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Olivia R. Barber, Christopher Thomas, Paul A. Jones, John J. McMahon and Paul Comfort

Purpose:

To determine the reliability of the 505 change-of-direction (COD) test performed with both a stationary and a flying start.

Methods:

Fifty-two female netball players (age 23.9 ± 5.4 y, height 169.9 ± 3.3 cm, body mass 65.2 ± 4.6 kg) performed 6 trials of the 505 COD test, 3 with a flying start and 3 with a stationary start, once per week over a 4-wk period to determine within- and between-sessions reliability.

Results:

Testing revealed high within-session reliability for the stationary start (ICC = .96–.97) and for the flying start (ICC = .90–.97). Similarly, both the stationary start (ICC = .965) and the flying start (ICC = .951) demonstrated high reliability between sessions, although repeated-measures analysis of variance (P < .001) revealed learning effects between sessions for both tests. Performances stabilized on day 2 for the static start and on day 3 for the flying start.

Conclusions:

The 505 COD test is a reliable test in female netball players, with either a stationary or flying start. Smallest detectable differences of 3.91% and 3.97% for the stationary start and the flying start, respectively, allow practitioners to interpret whether changes in time taken to complete the 505 COD test reflect genuine improvements in performance or are measurement errors. It is suggested that 1 d of familiarization testing be performed for the stationary start and 2 d of familiarization for the flying start, to minimize learning effects.

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David W. Brock, Olivia Thomas, Charles D. Cowan, David B. Allison, Glenn A. Gaesser and Gary R. Hunter

Background:

Numerous public health organizations have adopted national physical activity recommendations. Despite these recommendations, over half of the US population does not meet the minimum recommendation for physical activity, with large variations across individual US states.

Methods:

Using the 2005 Behavioral Risk Factor Surveillance System (BRFSS) prevalence data for physical activity and obesity by state, we performed a weighted least squares regression using prevalence of obesity (BMI ≥ 30 kg/m2) as the dependent variable and insufficiently physically active (included completely sedentary), age, race, gender, and median household income as the independent variables.

Results:

The unadjusted weighted least squares regression revealed a strong correlation between a state’s prevalence of obesity and the prevalence of insufficiently physically active (R = .76, R 2 = .58, P < .0001). After adjusting for age, gender, race, and median household income, the prevalence of insufficiently physically active is still a significant predictor of the state prevalence of obesity (partial R = .44, R 2 = .19 P = .004).

Conclusion:

Macroenvironmental and sociopolitical disparities between individual US states that transcend simple state-level demographic factors need to be examined more rigorously to identify unique barriers and promoters of physical activity.