Accelerometer use in a physical activity intervention trial

Current agreement between ActiGraph and CUPAR in measuring moderate to vigorous intensity physical activity for adolescents

The study aims to develop and validate the Curriculum-related Physical Activity Recall questionnaire (CUPAR) as a measure of physical activity in adolescents. 83 middle-school students (13.23 ± 0.74 yrs) completed the CUPAR and whore ActiGraph accelerometers for seven consecutive days. Correlations and Bland-Altman plots were to examine the agreement between these two measures. Significant correlations were observed between the CUPAR and ActiGraph accelerometer for 5-day MPA (r = 0.29, p < 0.01), and for both 5-day and 7-day VPA (r = 0.47 and 0.79, ps < 0.01), and MVPA (r = 0.79 and 0.42, ps < 0.01). Plots showed reasonable agreement between the CUPAR and ActiGraph estimates of VPA and MVPA. The agreement between CUPAR and ActiGraph was higher for in-school VPA (r = 0.58, p < 0.01) and MVPA (r = 0.44, p < 0.01) as compared to the out-school VPA (r = 0.22, p < 0.05) and MVPA (r = 0.26, p < 0.05). The CUPAR can reduce respondents' burden, representing a reliable and efficient measure of physical activity among adolescents, especially for PA occurred during in-school sessions and at vigorous intensity.

Age and school-segment difference in daily sedentary behavior and physical activity among student (9-23 years): a cross-sectional accelerometer-based survey

This study is cross-sectional in nature and aims to investigate and track sedentary behavior (SB) and physical activity among student (aged 9-23 years) for seven consecutive days using an accelerometer. It also intends to analyze the current status of the daily activities of students using age and school-segment differences. The study recruits a total of 384 students [age: 14.41 ± 3.52 years; body mass index (BMI): 19.66 ± 3.67] from four schools out of which 180 (46.88%) were male. The study uses the means and standard deviations for statistical analysis and independent sample t-tests to determine gender differences. Analysis of covariance is used to determine whether or not daily SB and physical activity were statistically significant students according to gender and school segment followed by LSD post hoc tests for multiple comparisons. The results demonstrate that students were less physically active [moderate- to vigorous-intensity physical activity (MVPA):60.4 ± 23.48 min/day] and more sedentary (598.47 ± 162.63 min/day). The sedentary time of the students displays an inverted U-trend, and their participation in MVPA exhibits a W-shape. After controlling for BMI, the results of ANCOVA point to a significant school-segment effect (p < 0.001) for SB (F = 83, η_p² = 0.4) and physical activity (low-intensity physical activity: F = 108.61, η_p² = 0.47; MPA: F = 401.65, η_p² = 0.76; high-intensity physical activity: F = 88.43, η_p² = 0.42; MVPA: F = 118.42, η_p² = 0.49). Based on the behavioral characteristics of students across school segments, this study concluded that interventions targeting students' physical activity and physical health should be school segment specific. The results of the study provide a basis for future analysis of factors influencing students' physical activity behaviors across school segments and for proposing targeted intervention strategies for the future.

Opal Actigraphy (Activity and Sleep) Measures Compared to ActiGraph: A Validation Study

Physical activity and sleep monitoring in daily life provide vital information to track health status and physical fitness. The aim of this study was to establish concurrent validity for the new Opal Actigraphy solution in relation to the widely used ActiGraph GT9X for measuring physical activity from accelerometry epic counts (sedentary to vigorous levels) and sleep periods in daily life. Twenty participants (age 56 + 22 years) wore two wearable devices on each wrist for 7 days and nights, recording 3-D accelerations at 30 Hz. Bland-Altman plots and intraclass correlation coefficients (ICCs) assessed validity (agreement) and test-retest reliability between ActiGraph and Opal Actigraphy sleep durations and activity levels, as well as between the two different versions of the ActiGraph. ICCs showed excellent reliability for physical activity measures and moderate-to-excellent reliability for sleep measures between Opal versus Actigraph GT9X and between GT3X versus GT9X. Bland-Altman plots and mean absolute percentage error (MAPE) also show a comparable performance (within 10%) between Opal and ActiGraph and between the two ActiGraph monitors across activity and sleep measures. In conclusion, physical activity and sleep measures using Opal Actigraphy demonstrate performance comparable to that of ActiGraph, supporting concurrent validation. Opal Actigraphy can be used to quantify activity and monitor sleep patterns in research and clinical studies.

Is the Risk Perception Attitude Framework Associated with the Accuracy of Self-Reported vs Actual Cardiometabolic Risk and Physical Activity in Young Adults with Overweight/Obesity?

