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Interinstitutional differences in clinical pediatric exercise laboratory (CPEL) practices may affect patient care and efficacy of multicenter research. Purpose: To describe current practices/procedures in CPELs and explore differences in CPELs employing exercise physiologists to those that do not. Methods: A 40-item survey was distributed to CPELs in North America focusing on (1) staffing; (2) exercise stress testing (EST) volumes, reporting, and interpretation; and (3) EST procedures/protocols. Results: Of the 55 responses, 89% were in the United States, 85% were children’s hospitals with university affiliation, and 58% were cardiology specific. Exercise physiologists were employed in 56% of CPELs, and 78% had master’s degrees or higher. Certifications were required in most CPELs (92% emergency life-support, 27% professional, and 21% clinical). Median volume was 201 to 400 ESTs per year, 80% used treadmill, and 10% used cycle ergometer as primary modalities. Ninety-three percent of CPELs offered metabolic ESTs, 87% offered pulmonary function testing, 20% used institution-specific EST protocols, and 72% offered additional services such as cardiac/pulmonary rehabilitation. CPELS staffing exercise physiologists performed higher volumes of ESTs (P = .004), were more likely to perform metabolic ESTs (P = .028), participated in more research (P < .001), and provided services in addition to ESTs (P = .001). Conclusions: Heterogeneity in CPELs staffing and operation indicates need for standardization.

Purpose: Replicating the studies of Gibson et al and Brownstein et al to assess performance, and physiological, and perceived variables during a repeated sprint protocol (RSP) with standardized versus self-selected recovery in youth soccer players. Methods: Nineteen male soccer players (age 13.1 [1.3] y) completed 2 separate RSPs. RSP₁: 10 × 30-m sprints with 30-second recovery and RSP₂: 10 × 30-m sprints interspersed with self-selected recovery periods. Mean time of both 10 × 30-m RSPs and self-selected recovery periods of RSP₂ were assessed. Heart rate, blood lactate concentration, and rates of perceived exertion were measured following RSPs. Results: RSP₂ revealed longer recovery periods (RSP₁: 30.0 [0.0] s; RSP₂: 39.0 [7.7] s; P < .001; effect size d = 1.648) with shorter repeated sprint time (mean 30-m sprint time: RSP₁: 4.965 [0.256] s; RSP₂: 4.865 [0.227] s; P = .014; d = 0.414). Blood lactate concentration (P = .002–.005; d = 0.730–0.958), heart rate (P < .001; d = 1.353), and rates of perceived exertion (RSP₁: 14.9 [1.9]; RSP₂: 12.9 [2.1]; P = .016; d = 1.046) were higher following RSP₁. Conclusion: In contrast to the original studies, the present replication study demonstrated that self-selected recovery periods during a RSP leads to better repeated sprint performance compared with standardized recovery periods in youth soccer players. The better repeated sprint performance with individual recovery durations in RSP₂ was achieved with less physiological and perceived effort.

Purpose: To assess the training load, energy expenditure, dietary intake, and sleep quality and quantity of junior tennis players during a tennis training camp. Methods: Ten junior academy tennis players (14 [1] y) completed a 6-day camp with daily morning and afternoon training. Players wore accelerometer watches to measure activity energy expenditure and sleep. Global positioning system units were worn to monitor external training load (distance covered, maximum velocity, and PlayerLoad^™). Dietary intake was obtained from a food diary and supplementary food photography. Results: Players covered significantly more distance and had higher PlayerLoad^™ during morning sessions than afternoon sessions (5370 [505] m vs 4726 [697] m, P < .005, d = 3.2; 725 [109] a.u. vs 588 [96] a.u., P < .005, d = 4.0). Players also ran further (5624 [897] m vs 4933 [343] m, P < .05, d = 1.0) and reached higher maximum velocities (5.17 [0.44] m·s⁻¹ vs 4.94 [0.39] m·s⁻¹, P < .05, d = 0.3) during simulated match play compared with drill sessions. Mean daily energy expenditure was 3959 (630) kcal. Mean energy intake was 2526 (183) kcal, resulting in mean energy deficits of 1433 (683) kcal. Players obtained an average of 6.9 (0.8) hours of sleep and recorded 28 (7) nightly awakenings. Conclusions: Junior academy tennis players failed to achieve energy balance and recorded suboptimal sleep quantity and quality throughout the training camp.

Purpose: The purpose of this study was to examine the psychological responses to intermittent activities of varying intensities and types among children with and without asthma. Methods: A total of 37 children and adolescents (51% male, aged 8–16 y, 54% nonwhite, and 54% without asthma) participated in this study. Participants completed 5 exercises in the same order: self-paced walking, resistance activities, dance video, gamified obstacle course, and step test. In-task mood was assessed using the Feeling Scale, in-task perceived exertion was assessed via the ratings of perceived exertion scale, and postactivity enjoyment was assessed using the Physical Activity Enjoyment Scale. Results: There was a significant main effect of exercise type on mood (P < .001), ratings of perceived exertion (P < .001), and enjoyment (P < .002). There was not a significant main effect of asthma status on mood, ratings of perceived exertion, or enjoyment (Ps > .05). Children with asthma reported significantly lower in-task mood during the step exercise (P < .037) and reported significantly lower postactivity enjoyment after the walk and obstacle course exercises (Ps < .03). Conclusions: Regardless of differences by asthma status for in-task mood during the obstacle course and for postactivity enjoyment during the walk and step exercises, both children with and without asthma reported high in-task mood and postactivity enjoyment during all 5 exercises.

