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Daniel M. Landers, Michael O. Wilkinson, Brad D. Hatfield and Heather Barber

The causal predominance of performance affecting later cohesiveness that has been shown in previous studies was examined by means of a series of statistical analyses designed to assess influence in a longitudinal panel design. Male students (N = 44) participating in a basketball league were administered cohesiveness and participation motivation scales at early, mid, and late season. In contrast to previous findings, the cross-lagged correlations showed that performance and cohesion were significantly related to each other with no causal predominance of one over the other. With the exception of the friendship measure, the cross-lagged correlations were no longer significant when earlier measures of the effect variable were controlled through partial correlation and path analysis techniques. In contrast to previous research, midseason cohesion, as measured by friendship, was a significant (p < .04) predictor of late season performance. The importance of interpersonal attraction in the recruitment and maintenance of intramural team members is discussed along with the necessity for determining, in future studies, the reliability of cohesiveness measures.

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Minna Aittasalo, Matti Pasanen, Mikael Fogelholm and Katriina Ojala

Purpose:

To examine the validity and repeatability of a short leisure time physical activity (LTPA) questionnaire during pregnancy.

Methods:

Seventy-nine women with uncomplicated pregnancies and weeks’ gestation ≤ 33 participated. After the first questionnaire (LTPAQ1) they entered 7-day LTPA and pedometer counts in a logbook and completed the second LTPA questionnaire (LTPAQ2). Validity was assessed with Spearman’s rank correlation coefficients by comparing LTPAQ2 with pedometer counts and logbook. For describing repeatability, change in the mean, geometric mean ratio, typical error, coefficient of variation (CV, %) and Bland-Altman plots were used.

Results:

Forty-five (57%) and 47 (59%) women were available for pedometer and logbook comparisons and 49 (62%) for repeatability assessment. LTPAQ2 showed no correlation with pedometer but moderate correlation with the logbook for the frequency of moderate to vigorous-intensity LTPA (rs = 0.68, 95% CI 0.48 to 0.81). In repeatability, the typical error for frequency estimates varied from 1.2 to 3.7 sessions and CV for duration from 119 to 369%. The corresponding values for systematic error were -1.0 to 0.3 sessions and 4 to 36%. The 95% limits of agreement for single variables were large.

Conclusions:

The questionnaire was valid for assessing moderate to vigorous-intensity LTPA but its individual repeatability proved weak.

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Dahn Shaulis, Lawrence A. Golding and Richard D. Tandy

This study assessed the relative and absolute reliability of the five tests in the AAHPERD functional fitness assessment for men and women over 60 years of age. Twenty-eight apparently healthy subjects, ages 60 to 81, were tested three times during a 2-week period on each item in the test battery: sit and reach flexibility, body agility, coordination, strength/endurance, and half-mile walk. Relative reliability was assessed for both sexes via intraclass correlation coefficient. Absolute reliability was evaluated using repeated measures ANOVA. Intraclass correlations among sessions for men and women, respectively, were 0.97 and 0.98 for flexibility, 0.98 and 0.96 for body agility, 0.89 and 0.71 for coordination, 0.94 and 0.81 for strength/endurance, and 0.99 and 0.96 for the walk. Repeated measures ANOVAs with Tukey’s post hoc tests revealed improved performance from repeated practice sessions in all tests, although the improvement was not consistent between tests. Although the tests have high intraclass correlations, researchers using the test battery should include a random control group to assess the effects of training.

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Timothy K. Behrens and Mary K. Dinger

Background:

The purpose of this study was to compare steps·d-1 between an accelerometer and pedometer in 2 free-living samples.

Methods:

Data from 2 separate studies were used for this secondary analysis (Sample 1: N = 99, Male: n = 28, 20.9 ± 1.4 yrs, BMI = 27.2 ± 5.0 kg·m-2, Female: n = 71, 20.9 ± 1.7 yrs, BMI = 22.7 ± 3.0 kg·m-2; Sample 2: N = 74, Male: n = 27, 38.0 ± 9.5 yrs, BMI = 25.7 ± 4.5 kg·m-2, Female: n = 47, 38.7 ± 10.1 yrs, BMI = 24.6 ± 4.0 kg·m-2). Both studies used identical procedures and analytical strategies.

Results:

The mean difference in steps·d-1 for the week was 1643.4 steps·d-1 in Study 1 and 2199.4 steps·d-1 in Study 2. There were strong correlations between accelerometer- and pedometer-determined steps·d-1 in Study 1 (r = .85, P < .01) and Study 2 (r = 0.87, P < .01). Bland-Altman plots indicated agreement without bias between steps recorded from the devices in Study 1 (r = −0.14, P < .17) and Study 2 (r = −0.09, P < .40). Correlations examining the difference between accelerometer–pedometer steps·d-1 and MVPA resulted in small, inverse correlations (range: r = −0.03 to −0.28).

Conclusions:

These results indicate agreement between accelerometer- and pedometer-determined steps·d-1; however, measurement bias may still exist because of known sensitivity thresholds between devices.

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Tiago V. Barreira, John P. Bennett and Minsoo Kang

Purpose:

To obtain validity evidence for the measurement of step counts by spring-levered and piezoelectric pedometers during dance.

