbit-Flex and Actigraph also increased. Fitbit-Flex over-estimated step counts in females (556 steps/day), males (1462 steps/day) and total participants (1038 steps/day) as well as for minutes of MVPA in females (4 min/day), males (15 min/day) and total participants (10 min/day). Fitbit-Flex had high sensitivity and specificity in classifying participants who achieved the recommended physical activity guidelines.
Fitbit-Flex is accurate in assessing attainment of physical activity guideline recommendations and is useful for monitoring physical activity in cardiac patients. The device does, however, slightly over-estimate step counts and MVPA.
•This is the first systematic review to explore the validity and reliability of consumer-grade activity trackers for recording step count and activity duration in older, community-dwelling ...adults.•Consumer wearables are valid in the measurement of step count and duration of physical activity, as confirmed by reference monitors or gold-standard validation techniques.•The majority of consumer wearables overestimated step count, and to a lesser extent duration of physical activity.•Slower walking speed and impaired ambulation reduced the level of agreement between consumer wearables and reference devices.
To understand the validity and reliability of consumer-grade activity trackers (consumer wearables) in older, community-dwelling adults.
A systematic review of studies involving adults aged over 65 years who underwent physical activity monitoring with consumer wearables. A total of 7 observational studies qualified, identified from electronic databases: MEDLINE, EMBASE, Cochrane Library and others (2014–2018). Validity was interpreted using correlation coefficients (CC) and percentage error for agreement between reference devices or gold-standard validation methods Reliability was compared using mean differences or ranges (under- or overestimation) of step count and activity time.
Total sample size was 290 adults, mean age of 70.2 ± 4.8 years and females constituting 46.7 ± 26.1%. The studies evaluated eight different consumer wearables used by community-dwelling adults with a range of co-morbidities. Daily step count for all consumer wearables correlated highly with validation criterion, especially the ActiGraph device: intraclass correlation coefficients (ICC) were 0.94 for Fitbit One, 0.94 for Zip, 0.86 for Charge HR and 0.96 for Misfit Shine. Slower walking pace and impaired ambulation reduced the levels of agreement. Daily step count captured by Fitbit Zip was on average 7117 (±5,880.6), which was overestimated by five of the eight consumer wearables compared with reference devices (range 167.6–2,690.3 steps/day). Measurement of activity duration was accurate compared with reference devices, yet less so than step count.
In older, community-dwelling adults, consumer wearables accurately measure step count and activity duration, as confirmed by reference devices and validation methods Further research is required to understand how co-morbidities, gait and activity levels interact with monitoring in free-living environments.
•Wearable trackers have acceptable accuracy, especially for measuring step counts, MVPA, ECG and HR.•Most older adults reported ease of use and also demonstrated high-level adherence over daily ...long-term use.•There are no standardised methods for quantifying data from wearable devices in older adults. As such frameworks and / or guidelines, are needed.
Wearable trackers as research or clinical tools are increasingly used to support the care of older adults, due to their practicality in self-monitoring and potential to promote healthy lifestyle behaviours. However, there is limited understanding of appropriate data collection and analysis methods in different contexts.
To summarise evidence on wearable data generation and management in older adults, focusing on physical activity (PA), electrocardiogram (ECG), and vital signs monitoring. In addition to examine the accuracy and utility of wearable trackers in the care of older people.
A systematic search of CINAHL, MEDLINE, PubMed and a manual search were conducted. Twenty studies on the use of wearable trackers by older adults met the inclusion criteria.
Methodological designs for data collection and analysis were heterogeneous, with diverse definitions of wear and no-wear time, the number and type of valid days, and proprietary algorithms. Wearable trackers had adequate accuracy for measuring step counts, moderate to vigorous physical activity (MVPA), ECG and heart rate (HR), but not for respiratory rate. Participants reported ease of use and had high-level adherence over daily long-term use. Moreover, wearable trackers encouraged users to increase their daily level of physical activity and decrease waist circumference, facilitating atrial fibrillation (AF) diagnoses and predicting length of stay.
Wearable trackers are multi-dimensional technologies offering a viable and promising approach for sustained and scaled monitoring of older people’s health. Frameworks and/or guidelines, including standards for the design, data management and application of use specifically for older adults, are required to enhance validity and reliability.
Background:
Barriers to exercise are common in people with coronary heart disease (CHD) and/or diabetes mellitus (DM), and may influence self-efficacy for exercise.