Objective: To compare the acute perceptive responses of different combined training methods in adolescents. Materials and Methods: The sample consisted of 50 adolescents, insufficiently active, aged between 14 and 18 years (58% female). The adolescents performed 2 sessions in a randomized order: moderate-intensity continuous training + resistance training (MICT + RT) and high-intensity interval training + resistance training (HIIT + RT). The rating of perceived exertion, affect, and satisfaction were measured by self-report in 5 moments during the combined training (HIIT or MICT—moments 1, 2, and 3; RT—moments 4 and 5) and 10 minutes after the end of the session. Results: During HIIT, adolescents reported higher values of rating of perceived exertion compared to the MICT session at moments 2 and 3 in both sexes (P < .05). In addition, at moments 2 and 3 of the HIIT session, female participants were reported to have a higher value of satisfaction compared to MICT (F = 3.953; P = .005; η ² = .067). Conclusion: During the execution of both HIIT + RT and MICT + RT protocols, adolescents showed an increase in the values of pleasure and satisfaction, regardless of sex.

Physical activities involving impact loading are important for improving bone strength and mineral density in children. There is little research quantifying impact loads associated with various high-impact activities. Purpose: Examine the magnitude of peak ground reaction forces (pGRF) across different jumping activities in children. Methods: Eight children between 8 and 12 years (9.63 [1.49] y; 1.42 [0.08] m; 33.69 [4.81] kg), performed 5 trials of a broad jump, countermovement jump, jumping jack, leap jump, and drop jump on a force plate. The pGRF were determined during the landing phase of each activity and expressed in units of body weight (BW). A repeated-measures analysis of variance was employed to assess differences in pGRF across activities. Results: Drop jump exhibited the greatest pGRF (3.09 [0.46] BW) in comparison with the vertical jumping jack (2.56 [0.21] BW; P < .001) and countermovement jump (2.45 [0.22] BW; P = .001), as well as the horizontal broad jump (2.25 [0.2] BW; P = .003), and leap jump (2.01 [0.1] BW; P = .002). Conclusion: Peak loads between 2 and 3.1 BW were exhibited across each jump activity, which is moderate compared with magnitudes in most jump interventions seeking to improve bone health. All conditions except drop jump exhibited loading <3 BW, suggesting these activities may not produce sufficient loads to improve bone outcomes.

Purpose: To identify the smallest change in handgrip strength (HGS) in children that can be considered of practical significance. Method: A total of 290 male and female children, aged 6–13 years, performed a HGS testing protocol 3 times within a 7-day period. The typical error of measurement (TE), coefficient of variation, and smallest worthwhile change (SWC) were calculated for each sex and age group (grade). Results: The TE for the combined group of grade 1 to 7 children was 1.3 kg. Changes in HGS associated with a small change were 1.3 kg, making it difficult for the HGS test to detect these changes. The TE was less than the medium (3.3 kg) and large (5.3 kg) changes in HGS for all the grades and sexes, making changes of these magnitudes more interpretable as they exceed the “noise” (TE) of the measurement. Conclusion: Changes in HGS greater than the TE and SWC can be considered real changes of practical significance. This provides researchers with an extra level of analysis when trying to determine the practical relevance of the observed changes.

Purpose: The authors examined associations between preschoolers’ daily glycemic variability, parents’ report of hypoglycemia fear, and preschoolers’ daily moderate to vigorous physical activity (MVPA) and sedentary behavior (SB) in 25 families of preschoolers with type 1 diabetes. Methods: Parents completed a valid measure of hypoglycemia fear, and their child wore an accelerometer for up to 7 days. Parents provided glucose data from their child’s devices. The authors used multiple regression and multilevel modeling to analyze their data. Results: Preschoolers (mean age 4.2 [1.7] y; 50% boys) engaged in a mean of 154.5 (59.6) and 339.2 (85.1) minutes of MVPA and SB per day, respectively, and parents reported relatively low levels of hypoglycemia worry and avoidance behaviors. Preschoolers’ SB (r = .19, P = .02) and MVPA (r = −.20, P = .01) levels were significantly correlated with parental hypoglycemia worry scores but not with parents’ hypoglycemia behavior scores (P = .15 and P = .92, respectively). While multilevel models did not show an association between MVPA and preschoolers’ glycemic variability, preschoolers who engaged in more daily SB experienced higher glycemic variability (P = .04). Conclusions: Research exploring MVPA, SB, and parental hypoglycemia fear in preschoolers with type 1 diabetes could have important clinical implications because it may reveal modifiable treatment targets that can impact preschoolers’ health and activity patterns.