Rasch measurement: the Arm Activity measure (ArmA) passive function sub-scale

Abstract

Purpose: To evaluate the conformity of the Arm Activity measure (ArmA) passive function sub-scale to the Rasch model. Methods: A consecutive cohort of patients (n = 92) undergoing rehabilitation, including upper limb rehabilitation and spasticity management, at two specialist rehabilitation units were included. Rasch analysis was used to examine scaling and conformity to the model. Responses were analysed using Rasch unidimensional measurement models (RUMM 2030). The following aspects were considered: overall model and individual item fit statistics and fit residuals, internal reliability, item response threshold ordering, item bias, local dependency and unidimensionality. Results: ArmA contains both active and passive function sub-scales, but in this analysis only the passive function sub-scale was considered. Four of the seven items in the ArmA passive function sub-scale initially had disordered thresholds. These items were rescored to four response options, which resulted in ordered thresholds for all items. Once the items with disordered thresholds had been rescored, item bias was not identified for age, global disability level or diagnosis, but with a small difference in difficulty between males and females for one item of the scale. Local dependency was not observed and the unidimensionality of the sub-scale was supported and good fit to the Rasch model was identified. The person separation index (PSI) was 0.95 indicating that the scale is able to reliably differentiate at least two groups of patients. Conclusions: The ArmA passive function sub-scale was shown in this evaluation to conform to the Rasch model once disordered thresholds had been addressed. Using the logit scores produced by the Rasch model it was possible to convert this back to the original scale range.

Implications for Rehabilitation

• The ArmA passive function sub-scale was shown, in this evaluation, to conform to the Rasch model once disordered thresholds had been addressed and therefore to be a clinically applicable and potentially useful hierarchical measure.

• Using Rasch logit scores it has be possible to convert back to the original ordinal scale range and provide an indication of real change to enable evaluation of clinical outcome of importance to patients and clinicians.

• Activities
• arm
• Arm Activity measure
• psychometrics
• Rasch
• unidimensionality

Acknowledgements

Authors thank Professor Lynne Turner-Stokes for input and advice on previous work leading to the current analysis. This article is dedicated in memory of, and with thanks to, Professor Bipin Bhakta for advice on previous work leading to the current analysis, and also with thanks to Professor Paula Kersten, for comment on previous work contributing to the development of the current analysis.

Declaration of interest

Stephen Ashford is funded by the National Institute of Health Research (NIHR) in the form of a Clinical Lectureship award.

The first author undertook the initial development and construction of the ArmA.

This paper presents independent research funded by the National Institute for Health Research (NIHR) UK and NIHR CLAHRC Northwest London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the NIHR, NIHR CLAHRC Northwest London or the Department for Health, UK.