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John R. Sirard and Megan E. Slater

Background:

Accelerometer use in physical activity research has become increasingly popular but is prone to problems with missing data, which complicate the data reduction and analysis process. The purpose of this study was to determine the effect of hypothesized compliance strategies on improving compliance with wearing a physical activity accelerometer in high school students.

Methods:

Each of four local high schools was assigned to one of four compliance strategies: (1) receiving three phone calls, (2) completing a daily journal, (3) compensation contingent on number of complete (≥ 10 hours) days of data, and (4) control condition. Participants wore ActiGraph accelerometers for seven days to determine compliance and physical activity.

Results:

The contingent group had the highest level of compliance with 96% of the participants acquiring at least four of seven complete days of data. After controlling for grade level, school level percent minority students, and school level socioeconomic status (SES), the contingent group’s compliance remained significantly higher (P = .04) than the journal (85%), phone (72%), and control (70%) participants.

Conclusions:

The contingent compliance strategy improved the amount of time the students wore the monitor each day and, thus, the total number of days with ≥ 10 hours of data.

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Cory J. Greever, John Sirard and Sofiya Alhassan

Background:

The purpose of this study was to examine the temporal patterns of preschoolers’ physical activity (PA) levels during a typical outdoor free playtime.

Methods:

Baseline playtime accelerometer counts (4.3 ± 0.8 days) from 3 preschool PA intervention studies were used (n = 326 children, age = 4.0 ± 0.8 years). Data were collected using 15-second epochs and classified into sedentary, light, or moderate-tovigorous physical activity (MVPA). Patterns of change during playtime were analyzed using orthogonal polynomial comparisons.

Results:

For all ages, there was a U-shaped pattern of change for the percent of epochs classified as sedentary [F(1, 323) = 47.12, P < .001) and an inverted U-shaped pattern of change for the percent of epochs classified as MVPA [F(1,323) = 32.15, P < .001]. Age-stratified analyses indicated that the 3-year-olds maintained the decrease in sedentary time [F(2,323) = 6.408, P = .002] and the increase in MVPA [F(2,323) = 3.2, P = .04] to a greater extent than the 4- and 5-year-olds.

Conclusions:

Preschool children gradually became more active during the first 10 to 15 minutes of outdoor gross motor playtime and less active over the final 10 to 15 minutes of playtime. During the second half of playtime 3-year-olds maintained these changes to a greater degree than 4- and 5-year-olds.

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Christine W. St. Laurent, Brittany Masteller and John Sirard

Purpose: The purpose of this pilot study was to assess the efficacy of a suspension-training movement program to improve muscular- and skill-related fitness and functional movement in children, compared with controls. Methods: In total, 28 children [male: 46%; age: 9.3 (1.5) y; body mass index percentile: 68.6 (27.5)] were randomly assigned to intervention (n = 17) or control (n = 11) groups. The intervention group participated in a 6-week suspension-training movement program for two 1-hour sessions per week. Muscular- and skill-related fitness and functional movement assessments were measured at baseline and following the intervention. Analyses of covariance models were used to assess the effects of time and intervention. Results: The intervention participants achieved greater improvements in Modified Pull-Up performance (P = .01, Cohen’s d = 0.54) and Functional Movement Screen score (P < .001, Cohen’s d = 1.89), relative to controls. Conclusion: The suspension-training intervention delivered twice a week was beneficial for upper body pulling muscular endurance and the Functional Movement Screen score. Future interventions using this modality in youth would benefit from larger, more diverse samples (through schools or community fitness centers) and a longer intervention length.

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Greg Petrucci Jr., Patty Freedson, Brittany Masteller, Melanna Cox, John Staudenmayer and John Sirard

