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Emma L. J. Eyre, Jason Tallis, Susie Wilson, Lee Wilde, Liam Akhurst, Rildo Wanderleys and Michael J. Duncan

. For these reasons, recent focus has been placed on the validity of estimating activity intensities in children ( Chinapaw et al., 2010 ; De Vries et al., 2009 ; Lubans et al., 2011 ), older adults ( Garatachea et al., 2010 ), and, to a lesser extent, young adults ( Watson et al., 2014 ). Young

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Dawn P. Gill, Gareth R. Jones, GuangYong Zou and Mark Speechley

The purpose of this study was to develop a brief physical activity interview for older adults (Phone-FITT) and evaluate its test–retest reliability and validity. Summary scores were derived for household, recreational, and total PA. Reliability was evaluated in a convenience sample from a fall-prevention study (N = 43, 79.4 ± 2.9 years, 51% male), and validity, in a random sample of individuals in older adult exercise programs (N = 48, 77.4 ± 4.7 years, 25% male). Mean time to complete the Phone-FITT was 10 min for participants sampled from exercise programs. Evaluation of test–retest reliability indicated substantial to almost perfect agreement for all scores, with intraclass correlation coefficients (95% confidence intervals) ranging from .74 (.58–.85) to .88 (.8–.94). For validity, Spearman’s rho correlations of Phone-FITT scores with accelerometer counts ranged from .29 (.01–.53) to .57 (.34–.73). Correlations of Phone-FITT recreational scores with age and seconds to complete a self-paced step test ranged from –.29 (–.53 to –.01) to –.45 (–.68 to –.14). This study contributes preliminary evidence of the reliability and validity of the Phone-FITT.

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Fotini Venetsanou, Irene Kossyva, Nadia Valentini, Anastasia-Evangelia Afthentopoulou and Lisa Barnett

Motor Development 2nd version (TGMD-2; Ulrich, 2000 ). The strength of the PMSC, compared to previous instruments, is that it provides comprehensive information about the movement skills needed for children’s participation in sports and/or physical activity ( Barnett et al., 2015b ). The validity and

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Kate Giles and Alison L. Marshall

Background:

One- to two-week test–retest reliability and construct validity (against pedometer step counts) of the CHAMPS physical activity questionnaire were evaluated in older Australian adults.

Methods:

Participants (n = 100, age >65 years) were invited to complete CHAMPS by mail. Spearman correlation coefficients are reported for physical activity constructs time (min/wk) and sessions per week for walking, moderate-, and vigorous-intensity activity and total physical activity. Correct classification of participants as meeting physical activity recommendations was assessed using percent agreement and kappa statistics.

Results:

Seventy-three participants completed CHAMPS at T1; 54 provided repeat data (T2). Sixty percent of the participants provided complete data. Good to excellent test– retest reliability was observed for all the physical activity constructs (r s = .70 to .89 for sessions/wk and r s = .65 to .75 for min/wk). Agreement between proportions classified as meeting recommendations at T1 and T2 was good (79%; kappa = 0.55). Fair to low validity coefficients were observed between steps and T1 CHAMPS walking and total activity sessions/wk (r s = .57 and r s = .52), and min/wk (r s = .40 and r s = .21).

Conclusions:

Mailed self-complete CHAMPS data provided reliable and valid estimates of physical activity in older Australian adults. Observed measurement coefficients were comparable to those reported in previous evaluations of CHAMPS. Further work is required to identify strategies to prevent data loss.

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Roel De Ridder, Julien Lebleu, Tine Willems, Cedric De Blaiser, Christine Detrembleur and Philip Roosen

needed to obtain the gait parameters. This aspect is really important to facilitate technology adoption. 7 However, before using them for clinical interpretation, we need to define their reliability and validity. The latter can be done by comparing the spatiotemporal parameters of gait obtained from the

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James W. Navalta, Jeffrey Montes, Nathaniel G. Bodell, Charli D. Aguilar, Ana Lujan, Gabriela Guzman, Brandi K. Kam, Jacob W. Manning and Mark DeBeliso

