Objective: To (1) compare the 1-repetition-maximum (1RM) performance between the push press, push jerk, and split jerk and (2) explore these differences between weightlifters, CrossFit athletes, and a mixed group of athletes. Methods: Forty-six resistance-trained males (age 28.8 [6.4] y; height 180.0 [6.0] cm; body mass 84.1 [10.2] kg; weightlifting training experience 3.64 [3.14] y) participated in this study. The 1RM performance of the push press, push jerk, and split jerk was assessed during the same session in a sequential order (ie, combined 1RM assessment method). Thirty-six participants were retested to determine between-sessions reliability of the 1RM values. Results: Intraclass correlation coefficients (ICCs) and associated 95% confidence intervals (CIs) showed a high between-sessions reliability for the push press (ICC = .98; 95% CI, .95–.99), push jerk (ICC = .99; 95% CI, .98–1.00), and split jerk (ICC = .99; 95% CI, .98–1.00). There was a significant main effect of exercise (η 2 = .101) and exercise × group interaction (η 2 = .012) on 1RM performance (P < .001), whereas the main effect of group did not reach statistical significance (P = .175). Conclusions: This study provides evidence that the weightlifting overhead press derivatives affect 1RM performance. In addition, the interaction of exercise and sport group was caused by the higher differences in 1RM performance between exercises for weightlifters compared with CrossFit and a mixed group of athletes. Therefore, strength and conditioning professionals should be aware that the differences in 1RM performance between weightlifting overhead-press derivatives may be affected by sport group.
Marcos A. Soriano, Amador García-Ramos, Antonio Torres-González, Joaquín Castillo-Palencia, Pedro J. Marín, Pilar Sainz de Baranda and Paul Comfort
Kelley Pettee Gabriel, Adriana Pérez, David R. Jacobs Jr, Joowon Lee, Harold W. Kohl III and Barbara Sternfeld
Background: Single-method assessment of physical activity (PA) has limitations. The utility and cross-validation of a composite PA score that includes reported and accelerometer-derived PA data has not been evaluated. Methods: Participants attending the Year 20 exam were randomly assigned to the derivation (two-thirds) or validation (one-third) data set. Principal components analysis was used to create a composite score reflecting Year 20 combined reported and accelerometer PA data. Generalized linear regression models were constructed to estimate the variability explained (R 2) by each PA assessment strategy (self-report only, accelerometer only, composite score, or self-report plus accelerometer) with cardiovascular health indicators. This process was repeated in the validation set to determine cross-validation. Results: At Year 20, 3549 participants (45.2 [3.6] y, 56.7% female, and 53.5% black) attended the clinic exam and 2540 agreed to wear the accelerometer. Higher R 2 values were obtained when combined assessment strategies were used; however, the approach yielding the highest R 2 value varied by cardiovascular health outcome. Findings from the cross-validation also supported internal study validity. Conclusions: Findings support continued refinement of methodological approaches to combine data from multiple sources to create a more robust estimate that reflects the complexities of PA behavior.
Matthew Weston, Warren Gregson, Carlo Castagna, Simon Breivik, Franco M. Impellizzeri and Ric J. Lovell
Athlete case studies have often focused on the training outcome and not the training process. Consequently, there is a dearth of information detailing longitudinal training protocols, yet it is the combined assessment of both outcome and process that enhances the interpretation of physical test data. We were provided with a unique opportunity to assess the training load, physical match performance, and physiological fitness of an elite soccer referee from the referee’s final season before attaining full-time, professional status (2002) until the season when he refereed the 2010 UEFA Champions League and FIFA World Cup finals. An increased focus on on-field speed and gym-based strength training was observed toward the end of the study period and longitudinal match data showed a tendency for decreased total distances but an increased intensity of movements. Laboratory assessments demonstrated that VO2max remained stable (52.3 vs 50.8 mL-kg–1-min–1), whereas running speed at the lactate threshold (14.0 vs 12.0 km-h-1) and running economy (37.3 vs 43.4 mLkg–1min–1) both improved in 2010 compared with 2002.
Kelley D. Henderson, Sarah A. Manspeaker and Zevon Stubblefield
. 4 There is not a conclusive set of criteria for the diagnosis of ER among athletes, therefore, diagnosis typically requires the combined assessment of both clinical exam and laboratory findings. 2 , 5 Signs of ER often include extreme myalgia, cola-colored urine, muscle weakness and stiffness, and
Theresa C. Hauge, Garrett E. Katz, Gregory P. Davis, Kyle J. Jaquess, Matthew J. Reinhard, Michelle E. Costanzo, James A. Reggia and Rodolphe J. Gentili
. Gentili , R.J. , Jaquess , K.J. , Shuggi , I.M. , Shaw , E.P. , Oh , H. , Lo , L.C. , . . . Hatfield , B.D. ( 2018 ). Combined assessment of attentional reserve and cognitive-motor effort under various levels of challenge with a dry EEG system . Psychophysiology, 55 ( 6 ), e13059 . 10
Bente M. Raafs, Esther G.A. Karssemeijer, Lizzy Van der Horst, Justine A. Aaronson, Marcel G.M. Olde Rikkert and Roy P.C. Kessels
of doubt, the studies were discussed with a second reviewer (E.G.A. Karssemeijer) until a consensus about the conclusion was reached. The combined assessment of all of the domains was used to define a total risk of bias judgment. Data Extraction and Statistical Analysis The software package