The Efficacy of Individualized Last Repetition Velocities for Autoregulating and Monitoring in Resistance Training
dc.contributor.advisor | Chilibeck, Philip D | |
dc.contributor.committeeMember | Lovo, Stacey G | |
dc.contributor.committeeMember | Candow, Darren G | |
dc.contributor.committeeMember | Kim, Soo Y | |
dc.contributor.committeeMember | Blackburn, David F | |
dc.contributor.committeeMember | Banyard, Harry G | |
dc.creator | Hickmott, Landyn M. | |
dc.date.accessioned | 2024-01-08T19:56:56Z | |
dc.date.available | 2024-01-08T19:56:56Z | |
dc.date.copyright | 2023 | |
dc.date.created | 2023-12 | |
dc.date.issued | 2024-01-08 | |
dc.date.submitted | December 2023 | |
dc.date.updated | 2024-01-08T19:56:57Z | |
dc.description.abstract | Traditional resistance training (RT) methods often involve a fixed prescription based on a pre- determined percentage of one-repetition maximum (1RM); however, a plethora of variables may impact an individual’s performance on a micro- and macro-level: fitness, fatigue, readiness, amongst several others. Autoregulated resistance training has developed as a potential framework to rectify traditional methods by systematically measuring and adjusting the programming prescription on a short-, medium-, and long-term monitoring basis according to an individual’s performance and context-specific goals. Although initial findings have provided some evidence to support the efficacy of autoregulation on muscular adaptations in college-aged resistance- trained males, the available evidence is unclear whether autoregulation indeed provides a greater advantage over traditional methods for additional neuromuscular adaptations, performance outcomes, and functional measures in varying populations and females. Therefore, the primary purpose of this PhD thesis/dissertation was four-fold. The initial purpose was to systematically review and meta-analyze the existing evidence on the effect of load and volume autoregulation on muscular strength and hypertrophy adaptations. Autoregulated compared to traditional load prescription resulted in significantly greater increases in 1RM strength. Autoregulating volume with lower and higher magnitudes of intra-set fatigue were most effective for improving 1RM strength and hypertrophy; respectively. The second purpose was to conceptualize a theoretical velocity-based training model based on the advantages and limitations of the current traditional and autoregulation methods: the Individualized Last Repetition Velocity Model (LRV Model), which is described in a narrative review. The third purpose was to compare the accuracy of subjective estimations to objective velocities (an iteration of the LRV Model) at quantifying proximity to failure for the bench press in resistance trained males and females across numerous parameters, in which objective velocities displayed significantly greater accuracy. The final purpose was to compare the efficacy of traditional methods, subjective autoregulation, and objective autoregulation (the LRV Model iteration) for load prescription on neuromuscular adaptations, performance outcomes, and functional measures in older adult males and females. Objective autoregulation elicited the best improvements in bench press strength and knee extensor hypertrophy. This thesis provides novelty regarding the efficacy of individualized average concentric last repetition velocities for autoregulating and monitoring. | |
dc.format.mimetype | application/pdf | |
dc.identifier.uri | https://hdl.handle.net/10388/15412 | |
dc.language.iso | en | |
dc.subject | Resistance Training | |
dc.subject | Autoregulating | |
dc.subject | Monitoring | |
dc.subject | Velocity-Based Training | |
dc.subject | Individualized Last Repetition Velocities | |
dc.title | The Efficacy of Individualized Last Repetition Velocities for Autoregulating and Monitoring in Resistance Training | |
dc.type | Thesis | |
dc.type.material | text | |
thesis.degree.department | Medicine | |
thesis.degree.discipline | Health Sciences | |
thesis.degree.grantor | University of Saskatchewan | |
thesis.degree.level | Doctoral | |
thesis.degree.name | Doctor of Philosophy (Ph.D.) |