We examined the accuracy of perceived vs actual cardiometabolic risk and physical activity within the Risk Perception Attitude Framework (RPA). We analyzed baseline data from 343 young adults (23.3 ± 4.4 years) participating in a weight management clinical trial. Cardiometabolic risk factors were measured according to standard clinical procedures. A cardiometabolic risk score was created from five biomarkers according to whether or not a standard clinical risk cut point was exceeded. Physical activity was determined by ActiGraph and self-report. Perceived risk and physical activity self-efficacy were assessed by validated measures. The Proactive cluster (low perceived risk/high self-efficacy) was most accurate regarding actual vs perceived risk awareness (54%), while the Responsive cluster (high perceived risk/high self-efficacy) was the least accurate (16%). All RPA clusters underestimated their actual physical activity, self-reporting less than half the moderate-to-vigorous physical activity that was captured via accelerometry. The RPA Framework can identify young adults unlikely to be aware of their cardiometabolic risk. Given the growing prevalence of metabolic syndrome, efforts early in adulthood to increase knowledge and awareness of cardiometabolic risk, and behaviors necessary to reduce that risk, can have substantial impact on future health.

Wearable-Based Stair Climb Power Estimation and Activity Classification

Stair climb power (SCP) is a clinical measure of leg muscular function assessed in-clinic via the Stair Climb Power Test (SCPT). This method is subject to human error and cannot provide continuous remote monitoring. Continuous monitoring using wearable sensors may provide a more comprehensive assessment of lower-limb muscular function. In this work, we propose an algorithm to classify stair climbing periods and estimate SCP from a lower-back worn accelerometer, which strongly agrees with the clinical standard (r = 0.92, p < 0.001; ICC = 0.90, [0.82, 0.94]). Data were collected in-lab from healthy adults (n = 65) performing the four-step SCPT and a walking assessment while instrumented (accelerometer + gyroscope), which allowed us to investigate tradeoffs between sensor modalities. Using two classifiers, we were able to identify periods of stair ascent with >89% accuracy [sensitivity = >0.89, specificity = >0.90] using two ensemble machine learning algorithms, trained on accelerometer signal features. Minimal changes in model performances were observed using the gyroscope alone (±0−6% accuracy) versus the accelerometer model. While we observed a slight increase in accuracy when combining gyroscope and accelerometer (about +3−6% accuracy), this is tolerable to preserve battery life in the at-home environment. This work is impactful as it shows potential for an accelerometer-based at-home assessment of SCP.

Free-living monitoring of ambulatory activity after treatments for lower extremity musculoskeletal cancers using an accelerometer-based wearable - a new paradigm to outcome assessment in musculoskeletal oncology?

PURPOSE

Ambulatory activity (walking) is affected after sarcoma surgery yet is not routinely assessed. Small inexpensive accelerometers could bridge the gap. Study objectives investigated, whether in patients with lower extremity musculoskeletal tumours: (A) it was feasible to conduct ambulatory activity assessments in patient's homes using an accelerometer-based wearable (AX3, Axivity). (B) AX3 assessments produced clinically useful data, distinguished tumour sub-groups and related to existing measures.

METHODS

In a prospective cross-sectional pilot, 34 patients with musculoskeletal tumours in the femur/thigh (19), pelvis/hip (3), tibia/leg (9), or ankle/foot (3) participated. Twenty-seven had limb-sparing surgery and seven amputation. Patients were assessed using a thigh-worn monitor. Summary measures of volume (total steps/day, total ambulatory bouts/day, mean bout length), pattern (alpha), and variability (S₂) of ambulatory activity were derived.

RESULTS

AX3 was well-tolerated and feasible to use. Outcomes compared to literature but did not distinguish tumour sub-groups. Alpha negatively correlated with disability (walking outside (r=-418, p = 0.042*), social life (r=-0.512, p = 0.010*)). Disability negatively predicted alpha (unstandardised co-efficient= -0.001, R²=0.186, p = 0.039*).

CONCLUSIONS

A wearable can assess novel attributes of walking; volume, pattern, and variability after sarcoma surgery. Such outcomes provide valuable information about people's physical performance in their homes, which can guide rehabilitation. Implications for rehabilitationRoutine capture of ambulatory activity by sarcoma services in peoples' homes can provide important information about individuals "actual" physical activity levels and limitations after sarcoma surgery to inform personalised rehabilitation and care needs, including timely referral for support.Routine remote ambulatory monitoring about out of hospital activity can support personalised care for patients, including identifying high risk patients who need rapid intervention and care closer to home.Use of routine remote ambulatory monitoring could enhance delivery of evidence-based care closer to peoples' homes without disrupting their daily routine and therefore reducing patient and carer burden.Collection of data close to home using questionnaires and objective community assessment could be more cost effective and comprehensive than in-hospital assessment and could reduce the need for hospital attendance, which is of importance to vulnerable patients, particularly during the Covid-19 pandemic.