Purpose:
The purpose of this study ...was to describe the exercise barriers experienced by people who have CHD and/or DM participating in the Healthy Eating and Exercise Lifestyle Program and to determine whether these barriers influence self-efficacy.
Methods:
Participants (n = 134) identified their barriers to exercise and completed the self-efficacy for exercise survey at baseline, at 4 months (following structured and supervised exercise) and at 12 months (following home-based exercise with three follow-up calls).
Results:
The sample mean age was 63.6 years (SD 8.5) and 58% were male. Barriers to exercise were reported by 88% at baseline, 76% at 4 months, and 47% at 12 months. The most common barriers were lack of motivation (40.3%), lack of time overall (30.6%), and lack of time due to family commitments (17.2%). Only motivation changed significantly over time from baseline (40%) to 4 months (23%, p = 0.040). Lower self-efficacy for exercise was associated with lack of motivation at 12 months only, more depressive symptoms at baseline and 4 months, and a CHD diagnosis and higher body mass index at 12 months. In contrast, male gender and having higher self-efficacy at baseline were associated with higher self-efficacy for exercise at 4 and 12 months.
Conclusion:
Patients identified many exercise barriers despite participating in a lifestyle-change program. Lack of motivation negatively influenced self-efficacy for exercise at 12 months. Other factors needing attention include baseline self-efficacy, depressive symptoms, being female, being more overweight, and having CHD.
Concordant assessments of physical activity (PA) and related measures in cardiac rehabilitation (CR) is essential for exercise prescription. This study compared exercise measurement from an in-person ...walk test; wearable activity tracker; and self-report at CR entry, completion (8-weeks) and follow-up (16-weeks). Forty patients beginning CR completed the Six-Minute Walk Test (6MWT), Physical Activity Scale for the Elderly (PASE), and wore Fitbit-Flex for four consecutive days including two weekend days. The sample mean age was 66 years; 67% were male. Increased exercise capacity at CR completion and follow-up was detected by a 6MWT change in mean distance (39 m and 42 m;
= 0.01, respectively). Increased PA participation at CR completion was detected by Fitbit-Flex mean change in step counts (1794;
= 0.01). Relative changes for Fitbit-Flex step counts and a 6MWT were consistent with previous research, demonstrating Fitbit-Flex's potential as an outcome measure. With four days of data, Fitbit-Flex had acceptable ICC values in measuring step counts and MVPA minutes. Fitbit-Flex steps and 6MWT meters are more responsive to changes in PA patterns following exposure to a cardiac rehabilitation program than Fitbit-Flex or PASE-estimated moderate-vigorous PA (MVPA) minutes. Fitbit-Flex step counts provide a useful additional measure for assessing PA outside of the CR setting and accounts for day-to-day variations. Two weekend days and two weekdays are needed for Fitbit-Flex to estimate PA levels more precisely.
Background:
The benefits of exercise and weight reduction for overweight or obese people with coronary heart disease and/or diabetes mellitus are well recognised. The Healthy Eating and Exercise ...Lifestyle Program demonstrated these outcomes at 4 months, but longer-term outcomes are not yet reported.
Aim:
To determine whether positive weight, body mass index, waist and exercise duration outcomes were sustained in the long term (12 months) and to identify the independent predictors of these outcomes at 4 and 12 months.
Methods:
Longitudinal design, combining data of all Healthy Eating and Exercise Lifestyle Program participants (intervention and wait-list control, n = 134). Participants had a body mass index between 27 and 39 kg/m2 and had completed cardiac rehabilitation and/or diabetes education programmes. Healthy Eating and Exercise Lifestyle Program intervention included an active phase of two 1-hour group-based supervised structured exercise sessions every week for 4 months and four 90-minute group information and support sessions. The maintenance phase included one 90-minute group-based booster information session and three 15-minute goal-focused telephone follow-up calls over 8 months.
Results:
Participants had statistically significant reductions from baseline in weight, body mass index and waist circumference and improvements in exercise duration and capacity at 4 and 12 months. Time, self-efficacy, depressive symptoms and male gender were independent predictors for body mass index, waist and/or exercise duration (p < 0.05).
Conclusion:
The Healthy Eating and Exercise Lifestyle Program was an effective programme to achieve and sustain weight loss and increase exercise participation over 1 year.
This paper aims to measure the impact of the implemented nonpharmaceutical interventions (NPIs) in the Kingdom of Saudi Arabia (KSA) during the pandemic using simulation modeling.
