Motor skills in students can be developed or improved through regular physical activity such as walking in nature, Nordic walking, hiking, cycling and swimming. This study aimed to examine the relationship between motor skills and various anthropometric and health-related factors, and to appraise any differences in motor performance and body mass index (BMI) on a sample of university students from Croatia. A total of 122 students (73 of them in health programs and 49 in non-health programs) aged 18 to 44 years participated in the study. Motor abilities were evaluated using standardized motor tests, while body composition was assessed via bioelectrical impedance analysis, which measured fat tissue, muscle and bone mass, metabolic age, degree of obesity, total body water, and BMI. While the groups were similar in terms of BMI and weight, students in non-health-related study programs had significantly higher values across a wide array of detailed body composition measures, particularly related to fat and muscle mass. Significant negative correlations were observed between body fat percentage and trunk lift performance (r = −0.55, p < 0.01), as well as between metabolic age and trunk lift performance (r = −0.44, p < 0.01) in health students. In non-health students, the strongest negative correlation was found between body fat percentage and flexibility (r = −0.47, p < 0.01). Higher muscle mass was a positive predictor of motor performance while higher fat mass and metabolic age were significant negative predictors. These findings underscore the impact of body composition on motor performance, particularly strength and flexibility, and highlight the need for targeted preventive strategies among university students. The study supports the implementation of early interventions promoting physical activity and healthy body composition to preserve motor abilities and long-term functional health in this critical age group—especially since lifestyle habits formed during university years tend to persist into adulthood.

Background: Physical activity, metacognitive awareness, and empathy are interconnected factors that play a significant role in the overall well-being of university students. Together, these elements contribute to the development of more self-aware, emotionally intelligent, and academically engaged students. The aim of this study is to explore the relationship between physical activity, empathy, and metacognition among physiotherapy students, as well as determining whether differences exist between undergraduate and graduate students. Methods: A cross-sectional study evaluated 468 physiotherapy students using the International Physical Activity Questionnaire—short version, the Metacognitive Awareness Inventory, and a shortened version of the Empathy Quotient supplemented with demographic questions. The respondents were students of undergraduate and graduate studies of physiotherapy, were male and female, and were between the ages of 18 and 25 years. Results: Higher levels of vigorous-intensity physical activity, walking, and total physical activity are significantly associated with increases in Declarative Knowledge (p = 0.000; p = 0.001; p = 0.000), Empathy Quotient (p = 0.029; p = 0.000; p = 0.006), and Cognitive Empathy (p = 0.002; p = 0.000; p = 0.001). Undergraduate students demonstrated higher levels of Declarative Knowledge (p = 0.000), whereas graduate students scored higher in Procedural Knowledge (p = 0.020), Planning (p = 0.000), Information Management Strategies (p = 0.000), and Evaluation (p = 0.005). Undergraduate students demonstrated higher overall empathy, cognitive empathy, and social skills (p = 0.000). Conclusions: This is the first study to examine this issue in the context of physiotherapy students. Our findings highlight the importance of creating integrated programs that promote physical activity, metacognitive awareness, and empathy concurrently among physiotherapy students. Enhancing metacognitive skills through targeted educational strategies helps students strengthen their critical thinking and self-regulation, enhance academic outcomes, and better prepare students for their professional role.

Motor skills in students can be developed or improved through regular physical activity such as walking in nature, Nordic walking, hiking, cycling and swimming. This study aimed to examine the relationship between motor skills and various anthropometric and health-related factors, and to appraise any differences in motor performance and body mass index (BMI) on a sample of university students from Croatia. A total of 122 students (73 of them in health programs and 49 in non-health programs) aged 18 to 44 years participated in the study. Motor abilities were evaluated using standardized motor tests, while body composition was assessed via bioelectrical impedance analysis, which measured fat tissue, muscle and bone mass, metabolic age, degree of obesity, total body water, and BMI. While the groups were similar in terms of BMI and weight, students in non-health-related study programs had significantly higher values across a wide array of detailed body composition measures, particularly related to fat and muscle mass. Significant negative correlations were observed between body fat percentage and trunk lift performance (r=–0.547, p<0.01), as well as between metabolic age and trunk lift performance (r=–0.444, p<0.01) in health students. In non-health students, the strongest negative correlation was found between body fat percentage and flexibility (r=–0.467, p<0.01). Multiple linear regression analysis revealed that higher muscle mass was a positive predictor of motor performance (β=0.565, p<0.001), while higher fat mass and metabolic age were significant negative predictors (β=–0.858, p=0.049; β=–0.911, p=0.003, respectively). Students with excessive body weight consistently exhibited higher fat mass, metabolic age, as well as poorer motor outcomes. These findings underscore the impact of body composition on motor performance, particularly strength and flexibility, and highlight the need for targeted preventive strategies among university students. The study supports the implementation of early interventions promoting physical activity and healthy body composition to preserve motor abilities and long-term functional health in this critical age group – especially since lifestyle habits formed during university years tend to persist into adulthood.