A randomized controlled trial of a community-based obesity intervention utilizing motivational interviewing and community resource mobilization for low-income families: Study protocol and baseline characteristics

Low-income, racially diverse families with one parent with obesity are at high risk for child obesity. Effective approaches to promote healthy behaviors and prevent additional weight gain in family members are needed. Motivational interviewing (MI) may assist families to engage, identify motivations for change and establish goals. However, families with limited resources face other barriers to goal achievement that may be addressed through connection with community organizations. This paper describes a unique protocol combining MI and community connection. This randomized controlled trial includes low-income families with one parent with obesity and at least one child aged 6 to 12 years. Families in the intervention group receive an innovative, 12-month intervention combining health coaching using MI to promote lifestyle behavior change goals and community resource mobilization to assist with basic needs and resources to aid goals. The study protocol is modeled on community-based participatory research principles. Data is collected at baseline, 6 months, 12 months, and 18 months include questionnaires, body measurements, and accelerometer data. For adults, primary outcomes are Body Mass Index (BMI), minutes of moderate to vigorous physical activity (MVPA), and hours of sedentary time per day. For children, primary outcomes are sedentary time, MVPA, and the Family Nutrition and Physical Activity Score. From this hard-to-reach population, 236 diverse families were recruited. If the study is deemed effective, it has the potential to demonstrate that the combination of MI, resource mobilization, and utilization of existing community organizations is a sustainable model to assist families at risk for obesity.

Comparison of chest- and wrist-based actigraphy in pulmonary arterial hypertension

Aims

Activity trackers for clinical trials and remote monitoring are appealing as they provide objective data outside of the clinic setting. Algorithms determine physical activity intensity and count steps. Multiple studies show physical inactivity in pulmonary arterial hypertension (PAH). There are no studies comparing different activity trackers worn on different parts of the body in PAH. We had patients with PAH simultaneously wear two different accelerometers, compared measures between the two devices, and correlated the measures with standard clinical metrics in PAH.

Methods and results

This was a single-centre, prospective observational study. Daily physical activity and daily total steps were measured using Actigraph GT9X Link and MC10 Biostamp nPoint for 5-10 days. Actigraph was worn on the non-dominant hand and the MC10 Biostamp nPoint was worn on the chest and leg with disposable adhesives. Twenty-two participants wore both accelerometers >12 h/day for an average 7.8 days. The average activity time measured by Actigraph was significantly higher than that measured by MC10 (251 ± 25 min vs. 113 ± 18 min, P = 0.0001). Actigraph's algorithm reported more time in light activity than moderate (190 ± 62 min vs. 60 ± 56 min, P = 0.0001). REVEAL 2.0 scores correlated highly with activity time measured using either device. Invasively measured haemodynamics within 7 days did not correlate with activity time or daily steps.

Conclusion

Different activity trackers yield discordant results in PAH patients. Further studies are needed in determining the best device, optimal wear time, and different thresholds for activities in chronic diseases.

Reducing sedentary time using an innovative mHealth intervention among patients with total knee replacement: Rationale and study protocol

INTRODUCTION

Although knee replacement is effective for improving pain and physical function, subsequent improvements in physical activity typically do not follow. As a result, many patients spend most of their day engaged in sedentary behavior, which may put them at higher risk of experiencing poor function and disability. Intervening on sedentary time, rather than physical activity, may be a more feasible first-step approach for modifying activity-related behaviors in adults who received knee replacement.

OBJECTIVE

The purpose of this study is to examine the use of a mobile health (mHealth) intervention to reduce sedentary time among adults who received a knee replacement at 3 and 6 months after surgery.

METHODS

Patients (n = 92) scheduled for knee replacement will be recruited and at 4 weeks after surgery, they will be randomized to either NEAT!2 or Control. NEAT!2 participants will use the NEAT!2 smartphone app, which provides a vibration and/or audible tone to interrupt prolonged bouts of sitting detected from the smartphone's internal accelerometer, until 3 months after surgery. NEAT!2 participants will receive biweekly coaching calls between 4 and 12 weeks after surgery. Control participants will receive an education control app and receive non-intervention calls to assess general surgery recovery. Both groups will receive 3 retention calls between 3 and 6 months. Data collection will occur pre-operatively and at 3 and 6 months after surgery.

DISCUSSION

The results of this study will help to determine whether an innovative remotely-delivered, mHealth sedentary reduction intervention can decrease sedentary time in adults after knee replacement.

Utilization of wearable technology to assess gait and mobility post-stroke: a systematic review

Background

Extremity weakness, fatigue, and postural instability often contribute to mobility deficits in persons after stroke. Wearable technologies are increasingly being utilized to track many health-related parameters across different patient populations. The purpose of this systematic review was to identify how wearable technologies have been used over the past decade to assess gait and mobility in persons with stroke.

Methods

We performed a systematic search of Ovid MEDLINE, CINAHL, and Cochrane databases using select keywords. We identified a total of 354 articles, and 13 met inclusion/exclusion criteria. Included studies were quality assessed and data extracted included participant demographics, type of wearable technology utilized, gait parameters assessed, and reliability and validity metrics.

Results

The majority of studies were performed in either hospital-based or inpatient settings. Accelerometers, activity monitors, and pressure sensors were the most commonly used wearable technologies to assess gait and mobility post-stroke. Among these devices, spatiotemporal parameters of gait that were most widely assessed were gait speed and cadence, and the most common mobility measures included step count and duration of activity. Only 4 studies reported on wearable technology validity and reliability metrics, with mixed results.

