TY - JOUR
T1 - What Psychosocial Factors Determine the Physical Activity Patterns of University Students?
AU - Murphy, Joseph
AU - McDonccha, Ciaran
AU - Murphy, Marie H
AU - Murphy, Niamh
AU - Nevill, Alan
AU - Woods, Catherine
PY - 2019/5/1
Y1 - 2019/5/1
N2 - 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
AB - 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
KW - Active commuting
KW - Cluster analysis
KW - Psychology
KW - Youth
UR - http://www.scopus.com/inward/record.url?scp=85065348318&partnerID=8YFLogxK
U2 - 10.1123/jpah.2018-0205
DO - 10.1123/jpah.2018-0205
M3 - Article
C2 - 30975020
SN - 1543-3080
VL - 16
SP - 325
EP - 332
JO - Journal of Physical Activity and Health
JF - Journal of Physical Activity and Health
IS - 5
ER -