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Addressing the Targeting Range of the ABILHAND-56 in Relapsing-remitting Multiple Sclerosis: A Mixed Methods Psychometric Study

Abstract

Background: ABILHAND, a manual ability patient-reported outcome instrument originally developed for stroke patients, has been used in multiple sclerosis clinical trials; however, psychometric analyses indicated the measure's limited measurement range and precision in higher-functioning multiple sclerosis patients.

Objective: The purpose of this study was to identify candidate items to expand the measurement range of the ABILHAND-56, thus improving its ability to detect differences in manual ability in higher-functioning multiple sclerosis patients.

Methods: A step-wise mixed methods design strategy was used, comprising two waves of patient interviews, a combination of qualitative (concept elicitation and cognitive debriefing) and quantitative (Rasch measurement theory) analytic techniques, and consultation interviews with three clinical neurologists specializing in multiple sclerosis.

Results: Original ABILHAND was well understood in this context of use. Eighty-two new manual ability concepts were identified. Draft supplementary items were generated and refined with patient and neurologist input. Rasch measurement theory psychometric analysis indicated supplementary items improved targeting to higher-functioning multiple sclerosis patients and measurement precision. The final pool of Early Multiple Sclerosis Manual Ability items comprises 20 items.

Conclusion: The synthesis of qualitative and quantitative methods used in this study improves the ABILHAND content validity to more effectively identify manual ability changes in early multiple sclerosis and potentially help determine treatment effect in higher-functioning patients in clinical trials.

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Regnault A, Loubert A, Brennan R, Meunier J, Naujoks C, Cano S Mult Scler J Exp Transl Clin. 2023; 9(3):20552173231201422.

PMID: 37780483 PMC: 10540592. DOI: 10.1177/20552173231201422.


Applying a mixed methods design to test saturation for qualitative data in health outcomes research.

Fofana F, Bazeley P, Regnault A PLoS One. 2020; 15(6):e0234898.

PMID: 32559246 PMC: 7304618. DOI: 10.1371/journal.pone.0234898.

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