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Con Burns, John J. Murphy, and Ciaran MacDonncha

Background:

Knowledge of the physical activity correlate profile of adolescent females will provide insight into decreasing physical activity patterns among adolescent females.

Methods:

Correlates of physical activity and physical activity stage of change were assessed during 2007–2008 among 871 Irish adolescent females in years 1–6 in secondary schools (15.28 ± 1.8 years). Multivariate Analysis of Variance was used to identify whether differences in correlates of physical activity could be detected across year in school and physical activity stages of change.

Results:

Significant differences (P < .01) were found in 11 of the 16 measured correlates across year in school and in 14 of the 16 correlates across stage of change. Effect size estimates and regression analysis revealed perceived competence, peer social support and intention to be physically active (partial eta range (ηp 2) .21–.25) to be the most important predictors of physical activity stage of change.

Conclusions:

Females in more senior years in school and in earlier physical activity stages of change reported a significantly less positive physical activity correlate profile than females in junior years and in later physical activity stages of change. This finding supports the construct validity of the physical activity stages of change.

Open access

Brendan T. O’Keeffe, Alan E. Donnelly, and Ciaran MacDonncha

Purpose: To examine the test–retest reliability of student-administered (SA) health-related fitness tests in school settings and to compare indices of reliability with those taken by trained research-assistants. Methods: Participants (n = 86; age: 13.43 [0.33] y) were divided into 2 groups, SA (n = 45, girls = 26) or research-assistant administered (RA; n = 41, girls = 21). The SA group had their measures taken by 8 students (age: 15.59 [0.56] y, girls = 4), and the RA group had their measures taken by 8 research-assistants (age: 21.21 [1.38], girls = 5). Tests were administered twice by both groups, 1 week apart. Tests included body mass index, handgrip strength, standing broad jump, isometric plank hold, 90° push-up, 4 × 10-m shuttle run, back-saver sit and reach, and blood pressure. Results: Intraclass correlation coefficients for SA (≥.797) and RA (≥.866) groups were high, and the observed systematic error (Bland–Altman plot) between test 1 and test 2 was close to 0 for all tests. The coefficient of variation was less than 10% for all tests in the SA group, aside from the 90° push-up (24.3%). The SA group had a marginally lower combined mean coefficient of variation across all tests (6.5%) in comparison with the RA group (6.8%). Conclusion: This study demonstrates that, following familiarization training, SA health-related fitness tests in school-based physical education programs can be considered reliable.

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Gráinne Hayes, Kieran Dowd, Ciaran MacDonncha, and Alan Donnely

Background: Multiple activity monitors are utilized for the estimation of moderate- to vigorous-intensity physical activity in youth. Due to differing methodological approaches, results are not comparable when developing thresholds for the determination of moderate- to vigorous-intensity physical activity. This study aimed to develop and validate count-to-activity thresholds for 1.5, 3, and 6 metabolic equivalents of task in five of the most commonly used activity monitors in adolescent research. Methods: Fifty-two participants (mean age = 16.1 [0.78] years) selected and performed activities of daily living while wearing a COSMED K4b2 and five activity monitors; ActiGraph GT1M, ActiGraph wGT3X-BT, activPAL3 micro, activPAL, and GENEActiv. Receiver-operating-characteristic analysis was used to examine the area under the curve and to define count-to-activity thresholds for the vertical axis (all monitors) and the sum of the vector magnitude (ActiGraph wGT3X-BT and activPAL3 micro) for 15 s (all monitors) and 60 s (ActiGraph monitors) epochs. Results: All developed count-to-activity thresholds demonstrated high levels of sensitivity and specificity. When cross-validated in an independent group (N = 20), high levels of sensitivity and specificity generally remained (≥73.1%, intensity and monitor dependent). Conclusions: This study provides researchers with the opportunity to analyze and cross-compare data from different studies that have not employed the same motion sensors.

Open access

Marie H. Murphy, Angela Carlin, Catherine Woods, Alan Nevill, Ciaran MacDonncha, Kyle Ferguson, and Niamh Murphy

Background: Time spent in university represents a period of transition and may be an appropriate time to promote physical activity among young adults. The aim of this study was to assess participation of university students in sport and physical activity in Ireland and to explore the association between physical activity and perceptions of overall health, mental health, and happiness. Methods: The Student Activity and Sport Study Ireland was a cross-sectional online survey among a representative sample (n = 8122) of university students in Ireland. Binary logistic regressions were performed to examine associations between self-reported physical activity and gender (predictor variables) and individual perceptions of overall health, mental health, and happiness (binary outcomes). Results: Only 64.3% of respondents met the recommended level of 150 minutes of moderate to vigorous physical activity per week with males significantly more active than females (72.1% vs 57.8% meeting guidelines). Those meeting physical activity guidelines were more likely to report greater overall health and higher mental health and happiness scores compared with their inactive peers. Conclusions: Active students enjoy better health (overall and mental) and are happier than their inactive peers. This provides a clear rationale for providing students with opportunities to be active at university. The data provide a baseline to monitor changes in physical activity patterns.

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Joseph J. Murphy, Ciaran MacDonncha, Marie H. Murphy, Niamh Murphy, Alan M. Nevill, and Catherine B. Woods

Background: Although levels of physical activity (PA) have been researched, no information on how university students organize their PA across different life domains is available. The purpose of this study is to explore if and how students organize their PA across transport and recreational domains, and to identify the psychosocial factors related to these patterns. Methods: Students from 31 Irish universities completed a supervised online survey measuring participant characteristics, psychosocial factors, and PA. Two-step cluster analysis was used to identify specific PA patterns in students. Binary logistic regressions identified factors associated with cluster membership while controlling for age, sex, household income, and perceived travel time to a university. Results: Analysis was performed on 6951 students (50.7% male; 21.51 [5.55] y). One Low Active cluster emerged. Four clusters containing a form of PA emerged including Active Commuters, Active in University, Active Outside University, and High Active. Increases in motivation and planning improved the likelihood of students being categorized in a cluster containing PA. Conclusion: One size does not fit all when it comes to students PA engagement, with 5 patterns identified. Health professionals are advised to incorporate strategies for increasing students’ motivation, action planning, and coping planning into future PA promotion efforts.