{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T10:10:23Z","timestamp":1789121423665,"version":"build-2803163510"},"reference-count":55,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T00:00:00Z","timestamp":1789084800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Funct. Morphol. Kinesiol.","JFMK"],"abstract":"<jats:p>Despite major advances in exercise physiology, biomechanics, and mechanobiology, exercise science still lacks a clear conceptual definition of the mechanical stimulus experienced by skeletal muscle during resistance training. Current approaches rely on diverse external, internal, and biomechanical variables (e.g., volume-load, force, power, velocity, time under tension, or muscle architecture), yet none individually captures the muscle-specific mechanical exposure relevant to muscular adaptation. This conceptual inconsistency limits comparisons across studies, complicates training prescription, and hinders the development of individualized monitoring strategies. This integrative review critically synthesizes current evidence from mechanobiology, skeletal muscle physiology, biomechanics, and resistance training to examine how mechanical stimuli are currently conceptualized, quantified, and interpreted. Based on this synthesis, we propose a working definition of Mechanical Dose as the cumulative, muscle-specific mechanical exposure experienced over a defined time window, characterized by loading magnitude, rate, duration, frequency, and spatial distribution, and conditioned by contraction mode and muscle\u2013tendon geometry. Rather than representing a directly measurable variable, mechanical dose is presented as a latent conceptual construct that can only be estimated through combinations of biomechanical, physiological, and morphological indicators. Building upon this definition, we introduce an integrative conceptual framework linking external load, movement biomechanics, mechanical dose, mechanotransduction, and tissue adaptation. We further discuss how this framework may guide future research on the interpretation of field-based monitoring, resistance training prescription, recovery management, and future explainable artificial intelligence approaches in sport science. By reframing mechanical dose as the central construct connecting biomechanics and biological adaptation, this review provides a unified conceptual basis for future research and contributes toward a more biologically informed paradigm of exercise prescription and monitoring.<\/jats:p>","DOI":"10.3390\/jfmk11030368","type":"journal-article","created":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T08:17:42Z","timestamp":1789114662000},"page":"368","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards a Conceptual Framework for Mechanical Dose in Skeletal Muscle: Integrating Mechanobiology and Resistance Training"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5956-9790","authenticated-orcid":false,"given":"Pedro","family":"Morou\u00e7o","sequence":"first","affiliation":[{"name":"Department of Sport, Exercise and Health, University of Leiria and Oeste, 2411-901 Leiria, Portugal"},{"name":"National Program for Physical Activity Promotion, Directorate-General of Health, 1049-005 Lisbon, Portugal"},{"name":"Cl\u00ednica Espregueira, FIFA Medical Centre of Excellence, 4350-415 Porto, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1211","DOI":"10.1136\/bjsports-2023-106807","article-title":"Resistance training prescription for muscle strength and hypertrophy in healthy adults: A systematic review and Bayesian network meta-analysis","volume":"57","author":"Currier","year":"2023","journal-title":"Br. 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