To measure the ...impact of NPI, a hybrid agent-based and system dynamics simulation model was built and validated. Data were collected prospectively on a weekly basis. The core epidemiological model is based on a complex Susceptible-Exposed-Infectious-Recovered and Dead model of epidemic dynamics. Reverse engineering was performed on a weekly basis throughout the study period as a mean for model validation which reported on four outcomes: total cases, active cases, ICU cases, and deaths cases. To measure the impact of each NPI, the observed values of active and total cases were captured and compared to the projected values of active and total cases from the simulation. To measure the impact of each NPI, the study period was divided into rounds of incubation periods (cycles of 14 days each). The behavioral change of the spread of the disease was interpreted as the impact of NPIs that occurred at the beginning of the cycle. The behavioral change was measured by the change in the initial reproduction rate (R0).
After 18 weeks of the reverse engineering process, the model achieved a 0.4 % difference in total cases for prediction at the end of the study period. The results estimated that NPIs led to 64 % change in The R0. Our breakdown analysis of the impact of each NPI indicates that banning going to schools had the greatest impact on the infection reproduction rate (24 %).
We used hybrid simulation modeling to measure the impact of NPIs taken by the KSA government. The finding further supports the notion that early NPIs adoption can effectively limit the spread of COVID-19. It also supports using simulation for building mathematical modeling for epidemiological scenarios.
Background Assessment of physical activity (PA) for cardiac rehabilitation (CR) participants is critical to monitor changes. However, the validity and reliability of PA measures to assess PA ...throughout the day, not only during exercise training, is poorly investigated. Aim To establish a reliable and valid measure to assess overall PA in CR participants. Methods A narrative literature review was performed based on a systematic search of EMBASE, CINAHL, MEDLINE and PubMed databases. Eight studies comparing two or more PA measures with at least one direct measure met the inclusion criteria. Results Methodological designs were heterogeneous. Correlations and levels of agreement between self-reported measures and direct measures were weak to moderate, while the correlations between direct measures were high. Of the direct measures, the SenseWear armband had the highest validity, and the PA diary and MobilePAL questionnaires performed better than other self-reported PA measures. Conclusion Direct measures were more valid and reliable than self-reported measures. No recommendation for a definitive PA measure was made due to lack of strong evidentiary support for one PA measure over another. There is a need for accurate measures of overall PA in evaluating current and changing PA levels following CR.
Purpose of review
The purpose of this study was to explore the potential of wearable activity trackers to promote self-care management for physical activity in heart failure (HF).
Recent findings
...Exercise participation decreases hospital admissions and improves quality of life in HF, and activity tracking devices provide more precise means to assess free-living physical activity and thus enable tailored exercise instruction. Use of activity trackers by cardiac patients for self-monitoring and motivational purposes is associated with increased levels of physical activity and is predictive of disease severity. However, more research is required to establish the feasibility and validity of these devices in HF patients. It is also critical that the devices can be easily used to collect, process and utilise relevant data.
Summary
Activity trackers have the potential to promote HF self-care because they provide monitoring of physical activity behaviours and the potential to generate habit formation and goal reinforcement, all of which foster physical activity.
Over 98% of the world's greenhouse gas emissions in 2014 came from carbon dioxide (CO2), methane, and nitrous oxide. Over one century, CO2 emissions increased from 3.09 to 37.12 billion metric tons. ...The healthcare sector is one of the major sources of greenhouse gas emissions. The carbon footprint of a country's healthcare system is influenced by its domestic economy, healthcare expenditure, and energy system. The aim of this study is to present a concise of the present status of carbon emissions within the healthcare sectors on a global scale, as well as the forthcoming endeavors to mitigate these emissions. A narrative review of studies on climate change, carbon emissions, and greenhouse gases in the healthcare sector was conducted using Medline PubMed, Web of Science, Scopus and Google Scholar databases from 2005 to April 2023. According to the data, several countries emit more carbon per capita than others. The Conference of the Parties on Climate Change (COP26) recently encompassed extensive efforts culminating in releasing initiatives toward zero-carbon healthcare sectors. Efforts in some medical practices, smart technology to save energy, digital health, artificial intelligence technology, and monitoring have contributed to reducing carbon emissions. In conclusion, the healthcare sector with zero carbon emissions must be sustainable, adaptable, and efficient while delivering safe, high-quality care. Addressing the sector's carbon footprint requires innovative strategies, a multisector approach, health professionals' participation, community engagement, and regular monitoring of emissions and performance indicators to ensure patient service quality and low carbon emissions in the healthcare sector.
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