Conclusion

The use of various wearable technologies has enabled researchers and clinicians to monitor patients’ activity in a multitude of settings post-stroke. Using data from wearables may provide clinicians with insights into their patients’ lived-experiences and enrich their evaluations and plans of care. However, more studies are needed to examine the impact of stroke on community mobility and to improve the accuracy of these devices for gait and mobility assessments amongst persons with altered gait post-stroke.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00863-x.

Physical Activity Change in an RCT: Comparison of Measurement Methods

Objectives: We aimed to quantify the agreement between self-report, standard cut-point accelerometer, and machine learning accelerometer estimates of physical activity (PA), and exam- ine how agreement changes over time among older adults in an intervention setting. Methods: Data were from a randomized weight loss trial that encouraged increased PA among 333 postmenopausal breast cancer survivors. PA was estimated using accelerometry and a validated questionnaire at baseline and 6-months. Accelerometer data were processed using standard cut-points and a validated machine learning algorithm. Agreement of PA at each time-point and change was assessed using mixed effects regression models and concordance correlation. Results: At baseline, self-report and machine learning provided similar PA estimates (mean dif- ference = 11.5 min/day) unlike self-report and standard cut-points (mean difference = 36.3 min/ day). Cut-point and machine learning methods assessed PA change over time more similarly than other comparisons. Specifically, the mean difference of PA change for the cut-point versus machine learning methods was 5.1 min/day for intervention group and 2.9 in controls, whereas it was ≥ 24.7 min/day for other comparisons. Conclusions: Intervention researchers are facing the issue of self-report measures introducing bias and accelerometer cut-points being insensi- tive. Machine learning approaches may bridge this gap.

Accuracy of Samsung Gear S Smartwatch for Activity Recognition: Validation Study

Background

Wearable accelerometers have greatly improved measurement of physical activity, and the increasing popularity of smartwatches with inherent acceleration data collection suggest their potential use in the physical activity research domain; however, their use needs to be validated.

Objective

This study aimed to assess the validity of accelerometer data collected from a Samsung Gear S smartwatch (SGS) compared with an ActiGraph GT3X+ (GT3X+) activity monitor. The study aims were to (1) assess SGS validity using a mechanical shaker; (2) assess SGS validity using a treadmill running test; and (3) compare individual activity recognition, location of major body movement detection, activity intensity detection, locomotion recognition, and metabolic equivalent scores (METs) estimation between the SGS and GT3X+.

Methods

To validate and compare the SGS accelerometer data with GT3X+ data, we collected data simultaneously from both devices during highly controlled, mechanically simulated, and less-controlled natural wear conditions. First, SGS and GT3X+ data were simultaneously collected from a mechanical shaker and an individual ambulating on a treadmill. Pearson correlation was calculated for mechanical shaker and treadmill experiments. Finally, SGS and GT3X+ data were simultaneously collected during 15 common daily activities performed by 40 participants (n=12 males, mean age 55.15 [SD 17.8] years). A total of 15 frequency- and time-domain features were extracted from SGS and GT3X+ data. We used these features for training machine learning models on 6 tasks: (1) individual activity recognition, (2) activity intensity detection, (3) locomotion recognition, (4) sedentary activity detection, (5) major body movement location detection, and (6) METs estimation. The classification models included random forest, support vector machines, neural networks, and decision trees. The results were compared between devices. We evaluated the effect of different feature extraction window lengths on model accuracy as defined by the percentage of correct classifications. In addition to these classification tasks, we also used the extracted features for METs estimation.

Results

The results were compared between devices. Accelerometer data from SGS were highly correlated with the accelerometer data from GT3X+ for all 3 axes, with a correlation ≥.89 for both the shaker test and treadmill test and ≥.70 for all daily activities, except for computer work. Our results for the classification of activity intensity levels, locomotion, sedentary, major body movement location, and individual activity recognition showed overall accuracies of 0.87, 1.00, 0.98, 0.85, and 0.64, respectively. The results were not significantly different between the SGS and GT3X+. Random forest model was the best model for METs estimation (root mean squared error of .71 and r-squared value of .50).

Conclusions

Our results suggest that a commercial brand smartwatch can be used in lieu of validated research grade activity monitors for individual activity recognition, major body movement location detection, activity intensity detection, and locomotion detection tasks.

Validity of wearable activity monitors for tracking steps and estimating energy expenditure during a graded maximal treadmill test

The purpose of this study was to assess the accuracy of energy expenditure (EE) estimation and step tracking abilities of six activity monitors (AMs) in relation to indirect calorimetry and hand counted steps and assess the accuracy of the AMs between high and low fit individuals in order to assess the impact of exercise intensity. Fifty participants wore the Basis watch, Fitbit Flex, Polar FT7, Jawbone, Omron pedometer, and Actigraph during a maximal graded treadmill test. Correlations, intra-class correlations, and t-tests determined accuracy and agreement between AMs and criterions. The results indicate that the Omron, Fitbit, and Actigraph were accurate for measuring steps while the Basis and Jawbone significantly underestimated steps. All AMs were significantly correlated with indirect calorimetry, however, no devices showed agreement (p < .05). When comparing low and high fit groups, correlations between AMs and indirect calorimetry improved for the low fit group, suggesting AMs may be better at measuring EE at lower intensity exercise.

