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Rehabilitation Treatment Specification System: Content and Criterion Validity Across Evidence-Based Voice Therapies
Jarrad H Van Stan1,2,3, Nelson Roy4, Joseph Stemple5
1Massachusetts General Hospital, Boston.
Purpose:
Systematically improving voice therapy outcomes is challenging as the clinician actions (i.e., active ingredients) responsible for improved patient functioning (i.e., targets) are relatively unknown. The theory-driven Rehabilitation Treatment Specification System (RTSS) and standard, voice-specific terminology based on the RTSS (RTSS-Voice) may help address this problem. This qualitative study evaluated if the RTSS and RTSS-Voice can describe four evidence-based voice therapies for muscle tension dysphonia without missing critical aspects (content validity) and identify commonalities and differences across them (criterion validity).
Method:
Qualitative interviews were completed between the clinicians (protocol experts) who developed and/or popularized the vocal function exercises, laryngeal reposturing, circumlaryngeal massage, and conversation training therapies as well as RTSS experts to produce RTSS specifications that met two consensus criteria: (a) The protocol expert agreed that the specification represented their treatment theory, and (b) the RTSS experts agreed that the specifications correctly adhered to both the RTSS framework and the RTSS-Voice's standard terminology.
Results:
The RTSS and RTSS-Voice comprehensively described voice therapy variations across and within the four diverse treatment programs, needing only the addition of one new target: overall auditory-perceptual severity.
Conclusions:
The RTSS and RTSS-Voice exhibited strong content validity. The standard RTSS-Voice terminology helped identify, for the first time, commonalities and differences in treatment ingredients, targets, and mechanisms of action across four treatments developed for the same patient population. In the long term, the RTSS and RTSS-Voice could provide the framework for an ever-growing collection of clinically meaningful and evidence-based therapy algorithms with potential to improve research, education, and clinical care.
Supplemental Material:
https://doi.org/10.23641/asha.25537624.
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