Get up, stand up: a randomized controlled trial to assess the effectiveness of a messenger-based intervention to reduce sedentary behavior in university students

Sedentary behavior is associated with the mental health of university students during the Covid-19 pandemic, and not practicing physical activity accentuates its adverse effects: cross-sectional study

BACKGROUND

Movement behaviours, such as sedentary behavior (SB) and physical inactivity, have become a public health issue due to their implications for physical and mental health. The literature indicates that the university environment influences the movement behaviors of university students, and the strategies adopted during the pandemic may have favored a decrease in the practice of physical activity and an increase in the time dedicated to SB in this population. We aimed to evaluate the association of SB and moderate to vigorous leisure-time physical activity (MVPA) with presence of symptoms of mental disorders during the COVID-19 pandemic.

METHODS

This is a multicenter survey conducted with undergraduate students from eight Brazilian universities between October 2021 and February 2022 using an online questionnaire. The outcome variable was symptoms of anxiety and depression, assessed by the Depression, Anxiety, and Stress Scale-21. SB was assessed by total sitting time, being that individuals with ≥ 9 h/day were classified with high SB. The practice of MVPA was evaluated based on weekly frequency, duration, and type of exercise. Subsequently, the ratio between the time spent in MVPA (minutes/day) and the time spent in SB (hours/day) was calculated, being considered as cutoff point was the practice of 2.5 min of MVPA for each sedentary hour. To assess the association between the outcome and explanatory variables, multivariable logistic regression was performed.

RESULTS

A total of 8,650 students participated in the study, with an average age of 23.9 years (SD: ± 6.34). In the multivariate analysis, the odds of anxiety symptoms [OR: 1.37 (95% CI: 1.24-1.50)] and depression [OR: 1.61 (95% CI: 1.47-1.77)] were higher in individuals with ≥ 9 h of SB per day. In the analysis of the relationship between MVPA and SB, not engaging in 2.5 min of MVPA per hour of SB increases the odds of anxiety symptoms [OR: 1.44 (95% CI: 1.31-1.58)] and depression [OR: 1.74 (95% CI: 1.59-1.92)].

CONCLUSION

The results suggest that SB is a risk factor associated with symptoms of anxiety and depression and that not engaging in MVPA exacerbates the negative effects of SB.

Subjective Health Status, Health-Related Behavior, and Health Literacy of Health Professional Students: Results from a Cross-Sectional Study

The importance of health promotion for health professional students is increasingly crucial, as the rising requirements for those students can have a negative impact on their health. Despite this awareness, there is still limited knowledge in Germany about the specific health needs of this group of students. This study's aim was, therefore, to assess the subjective health of first-year students and to identify health needs. Thus, this study is based on an online survey using standardized measurement instruments. First-year students from three degree programs were included. The data were analyzed descriptively. A total of n = 98 (72.6%) participated in the survey. The results showed that a major proportion of participants (80.3%) rated their health positively, but a significant proportion reported weight disorders (24%) and pre-existing health conditions (62.1%) at baseline. Interestingly, a high proportion (59%) reported a high level of mental well-being at the time of the survey. However, worrying findings regarding lifestyle behaviors, including physical inactivity (40.6%), smoking (20%), risky alcohol use (24%), and unhealthy eating habits (37%) were determined. In terms of health literacy, around 45% of students rated their health competencies as problematic. Furthermore, it was found that students with low health literacy had a significantly higher prevalence of low mental well-being (53.3% vs. 30.8%, p = 0.036) and unhealthy eating habits (48.8% vs. 26.5%, p = 0.027) compared to students with sufficient health literacy. Health professional students should be considered a relevant target group for health and health competence promotion from the beginning of their studies. The identified fields of action should be addressed in the context of health promotion. This is of particular importance as they are not only aimed at improving the students' well-being but also will later work directly with patients and, therefore, have a direct influence on the health of others.

Objectively Assessing the Effect of a Messenger-based Intervention to Reduce Sedentary Behavior in University Students: A Pilot Study

AIM

Sedentary behavior poses a serious health risk. Students in particular are highly affected by prolonged, uninterrupted periods of sitting due to routines in everyday university life, such as attending lectures, self-study periods in the library, etc. Whereas university students are mostly young and therefore appear to be healthy, evidence-based consequences of prolonged sitting may come to pass in prospective times. Therefore, primary prevention must be initiated to shield university students from the occurrence of non-communicable diseases (NCDs). Consequently, the study aims to evaluate a messenger-based intervention designed to reduce sedentary time among university students.

SUBJECTS AND METHODS

The effectiveness of the intervention was assessed in a randomized controlled trial with a convenience sample of thirty-four German university students. ActivPal devices (Pal Technologies Ltd., Glasgow) were applied to measure sedentary behavior objectively before and after a 3-week intervention of messages to interrupt sedentary time. An additional evaluation of the messages was carried out.

RESULTS

Sedentary behavior decreased by about one hour in the intervention group. Explorative analysis shows a statistically significant, negative correlation between sedentary time at baseline and the change of sedentary behavior over time in the intervention group (r = - .81) indicating effectiveness of the intervention for the participants with the highest sedentary times at baseline. Additionally, the messages were considered appropriate by the participants.

CONCLUSION

A reduction of sedentary time of one hour per day in the intervention group is practically significant. The current investigation had similar findings with prior studies where promising results for the reduction of sedentary behavior were observed through mobile-based interventions. The detected effects of the intervention in this pilot study demonstrate an opportunity for further research in this field.

Profiling Physical Fitness of Physical Education Majors Using Unsupervised Machine Learning

The academic curriculum has shown to promote sedentary behavior in college students. This study aimed to profile the physical fitness of physical education majors using unsupervised machine learning and to identify the differences between sexes, academic years, socioeconomic strata, and the generated profiles. A total of 542 healthy and physically active students (445 males, 97 females; 19.8 [2.2] years; 66.0 [10.3] kg; 169.5 [7.8] cm) participated in this cross-sectional study. Their indirect VO2max (Cooper and Shuttle-Run 20 m tests), lower-limb power (horizontal jump), sprint (30 m), agility (shuttle run), and flexibility (sit-and-reach) were assessed. The participants were profiled using clustering algorithms after setting the optimal number of clusters through an internal validation using R packages. Non-parametric tests were used to identify the differences (p < 0.05). The higher percentage of the population were freshmen (51.4%) and middle-income (64.0%) students. Seniors and juniors showed a better physical fitness than first-year students. No significant differences were found between their socioeconomic strata (p > 0.05). Two profiles were identified using hierarchical clustering (Cluster 1 = 318 vs. Cluster 2 = 224). The matching analysis revealed that physical fitness explained the variation in the data, with Cluster 2 as a sex-independent and more physically fit group. All variables differed significantly between the sexes (except the body mass index [p = 0.218]) and the generated profiles (except stature [p = 0.559] and flexibility [p = 0.115]). A multidimensional analysis showed that the body mass, cardiorespiratory fitness, and agility contributed the most to the data variation so that they can be used as profiling variables. This profiling method accurately identified the relevant variables to reinforce exercise recommendations in a low physical performance and overweight majors.