Wearables for Promoting Physical Activity.

BACKGROUND: The rapid expansion and popularity of consumer-wearable physical activity monitors (WPAMs) has enabled the integration of technology into physical activity (PA) intervention, deployment, and evaluation. This brief review reports on the accuracy of consumer-WPAMs, considers the intervention effects of using consumer-WPAMs, and offers future considerations as the proliferation of this area of product development and consumer use continues to escalate. CONTENT: The studies reviewed document the utility for consumer-WPAMs to objectively assess PA, with output metrics similar to research-grade activity monitors. Early intervention efficacy for the use of consumer-WPAMs to increase PA holds considerable promise. Substantial increases in moderate- to vigorous-intensity PA (MVPA) have been reported across different research study designs and populations in which consumer-WPAMs have been used in isolation or in conjunction with other behavioral change strategies. The utility of consumer-WPAMs is currently being investigated in clinical populations, notably showing increases in PA in individuals at risk for cancer or post cancer survivors, in those with chronic obstructive pulmonary disease, and in postsurgical patients. There has been a proliferation of registered trials at clinicaltrials.gov, and an increase of disseminated works regarding the use of consumer-WPAMs is expected. SUMMARY: There are many research studies documenting the validity and intervention effectiveness of consumer-WPAMs; evidence is emerging on the health benefits linked to use of such devices. Future work on the long-term effects of consumer-WPAMs on behavior and health is warranted, and prospects appear exciting as wearable technology advances and adoption increases.

Increasing the Energy Expenditure of Seated Activities in Older Adults with a Portable Elliptical Device.

BACKGROUND: The ill-health effects of sedentary behavior are becoming well-documented, yet older adults spend 70-80% of waking hours sedentary. PURPOSE: To determine if a portable elliptical device increases energy expenditure (EE) while performing popular seated activities. METHODS: Twenty older adults (68.1 ± 1.4 years) participated to compare the measured EE between seated rest and three randomized seated pedaling activities: computer use, reading, TV viewing. Each pedaling activity included 5-min of self-selected paced/no resistance (SSP) and externally paced/added resistance pedaling (Paced). RESULTS: A significant increase in EE existed during SSP (+1.44 ± 0.12 kcal/min) and Paced (+2.19 ± 0.09 kcal/min) pedaling relative to Seated Rest (p < .001). EE during the Paced activities was significantly greater than all SSP activities (p <.01). CONCLUSION: Extrapolating these results, pedaling at a SSP for an hour while performing seated activities is equivalent to the net EE of walking 1.6 miles. Future home-based effectiveness and feasibility should be explored.

Physical Activity and the Link Among Stress, Burnout, and Well-Being in Athletic Trainers.

CONTEXT: Stress is a leading cause of burnout in working professionals, including athletic trainers (ATs). One consequence of burnout for ATs is lower perceptions of well-being, which have implications for mental and physical health. Physical activity is known to help reduce stress. Thus, activity may help reduce stress and burnout in ATs while enhancing well-being. OBJECTIVE: To examine a theoretically based mediating model whereby leisure time physical activity was linked to subjective well-being by way of ATs' perceived stress and burnout. DESIGN: Cross-sectional study. SETTING: Online survey during the fall sports season. PATIENTS OR OTHER PARTICIPANTS: Practicing certified ATs (N = 163; mean age = 30.5 ± 6.7 years). MAIN OUTCOME MEASURE(S): Via a secure link, participants completed a survey that measured leisure time planned physical activity, work-related stress, burnout, and perceived life satisfaction. Latent variable analysis was used to examine the hypothesized mediating model. RESULTS: Minutes spent in moderate or vigorous activity were not associated with stress. Minutes spent walking were negatively associated with perceived stress (ß = -0.18, P < .001). Stress was positively associated with exhaustion (ß = 0.89, P < .001), negatively associated with personal accomplishment (ß = -0.70, P < .001), and positively associated with depersonalization (ß = 0.71, P < .001). Exhaustion was negatively associated (ß = -0.57, P < .001) and personal accomplishment was positively associated (ß = 0.31, P = .013) with well-being. Minutes spent walking were positively linked to well-being via stress and exhaustion. The negative relationship between stress and well-being was mediated by exhaustion and personal accomplishment. CONCLUSIONS: Leisure time walking was indirectly and positively linked to well-being. Walking could be a strategy to reduce stress and burnout in ATs and thereby improve well-being.

