One challenge in rehabilitation is determining whether improvement in the patient is a treatment-specific effect or due to extraneous factors (eg, the passage of time, spontaneous recovery).
Descriptive, model building, and 2 cases illustrating the model.
The Model for Assessing Treatment Effect (MATE) incorporates the conceptual frameworks of the International Classification of Functioning, Disability, and Health (ICF), along with single-case experimental methodology.
The MATE contains 7 levels organized in a hierarchy, representing (i) increasing specificity of evaluation procedures and (ii) control of extraneous variables during therapy. Two illustrative cases of patients with traumatic brain injury undergoing inpatient rehabilitation for, inter alia, cognitive-communication impairments are described to illustrate common clinical practice (level 2 of MATE) and a superior method using a multiple-baseline design across behaviors, enabling rigorous evaluation of treatment effect (level 6 of MATE).
The MATE offers a systematic, evidence-based approach for implementing ICF-informed goals into clinical practice. It also provides a benchmark against which a clinical service can be evaluated in terms of the rigor of its therapy program.
Rehabilitation Studies Unit (Dr Tate), Northern Clinical School, Sydney Medical School, University of Sydney, Australia; Department of Linguistics (Ms Taylor), Faculty of Human Sciences, Macquarie University, Sydney, Australia; and Cortex Communication Partners (Mss Taylor and Aird), Sydney, Australia.
Corresponding Author: Robyn L. Tate, PhD, MPsychol, Rehabilitation Studies Unit, PO Box 6, RYDE NSW 1680, Sydney, Australia (email@example.com).
This work was conducted while authors C.T. and V.A. were employed as senior speech pathologists in the Brain Injury Rehabilitation Service at the Royal Rehabilitation Centre, Sydney. We thank patients “Garry” and “David” for their participation, Dr Michael Perdices for helpful discussions and advice on methodology, and Carmel Whitty, speech pathologist, for scoring the data as a blind assessor.
The authors declare no conflicts of interest.