Timothy B Davies1, Derek L Tran2,3,4, Clorinda M Hogan2, G Gregory Haff5,6, Christopher Latella5,7. 1. Discipline of Exercise and Sport Science, Faculty of Medicine and Health, Sydney School of Health Sciences, The University of Sydney, Camperdown, NSW, 2050, Australia. timothy.davies@sydney.edu.au. 2. Discipline of Exercise and Sport Science, Faculty of Medicine and Health, Sydney School of Health Sciences, The University of Sydney, Camperdown, NSW, 2050, Australia. 3. Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia. 4. Department of Cardiology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia. 5. School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia. 6. Directorate of Physiotherapy and Sport, University of Salford, Greater Manchester, UK. 7. Neurophysiology Research Laboratory, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.
Abstract
BACKGROUND: The acute responses to cluster set resistance training (RT) have been demonstrated. However, as compared to traditional sets, the effect of cluster sets on muscular and neuromuscular adaptations remains unclear. OBJECTIVE: To compare the effects of RT programs implementing cluster and traditional set configurations on muscular and neuromuscular adaptations. METHODS: Systematic searches of Embase, Scopus, Medline and SPORTDiscus were conducted. Inclusion criteria were: (1) randomized or non-randomized comparative studies; (2) publication in English; (3) participants of all age groups; (4) participants free of any medical condition or injury; (5) cluster set intervention; (6) comparison intervention utilizing a traditional set configuration; (7) intervention length ≥ three weeks and (8) at least one measure of changes in strength/force/torque, power, velocity, hypertrophy or muscular endurance. Raw data (mean ± SD or range) were extracted from included studies. Hedges' g effect sizes (ES) ± standard error of the mean (SEM) and 95% confidence intervals (95% CI) were calculated. RESULTS: Twenty-nine studies were included in the meta-analysis. No differences between cluster and traditional set configurations were found for strength (ES = - 0.05 ± 0.10, 95% CI - 0.21 to 0.11, p = 0.56), power output (ES = 0.02 ± 0.10, 95% CI - 0.17 to 0.20, p = 0.86), velocity (ES = 0.15 ± 0.13, 95% CI - 0.10 to 0.41, p = 0.24), hypertrophy (ES = - 0.05 ± 0.14, 95% CI - 0.32 to 0.23, p = 0.73) or endurance (ES = - 0.07 ± 0.18, 95% CI - 0.43 to 0.29, p = 0.70) adaptations. Moreover, no differences were observed when training volume, cluster set model, training status, body parts trained or exercise type were considered. CONCLUSION: Collectively, both cluster and traditional set configurations demonstrate equal effectiveness to positively induce muscular and neuromuscular adaptation(s). However, cluster set configurations may achieve such adaptations with less fatigue development during RT which may be an important consideration across various exercise settings and stages of periodized RT programs.
BACKGROUND: The acute responses to cluster set resistance training (RT) have been demonstrated. However, as compared to traditional sets, the effect of cluster sets on muscular and neuromuscular adaptations remains unclear. OBJECTIVE: To compare the effects of RT programs implementing cluster and traditional set configurations on muscular and neuromuscular adaptations. METHODS: Systematic searches of Embase, Scopus, Medline and SPORTDiscus were conducted. Inclusion criteria were: (1) randomized or non-randomized comparative studies; (2) publication in English; (3) participants of all age groups; (4) participants free of any medical condition or injury; (5) cluster set intervention; (6) comparison intervention utilizing a traditional set configuration; (7) intervention length ≥ three weeks and (8) at least one measure of changes in strength/force/torque, power, velocity, hypertrophy or muscular endurance. Raw data (mean ± SD or range) were extracted from included studies. Hedges' g effect sizes (ES) ± standard error of the mean (SEM) and 95% confidence intervals (95% CI) were calculated. RESULTS: Twenty-nine studies were included in the meta-analysis. No differences between cluster and traditional set configurations were found for strength (ES = - 0.05 ± 0.10, 95% CI - 0.21 to 0.11, p = 0.56), power output (ES = 0.02 ± 0.10, 95% CI - 0.17 to 0.20, p = 0.86), velocity (ES = 0.15 ± 0.13, 95% CI - 0.10 to 0.41, p = 0.24), hypertrophy (ES = - 0.05 ± 0.14, 95% CI - 0.32 to 0.23, p = 0.73) or endurance (ES = - 0.07 ± 0.18, 95% CI - 0.43 to 0.29, p = 0.70) adaptations. Moreover, no differences were observed when training volume, cluster set model, training status, body parts trained or exercise type were considered. CONCLUSION: Collectively, both cluster and traditional set configurations demonstrate equal effectiveness to positively induce muscular and neuromuscular adaptation(s). However, cluster set configurations may achieve such adaptations with less fatigue development during RT which may be an important consideration across various exercise settings and stages of periodized RT programs.
Authors: G Gregory Haff; Adrian Whitley; Lora B McCoy; Harold S O'Bryant; J Lon Kilgore; Erin E Haff; Kyle Pierce; Michael H Stone Journal: J Strength Cond Res Date: 2003-02 Impact factor: 3.775
Authors: James J Tufano; Jenny A Conlon; Sophia Nimphius; Lee E Brown; Laurent B Seitz; Bryce D Williamson; G Gregory Haff Journal: Int J Sports Physiol Perform Date: 2016-08-24 Impact factor: 4.010
Authors: Scott J Dankel; Kevin T Mattocks; Matthew B Jessee; Samuel L Buckner; J Grant Mouser; Jeremy P Loenneke Journal: Eur J Appl Physiol Date: 2017-08-03 Impact factor: 3.078
Authors: James J Tufano; Jenny A Conlon; Sophia Nimphius; Lee E Brown; Harry G Banyard; Bryce D Williamson; Leslie G Bishop; Amanda J Hopper; G Gregory Haff Journal: Int J Sports Physiol Perform Date: 2016-09-06 Impact factor: 4.010
Authors: Urs Granacher; Melanie Lesinski; Dirk Büsch; Thomas Muehlbauer; Olaf Prieske; Christian Puta; Albert Gollhofer; David G Behm Journal: Front Physiol Date: 2016-05-09 Impact factor: 4.566
Authors: Derek L Tran; Hannah Gibson; Andrew J Maiorana; Charlotte E Verrall; David W Baker; Melanie Clode; David R Lubans; Diana Zannino; Andrew Bullock; Suzie Ferrie; Julie Briody; Peter Simm; Vishva Wijesekera; Michelle D'Almeida; Sally E Gosbell; Glen M Davis; Robert Weintraub; Anthony C Keech; Rajesh Puranik; Martin Ugander; Robert Justo; Dominica Zentner; Avik Majumdar; Leeanne Grigg; Jeff S Coombes; Yves d'Udekem; Norman R Morris; Julian Ayer; David S Celermajer; Rachael Cordina Journal: Front Pediatr Date: 2022-01-06 Impact factor: 3.418