Using an internet intervention to support self-management of low back pain in primary care: findings from a randomised controlled feasibility trial (SupportBack)

OBJECTIVE

To determine the feasibility of a randomised controlled trial of an internet intervention for low back pain (LBP) using three arms: (1) usual care, (2) usual care plus an internet intervention or (3) usual care plus an internet intervention with additional physiotherapist telephone support.

DESIGN AND SETTING

A three-armed randomised controlled feasibility trial conducted in 12 general practices in England.

PARTICIPANTS

Primary care patients aged over 18 years, with current LBP, access to the internet and without indicators of serious spinal pathology or systemic illness.

INTERVENTIONS

The 'SupportBack' internet intervention delivers a 6-week, tailored programme, focused on graded goal setting, self-monitoring and provision of tailored feedback to encourage physical activity. Additional physiotherapist telephone support consisted of three brief telephone calls over a 4-week period, to address any concerns and provide reassurance.

OUTCOMES

The primary outcomes were the feasibility of the trial design including recruitment, adherence and retention at follow-up. Secondary descriptive and exploratory analyses were conducted on clinical outcomes including LBP-related disability at 3 months follow-up.

RESULTS

Primary outcomes: 87 patients with LBP were recruited (target 60-90) over 6 months, and there were 3 withdrawals. Adherence to the intervention was higher in the physiotherapist-supported arm, compared with the stand-alone internet intervention. Trial physiotherapists adhered to the support protocol. Overall follow-up rate on key clinical outcomes at 3 months follow-up was 84%.

CONCLUSIONS

This study demonstrated the feasibility of a future definitive randomised controlled trial to determine the clinical and cost-effectiveness of the SupportBack intervention in primary care patients with LBP.

TRIAL REGISTRATION NUMBER

ISRCTN31034004; Results.

Digitally enhanced recovery: Investigating the use of digital self-tracking for monitoring leisure time physical activity of cardiovascular disease (CVD) patients undergoing cardiac rehabilitation

Research has shown that physical activity is essential in the prevention and treatment of chronic diseases like cardiovascular disease (CVD). Smart wearables (e.g., smartwatches) are increasingly used to foster and monitor human behaviour, including physical activity. However, despite this increased usage, little evidence is available on the effects of smart wearables in behaviour change. The little research which is available typically focuses on the behaviour of healthy individuals rather than patients. In this study, we investigate the effects of using smart wearables by patients undergoing cardiac rehabilitation. A field experiment involving 29 patients was designed and participants were either assigned to the study group (N = 13 patients who finished the study and used a self-tracking device) or the control group (N = 16 patients who finished the study and did not use a device). For both groups data about physiological performance during cardiac stress test was collected at the beginning (baseline), in the middle (in week 6, at the end of the rehabilitation in the organized rehabilitation setting), and at the end of the study (after 12 weeks, at the end of the rehabilitation, including the organized rehabilitation plus another 6 weeks of self-organized rehabilitation). Comparing the physiological performance of both groups, the data showed significant differences. The participants in the study group not only maintained the same performance level as during the midterm examination in week 6, they improved performance even further during the six weeks that followed. The results presented in this paper provide evidence for positive effects of digital self-tracking by patients undergoing cardiac rehabilitation on performance of the cardiovascular system. In this way, our study provides novel insight about the effects of the use of smart wearables by CVD patients. Our findings have implications for the design of self-management approaches in a patient rehabilitation setting. In essence, the use of smart wearables can prolong the success of the rehabilitation outside of the organized rehabilitation setting.

Physical Activity Assessment Between Consumer- and Research-Grade Accelerometers: A Comparative Study in Free-Living Conditions

Background

Wearable activity monitors such as Fitbit enable users to track various attributes of their physical activity (PA) over time and have the potential to be used in research to promote and measure PA behavior. However, the measurement accuracy of Fitbit in absolute free-living conditions is largely unknown.

Objective

To examine the measurement congruence between Fitbit Flex and ActiGraph GT3X for quantifying steps, metabolic equivalent tasks (METs), and proportion of time in sedentary activity and light-, moderate-, and vigorous-intensity PA in healthy adults in free-living conditions.

Methods

A convenience sample of 19 participants (4 men and 15 women), aged 18-37 years, concurrently wore the Fitbit Flex (wrist) and ActiGraph GT3X (waist) for 1- or 2-week observation periods (n=3 and n=16, respectively) that included self-reported bouts of daily exercise. Data were examined for daily activity, averaged over 14 days and for minutes of reported exercise. Average day-level data included steps, METs, and proportion of time in different intensity levels. Minute-level data included steps, METs, and mean intensity score (0 = sedentary, 3 = vigorous) for overall reported exercise bouts (N=120) and by exercise type (walking, n=16; run or sports, n=44; cardio machine, n=20).

