The purpose of this study was to compare the validity and reliability of three short physical activity self-report instruments to determine their potential for use with university student populations. The participants (N = 155; 44.5% male; 22.9 ± 5.13 years) wore an accelerometer for 9 consecutive days and completed a single-item measure, the a brief two item measure and the International Physical Activity Questionnaire—Short Form questionnaires on day 1 and 9. Correlations between self-reported and accelerometer derived moderate-to-vigorous physical activity levels were moderate for the International Physical Activity Questionnaire—Short Form, while poor for the single-item measure and the a brief two item measure. The agreement level was high with the International Physical Activity Questionnaire—Short Form (77.4%) and moderate for both the single-item measure (45.2 %) and a brief two item measure (44.5 %). The intraclass correlations between the two administrations were moderate to strong across all measures (0.52–0.70) in 133 participants. The International Physical Activity Questionnaire—Short Form is the most suitable of these three self-report instruments for use with this population due to higher correlations and levels of agreement with accelerometry.

Students engage in risky health-related behaviours that influence their current and future health status. Health-related behaviours cluster among adults and differently based on sub-populations characteristics but research is lacking for university populations. Examining the clustering of health- related behaviours can inform our initiatives and strategies, while examining cluster members’ characteristics can help target those who can prosper most from health promotion efforts. This study examines the clustering of health-related behaviours in Irish university students, and investigates the relationship with students’ sex, age, field of study and accommodation type. An online survey was completed by 5672 Irish university students (51.3% male; 21.60 ± 5.65 years) during 2014. Two-step cluster analysis was used to understand how health-related behaviours (physical activity, smoking, alcohol intake, drug use and dietary habits) cluster among male and female students. Binary logistic regressions were conducted to examine the likelihood of students falling into certain clusters based on their characteristics. Five cluster groups were identified in males and four in females. A quarter of males were categorised as ideal healthy with older students and those from certain fields of study having a higher likelihood of being classified in a low physical activity and poor diet (OR = 1.06–2.89), alcohol consumption (OR = 1.03–3.04), or smoking and drug use (OR = 1.06–2.73) cluster. Forty-five percent of females were categorised as ideal healthy with older females more likely to be in a low active and smoking cluster (OR = 1.03), and less likely to be in a convenience food cluster (OR = 0.96). Females from certain fields of study were also more likely to be classified in these clusters (OR = 1.59–1.76). Students living away from their family home had in increased likelihood of being in a cluster related to a higher frequency of alcohol consumption (OR = 1.72–3.05). Health-related behaviours cluster among this population and need to be taken into account when designing multi-health interventions and policies. These findings can be used to target student groups at risk, leading to more efficient and successful health promotion efforts. The addition of modules providing information regarding health-related behaviours are advised in all fields of study.

This is a state-of-the-art review of historical developments, current approaches and recommended future directions in physical activity (PA) research, practice and policy. Since the early epidemiological studies in the 1950s, PA research has developed from within a biomedical paradigm. There is now a strong evidence base linking PA with positive health outcomes. PA is currently understood as a multi-sector issue, requiring a multi-sector solution (e.g. transport, urban design, sport), resulting in multiple individual and societal benefits (e.g. addresses multiple Sustainable Development Goals), however, there is a disconnect between interventions, policy and practice. This may be due to limited cross-sector collaboration between, and within, the public and private sectors. Furthermore, the mix of policy instruments employed by governments to implement PA policy to date has been dominated by soft (e.g. communication) rather than hard options (e.g. fiscal). To progress in PA promotion, we need to move beyond health outcome and intervention evidence generation (e.g. focus on testing efficacy in highly controlled settings), to more complex, real world, politically informed, multi-sector, scale-up and policies, while concurrently collecting data to evaluate such efforts (e.g. natural experiments and evaluations of the policy process). PA programs may benefit from greater incorporation of public policy considerations, so that proposed interventions and policies are designed with potential political constraints in mind. We conclude by providing a call to action to advance the understanding of the role of politics in PA, in order to develop politically informed action on PA.

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 A...

Background: There is limited understanding of the challenges experienced and supports required to aid effective advocacy of the Global Action Plan on Physical Activity (GAPPA). The purpose of this study was to assess the challenges experienced and supports needed to advocate for the GAPPA across countries of different income levels. Methods: Stakeholders working in an area related to the promotion of physical activity were invited to complete an online survey. The survey assessed current awareness and engagement with the GAPPA, factors related to advocacy, and the perceived challenges and supports related to advocacy for implementation of the GAPPA. Closed questions were analyzed in SPSS, with a Pearson’s chi-square test used to assess differences between country income level. Open questions were analyzed using inductive thematic analysis. Results: Participants (n = 518) from 81 countries completed the survey. Significant differences were observed between country income level for awareness of the GAPPA and perceived country engagement with the GAPPA. Challenges related to advocacy included a lack of support and engagement, resources, priority, awareness, advocacy education and training, accessibility, and local application. Supports needed for future advocacy included guidance and support, cooperation and alliance, advocacy education and training, and advocacy resources. Conclusions: Although stakeholders from different country income levels experience similar advocacy challenges and required supports, how countries experience these can be distinct. This research has highlighted some specific ways in which those involved in the promotion of physical activity can be supported to scale up advocacy for the GAPPA. When implementing such supports, consideration of regional, geographic, and cultural barriers and opportunities is important to ensure they are effective and equitable.

Background: Self-reported physical activity (PA) questionnaires have traditionally been used for PA surveillance in children and adolescents, especially in free-living conditions. Objective measures are more accurate at measuring PA, but high cost often creates a barrier for their use in low- and middle-income settings. The advent of smartphone technology has greatly influenced mobile health and has offered new opportunities in health research, including PA surveillance. Objective: This review aimed to systematically explore the use of smartphone technology for PA surveillance in children and adolescents, specifically focusing on the use of smartphone apps. Methods: A literature search was conducted using 5 databases (PubMed, Scopus, CINAHL, MEDLINE, and Web of Science) and Google Scholar to identify articles relevant to the topic that were published from 2008 to 2023. Articles were included if they included children and adolescents within the age range of 5 to 18 years; used smartphone technology as PA surveillance; had PA behavioral outcomes such as energy expenditure, step count, and PA levels; were written in English; and were published between 2008 and 2023. Results: We identified and analyzed 8 studies (5 cross-sectional studies and 3 cohort studies). All participants were aged 12-18 years, and all studies were conducted in high-income countries only. Participants were recruited from schools, primary care facilities, and voluntarily. Five studies used mobile apps specifically and purposely developed for the study, whereas 3 studies used mobile apps downloadable from the Apple App Store and Android Play Store. PA surveillance using these apps was conducted from 24 hours to 4 weeks. Conclusions: Evidence of PA surveillance using smartphone technology in children and adolescents was insufficient, which demonstrated the knowledge gap. Additional research is needed to further study the feasibility and validity of smartphone apps for PA surveillance among children and adolescents, especially in low- and middle-income countries.