Improving single-subject change assessment: deriving the minimal detectable change of questionnaires' ordinal scores from Rasch analysis measures.
Purpose: The minimal detectable change (MDC) of questionnaire ordinal scores (MDCord) is the smallest score difference exceeding the measurement error. Being ordinal, it suffers from flaws, successfully addressed by the Rasch analysis (RA) and its robust interval measures. However, RA measures strug...
| Publicado en: | Disability & Rehabilitation Vol. 48; no. 7; pp. 2169 - 2187 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Apr2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=192729047&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 192729047 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09638288 B73 jtl: Disability & Rehabilitation issn: 09638288 maglogo: Y pubinfo: dt: Apr2026 vid: 48 iid: 7 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 192729047 188046929 192729047 192729047 10.1080/09638288.2025.2547398 192729047 ppf: 2169 ppct: 18 formats: tig: atl: Improving single-subject change assessment: deriving the minimal detectable change of questionnaires' ordinal scores from Rasch analysis measures. aug: au: Caronni, Antonio Picardi, Michela Scarano, Stefano Rota, Viviana Amadei, Maurizio affil: Department of Biomedical Sciences for Health, University of Milan, Milan, Italy sug: subj: Psychometrics Sensitivity and Specificity Reproducibility of Results Rasch Analysis Outcomes (Health Care) Evaluation Funding Source Italy Human Methodological Research Data Analysis Software Descriptive Statistics Questionnaires Measurement Error Upper Extremity Motor Skills Models, Statistical Decision Making, Clinical Activities of Daily Living Professional Practice, Evidence-Based Clinical Assessment Tools ab: Purpose: The minimal detectable change (MDC) of questionnaire ordinal scores (MDCord) is the smallest score difference exceeding the measurement error. Being ordinal, it suffers from flaws, successfully addressed by the Rasch analysis (RA) and its robust interval measures. However, RA measures struggle to become established, likely because scores are more straightforward. This study aims to derive the MDCord of two upper limb measures, the Fugl-Meyer Assessment-Upper Limb (FMA-UL) and the Functional Assessment Test for Upper Limb (FAST-UL), from the MDC of their RA interval measures (MDCint). Methods: Two methodologies are applied. The first, based on a sensitivity and specificity analysis, defines the MDCord as the score difference with the highest accuracy in identifying a change per the MDCint. The second derives the MDCord from RA strata, another MDCint formulation. Various computations are tested, possibly resulting in slightly different MDCord. Results: The MDCord of the FMA-UL from sensitivity and specificity analysis was 8 and 4–5 for the FAST-UL. Using RA strata, the FMA-UL MDCord was 8–10, and that of the FAST-UL was 4–5. Conclusions: An easy-to-use MDCord has been provided for the FMA-UL and the FAST-UL, which, anchored to the RA MDCint, benefits from its robust measurement properties. Clinical Trials Registry: NA. IMPLICATIONS FOR REHABILITATION: The Fugl-Meyer Assessment-Upper Limb (FMA-UL) and the Functional Assessment Test for Upper Limb (FAST-UL) provide total scores of upper limb dexterity, with the FMA-UL being a recognised criterion standard for assessment in central paresis. The Minimal Detectable Change (MDC) values for the FMA-UL and FAST-UL total scores were derived from Rasch analysis indices, yielding a range of 8–10 points for the former and 4–5 points for the latter. The MDCs for the FMA-UL and FAST-UL derived in this study allow clinicians and clinical researchers to precisely evaluate how an individual patient's upper limb impairment has changed over time. For psychometricians, this paper introduces new methods for obtaining simple, ordinal MDCs anchored on the Rasch analysis framework. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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