Results

Measures of steps were similar between devices for average day- and minute-level observations (all P values > .05). Fitbit significantly overestimated METs for average daily activity, for overall minutes of reported exercise bouts, and for walking and run or sports exercises (mean difference 0.70, 1.80, 3.16, and 2.00 METs, respectively; all P values < .001). For average daily activity, Fitbit significantly underestimated the proportion of time in sedentary and light intensity by 20% and 34%, respectively, and overestimated time by 3% in both moderate and vigorous intensity (all P values < .001). Mean intensity scores were not different for overall minutes of exercise or for run or sports and cardio-machine exercises (all P values > .05).

Conclusions

Fitbit Flex provides accurate measures of steps for daily activity and minutes of reported exercise, regardless of exercise type. Although the proportion of time in different intensity levels varied between devices, examining the mean intensity score for minute-level bouts across different exercise types enabled interdevice comparisons that revealed similar measures of exercise intensity. Fitbit Flex is shown to have measurement limitations that may affect its potential utility and validity for measuring PA attributes in free-living conditions.

Exploration of Sedentary Behavior in Residential Substance Abuse Populations: Results From an Intervention Study

BACKGROUND

There is a growing body of research linking sedentary behavior with increased risk of chronic disease and all-cause mortality. It is increasingly recommended that service providers address the multiple behavioral risk factors associated with these chronic diseases as part of routine substance abuse treatment.

OBJECTIVES

The study objective was to investigate rates of physical activity and sedentary behavior in a residential substance abuse population. In addition, efficacy of a sedentary behavior intervention, "Sit Switch," was examined for feasibility in this context.

METHODS

Participants (n = 54) were residents of The Salvation Army Recovery Service Centres located in Canberra and on the Gold Coast, Australia. Actigraph GT3X+ accelerometers were used to measure rates and patterns of sedentariness and physical activity. A nonrandomized controlled study of a single-session group intervention aimed at decreasing prolonged sitting ("Sit Switch") was conducted. Education, motivational-interviewing, and goal setting components underpinned the "Sit Switch" intervention.

RESULTS

Individuals were highly sedentary, spending 73% of daily activity at sedentary intensity engaged in inadequate levels of moderate physical activity (6.6%/day). The single session educational program did not lead to any significant changes in sedentary behavior. Conclusion/Importance: High levels of sedentariness and low levels of physical activity engagement are evident in residents in substance abuse treatment programs. It is strongly recommended that sedentariness, a modifiable risk behavior with independent consequences for cardiovascular disease and cancer, be addressed within residential programs.

Wearable Sensor/Device (Fitbit One) and SMS Text-Messaging Prompts to Increase Physical Activity in Overweight and Obese Adults: A Randomized Controlled Trial

BACKGROUND

Studies have shown self-monitoring can modify health behaviors, including physical activity (PA). This study tested the utility of a wearable sensor/device (Fitbit(®) One™; Fitbit Inc., San Francisco, CA) and short message service (SMS) text-messaging prompts to increase PA in overweight and obese adults.

MATERIALS AND METHODS

Sixty-seven adults wore a Fitbit One tracker for 6 weeks; half were randomized to also receive three daily SMS-based PA prompts. The Fitbit One consisted of a wearable tracker for instant feedback on performance and a Web site/mobile application (app) for detailed summaries. Outcome measures were objectively measured steps and minutes of PA by intensity using two accelerometers: Actigraph™ (Pensacola, FL) GT3X+ (primary measure) at baseline and Week 6 and Fitbit One (secondary measure) at baseline and Weeks 1, 2, 3, 4, 5, and 6.

RESULTS

Mixed-model repeated-measures analysis of primary measures indicated a significant within-group increase of +4.3 (standard error [SE]=2.0) min/week of moderate- to vigorous-intensity PA (MVPA) at 6-week follow-up (p=0.04) in the comparison group (Fitbit only), but no study group differences across PA levels. Secondary measures indicated the SMS text-messaging effect lasted for only 1 week: the intervention group increased by +1,266 steps (SE=491; p=0.01), +17.8 min/week MVPA (SE=8.5; p=0.04), and +38.3 min/week total PA (SE=15.9; p=0.02) compared with no changes in the comparison group, and these between-group differences were significant for steps (p=0.01), fairly/very active minutes (p<0.01), and total active minutes (p=0.02).

CONCLUSIONS

These data suggest that the Fitbit One achieved a small increase in MVPA at follow-up and that the SMS-based PA prompts were insufficient in increasing PA beyond 1 week. Future studies can test this intervention in those requiring less help and/or test strategies to increase participants' engagement levels.

Study protocol: a stepped wedge cluster randomised controlled trial of a healthy lifestyle intervention for people attending residential substance abuse treatment

BACKGROUND

Cardiovascular disease and cancer are leading causes of mortality for people with a history of alcohol or other substance use disorders. These chronic diseases share the same four primary behavioural risk factors i.e. excessive alcohol use, smoking, low intake of fruit and vegetables and physical inactivity. In addition to addressing problematic alcohol use, there is the potential for substance abuse treatment services to also address these other behaviours. Healthy Recovery is an 8-session group-based intervention that targets these multiple behavioural health risk factors and was developed specifically for people attending substance abuse treatment. This protocol describes a Cancer Institute NSW funded study that assesses the effectiveness of delivering Healthy Recovery for people who are attending residential alcohol and other substance abuse treatment.

