Efficacy of Supersets Versus Traditional Sets in Whole-Body Multiple-Joint Resistance Training: A Randomized Controlled Trial

Abstract Iversen, VM, Eide, VB, Unhjem, BJ, and Fimland, MS. Efficacy of supersets versus traditional sets in whole-body multiple-joint resistance training: A randomized controlled trial. J Strength Cond Res 38(8): 1372–1378, 2024—Time constraints often hinder exercise engagement, necessitating exploration of time-efficient resistance training methods. Superset training, where 2 exercises are performed successively with minimal rest, nearly halves session duration but is metabolically demanding, possibly reducing strength gains. In a randomized controlled trial with blinded test leaders, we examined the efficacy of supersets versus traditional sets in a full-body, multiple-joint resistance training workout on maximal strength in the trained exercises. Subjects took part in a 3-week introductory training phase before baseline testing to ensure they were thoroughly familiarized. Next, they were randomized to a superset- or a traditional-set group, performing 10 weeks of heavy multiple-joint resistance training twice per week. The exercise programs consisted of leg press, bench press, lat pull-down, and seated rows. The traditional training group had a 5.2-kg higher improvement in pull-down than the superset group ( p = 0.033), and a close to significant 4.8-kg higher improvement in seated rows ( p = 0.073). The improvements in leg press and bench press were quite similar for both groups ( p = 0.507–0.527). There were no changes between groups in body composition outcomes (0.151–0.640), but both groups increased muscle mass and reduced fat mass ( p < 0.05). In conclusion, superset training of multi-joint exercises hampered maximal strength gains somewhat compared with traditional-set training. However, there were very similar improvements in body composition, and strength gains were observed for all exercises in the superset group. Thus, whole-body, multiple-joint superset resistance training could be a viable time-saving approach.