Anatomy of psychology practitioner competence

Clustering approach reveals the hierarchical organization of competencies

Gonsalvez, Craig J.
Deane, Frank P.
Terry, Josephine
Hoong Gooi, Chien

Clinical and Health Psychology Research Initiative, School of Psychology, University of Western Sydney, Sydney, NSW, Australia
School of Psychology, Illawarra Institute for Mental Health, Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia
School of Psychology, University of Western Sydney, Sydney, NSW, Australia
School of Psychology, University of New South Wales, Sydney, NSW, Australia

Funding information Australian Government Office for Learning and Teaching, Grant/Award Number: ID14-3639

SUPPORTING INFORMATION Additional supporting information may be found online in the Supporting Information section.

Craig J. Gonsalvez, Clinical and Health Psychology Research Initiative, School of Psychology, University of Western Sydney, NSW, Australia [email protected]

Received June 13, 2019

revised January 14, 2020

Accepted April 13, 2020

Clinical Psychology: Science & Practice 27(4):p e12347, December 2020. | DOI: 10.1037/h0101779

Current competency frameworks for practitioners have been derived through expert consensus but lack empirical validation. We examined the stepwise anatomy of competence using the Clinical Psychology Practicum Competencies Rating Scale with items presented in fixed (Dataset I, 195 trainees) and random order (Dataset II, 353 trainees). Cluster analyses of supervisor ratings revealed that fixed-order items yielded clusters that were divided along thematic lines similar to a-priori domains (e.g., intervention, ethics). Random-order items yielded a markedly different set of clusters structured around knowledge, skills, relationship competencies, and meta-competencies. The results offer a novel and insightful conceptualization of the anatomy of competence with critical implications for training and assessment. Further, random presentation of competencies increases item independence and attenuates rater bias.