Groot, 2017 ; Nelson, Kaminsky, Dickin, & Montoye, 2016 ), or during flat ground walking and/or stair climbing ( An, Jones, Kang, Welk, & Lee, 2017 ; Huang, Xu, Yu, & Shull, 2016 ). These settings represent conditions that are relatively controlled. While some devices return more valid step measures

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Adam Šimůnek, Jan Dygrýn, Lukáš Jakubec, Filip Neuls, Karel Frömel and Gregory John Welk

has evaluated total energy expenditure ( 2 , 7 , 28 ), time spent in different zones of PA intensity, and step counts per day per week ( 1 , 2 , 3 , 21 ), as well as in specific isolated activities ( 3 , 9 , 14 , 28 , 32 ). In general, studies have supported the validity of the step count estimates in

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MeLisa Creamer, Heather R. Bowles, Belinda von Hofe, Kelley Pettee Gabriel, Harold W. Kohl III and Adrian Bauman

Background:

Computer-assisted techniques may be a useful way to enhance physical activity surveillance and increase accuracy of reported behaviors.

Purpose:

Evaluate the reliability and validity of a physical activity (PA) self-report instrument administered by telephone and internet.

Methods:

The telephone-administered Active Australia Survey was adapted into 2 forms for internet self-administration: survey questions only (internet-text) and with videos demonstrating intensity (internet-video). Data were collected from 158 adults (20–69 years, 61% female) assigned to telephone (telephone-interview) (n = 56), internet-text (n = 51), or internet-video (n = 51). Participants wore an accelerometer and completed a logbook for 7 days. Test-retest reliability was assessed using intraclass correlation coefficients (ICC). Convergent validity was assessed using Spearman correlations.

Results:

Strong test-retest reliability was observed for PA variables in the internet-text (ICC = 0.69 to 0.88), internet-video (ICC = 0.66 to 0.79), and telephone-interview (ICC = 0.69 to 0.92) groups (P-values < 0.001). For total PA, correlations (ρ) between the survey and Actigraph+logbook were ρ = 0.47 for the internet-text group, ρ = 0.57 for the internet-video group, and ρ = 0.65 for the telephone-interview group. For vigorous-intensity activity, the correlations between the survey and Actigraph+logbook were 0.52 for internet-text, 0.57 for internet-video, and 0.65 for telephone-interview (P < .05).

Conclusions:

Internet-video of the survey had similar test-retest reliability and convergent validity when compared with the telephone-interview, and should continue to be developed.

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Kerri L. Vasold, Andrew C. Parks, Deanna M.L. Phelan, Matthew B. Pontifex and James M. Pivarnik

displacement plethysmography has shown high reliability and validity for evaluating body composition in many populations, and it has been used frequently as a criterion measure for field techniques in the past two decades, as other methods such as hydrodensitometry and dual-energy X-ray absorptiometry are not

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Leanne Liggett, Andrew Gray, Winsome Parnell, Rob McGee and Yvette McKenzie

Background:

Objective measures, such as accelerometers, are increasingly being used to measure physical activity (PA) levels in children, and the use of validated and reliable instruments is desirable when measuring the effectiveness of programs. The purpose of this study was to determine the validity and reliability of the New Lifestyles NL-1000 accelerometer among preschoolers using a modified version of the Children’s Activity Rating Scale (CARS).

Methods:

Fourteen preschoolers wore the NL-1000 at their waist while the device measured activity levels [in seconds of moderate-to-vigorous physical activity (MVPA)]. They were also videoed for approximately 12 minutes while participating in normal activities at an early childhood center. At approximately 2-minute intervals, activity level readings derived from the NL-1000 were recorded. The video footage was analyzed using a modified CARS technique and the CARS scores compared with data obtained from the accelerometer.

Results:

Within subject reliability was measured using intraclass correlation coefficients (0.58 for CARS and 0.59 for NL-1000). Furthermore, 95% of the variation in CARS could be explained by variation in the accelerometer counts, with 2.4% of the variation being participant-specific.

Conclusion:

The NL-1000 is a sufficiently reliable and valid tool for assessing MVPA in preschoolers.