Dimensionality and Scaling Properties of the Patient Categorisation Tool in Patients With Complex Rehabilitation Needs Following Acquired Brain Injury

Siegert, Richard J.; Medvedev, Oleg; Turner-Stokes, Lynne

doi:10.2340/16501977-2327

Dimensionality and Scaling Properties of the Patient Categorisation Tool in Patients With Complex Rehabilitation Needs Following Acquired Brain Injury

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Date

2018-03-27

Authors

Siegert, Richard J.

Medvedev, Oleg

Turner-Stokes, Lynne

Item type

Journal Article

Publisher

Foundation of Rehabilitation Information

Abstract

Objective: To investigate the scaling properties of the Patient Categorisation Tool (PCAT) as an instrument to measure complexity of rehabilitation needs. Design: Psychometric analysis in a multicentre cohort from the UK national clinical database. Patients: A total of 8,222 patents admitted for specialist inpatient rehabilitation following acquired brain injury. Methods: Dimensionality was explored using principal components analysis with Varimax rotation, followed by Rasch analysis on a random sample of n = 500. Results: Principal components analysis identified 3 components explaining 50% of variance. The partial credit Rasch model was applied for the 17-item PCAT scale using a "super-items" methodology based on the principal components analysis results. Two out of 5 initially created super-items displayed signs of local dependency, which significantly affected the estimates. They were combined into a single superitem resulting in satisfactory model fit and unidimensionality. Differential item functioning (DIF) of 2 super-items was addressed by splitting between age groups (< 65 and ≥ 65 years) to produce the best model fit (?2/df = 54.72, p = 0.235) and reliability (Person Separation Index (PSI) = 0.79). Ordinal-tointerval conversion tables were produced. Conclusion: The PCAT has satisfied expectations of the unidimensional Rasch model in the current sample after minor modifications, and demonstrated acceptable reliability for individual assessment of rehabilitation complexity.

Keywords

rehabilitation, brain injury, psychometrics, health services needs and demands, Rasch analysis, Science & Technology, Life Sciences & Biomedicine, Sport Sciences, number, model, 4201 Allied Health and Rehabilitation Science, 32 Biomedical and Clinical Sciences, 42 Health Sciences, Bioengineering, 1103 Clinical Sciences, 1106 Human Movement and Sports Sciences, 3202 Clinical sciences, 4201 Allied health and rehabilitation science

Source

Journal of Rehabilitation Medicine, ISSN: 1650-1977 (Print); 1651-2081 (Online), Foundation of Rehabilitation Information, 50(5), 435-443. doi: 10.2340/16501977-2327