Document Type


Publication Date




Background: Intentions play a central role in numerous empirically supported theories of behavior and behavior change and have been identified as a potentially important antecedent to successful evidence-based treatment (EBT) implementation. Despite this, few measures of mental health clinicians’ EBT intentions exist and available measures have not been subject to thorough psychometric evaluation or testing. This paper evaluates the psychometric properties of the evidence-based treatment intentions (EBTI) scale, a new measure of mental health clinicians’ intentions to adopt EBTs.

Methods: The study evaluates the reliability and validity of inferences made with the EBTI using multi-method, multi-informant criterion variables collected over 12 months from a sample of 197 mental health clinicians delivering services in 13 mental health agencies. Structural, predictive, and discriminant validity evidence is assessed.

Results: Findings support the EBTI’s factor structure (χ2 = 3.96, df= 5, p = .556) and internal consistency reliability (α = .80). Predictive validity evidence was provided by robust and significant associations between EBTI scores and clinicians’ observer-reported attendance at a voluntary EBT workshop at a 1-month follow-up (OR = 1.92, p < .05), self-reported EBT adoption at a 12-month follow-up (R2 = .17, p < .001), and self-reported use of EBTs with clients at a 12-month follow-up (R2 = .25, p < .001). Discriminant validity evidence was provided by small associations with clinicians’ concurrently measured psychological work climate perceptions of functionality (R2 = .06, p < .05), engagement (R2 = .06, p < .05), and stress (R2 = .00, ns).

Conclusions: The EBTI is a practical and theoretically grounded measure of mental health clinicians’ EBT intentions. Scores on the EBTI provide a basis for valid inferences regarding mental health clinicians’ intentions to adopt EBTs. Discussion focuses on research and practice applications.

Copyright Statement

This document was originally published in Implementation Science by BioMed Central. Copyright restrictions may apply. doi: 10.1186/s13012-016-0417-3