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Jennifer S. Kennett, PhD is a 2024 graduate of the Counselor Education & Supervision Progam at Antioch University, Seattle.

Dissertation Committee

Stephanie Thorson-Olesen, PhD, Committee Chair

Dominique Avery, PhD, Committee Member

Shawn Patrick, PhD, Committee Member

Keywords

supervision, competency, pre-licensed, provisional license, assessment, evaluation, supervisee, outcomes, efficacy, supervisory alliance

Document Type

Dissertation

Publication Date

2024

Abstract

Supervision is a foundational component of education and training for new counselors. Ensuring provisionally licensed supervisees receive adequate supervision is vital, given the variation in training and experience requirements from state to state. Therefore, the purpose of this study was to evaluate three measures of supervisor competence and experience, the Supervision Experience and Supervisory Competence Assessment (version 2; SE-SC), the Generic Supervision Assessment Test (GSAT), and the Brief Supervisory Working Alliance Inventory (BSWAI) for use in the counseling profession within the United States. The instruments were evaluated for reliability and face validity using a sample of 104 provisionally licensed counselors across the United States. Participants completed a demographics questionnaire on personal, professional, and supervision experience characteristics. Next, they were randomly assigned to complete one of the three instruments. Cronbach’s alpha coefficients were calculated, and the means for the three instruments were compared using an analysis of variance. The results showed that both supervisor competency instruments were reliable and valid for the counseling profession, with Cronbach’s alphas ranging from .84 to .98. The Brief Supervisory Working Alliance Inventory was also reliable and valid (α = .91) as a measure of a component of what makes supervision effective based on the research. It is vital that the counseling profession continue to develop multiple-perspective supervisor competency benchmarking instruments that integrate all five identified supervisor competencies. Moreover, including reverse-coded subscales to identify inadequate and harmful supervision behaviors would increase the efficacy of tools for supervisor competency assessment.

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Jennifer S. Kenett, PhD, 2024

ORCID Scholar ID# 0009-0003-5524-6980

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