METHODS/DESIGN

The study uses a stepped wedge randomised controlled design, where randomisation occurs at the service level. Participants will be recruited from residential rehabilitation programs provided by The Australian Salvation Army. All participants who (1) currently smoke tobacco and (2) are expected to be in the residential program for the duration of the 5-week intervention will be asked to participate in the study. Those participants residing at the facilities assigned to the treatment condition will complete Healthy Recovery. The intervention is manual guided and will be delivered over a 5-week period, with participants attending 8 group sessions. All participants will continue to complete The Salvation Army residential program, a predominantly 12-step based, modified therapeutic community. Participants in the control condition will complete treatment as usual. Research staff blind to treatment allocation will complete the primary and secondary outcome assessments at baseline and then at weeks 8, 20 and 32 weeks post intervention.

DISCUSSION

This study will provide comprehensive data on the effect of delivering a healthy lifestyle intervention (i.e. Healthy Recovery) within a residential substance abuse setting. If shown to be effective, this intervention can be disseminated within other residential substance abuse programs.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trials Register (ANZCTR): ACTRN12615000165583. Registered 19(th) February 2015.

Validity of physical activity monitors for assessing lower intensity activity in adults

Background

Accelerometers can provide accurate estimates of moderate-to-vigorous physical activity (MVPA). However, one of the limitations of these instruments is the inability to capture light activity within an acceptable range of error. The purpose of the present study was to determine the validity of different activity monitors for estimating energy expenditure (EE) of light intensity, semi-structured activities.

Methods

Forty healthy participants wore a SenseWear Pro3 Armband (SWA, v.6.1), the SenseWear Mini, the Actiheart, ActiGraph, and ActivPAL monitors, while being monitored with a portable indirect calorimetry (IC). Participants engaged in a variety of low intensity activities but no formalized scripts or protocols were used during these periods.

Results

The Mini and SWA overestimated total EE on average by 1.0% and 4.0%, respectively, while the AH, the GT3X, and the AP underestimated total EE on average by 7.8%, 25.5%, and 22.2%, respectively. The pattern-recognition monitors yielded non-significant differences in EE estimates during the semi-structured period (p = 0.66, p = 0.27, and p = 0.21 for the Mini, SWA, and AH, respectively).

Conclusions

The SenseWear Mini provided more accurate estimates of EE during light to moderate intensity semi-structured activities compared to other activity monitors. This monitor should be considered when there is interest in tracking low intensity activities in groups of individuals.

Different location of triaxial accelerometer and different energy expenditures

PURPOSE

We performed a study to determine the best appropriate wearing site of a triaxial accelerometer at different exercise speeds.

MATERIALS AND METHODS

We conducted an observational study with 66 healthy Korean adults (26 men and 40 women). Resting metabolic rate (RMR) before exercise, physical activity-related energy expenditure (PAEE) by cardiorespiratory gas analyzer and Signal Vector Magnitude (SVM) were measured while wearing four triaxial accelerometers on four different sites (wrist, waist, upper arm, and ankle) at exercise speeds from 2-10 km/h.

RESULTS

The mean RMR was 4.03 mL/kg/min and Actual METs (oxygen consumption at different exercise speeds divided by individual RMR) compared with the calculated METs (oxygen consumption divided by 3.5 mL/kg/min) showed relatively low value. The overall correlation between PAEE and SVM was highest when the accelerometer was worn on the wrist at low exercise speed (r=0.751, p<0.001), waist at a moderate speed (r=0.821, p<0.001), and ankle at a high speed (r=0.559, p<0.001). Using regression analysis, it was shown that the ankle at a low speed (R²=0.564, p<0.001), high speed (R²=0.559, p<0.001), and the waist at a moderate speed (R²=0.821, p<0.001) were the best appropriate sites.

CONCLUSION

When measuring the PAEE and SVM at different exercise speeds, the ankle in low and high exercise speed, and waist in moderate speed are the most appropriate sites for an accelerometer.

Accelerometer-determined physical activity and its comparison with the International Physical Activity Questionnaire in a sample of Nigerian adults

INTRODUCTION

Accurate assessment of physical activity to identify current levels and changes within the population is dependent on the precision of the measurement tools. The aim of this study was to compare components of physical activity measured with an adapted version of the International Physical Activity Questionnaire (Hausa IPAQ-SF) and the accelerometer in a sample of Nigeria adults.

METHODS

One hundred and forty-four participants (Mean age = 32.6 ± 9.9 years, 40.3% women) in a cross-sectional study wore an accelerometer for seven consecutive days and completed the Hausa IPAQ-SF questionnaire on the eighth day. Total physical activity, time spent in moderate-to-vigorous activity (MVPA) and sedentary time assessed by Hausa IPAQ-SF and accelerometer were compared. The absolute and criterion- related validity of the Hausa IPAQ-SF was assessed by Bland-Altman analysis and Spearman Correlation Coefficients, respectively. Specificity and sensitivity were calculated to classify individuals according to the global standard guideline for sufficient physical activity.

