The purpose of this study was to investigate the discriminative ability of rebound jump squat force-time and power-time measures in differentiating speed performance and competition level in elite and elite junior rugby union players. Forty professional rugby union players performed 3 rebound jump squats with an external load of 40 kg from which a number of force-time and power-time variables were acquired and analyzed. Additionally, players performed 3 sprints over 30 m with timing gates at 5, 10, and 30 m. Significant differences (p < 0.05) between the fastest 20 and slowest 20 athletes, and elite (n = 25) and elite junior (n = 15) players in speed and force-time and power-time variables were determined using independent sample t-tests. The fastest and slowest sprinters over 10 m differed in peak power (PP) expressed relative to body weight. Over 30 m, there were significant differences in peak velocity and relative PP and rate of power development. There was no significant difference in speed over any distance between elite and elite junior rugby union players; however, a number of force and power variables including peak force, PP, force at 100 milliseconds from minimum force, and force and impulse 200 milliseconds from minimum force were significantly (p < 0.05) different between playing levels. Although only power values expressed relative to body weight were able to differentiate speed performance, both absolute and relative force and power values differentiated playing levels in professional rugby union players. For speed development in rugby union players, training strategies should aim to optimize the athlete's power to weight ratio, and lower body resistance training should focus on movement velocity. For player development to transition elite junior players to elite status, adding lean mass is likely to be most beneficial.

Background: The burden of mental, neurological, and substance (MNS) disorders is greater in low- and middle-income countries (LMICs). The rapid growth of digital health (i.e., eHealth) approaches offer new solutions for transforming pediatric mental health services and have the potential to address multiple resource and system barriers. However, little work has been done in applying eHealth to promote young children’s mental health in LMICs. It is also not clear how eHealth has been and might be applied to translating existing evidence-based practices/strategies (EBPs) to enable broader access to child mental health interventions and services. Methods: A scoping review was conducted to summarize current eHealth applications and evidence in child mental health. The review focuses on 1) providing an overview of existing eHealth applications, research methods, and effectiveness evidence in child mental health promotion (focused on children of 0–12 years of age) across diverse service contexts; and 2) drawing lessons learned from the existing research about eHealth design strategies and usability data in order to inform future eHealth design in LMICs. Results: Thirty-two (32) articles fitting our inclusion criteria were reviewed. The child mental health eHealth studies were grouped into three areas: i) eHealth interventions targeting families that promote child and family wellbeing; ii) eHealth for improving school mental health services (e.g., promote school staff’s knowledge and management skills); and iii) eHealth for improving behavioral health care in the pediatric care system (e.g., promote use of integrated patient-portal and electronic decision support systems). Most eHealth studies have reported positive impacts. Although most pediatric eHealth studies were conducted in high-income countries, many eHealth design strategies can be adapted and modified to fit LMIC contexts. Most user-engagement strategies identified from high-income countries are also relevant for populations in LMICs. Conclusions: This review synthesizes patterns of eHealth use across a spectrum of individual/family and system level of eHealth interventions that can be applied to promote child mental health and strengthen mental health service systems. This review also summarizes critical lessons to guide future eHealth design and delivery models in LMICs. However, more research in testing combinations of eHealth strategies in LMICs is needed.

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