Talent selection is often affected by the relative age effects (RAEs), resulting in the overrepresentation of relatively older (vs. relatively younger) players among those selected. The use of sport-specific tasks is suggested to reduce RAEs during talent selection. Purpose: To test the hypothesis that talent selection including only sport-specific tasks is not affected by the RAEs and to analyse the body size and biological maturity of the top selection level according to relative age. Methods: Participants were U14 female (n = 5428) and U15 (n = 4408) male handball players participating in four programs consisting of four selection levels (local, county, regional, and national) grouped in bi-annual age. Handball-specific generic skills, position-specific technical drills and in-game performance were the selection criteria evaluated by experts and coaches. Body dimensions were measured and bone age, as an indicator of maturity, was estimated. The relative age quartile distributions within the bi-annual cohorts were examined using Chi-square and Odds Ratios. Results: In terms of all the registered players no RAEs were evident. However, the RAEs of moderate effect size were evident at the county level; χ² = 53.2 (girls) and 66.4 (boys), OR = 2.5 and 3.3, respectively. The RAEs of a large effect size were found at the regional level; χ² = 139.5 (girls) and 144.9 (boys), OR = 8.2 and 5.2, respectively. At national level, RAEs were still present, but with no further increase in the effect size. At the highest selection level, there were no differences in the anthropometric measures between the relatively older and younger players. Conclusion: The findings provide support to the hypothesis that the selection process exacerbates RAEs even when using only sport-specific selection criteria. The performance metrics in technical skills, but also coaching assessments are likely involved. In addition, an advanced maturity and/or an above-average body size increases the selection odds for relatively younger players.

Fine motor function develops into adulthood, but little is known about the differential effects of biological maturation and experience on speed and complex sequential performance of the hand. To determine maturity levels, ultrasonic bone age (BA) was assessed in 225 adolescents (123 females; BA range: 9.9 to 17.9 years). The role of experience was evaluated based on chronological age (CA, range: 11.1 to 16.5 years), musical instrumental experience, and handedness. Multiple linear regression modeling showed that BA is the strongest predictor of sequential motor performance, while CA influenced motor speed when no musical instrumental experience was present. When present, the amount of highly specific musical instrumental experience becomes the main predictor of sequential performance.

Adolescence is a sensitive period in motor development but little is known about how long-term learning dependent processes shape hand function in tasks of different complexity. We mapped two fundamental aspects of hand function: simple repetitive and complex sequential finger movements, as a function of the length of musical instrumental training. We controlled maturational factors such as chronological and biological age of adolescent female participants (11 to 15 years of age, n=114). We demonstrated that experience improves performance as a function of task complexity, the more complex task being more susceptible for experience driven performance changes. Overall, these results suggest that fine motor skills involving cognitive control and relying on long-range functional brain networks are substantially shaped by experience. On the other hand, performance in a simple repetitive task that explains fine motor speed is primarily shaped by white matter development driven by maturational factors.

Dietary apps are widely used for tracking food intake due to their convenience and accessibility. However, their accuracy, particularly compared to expert-driven dietary assessment tools, remains insufficiently examined. This study evaluated the accuracy of dietary intake estimations-focusing on energy, carbohydrates, protein, and fat-using NutriComp (NC), a professional dietary software, and Yazio (Y), a commercial mobile application, to assess their suitability for both clinical practice and research purposes. Twenty-two 3-d dietary records were analyzed, with identical food entries provided for both tools. NC utilizes a scientifically validated food database, while Y incorporates user-generated, domestic, and international food data. Mean differences in energy and macronutrient estimations were compared using paired t tests, and agreement was assessed via Bland-Altman analysis. Significant differences were found for energy (P < 0.001), carbohydrates (P < 0.001), protein (P < 0.001), and fat (P = 0.019). NC reported systematically higher values for energy, carbohydrate, and protein intake, whereas Y tended to overestimate fat consumption. Bland-Altman analysis demonstrated systematic biases in energy (115.4 ± 197.1 kcal) and protein (20.3 ± 11.4 g), while fat intake exhibited greater variability (4.2 ± 14.8 g) in Y. These discrepancies may be related to differences in database quality, food categorization, and user input variations. While Y is user-friendly, its dependence on non-validated databases results in notable inaccuracies, limiting its clinical and scientific applicability. In contrast, NC's validated database ensures more precise estimations, making it more suitable for professional dietary assessments. These findings underscore the need for continuous validation and refinement of dietary tracking applications to enhance their reliability and long-term practical utility in nutritional monitoring and research.