Purpose: Determine the sensitivity of the Misfit Shine™ (MS) to detect changes in physical activity (PA) measures (steps, “points,” kCals) in laboratory (LAB) and free-living (FL) conditions. Methods: Twenty-one participants wore the MS and ActiGraph GT3X+™ accelerometer (AG) at the hip and dominant-wrist during three, one-hour LAB sessions: sedentary (SS), sedentary plus walking (SW), and sedentary plus jogging (SJ). Direct observation (DO) of steps served as the criterion measure. Devices were also worn during two FL conditions: 1) active week (ACT) and 2) inactive week (INACT). For LAB and FL, significant differences were examined using paired t-tests and linear mixed effects models, respectively. Linear mixed effects models were used to estimate differences between MS estimated steps and DO (α ≤ 0.05). Results: For all hip-worn MS measures and wrist-worn MS estimates of steps and “points,” there was a significant increase (p < .05) from SS to SJ. However, wrist-worn MS kCal estimates were greater for SJ, compared to SS and SW, which were similar to each other (95% CI [95.5, 152.8] and [141.1, 378.9], respectively). Compared with DO, MS hip significantly underestimated steps by 3.5%, while MS wrist significantly overestimated steps by 4.2%. During FL conditions, all MS measures were sensitive to changes between ACT and INACT (p < .0001). Conclusion: Although there were systematic errors in step estimates from the MS, it was sensitive to changes during LAB and FL, and may be a useful tool for interventionists where tracking changes in PA is an important exposure or outcome variable.

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Albert R. Mendoza, Kate Lyden, John Sirard, John Staudenmayer, Catrine Tudor-Locke and Patty S. Freedson

We evaluated the accuracy and precision of wearable activity trackers and a pedometer (ATPs) in estimating steps and sedentary time (ST) in free-living settings. Thirty-two healthy men and women (M ± SD: age = 32.3 ± 13.3 years; BMI = 24.4 ± 3.3 kg·m−2) were directly observed during three, 2-hour sessions on different days while wearing 10 devices and a biometric shirt. A validated direct observation (DO) system provided criterion measures for steps and ST. For steps, bias ranged from −753 steps/2-hrs (Fitbit Flex) to −57 steps/2-hrs (Polar Loop) and CIs ranged from [−1,144, −365] (Fitbit Flex) to [−291,175] (Polar Loop) steps/2-hrs. For all devices, step estimates were strongly correlated (r = 0.90 [Fitbit Flex] to r = 0.97 [New Lifestyles pedometer model 1000]) with DO counted steps. Estimates of ST were not accurate and were weakly correlated (r = −0.06 and r = 0.06 for Fitbit Flex and Fitbit One, respectively) with DO ST. Most ATPs were not accurate and varied in precision in estimating steps and ST in free-living settings. Implications from this study are that although point estimates of steps from ATPs are not accurate, ATPs’ ranking of step counts among individuals was high. However, the Fitbit Flex and Fitbit One are not recommended for estimating ST. This study advances our understanding of the performance of ATPs in estimating steps and ST in free-living settings, and significantly advances activity tracker and pedometer validation studies.

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Russell R. Pate, Rebecca Ross, Marsha Dowda, Stewart G. Trost and John R. Sirard

The purpose of this study was to examine the validity of the 3-Day Physical Activity Recall (3DPAR) self-report instrument in a sample of eighth and ninth grade girls (n = 70, 54.3% white, 37.1% African American). Criterion measures of physical activity were derived using the CSA 7164 accelerometer. Participants wore a CSA monitor for 7 consecutive days and completed the self-report physical activity recall for the last 3 of those days. Self-reported total METs, 30-min blocks of MVPA, and 30-min blocks of VPA were all significantly correlated with analogous CSA variables for 7 days (r = 0.35–0.51; P < 0.01) and 3 days (r = 0.27–0.46; P < 0.05) of monitoring. The results indicate that the 3DPAR is a valid instrument for assessing overall, vigorous, and moderate to vigorous physical activity in adolescent girls.

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John R. Sirard, Stewart G. Trost, Karin A. Pfeiffer, Marsha Dowda and Russell R. Pate

Background:

The purposes of this study were 1) to establish accelerometer count cutoffs to categorize activity intensity of 3 to 5-y old-children and 2) to evaluate the accelerometer as a measure of children’s physical activity in preschool settings.

Methods:

While wearing an ActiGraph accelerometer, 16 preschool children performed five, 3-min structured activities. Receiver Operating Characteristic (ROC) curve analyses identified count cutoffs for four physical activity intensities. In 9 preschools, 281 children wore an ActiGraph during observations performed by three trained observers (interobserver reliability = 0.91 to 0.98).

