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Assessing the Within‐Trial Treatment Integrity of Discrete‐Trial Teaching Programs Using Sequential Analysis
Author(s) -
Brand Denys,
Mudford Oliver C.,
ArnoldSaritepe Angela,
Elliffe Douglas
Publication year - 2017
Publication title -
behavioral interventions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.605
H-Index - 34
eISSN - 1099-078X
pISSN - 1072-0847
DOI - 10.1002/bin.1455
Subject(s) - retraining , psychology , session (web analytics) , clinical trial , markov chain , computer science , machine learning , medicine , pathology , world wide web , international trade , business
Discrete‐trial teaching is a strategy frequently used to teach functional skills to individuals with developmental and intellectual disabilities. Research has shown that the within‐trial components of the procedure should be administered with ≥90% treatment integrity to facilitate optimal learning. Usually within‐trial treatment integrity is measured using whole‐session methods such as percentage of trials correctly administered. This study demonstrated one‐step Markov transition matrices as a method of assessing within‐trial treatment integrity. All components of discrete trials were coded and time‐stamped from video recordings of therapist–learner dyads in their typical setting (home or school). Several types of within‐trial treatment integrity errors were identified using the Markov transition matrices, error sequences that could not be identified using a percentage correct analysis. Better identification of errors has the potential both to enhance treatment integrity and to gain efficiency by targeted retraining of therapists. Copyright © 2016 John Wiley & Sons, Ltd.