From Signal to Biological Meaning: A Systematic Review of Construct-Validity Evidence for External Training Load Metrics in Sport
- 1School of Physical Education, Yunnan Normal University, Kunming, China
Abstract
Background: External training load (ETL) metrics describe external work but often imply metabolic demand, neuromuscular load, tissue stress, fatigue, or adaptation. These interpretations require construct-validity evidence beyond device accuracy or reliability.
Methods: We searched MEDLINE, Embase, Web of Science, Scopus, and Academic Search Ultimate from inception to March 2026; final searches were on 1 March, except Embase on 7 March. Eligible peer-reviewed English studies evaluated an ETL indicator and its interpreted construct in athletes or physically active participants. Reports limited to technical accuracy, reliability, measurement error, or descriptive monitoring were excluded. We adjudicated one page-anchored construct-evidence chain per study. Measurement-property analyses used review-adapted COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN); prediction models used the Prediction model Risk Of Bias ASsessment Tool plus Artificial Intelligence (PROBAST+AI); other designs used Joanna Briggs Institute (JBI) tools. Conceptual and methodological heterogeneity across metrics, target constructs, comparators, and study designs precluded meaningful meta-analysis; therefore, we used evidence maps and narrative synthesis.
Results: Forty-six studies contributed 46 primary evidence chains. Main study samples ranged from 7 to 71 participants, with smaller analysis-specific subsamples; most studies included only men. Construct attribution was explicit in 14 studies and explicit but qualified in 26; four were implicit but qualified and two reverse-target. Thirteen studies (28%) used a direct construct-matched criterion. Alternative proxies supported 16 studies (35%), condition or group contrasts 11 (24%), and mixed routes six (13%). General exercise intensity was the most frequent construct family (15 studies, 33%). Appraisal identified common limitations in hypotheses testing and analysis. Nineteen studies (41%) explicitly distinguished technical performance from construct interpretation, and 12 (26%) explicitly justified comparator selection.
Conclusions: Most ETL metrics were supported as descriptions of external movement, work, or exposure rather than direct indicators of biological demand or response. Biological interpretations require an explicit construct, plausible mechanism, directional hypothesis, and construct-matched reference. Heterogeneity and methodological limitations reduce confidence in biological interpretations.
Graphical abstract:
Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s40798-026-01133-7.
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BibTeX
@article{li2026from,
title = {{From Signal to Biological Meaning: A Systematic Review of Construct-Validity Evidence for External Training Load Metrics in Sport}},
author = {Houchen Li and Qingqiong Yang and Bin Wang},
journal = {Sports Medicine - Open},
year = {2026},
month = oct,
doi = {10.1186/s40798-026-01133-7},
url = {https://doi.org/10.1186/s40798-026-01133-7},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - From Signal to Biological Meaning: A Systematic Review of Construct-Validity Evidence for External Training Load Metrics in Sport
AU - Houchen Li
AU - Qingqiong Yang
AU - Bin Wang
PY - 2026
DA - 2026/10/31
JO - Sports Medicine - Open
DO - 10.1186/s40798-026-01133-7
UR - https://doi.org/10.1186/s40798-026-01133-7
AB - Background: External training load (ETL) metrics describe external work but often imply metabolic demand, neuromuscular load, tissue stress, fatigue, or adaptation. These interpretations require construct-validity evidence beyond device accuracy or reliability. Methods: We searched MEDLINE, Embase, Web of Science, Scopus, and Academic Search Ultimate from inception to March 2026; final searches were on 1 March, except Embase on 7 March. Eligible peer-reviewed English studies evaluated an ETL indicator and its interpreted construct in athletes or physically active participants. Reports limited to technical accuracy, reliability, measurement error, or descriptive monitoring were excluded. We adjudicated one page-anchored construct-evidence chain per study. Measurement-property analyses used review-adapted COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN); prediction models used the Prediction model Risk Of Bias ASsessment Tool plus Artificial Intelligence (PROBAST+AI); other designs used Joanna Briggs Institute (JBI) tools. Conceptual and methodological heterogeneity across metrics, target constructs, comparators, and study designs precluded meaningful meta-analysis; therefore, we used evidence maps and narrative synthesis. Results: Forty-six studies contributed 46 primary evidence chains. Main study samples ranged from 7 to 71 participants, with smaller analysis-specific subsamples; most studies included only men. Construct attribution was explicit in 14 studies and explicit but qualified in 26; four were implicit but qualified and two reverse-target. Thirteen studies (28%) used a direct construct-matched criterion. Alternative proxies supported 16 studies (35%), condition or group contrasts 11 (24%), and mixed routes six (13%). General exercise intensity was the most frequent construct family (15 studies, 33%). Appraisal identified common limitations in hypotheses testing and analysis. Nineteen studies (41%) explicitly distinguished technical performance from construct interpretation, and 12 (26%) explicitly justified comparator selection. Conclusions: Most ETL metrics were supported as descriptions of external movement, work, or exposure rather than direct indicators of biological demand or response. Biological interpretations require an explicit construct, plausible mechanism, directional hypothesis, and construct-matched reference. Heterogeneity and methodological limitations reduce confidence in biological interpretations. Graphical abstract: Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s40798-026-01133-7.
SN - 2199-1170
SN - 2198-9761
ER -