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Leilani A. Madrigal, Vincenzo Roma, Todd Caze, Arthur Maerlender and Debra Hope

exploratory factor analysis was necessary to explore the emergence of sports-related anxiety factors. Next, using a split-sample procedure, a confirmatory factor analysis was used to validate the factor structure from exploratory factor analysis to determine how well the model fit the data. In further

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Euna Han, Lisa Powell, Sandy Slater and Christopher Quinn

Background:

Secondary data are often necessary to assess the availability of commercial physical activity (PA) facilities and examine its association with individual behaviors and outcomes, yet the validity of such sources has been explored only in a limited number of studies.

Methods:

Field data were collected on the presence and attributes of commercial PA facilities in a random sample of 30 urban, 15 suburban, and 15 rural Census tracts in the Chicago metropolitan statistical area and surrounding area.

Results:

Approximately 40% of PA establishments in the field data were listed for both urban and nonurban tracts in both lists except for nonurban tracts in D&B (35%), which was significantly improved in the combined list of D&B and InfoUSA. Approximately one-quarter of the PA facilities listed in D&B were found on the ground, whereas 40% to 50% of PA facilities listed in InfoUSA were found on the ground. PA establishments that offered instruction programs or lessons or that had a court or pool were less likely to be listed, particularly in the nonurban tracts.

Conclusions:

Secondary commercial business lists on PA facilities should be used with caution in assessing the built environment.

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Weimo Zhu and Miyoung Lee

Background:

The purpose of this study was to investigate the validity and reliability evidences of the Omron BI pedometer, which could count steps taken even when worn at different locations on the body.

Methods:

Forty (20 males and 20 females) adults were recruited to walk wearing 5 sets, 1 set at a time, of 10 BI pedometers during testing, 1 each at 10 different locations. For comparison, they also wore 2 Yamax Digi-Walker SW-200 pedometers and a Dynastream AMP 331 activity monitor. The subjects walked in 3 free-living conditions: a fat sidewalk, stairs, and mixed conditions.

Results:

Except for a slight decrease in accuracy in the pant pocket locations, Omron BI pedometers counted steps accurately across other locations when subjects walked on the fat sidewalk, and the performance was consistent across devices and trials. When the subjects climbed up stairs, however, the absolute error % of the pant pocket locations increased significantly (P < .05) and similar or higher error rates were found in the AMP 331 and SW-200s.

Conclusions:

The Omron BI pedometer can accurately count steps when worn at various locations on the body in free-living conditions except for front pant pocket locations, especially when climbing stairs.

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Bing Han, Deborah A. Cohen, Kathryn Pitkin Derose, Terence Marsh, Stephanie Williamson and Laura Raaen

Purpose:

This study aims to examine the reliability of a 12-button counter to simultaneously assess physical activity (PA) by age and gender subgroups in park settings.

Methods:

A total of 1,160 pairs of observations were conducted in 481 target areas of 19 neighborhood parks in the great Los Angeles, California, area between June 2013 and March 2014. Interrater reliability was assessed by Pearson’s correlation, intra-class correlation (ICC), and agreement probability in metabolic equivalents (METs). Cosine similarity was used to check the resemblance of distributions among age and gender categories. Pictures taken in a total of 112 target areas at the beginning of the observations were used as a second reliability check.

Results:

Interrater reliability was high for the total METs and METs in all age and gender categories (between 0.82 and 0.97), except for male seniors (correlations and ICC between 0.64 and 0.77, agreement probability 0.85 to 0.86). Reliability was higher for total METs than for METs spent in moderate-to-vigorous PA. Correlation and ICC between observers’ measurement and picture-based counts are also high (between 0.79 and 0.94).

Conclusion:

Trained observers can reliably use the 12-button counter to accurately assess PA distribution and disparities by age and gender.

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Rosemary A. Arthur, Nichola Callow, Ross Roberts and Freya Glendinning

framework and then validating two coaching of PS questionnaires. The third phase of the program was a quasi-experimental controlled trial to evaluate the effectiveness of the adjusted intervention informed by the pilot intervention and evaluated using the validated questionnaires. The pilot intervention and

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Berit Steenbock, Marvin N. Wright, Norman Wirsik and Mirko Brandes

relationships between accelerometer output and EE differ in preschoolers compared with older children, prediction equations require development and validation in this specific age group ( Butte et al., 2014 ). Considerable progress has been made in predicting EE for adults and older children ( Jimmy, Seiler

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Eleanor Quested, Nikos Ntoumanis, Andreas Stenling, Cecilie Thogersen-Ntoumani and Jennie E. Hancox

.1080/17509840903235330 Bartholomew , K. , Ntoumanis , N. , & Thøgersen-Ntoumani , C. ( 2010 ). The controlling interpersonal style in a coaching context: Development and initial validation of a psychometric scale . Journal of Sport & Exercise Psychology, 32 ( 2 ), 193 – 216 . PubMed ID: 20479478 doi:10.1123/jsep.32

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Matthew Pearce, Tom R.P. Bishop, Stephen Sharp, Kate Westgate, Michelle Venables, Nicholas J. Wareham and Søren Brage

bias if the studies that are included with optimal data have specific characteristics. Another approach to harmonization is to use validation studies which report the statistical (e.g., regression) models of relationships between values from the less precise methods and the latent true level of

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J. Jimenez-Pardo, J.D. Holmes, M.E. Jenkins and A.M. Johnson

Physical activity is generally thought to be beneficial to individuals with Parkinson’s disease (PD). There is, however, limited information regarding current rates of physical activity among individuals with PD, possibly due to a lack of well-validated measurement tools. In the current study we sampled 63 individuals (31 women) living with PD between the ages of 52 and 87 (M = 70.97 years, SD = 7.53), and evaluated the amount of physical activity in which they engaged over a 7-day period using a modified form of the Physical Activity Scale for Individuals with Physical Disabilities (PASIPD). The PASIPD was demonstrated to be a reliable measure within this population, with three theoretically defensible factors: (1) housework and home-based outdoor activities; (2) recreational and fitness activities; and (3) occupational activities. These results suggest that the PASIPD may be useful for monitoring physical activity involvement among individuals with PD, particularly within large-scale questionnaire-based studies.

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Michelle Renee Umstattd, Rob Motl, Sara Wilcox, Ruth Saunders and Melissa Watford

Background:

Theoretically, self-regulatory strategies (eg, goal setting, self-monitoring) are an important influence of behavior change, but very little research has examined the relationship between self-regulation and physical activity (PA) behavior. Petosa’s (1993) 43-item PA self-regulation scale (PASR-43) affords the opportunity for studying this construct in the context of PA; however the PASR-43 has not been tested for structural aspects of validity. Therefore, this study examines the structural validity of the PASR-43 in older adults.

Methods:

The structural validity of the PASR-43 was tested in a large sample of older adults from North and South Carolina and Ohio (N = 460) using maximum likelihood estimation and confirmatory factor analysis in AMOS 5.0.

Results:

The original 6-factor model for the PASR-43 scale did not represent an acceptable fit to the data (x2 = 4732.25, df = 845, P < .0001, RMSEA = 0.10, NNFI = 0.67, CFI = 0.71). Based on a post hoc specification search, iterative model modifications resulted in a 12-item PA self-regulation scale (PASR-12) that represented an excellent fit to the data (x2 = 70.75, df = 39, P = .001, RMSEA = 0.04, NNFI = 0.98, CFI = 0.99).

Conclusions:

The PASR-12 provides a concise and valid measure of PA self-regulation for use with older adults. Future studies should cross-validate the PASR-12 and examine invariance across time and between age, ethnic, gender, and geographical groups.