Validation of a series of walking and stepping tests to predict maximal oxygen consumption in adults aged 18-79 years.

INTRODUCTION: Field tests to estimate maximal oxygen consumption (VO2max) are an alternative to traditional exercise testing methods. Published field tests and their accompanying estimation equations account for up to 80% of the variance in VO2max with an error rate of ~4.5 ml.kg-1.min-1. These tests are limited to very specific age-range populations. The purpose of this study was to create and validate a series of easily administered walking and stepping field equations to predict VO2max across a range of healthy 18-79-year-old adults. METHODS: One-hundred-fifty-seven adults completed a graded maximal exercise test to assess VO2max. Five separate walking and three separate stepping tests of varying durations, number of stages, and intensities were completed. VO2max estimation equations were created using hierarchal multiple regression. Covariates including age, sex, body mass, resting heart rate, distance walked, gait speed, stepping cadence, and recovery heart rate were entered into each model using a stepwise approach. Each full model created had the same base model consisting of age, sex, and body mass. Validity of each model was assessed using a Jackknife cross-validation analysis, and percent bias and root mean square error (RMSE) were calculated. RESULTS: Base models accounted for ~72% of the total variance of VO2max. Full model variance ranged from ~79-83% and bias was minimal (<±1.0%) across models. RMSE for all models were approximately 4.5 ml.kg-1.min-1. Stepping tests performed better than walking tests by explaining ~2.5% more of the variance and displayed smaller RMSE. CONCLUSION: All eight models accounted for a large percentage of VO2max variance (~81%) with a RMSE of ~4.5 ml.kg-1.min-1. The variance and level of error of models examined highlight good group mean prediction with greater error expected at the individual level. All the models perform similarly across a broad age range, highlighting flexibility in application of these tests to a more general population.

Accelerometer Calibration: The Importance of Considering Functionality.

PURPOSE: To compare the accuracy and precision of a hip-worn accelerometer to predict energy cost during structured activities across motor performance and disease conditions. METHODS: 118 adults self-identifying as healthy (n = 44) and those with arthritis (n = 23), multiple sclerosis (n = 18), Parkinson's disease (n = 17), and stroke (n =18) underwent measures of motor performance and were categorized into groups: Group 1, usual; Group 2, moderate impairment; and Group 3, severe impairment. The participants completed structured activities while wearing an accelerometer and a portable metabolic measurement system. Accelerometer-predicted energy cost (metabolic equivalent of tasks [METs]) were compared with measured METs and evaluated across functional impairment and disease conditions. Statistical significance was assessed using linear mixed effect models and Bayesian information criteria to assess model fit. RESULTS: All activities' accelerometer counts per minute (CPM) were 29.5-72.6% less for those with disease compared with those who were healthy. The predicted MET bias was similar across disease, -0.49 (-0.71, -0.27) for arthritis, -0.38 (-0.53, -0.22) for healthy, -0.44 (-0.68, -0.20) for MS, -0.34 (-0.58, -0.09) for Parkinson's, and -0.30 (-0.54, -0.06) for stroke. For functional impairment, there was a graded reduction in CPM for all activities: Group 1, 1,215 CPM (1,129, 1,301); Group 2, 789 CPM (695, 884); and Group 3, 343 CPM (220, 466). The predicted MET bias revealed similar results across the Group 1, -0.37 METs (-0.52, -0.23); Group 2, -0.44 METs (-0.60, -0.28); and Group 3, -0.33 METs (-0.55, -0.13). The Bayesian information criteria showed a better model fit for functional impairment compared with disease condition. CONCLUSION: Using functionality to improve accelerometer calibration could decrease variability and warrants further exploration to improve accelerometer prediction of physical activity.

Identification of Latent Classes of Motor Performance in a Heterogenous Population of Adults.

