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The impact of test loads on the accuracy of 1RM prediction using the load-velocity relationship

Overview of attention for article published in BMC Sports Science, Medicine and Rehabilitation, May 2018
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  • Good Attention Score compared to outputs of the same age (67th percentile)

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8 tweeters

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2 Dimensions

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51 Mendeley
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Title
The impact of test loads on the accuracy of 1RM prediction using the load-velocity relationship
Published in
BMC Sports Science, Medicine and Rehabilitation, May 2018
DOI 10.1186/s13102-018-0099-z
Pubmed ID
Authors

Mark G. L. Sayers, Michel Schlaeppi, Marina Hitz, Silvio Lorenzetti

Abstract

Numerous methods have been proposed that use submaximal loads to predict one repetition maximum (1RM). One common method applies standard linear regression equations to load and average vertical lifting velocity (Vmean) data developed during squat jumps or three bench press throw (BP-T). The main aim of this project was to determine which combination of three submaximal loads during BP-T result in the most accurate prediction of 1RM Smith Machine bench press strength in healthy individuals. In this study combinations of three BP-T loads were used to predict 1RM Smith Machine bench press strength. Additionally, we examined whether regression models developed using peak vertical bar velocity (Vpeak), rather than Vmean, provide the most accurate prediction of Smith Machine bench press 1RM. 1RM Smith Machine bench press strength was measured directly in 12 healthy regular weight trainers (body mass = 80.8 ± 5.7 kg). Two to three days later a linear position transducer attached to the collars on a Smith Machine was used to record Vmean and Vpeak during BP-T between 30 and 70% of 1RM (10% increments). Repeated measures analysis of variance testing showed that the mean values for slope and ordinate intercept for the regression models at each of the load ranges differed significantly depending on whether Vmean or Vpeak were used in the prediction models (P < 0.001). Conversely, the abscissa intercept did not differ significantly between either measure of vertical bar velocity at each load range. The key finding in this study was that 1RM Smith Machine bench press strength can be determined with high relative accuracy by examining Vmean and Vpeak during BP-T over three loads, with the most precise models using Vpeak during loads representing 30, 40 and 50% of 1RM (R 2  = 0.96, SSE = 4.2 kg). These preliminary findings indicate that exercise programmers working with normal healthy populations can accurately predict Smith Machine 1RM bench press strength using relatively light load Smith Machine BP-T testing, avoiding the need to expose their clients to potentially injurious loads.

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 24%
Student > Bachelor 9 18%
Professor 5 10%
Student > Postgraduate 4 8%
Researcher 4 8%
Other 9 18%
Unknown 8 16%
Readers by discipline Count As %
Sports and Recreations 25 49%
Nursing and Health Professions 5 10%
Computer Science 1 2%
Agricultural and Biological Sciences 1 2%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 2 4%
Unknown 16 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 July 2018.
All research outputs
#4,139,121
of 15,809,016 outputs
Outputs from BMC Sports Science, Medicine and Rehabilitation
#99
of 231 outputs
Outputs of similar age
#89,938
of 281,898 outputs
Outputs of similar age from BMC Sports Science, Medicine and Rehabilitation
#1
of 1 outputs
Altmetric has tracked 15,809,016 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 231 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.4. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 281,898 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them