Pierobon, AndrésKrägeloh, Chris2026-03-312026-03-312026-03-14Musculoskelet Sci Pract, ISSN: 2468-8630 (Print); 2468-7812 (Online), Elsevier BV, 83, 103544-. doi: 10.1016/j.msksp.2026.1035442468-86302468-7812http://hdl.handle.net/10292/20848INTRODUCTION: The assessment of physical function is central to clinical decision-making in rehabilitation and musculoskeletal care. Patient-reported outcome measures (PROMs) are widely used because they are simple, cost-effective, and patient-centred. However, many PROMs were developed using Classical Test Theory, which assumes equal distances between ordinal response options and overlooks differences in item difficulty and person ability. These limitations can reduce measurement precision and cause ceiling effects, particularly among individuals with high physical function. Rasch analysis, a modern psychometric approach based on Item Response Theory, addresses these issues and enhances the measurement properties of PROMs. PURPOSE: This article introduces Rasch analysis as a methodological framework for developing and refining PROMs to assess physical function. It explains the principles of the Rasch model, its application to dichotomous and polytomous data, and how it transforms ordinal scores into interval-level measurements. Example figures illustrate key outputs such as category probability curves, person-item maps, and threshold ordering. Advantages, limitations, and practical considerations for integrating Rasch analysis into outcome measure development are discussed. IMPLICATIONS: Rasch analysis enables clinicians and researchers to better understand item difficulty and estimate patients' functional ability with greater precision. Incorporating Rasch-developed PROMs enhances the validity, interpretability, and responsiveness of functional assessments. Clinicians can use these measures with increased confidence when monitoring progress and evaluating treatment outcomes, supporting more accurate goal setting and improved rehabilitation practice.© 2026 The Authors. Published by Elsevier Ltd. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You are not required to obtain permission to reuse this article.4201 Allied Health and Rehabilitation Science42 Health SciencesBehavioral and Social SciencePhysical RehabilitationPrecision MedicineRehabilitation7.1 Individual care needs8.4 Research design and methodologies (health services)7.3 Management and decision making3 Good Health and Well BeingRasch Analysis in the Development of Self-reported Outcome Measures to Assess Physical FunctionJournal ArticleOpenAccess10.1016/j.msksp.2026.103544