OBJECTIVE: To determine classes of motor performance based on community deployable motor impairment and functional tests in a heterogeneous adult population. DESIGN: Sixteen tests of limb-specific and whole-body measures of motor impairment and function were obtained. Linear regression analysis was used to dichotomize performance on each test as falling within or outside the age- and sex-predicted values. Latent class analysis was used to determine 3 classes of motor performance. The chi-square test of association and the Fisher exact test were used for categorical variables, and analysis of variance and the Kruskal-Wallis test were used for continuous variables to evaluate the relationship between demographic characteristics and latent classes. SETTING: General community. PARTICIPANTS: Individuals (N=118; 50 men) participated in the study. Quota sampling was used to recruit individuals who self-identified as healthy (n=44) or currently living with a preexisting chronic health condition, including arthritis (n=19), multiple sclerosis (n=18), Parkinson disease (n=17), stroke (n=18), or low functioning (n=2). INTERVENTION: Not applicable. MAIN OUTCOME MEASURE: Latent classes of motor performance. RESULTS: Across the entire sample, 3 latent classes of motor performance were determined that clustered individuals with motor performance falling: (1) within predicted values on most of the tests (expected class), (2) outside predicted values on some of the tests (moderate class), and (3) outside predicted values on most of the tests (severe class).The ability to distinguish between the respective classes based on the percent chance of falling outside predicted values was achieved using the following community deployable motor performance tests: 10-meter walk test (22%, 80%, and 100%), 6-minute walk test (14.5%, 37.5%, and 100%), grooved pegboard test (23%, 38%, and 100%), and modified physical performance test (3%, 54%, and 96%). CONCLUSIONS: In this heterogeneous group of adults, we found 3 distinct classes of motor performance, with the sample clustering into an expected test score group, a moderate test score deficiency group, and a severed test score deficiency group. Based on the motor performance tests, we established that community deployable, easily administered testing could accurately predict the established clusters of motor performance.

Efficacy of an Individually Tailored, Internet-Mediated Physical Activity Intervention in Older Adults: A Randomized Controlled Trial.

OBJECTIVE: This study determined the effectiveness of an individually tailored, Internet-mediated physical activity (PA) intervention for increasing walking behavior in inactive older adults. METHOD: This 12-week randomly controlled intervention divided participants ( N = 170) into three groups: control (CON, n = 51), pedometer only (PED, n = 62), and an individually tailored, Internet-mediated pedometer (TI-PED, n = 57) group. The PED group was instructed to increase weekly step count by 10% until 10,000 steps per day was achieved. The TI-PED group was given the same goal and received tailored feedback via an online platform. Changes in average step count pre-to-post were assessed. RESULTS: Total retention rate at postintervention was 75.3%. PED ( p < .001) and TI-PED ( p < .001) increased step count pre-to-post, which was higher than the CON group at 12 weeks (PED, p < .001; TI-PED, p < .001). The TI-PED group had a higher step count at 12 weeks than the PED group ( p < .001). DISCUSSION: Individually tailored, Internet-mediated PA interventions are an effective way to significantly increase PA in older adults.

Energy Cost of Slow and Normal Gait Speeds in Low and Normally Functioning Adults.

OBJECTIVE: Slow walking speed paired with increased energy cost is a strong predictor for mortality and disability in older adults but has yet to be examined in a heterogeneous sample (ie, age, sex, disease status). The aim of this study was to examine energy cost of slow and normal walking speeds among low- and normal-functioning adults. DESIGN: Adults aged 20-90 yrs were recruited for this study. Participants completed a 10-m functional walk test at a self-selected normal walking speed and were categorized as low functioning or normal functioning based on expected age- and sex-adjusted average gait speed. Participants completed two successive 3-min walking stages, at slower than normal and normal walking speeds, respectively. Gas exchange was measured and energy cost per meter (milliliter per kilogram per meter) was calculated for both walking speeds. RESULTS: Energy cost per meter was higher (P < 0.0001) in the low-functioning group (n = 76; female = 59.21%; mean ± SD age = 61.13 ± 14.68 yrs) during the slower than normal and normal (P < 0.0001) walking speed bouts compared with the normal-functioning group (n = 42; female = 54.76%; mean ± SD age = 51.55 ± 19.51 yrs). CONCLUSIONS: Low-functioning adults rely on greater energy cost per meter of walking at slower and normal speeds. This has implications for total daily energy expenditure in low-functioning, adult populations.