RESULTS

Compared with the accelerometer, higher time in MVPA and total physical activity were reported on the Hausa IPAQ-SF (p<0.001), while low to moderate correlations (Rs = 0.03-0.38) were found between the two methods. The 95% limits of agreement were wide between methods for total physical activity (-23019 to 20375 METmin.d(-1)) and sedentary time (-510 to 150 min.d(-1)). The sensitivity (76.2%) of Hausa IPAQ-SF to identify insufficiently active people was good, but its specificity (33.3%) to correctly classify sufficiently active people was low.

CONCLUSIONS

The Hausa IPAQ-SF overestimated components of physical activity among Nigerian adults, and demonstrated poor to moderate evidence of absolute and criterion validity. Further evaluation of IPAQ and other self-report physical activity instruments in other Africa populations could enhance accurate evaluation of physical activity data in the region countries.

Physical activity limitation as measured by accelerometry in pulmonary arterial hypertension

BACKGROUND

The 6-min walk test, commonly used to assess exercise capacity and response to therapy in pulmonary arterial hypertension (PAH), has many well-described limitations. Sedentary time is associated with adverse cardiovascular outcomes and reduced quality of life, and measuring sedentary time and physical activity using accelerometry is another potential way to quantify exercise capacity in PAH. Whether sedentary time is different in patients with PAH vs control subjects is unknown.

METHODS

Physical activity was measured in 20 patients with PAH and 30 matched healthy control subjects using accelerometry for 7 consecutive days. Patients with PAH completed standard 6-min walk testing, and baseline demographics were recorded for all study participants. Total daily activity counts, sedentary time, and proportion of time at various activity levels were compared between groups.

RESULTS

Sedentary time was significantly higher in patients with PAH (mean, 92.1% daily activity; 95% CI, 89.5-94.8%) than in control subjects (mean, 79.9% daily activity; 95% CI, 76.4%-83.5%; P < .001), and all levels of physical activity were reduced in the PAH group compared with the control group ( P < .01 for all). Daily moderate to vigorous physical activity was reduced in the PAH group (7.5 min; 95% CI; 0.8-15.6 min) compared with the control group (mean, 64.7 min; 95% CI, 51.1-78.2 min; P < .001). Activity counts correlated with 6-min walk distance in the PAH group (Spearman rank correlation 5 0.72, P < .001).

CONCLUSIONS

Sedentary time is increased in patients with PAH and may lead to increased risk for metabolic and cardiovascular morbidity. Quantitation of daily activity and sedentary time using accelerometry may be a novel end point for PAH management and clinical trials.

A short-term physical activity randomized trial in the Lower Mississippi Delta

Background

The purpose of this study was to determine if a short-term pedometer-based intervention results in immediate increases in time spent in moderate-to-vigorous physical activity (MVPA) compared to a minimal educational intervention.

Methods

A sample of 43 overweight adults 35 to 64 years of age participated in a one week pedometer-based feasibility trial monitored by accelerometry. Participants were randomized into a one-week education-only group or a group that also wore a pedometer. Accelerometer-measured MVPA was measured over 7 days at baseline and again for 7 days immediately post-intervention.

Results

Minutes of MVPA increased significantly in the overall sample (p = 0.02); however, the effect of adding the pedometer to the education program was not significant (p = 0.89). Mean (±SE) MVPA increased from 12.7±2.4 min/day to 16.2±3.6 min/day in the education-only group and from 13.2±3.3 min/day to 16.3±3.9 min/day in the education+pedometer group. The correlation between change in steps/day and change in MVPA was 0.69 (p<0.0001).

Conclusions

The results of this study suggest that the addition of a pedometer to a short-term education program does not produce added benefits with respect to increasing physical activity in the Lower Mississippi Delta.

Trial Registration

ClinicalTrials.gov NCT01264757

Instrument selection for randomized controlled trials: why this and not that?

A fundamental linchpin for obtaining rigorous findings in quantitative research involves the selection of survey instruments. Psychometric recommendations are available for the processes for scale development and testing and guidance for selection of established scales. These processes are necessary to address the validity link between the phenomena under investigation, the empirical measures and, ultimately, the theoretical ties between these and the world views of the participants. Detailed information is most often provided about study design and protocols, but far less frequently is a detailed theoretical explanation provided for why specific instruments are chosen. Guidance to inform choices is often difficult to find when scales are needed for specific cultural, ethnic, or racial groups. This paper details the rationale underlying instrument selection for measurement of the major processes (intervention, mediator and moderator variables, outcome variables) in an ongoing study of postpartum Latinas, Madres para la Salud [Mothers for Health]. The rationale underpinning our choices includes a discussion of alternatives, when appropriate. These exemplars may provide direction for other intervention researchers who are working with specific cultural, racial, or ethnic groups or for other investigators who are seeking to select the 'best' instrument. Thoughtful consideration of measurement and articulation of the rationale underlying our choices facilitates the maintenance of rigor within the study design and improves our ability to assess study outcomes.