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Researchers in the field of excellence in sport performance are becoming increasingly focused on the study of sport-specific characteristics and requirements. In accordance with this, the purposes of this study were (a) to examine the morphologic-, fitness-, handball-specific skills and psychological and "biosocial" differences between top elite and nontop elite team-handball players and (b) to investigate the extent to which they may be used to identify top elite team-handball players. One hundred sixty-seven adult male team-handball players were studied and divided in 2 groups: top elite (n = 41) and nontop elite (n = 126). Twenty-eight morphologic-, 9 fitness-, 1 handball-specific skills and 2 psychological-based and 2 "biosocial"-based attributes were used. Top elite and nontop elite groups were compared for each variable of interest using Student's t-test, and 5 logistic regression analyses were performed with the athlete's performance group (top elite or nontop elite) as the dependent variable and the variables of each category as predictors. The results showed that (a) body mass, waist girth, radiale-dactylion length, midstylion-dactylion length, and absolute muscle mass (morphologic model); (b) 30-m sprint time, countermovement jump height and average power, abdominal strength and the class of performance in the Yo-Yo Intermittent Endurance Test (fitness model); (c) offensive power (specific-skills model); (d) ego-based motivational orientation (psychological model); (e) socioeconomic status and the energy spent (for week) in handball activity (biosocial model); significantly (p < 0.05) contributed to predict the probability of an athlete to be a top elite team-handball player. Moreover, the fitness model exhibited higher percentages of correct classification (i.e., 91.5%) than all the other models did. This study provided (a) the rational to reduce the battery of tests for evaluation purposes, and (b) the initial step to work on building a multidisciplinary model to predict the probability of a handball athlete to be a top elite player.

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This study supports the importance of a combined self-management and exercise intervention to improve functional lower limb strength and aerobic capacity in a Portuguese sample. Additionally, pain and other symptoms have improved clinically.

A dimensão da amostra, o tipo de variá-veis, o seu formato de medida, a construção dos instrumentos de recolha de dados válidos e fiáveis, são aspectos a ter em consideração no processo de investigação. No âmbito das ciências sociais, da saúde e especificamente na área de enfermagem, os instrumentos de recolha de dados são muitas vezes compostos por variáveis componentes ou indicadores que dão origem a variáveis latentes ou não observáveis diretamente, daí a importância da decisão relativa à forma como são medidas (escala ordinal, Likert ou de tipo Likert). As escalas psicométricas são exemplos de instrumentos, pelo tipo de variáveis que as integram, que podem trazer problemas de medida e de análise estatística (testes paramétricos versus não paramétricos). Assim o investigador quando usa estas variáveis deve respeitar alguns pressupostos baseados em estudos de simulação ou em recomendações fundamentadas na evidência científica, de forma a tomar a melhor decisão.

Background:Physical activity (PA) is beneficial, enhancing healthy development. However, one-third of school-age children practicing sports regularly suffer from an injury. These injuries are associated with sex, chronological age, and PA level.Purpose:To identify the importance of age, PA level, and maturity as predictors of injury in Portuguese youth.Study Design:Descriptive epidemiological study.Level of Evidence:Level 3.Methods:Information about injury and PA level was assessed via 2 questionnaires (LESADO RAPIL II) from 647 subjects aged 10 to 17 years. Maturity offset according to Mirwald (time before or after peak height velocity) and Tanner-Whitehouse III bone age estimates were used to evaluate maturation. Binary logistic regression and gamma regression were used to determine significant predictors of injury and injury rate.Results:Injury occurrence was higher for both sexes in recreational, school, and federated athletes (athletes engaged in sports that are regulated by their respective federations, with formal competition). These injuries also increased with age in boys and in the higher maturity offset group in girls. Injury rate was higher for both sexes in the no sports participation group. Early-maturing girls, with higher bone age and lower maturity offset, showed higher injury rate.Conclusion:Injuries in Portuguese youth were related to PA level, age, and biological maturation. Recreational, school, and federated athletes had more injury ocurrences while subjects with no sports participation had higher injury risk. Older subjects had more injuries. Early-maturing girls that had just passed peak height velocity may be particularly vulnerable to risk of sports injury because of the growing process.Clinical Relevance:Increased knowledge about injury with specific PA exposure data is important to an overall risk management strategy. This study has deepened the association between injury and biological maturation variables.

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