Evidence map›Paper›PMID 41381816›Full record

SynthesisSports medicine (Auckland, N.Z.)2026

Non-Specific Strength Changes Between High- and Low-Load Isotonic Resistance Training: A Systematic Review and Meta-Analysis.

William B Hammert, Ryo Kataoka, Yujiro Yamada, Robert W Sallberg, Anna Kang, Samuel L Buckner, Jeremy P Loenneke

Abstract readSystematic ReviewMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Sports medicine (Auckland, N.Z.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

William B HammertKevser Ermin Applied Physiology Laboratory, Department of Health, Exercise Science, and Recreation Management, The University of Mississippi, P.O. Box 1848, University, MS, 38677, USA.
Ryo KataokaKevser Ermin Applied Physiology Laboratory, Department of Health, Exercise Science, and Recreation Management, The University of Mississippi, P.O. Box 1848, University, MS, 38677, USA.
Yujiro YamadaKevser Ermin Applied Physiology Laboratory, Department of Health, Exercise Science, and Recreation Management, The University of Mississippi, P.O. Box 1848, University, MS, 38677, USA.
Robert W SallbergKevser Ermin Applied Physiology Laboratory, Department of Health, Exercise Science, and Recreation Management, The University of Mississippi, P.O. Box 1848, University, MS, 38677, USA.
Anna KangKevser Ermin Applied Physiology Laboratory, Department of Health, Exercise Science, and Recreation Management, The University of Mississippi, P.O. Box 1848, University, MS, 38677, USA.
Samuel L BucknerExercise Science Program, USF Muscle Lab, University of South Florida, Tampa, FL, USA.
Jeremy P LoennekeKevser Ermin Applied Physiology Laboratory, Department of Health, Exercise Science, and Recreation Management, The University of Mississippi, P.O. Box 1848, University, MS, 38677, USA. jploenne@olemiss.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn comparisons between high- and low-load isotonic resistance training, it has become common to include non-specific strength tests (e.g., isometric and isokinetic strength tests), presumably in attempt to minimize the influence of training specificity and better understand the efficacy of low-load training for developing maximal strength. Many have suggested that high- and low-load isotonic resistance training are similarly effective for increasing non-specific strength, provided exercise is performed to task failure. However, little work has been completed to examine the accuracy of such statements.

objectiveWe aimed to quantitatively identify whether high-load isotonic resistance training results in differential changes in non-specific strength compared to low-load isotonic training.

methodsA systematic search of the literature was conducted using PubMed, Scopus, and Embase from inception to 14 June, 2025. To be included in the present review, a study needed to: (a) be performed in healthy adult humans ≥ 18 years of age; (b) include isotonic high- and low-load isotonic resistance training protocols that were prescribed to task failure; (c) have measured non-specific strength at both pre- and post-intervention via an isometric or isokinetic maximum strength task; (d) matched the number of strength tests between the high- and low-load training groups; (e) be published in a peer-reviewed journal; and (f) published in the English language. A random-effect meta-analysis using robust estimation variation was then implemented on the changes (i.e., pre- to post-intervention) in non-specific strength between high- and low-load isotonic resistance training.

resultsThe literature search yielded 7885 unique articles, of which ten studies were selected for inclusion in the present analysis. Using effect size values calculated from the change score standard deviations resulted in 44 ES from ten studies (245 total participants; high load, n = 114; low load, n = 131). The overall effect size (Cohen's d) was 0.322 with a standard error of 0.17, a 95% confidence interval of - 0.08 to 0.72 (p = 0.104), and 95% prediction intervals that ranged from - 0.45 to 1.1. A supplemental analysis using pre-standard deviations resulted in similar conclusions.

conclusionsThe results of the current analysis were inconclusive as to whether high- and low-load isotonic training induced differential changes in non-specific strength. The overall effect size appeared to be biased towards favoring high-load isotonic training; however, the confidence intervals were wide and crossed zero.

Indexed as

Muscle StrengthResistance TrainingHumans

Identifiers

PMID41381816
PMCPMC13018011

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.