Date of Graduation
Summer 2023
Degree
Master of Science in Applied Behavior Analysis
Department
Psychology
Committee Chair
Jordan Belisle
Abstract
The need for evidence based technologies supporting the development of behavioral repertoires essential for daily living is increasing, and while empirical research is valued among behavior analysts, limited psychometric research exists in behavior. Assessing and promoting daily living skills (DLS) requires empirical assessments and training technologies to enhance independence and autonomy, consistent with applied behavior analysis principles. The LIFE Skill Emergence System: Functional Module contains both a 250-item behavioral assessment evaluating DLS as well as a curriculum that integrates behavior analytic procedures such as chaining, task analyses, direct training, generalization, and relational framing to support DLS in behavior programming. The thesis combines and discusses 2, multi-authored manuscripts centered around the examination of the LIFE Skills Emergence System: Functional Module. The first chapter establishes the convergent validity and reliability of the LIFE Skills Functional Module Assessment, supporting the validity across established measures of adaptive behavior, derived verbal relations, and autism symptom severity. The second chapter consists of a single-subject experimental design to evaluate an adapted program from the LIFE Curriculum to teach a series of flexible dance skills to promote independent leisure skills. Findings in the two present studies demonstrate the utility of LIFE from accurately assessing essential daily living skills and adaptive behaviors, to apply the key elements in programming to promote autonomy in independent daily living skills.
Keywords
LIFE assessment, LIFE curriculum, adaptive behavior, chaining, convergent validity, daily living skills
Subject Categories
Applied Behavior Analysis
Copyright
© Shelby Blecha
Recommended Citation
Blecha, Shelby, "From Assessment to Treatment: Evaluating the LIFE Skills Emergence System Functional Module" (2023). MSU Graduate Theses. 3899.
https://bearworks.missouristate.edu/theses/3899