Results:

Separate count cutoffs for 3, 4, and 5-y olds were established. Sensitivity and specificity for the count cutoffs ranged from 86.7% to 100.0% and 66.7% to 100.0%, respectively. ActiGraph counts/15 s were different among all activities (P < 0.05) except the two sitting activities. Correlations between observed and ActiGraph intensity categorizations at the preschools ranged from 0.46 to 0.70 (P < 0.001).

Conclusions:

The ActiGraph count cutoffs established and validated in this study can be used to objectively categorize the time that preschool-age children spend in different physical activity intensity levels.

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John R. Sirard, Ann Forsyth, J. Michael Oakes and Kathryn H. Schmitz

Background:

The purpose of this study was to determine 1) the test-retest reliability of adult accelerometer-measured physical activity, and 2) how data processing decisions affect physical activity levels and test-retest reliability.

Methods:

143 people wore the ActiGraph accelerometer for 2 7-day periods, 1 to 4 weeks apart. Five algorithms, varying nonwear criteria (20 vs. 60 min of 0 counts) and minimum wear requirements (6 vs. 10 hrs/day for ≥ 4 days) and a separate algorithm requiring ≥ 3 counts per min and ≥ 2 hours per day, were used to process the accelerometer data.

Results:

Processing the accelerometer data with different algorithms resulted in different levels of counts per day, sedentary, and moderate-to-vigorous physical activity. Reliability correlations were very good to excellent (ICC = 0.70−0.90) for almost all algorithms and there were no significant differences between physical activity measures at Time 1 and Time 2.

Conclusions:

This paper presents the first assessment of test-retest reliability of the Actigraph over separate administrations in free-living subjects. The ActiGraph was highly reliable in measuring activity over a 7-day period in natural settings but data were sensitive to the algorithms used to process them.

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Jeanette M. Garcia, Alen Agaronov, John R. Sirard, Diane Whaley, David J. Rice and Arthur Weltman

Background:

Sedentary behavior (SB) increases throughout adolescence, and is associated with adverse health outcomes.

Purpose:

Examine psychosocial and friend influences on SB and screen time in adolescents using a mixed-methods design.

Methods:

108 middle and high school students wore accelerometers to measure objective SB, completed screen time and psychosocial questionnaires, and nominated friends to complete activity questionnaires. Focus groups centered around influences on SB behavior. Regression analyses and NVivo software analyzed quantitative and qualitative data.

Results:

Screen time was associated with greater screen time enjoyment, lower self-efficacy, and friends’ screen time (r 2 = .21, P < .0001). Friends influenced whether adolescents engaged in screen time behaviors, with active friends encouraging less screen time.

Conclusion:

Active friends influenced adolescents to engage in less SB. Interventions should place an emphasis on encouraging less screen time, and providing opportunities for adolescents and their friends to engage in activities that promote physical activity rather than SB.

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Jeanette M. Garcia, John R. Sirard, Ross Larsen, Meg Bruening, Melanie Wall and Dianne Neumark-Sztainer

Objective:

The purpose of this study was to examine, using structural equation modeling, the associations between nominated friend physical activity (PA), friend social support with individual PA-related psychological factors, and adolescent PA.

Methods:

Data were obtained from EAT 2010 (Eating and Activity Among Teens), a large cross-sectional study conducted in 20 middle and high schools. The sample consisted of 1951 adolescents (mean age: 14.25 ± 1.96, 54% female, 68% ethnic minorities). PA, parent and friend social support (perceived social support for PA from parents and friends), and psychological measures (PA enjoyment, PA self-efficacy, and PA barriers) were assessed by self-report questionnaires. The SEM analysis consisted of 1 observed variable: friend PA, and 2 latent constructs: psychological factors, perceived social support.

Results:

The model was a good fit, indicating that there were significant direct effects of both friend PA (P < .01) and psychological factors (P < .0001) on adolescent PA. In addition, psychological factors mediated the association between friend PA and adolescent PA.

Conclusion:

The results of this model suggest that psychological factors and friend PA are associated with adolescent PA, and that psychological factors may play an important role. Future studies should further examine the association of both friend PA and psychological variables with adolescent PA.