Where, when, how, and with whom do young university students engage in physical activity? A cluster-derived spectrum of patterns across 16 European universities

Young adults are particularly at risk of dropping out of physical activity (PA). European policies have addressed this issue by promoting PA and encouraging better monitoring of PA through standardized and specific measures of its quantity. The current paper used an ecological approach that considers interrelated determinants at the individual, social, environmental, and policy levels to survey 2,165 undergraduate students (65.3% female) aged 18–25 years from 16 universities via an online questionnaire as part of the “How Young People in Europe Move” (HYPEM) project. A cluster analysis of mixed data was performed to identify profiles of sport and PA participation among undergraduates from 12 European countries and to examine their associations with individual and contextual characteristics. The results showed that individual and contextual characteristics were associated with spatial, temporal, social, intensity-related, and equipment-related dimensions of PA participation. Additionally, space, time and equipment were key variables for profiling students. Furthermore, the cluster analysis revealed three typologies of student sports and PA participation: ‘Autonomous’, ‘Networked Supervised’, and ‘Regularly Supervised’. These profiles suggest that undergraduate students engage in PA through various formats, ranging from flexible, self-organized practices to more structured, supervised forms of participation. Differences were also observed across participating institutions, indicating that contextual factors should be considered when interpreting these exploratory profiles. These profiles may help generate hypotheses about how university PA opportunities could be designed and evaluated in future prospective and intervention studies.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-11-04
DOI
https://doi.org/10.1371/journal.pone.0360751
Primary Topic
Physical Activity and Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Where, when, how, and with whom do young university students engage in physical activity? A cluster-derived spectrum of patterns across 16 European universities

Clément Llena, Thibaut Derigny, Tobias Vogt, Aurore Huchez et al.
1 links
PLoS ONE
Physical Activity and Health
article

Where, when, how, and with whom do young university students engage in physical activity? A cluster-derived spectrum of patterns across 16 European universities

Clément Llena, Thibaut Derigny, Tobias Vogt, Aurore Huchez, Libor Flemr, Alessandro Porrovecchio, Yvonne Delevoye, Isabelle Joing, Marek Rejman, João Paulo Vilas‐Boas, Pedro Rufino Olivares, Vanessa Lentillon‐Kaestner, Bárbara Mazza, Léa Mekkaoui, Przemysław Nosal, M. Garcin, Olivier Dieu, Hee Jung Hong, Søren Andkjær, Christopher L. Fullerton, Annette Michelsen la Cour, Nico Bortoletto, Félix Berrigan, Audran Aulanier, Susana Maria Soares, François Potdevin, Enrico Michelini, Joseph Gandrieau, Alexandre Mouton, Bjørn Harald Olstad, Louise Fermon, Ricardo J. Fernandes, Mário J. Costa, Alexis Mauger
article en

Abstract

Young adults are particularly at risk of dropping out of physical activity (PA). European policies have addressed this issue by promoting PA and encouraging better monitoring of PA through standardized and specific measures of its quantity. The current paper used an ecological approach that considers interrelated determinants at the individual, social, environmental, and policy levels to survey 2,165 undergraduate students (65.3% female) aged 18–25 years from 16 universities via an online questionnaire as part of the “How Young People in Europe Move” (HYPEM) project. A cluster analysis of mixed data was performed to identify profiles of sport and PA participation among undergraduates from 12 European countries and to examine their associations with individual and contextual characteristics. The results showed that individual and contextual characteristics were associated with spatial, temporal, social, intensity-related, and equipment-related dimensions of PA participation. Additionally, space, time and equipment were key variables for profiling students. Furthermore, the cluster analysis revealed three typologies of student sports and PA participation: ‘Autonomous’, ‘Networked Supervised’, and ‘Regularly Supervised’. These profiles suggest that undergraduate students engage in PA through various formats, ranging from flexible, self-organized practices to more structured, supervised forms of participation. Differences were also observed across participating institutions, indicating that contextual factors should be considered when interpreting these exploratory profiles. These profiles may help generate hypotheses about how university PA opportunities could be designed and evaluated in future prospective and intervention studies.

PLoS ONEVol. 21(11)
University of Stirling (GB), University of Teramo (IT), Centre National de la Recherche Scientifique (FR), Université de Sherbrooke (CA), Osaka University of Health and Sport Sciences (JP), German Sport University Cologne (DE), Université de Pau et des Pays de l'Adour (FR), University of Trás-os-Montes and Alto Douro (PT), University of Liège (BE), Osnabrück University (DE), University of Southern Denmark (DK), University of Kent (GB), Université de Lille (FR), Haute École Pédagogique du Canton de Vaud (CH), College of Physical Education and Sport Palestra (CZ), Unité de Recherche Pluridisciplinaire Sport, Santé, Société (FR), Laboratoire Motricité Humaine Éducation Sport Santé (FR), Sciences Cognitives et Sciences Affectives (FR), Transitions Energétiques et Environnementales (FR), Université d'Artois (FR), Adam Mickiewicz University in Poznań (PL), Norwegian School of Sport Sciences (NO), Universidad de Huelva (ES), Sapienza University of Rome (IT)
Good health and well-being, Quality education
Openalex Percentile: Top 23%
Physical Activity and Health
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon