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Reliability of meta-analyses to evaluate resistance training programmes

PainSci » bibliography » Arruda et al 2016
Tags: exercise, strength, self-treatment, treatment

One article on PainSci cites Arruda 2016: Strength Training Frequency

PainSci commentary on Arruda 2016: ?This page is one of thousands in the bibliography. It is not a general article: it is focused on a single scientific paper, and it may provide only just enough context for the summary to make sense. Links to other papers and more general information are provided wherever possible.

This short paper is a criticism of Schoenfeld et al, basically making the case that the data just wasn't homogenous enough for a good quality meta-analysis (a good apples-to-apples comparison). They raised specific concerns about a mixture of data about upper and lower body training, unknown variations in intensity, and the overlapping effects of different exercises. They think the study was “premature” and its results should be viewed “with caution.” Their conclusion is worth quoting in full:

In conclusion, considering the large number of variables involved in resistance training and the methodological inconsistencies in the current literature, it seems impossible to make comparisons of different studies or include different studies in the same analysis. For a meta-analysis to be valid, a large amount of data on homogeneous subgroups should accumulate for topics where there is strong consensus about which variables have theoretical importance, and this does not seem to be the case for resistance training studies. Because of this, the generalisation of meta-analyses should be viewed with caution until we have a large number of studies providing adequate control of variables. Rather than prematurely perform meta-analyses on differing resistance training variables, which are all hindered by the inherent limitations of meta-analyses (Shapiro, 1994) including low study numbers and study heterogeneity (Field, 2015), and serve only to reduce the complexity of resistance training variables to a single statistic, greater value can be obtained by designing and conducting studies of larger and homogenous samples that can adequately address the topics considered. Otherwise, we can be comparing oranges with apples or, worse, we can be assuming that oranges and apples are the same.

~ Paul Ingraham

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Arruda 2016 is about:

This page is part of the PainScience BIBLIOGRAPHY, which contains plain language summaries of thousands of scientific papers & others sources. It’s like a highly specialized blog. A few highlights:

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