Elsevier

General Hospital Psychiatry

Volume 33, Issue 4, July–August 2011, Pages 336-342
General Hospital Psychiatry

Psychiatry and Primary Care
Training primary care staff to deliver a computer-assisted cognitive–behavioral therapy program for anxiety disorders

https://doi.org/10.1016/j.genhosppsych.2011.04.011Get rights and content

Abstract

Objectives

This paper describes the training approach used with primary care staff to deliver an evidence-based computer-assisted cognitive–behavioral therapy (CBT) program for anxiety disorders within a collaborative care treatment delivery model.

Methods

We describe the training and proficiency evaluation procedures utilized in the Coordinated Anxiety Learning and Management (CALM) study, a large multisite study of collaborative care for anxiety disorders in primary care. Training incorporated readings, didactic presentations, video demonstrations of CBT skills, role-plays, computer-assisted practice, CBT training cases and ongoing group supervision provided by study psychologists.

Results

Proficiency training case data from 15 clinicians are presented. The anxiety clinical specialists (ACSs) were highly proficient at delivering the CBT component of the CALM intervention. The ACSs also provided Likert-scale ratings and open-ended responses about their experiences with the training. Overall, the training was rated very positively and was described as very thorough, indicating a high level of acceptability to clinicians. Recommendations for future training are described.

Conclusions

Primary care staff with none or minimal prior CBT experience can be trained to deliver a computer-assisted, evidence-based treatment for anxiety disorders. The implications for dissemination and transportability of evidenced-based interventions are discussed.

Section snippets

Training novice primary care staff to deliver a computer-assisted cognitive–behavioral therapy program for anxiety disorders

There is a substantial need for treatments for anxiety disorders in primary care that are both effective and easy to disseminate. Anxiety disorders are the most common mental health problem seen in primary care, outnumbering even depressive disorders [1]. Additionally, anxiety is poorly recognized by primary care physicians (PCPs), and when recognized, evidenced-based treatments such as cognitive–behavioral therapy (CBT) are used infrequently, and anxiolytic medications — though more common —

Subjects

Subjects were 15 primary care staff hired to work either part or full time as ACSs as part of the CALM study at one of the 13 primary care clinics among the four study sites: Los Angeles, San Diego, Seattle and Little Rock, AK. As Table 1 shows, the clinicians who took part in this study, ACSs, were nearly all Master's-level clinicians, female, licensed and experienced in working with a clinical population that includes medical as well as emotional problems. However, the ACSs had relatively

Training case proficiency

As Table 2 shows, across all study sites, the mean number of training cases was 2.13 (S.D. 0.35). The mean proficiency score, based on 1–7 Likert scale across all ACS training cases, was 6.37, with an S.D. of .97.

Role-play competence

The ACSs mean score on role-plays demonstrating CBT skills based on expert psychologist ratings on a 1–7 Likert scale was 6.31 (S.D.=2.21).

Quizzes

The mean score on quizzes assessing ACS knowledge of readings and didactic presentations was 98%.

ACS experience and training performance

Pearson product–moment correlations were conducted

Discussion and conclusions

Although a number of evidenced-based psychotherapies, including CBT, are known to be clinically effective, many do not have access to them in part because widespread dissemination and implementation of these practices have been challenging. The goal of our work was to develop and evaluate a system for training primary care staff to deliver evidenced-based treatment for anxiety disorders. Such a system would provide an important mechanism for dissemination of evidence-based care for anxiety

Acknowledgments

This work was supported by the following NIMH grants: U01 MH070018 to RAND (PI: Cathy Sherbourne), U01 MH058915 to UCLA (PI: Michelle Craske), U01 MH057835 and K24 MH64122 to the University of California, San Diego (PI: Murray Stein), UO1 MH057858 and K24 MH065324 to the University of Washington (PI: Peter Roy-Byrne), U01-MH070022 to UAMS (PI: Greer Sullivan). The authors would like to thank Daniel E. Glenn and Tomislav D. Zbozinek for their contributions to this manuscript.

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