Assessing the quality of research output is challenging. Systematic reviews and meta-analyses of randomized trials have a pivotal role in informing clinical practice and policy decisions, and there is a broad agreement that the method quality of primary research should be carefully assessed (Albanese et al., 2020). One of the instruments to do that is the Physiotherapy Evidence Database (PEDro) scale, specifically designed to assess the quality of methods used in clinical trials in the field of physiotherapy (Elkins et al., 2013). Its reliability in terms of ICC values ranges from 0.55 (95% confidence interval CI: 0.47–0.65) for the original scale, to 0.82 (95% CI: 0.70–0.89) for the Portuguese version (Shiwa et al., 2011). The PEDro scale consists of 11 items encompassing the domains of external validity (item 1: Eligibility criteria and source), internal validity (items 2 to 9: Random allocation; Concealed allocation; Baseline comparability; Blinding of participants; Blinding of therapists; Blinding of assessors; Adequate follow-up (>85%); and Intention-to-treat analysis), and statistical reporting (items 10 and 11: Betweengroup statistical comparisons and Reporting of point measures and measures of variability) (Cashina, McAuleya, 2020). Each item is scored as either present (1) or absent (0), leading to a maximum score of 10 (Paci, Bianchini and Baccini, 2022). A trial is considered of moderate to high quality if it scores at least 6 of 10 (Paci, Bianchini and Baccini, 2022). The purpose of the PEDro score is to help researchers identify trials that have good internal validity (items 2–9) and that report enough data to make their results interpretable (items 10 and 11) (Moseleya et al., 2020). Interpreting these items correctly is critical to high-quality, evidence-based health practice. Unlike PEDro, however, the Cochrane Collaboration distinguishes between the methodological quality of a study and the risk of bias: a study of high quality can still be at high risk of bias (Higgins et al., 2011). The Cochrane risk of bias (RoB) tool focuses on the internal validity of trials and assesses six domains of bias: selection bias, performance bias, detection bias, attrition bias, reporting bias, and other bias (Higgins et al., 2011). These two tools can complement each other for an even better quality assessment of physiotherapy research and help disseminate and make transparent and available research output, encouraging interdisciplinary research along the way.

Introduction: Prolonged sitting, computer work and digital workload are associated with frequent occurrence of pain in the spine and upper extremities, as well as increased stress and mental problems. Some difficulties often arise from static strain caused by long hours of computer work and inappropriate ergonomic working conditions. The aim of this study was to assess the occurrence of the difficulties described in non-teaching staff in an academic environment. Methods: The cross-sectional design of this study included 34 non-teaching employees of University North. Demographic data and the Nordic Musculoskeletal Questionnaire and Questionnaire on depression, anxiety and stress (The Depression, Anxiety and Stress Scale—DASS-21) were used. Results: The results presented a moderate level of stress in 32.4% of participants, while 29.4% had a normal level of stress. A normal level of anxiety was observed in 44.1% of participants, whereas 23.5% reported extremely severe anxiety. A statistically significant difference was found between troubles in the shoulders during the last 12 months and stress levels. Also, a statistically significant difference was found between troubles in the wrists/hands during the last 12 months and depression. Conclusions: Given the relatively small sample size and the large number of statistical comparisons performed, these findings may represent either true associations or chance findings and therefore require confirmation in larger longitudinal studies specifically designed to investigate the relationship between psychological factors and musculoskeletal complaints.