Methods:

Thirty-five adults in a college dance class participated in this study. Participants completed trials of 3- and 5-min of different styles of dance wearing Walk4life MVP and Omron HJ-303 pedometers, while their steps were visually counted. Pearson correlation, paired t-test, mean absolute percent error (MAPE), and mean bias were calculated between actual step and pedometer step counts for the 3- and 5-min dances separately.

Results:

For the Walk4life trials the correlations were .92 and .77 for the 3- and 5-min dances. No significant differences were shown by t-test for the 3- (P = .16) and 5-min dances (P = .60). However, MAPE was high, 17.7 ± 17.7% and 19.4 ± 18.3% for the 2 dance durations, respectively. For the Omron, the correlations were .44 and .58 for the 3- and 5-min dances, respectively. No significant differences were shown by t-test for the 3-min (P = .38) and for the 5-min (P = .88) dances. However, MAPE was high, 19.3 ± 16.4% and 26.6 ± 15.2% for the 2 dance durations, respectively.

Conclusions:

This study demonstrated that pedometers can be used to estimate the number of steps taken by a group of college students while dancing, however caution is necessary with individual values.

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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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Urs Granacher, Andre Lacroix, Katrin Roettger, Albert Gollhofer and Thomas Muehlbauer

This study investigated associations between variables of trunk muscle strength (TMS), spinal mobility, and balance in seniors. Thirty-four seniors (sex: 18 female, 16 male; age: 70 ± 4 years; activity level: 13 ± 7 hr/week) were tested for maximal isometric strength (MIS) of the trunk extensors, flexors, lateral flexors, rotators, spinal mobility, and steady-state, reactive, and proactive balance. Significant correlations were detected between all measures of TMS and static steady-state balance (r = .43−.57, p < .05). Significant correlations were observed between specific measures of TMS and dynamic steady-state balance (r = .42−.55, p < .05). No significant correlations were found between all variables of TMS and reactive/proactive balance and between all variables of spinal mobility and balance. Regression analyses revealed that TMS explains between 1–33% of total variance of the respective balance parameters. Findings indicate that TMS is related to measures of steady-state balance which may imply that TMS promoting exercises should be integrated in strength training for seniors.

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Pedro C. Hallal, Eduardo Simoes, Felipe F. Reichert, Mario R. Azevedo, Luiz R. Ramos, Michael Pratt and Ross C. Brownson

Purpose:

To evaluate the validity and reliability of the telephone-administered long IPAQ version.

Methods:

The questionnaire was administered by telephone to adults on days 1 and 6. On day 1, the same questionnaire was administered by face-to-face interview, and accelerometers were delivered to subjects. Reliability was measured by comparing data collected using the telephone questionnaire on days 1 and 6. Validity was measured by comparing the telephone questionnaire data with (a) face-to-face questionnaire and (b) accelerometry.

Results:

Data from all instruments were available for 156 individuals. The Spearman correlation coefficient for telephone interview reliability was 0.92 for the leisure-time section of IPAQ, and 0.87 for the transport-related section of IPAQ. The telephone interview reliability kappa was 0.78. The Spearman correlation between the telephone-administered and the face-to-face questionnaire was 0.94 for the leisure-time and 0.82 for the transport-related section. The kappa was 0.69. There was a positive association between quartiles of accelerometer data and total telephone-administered IPAQ score (P < .001). The Spearman correlation was 0.22.

Conclusions:

The telephone-administered IPAQ presented almost perfect reliability and very high agreement with the face-to-face version. The agreement with accelerometer data were fair for the continuous score, but moderate for the categorical physical activity variables.

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Barbara Resnick and Elizabeth Galik

The purpose of this study was to develop and test a measure of physical activity for residents in long-term-care facilities, the Physical Activity Survey in Long-Term Care (PAS-LTC). Sixty-six activities are included in the PAS-LTC: routine physical activity, personal-care activities, structured exercise, recreational activities, caretaking activities, and repetitive activities. The study included 13 residents in a long-term-care facility, most of whom were women (62%), with an average age of 84 years (± 6.0) and an average Mini Mental State Examination score of 6 (± 6.9). There was evidence of interrater reliability of the PAS-LTC with intraclass correlations of .83-.94. There was some evidence of validity of the measure with statistically significant correlations between PAS-LTC recorded during the evening and night shifts and the number of counts of activity per the ActiGraph (r = .60 and r = .57, respectively, p < .05) and the calories estimated (r = .58 and r = .60, respectively, p < .05). The PAS-LTC completed during the day shift and total activity based on the PAS-LTC showed nonsignificant correlations of .40 or greater with the ActiGraph activity counts and calories.

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Jesse Mala, Jennifer McGarry, Kristen E. Riley, Elaine C.-H. Lee and Lindsay DiStefano

correlation coefficients ranging from .89 to .96 ( Tulsky et al., 2013 ; Weintraub et al., 2013 ; Zelazo et al., 2013 ). These studies also found correlations for convergent validity ranging from .48 to .69 ( p  < .001; Tulsky et al., 2013 ; Weintraub et al., 2013 ; Zelazo et al., 2013 ). NIH Toolbox