Cognitive Behavioral Therapy (CBT) has been demonstrated to be effective for numerous presenting problems, including depression, anxiety, and post-traumatic stress disorder (PTSD). Several large mental health systems have invested heavily in programs to train their clinicians in CBTs, but relatively little attention has been devoted to the monitoring or promotion of CBT quality after training is complete. Identifying strategies to do so can facilitate research and training, and is critical to ensuring consumer access to high quality, evidence-based treatments. The lack of a scalable, effective, and efficient method of monitoring quality is a key barrier to efforts to promote high-quality implementation. Self-report fidelity assessments increase clinician and consumer burden and may not accurately reflect clinician skill or the intensity with which CBT interventions are delivered. Observation and expert ratings are time and resource intensive and unlikely to be feasible or affordable in large systems. To maximize the likelihood of broad implementation once effective strategies to monitor quality are established, it is essential that these strategies are feasible and acceptable in routine care contexts, leveraging information collected during routine care. To date, few monitoring strategies that do not involve observation, client/caregiver reports, or clinician self-reports have been tested. To address this critical implementation challenge, we propose to refine and evaluate a method of monitoring quality that is based on an evaluation of CBT worksheets that are completed in session. Because the worksheets were developed to implement core cognitive and behavioral elements and are embedded in CBTs across diagnostic categories, they may be used to elucidate the clinician?s ability to guide the client through CBT interventions in session. Preliminary research with this measure demonstrated high correlations between the measure and observer ratings of clinician competence, associations with subsequent symptom change, and high agreement between raters with differing levels of familiarity with CBT. Completion of the ratings based on worksheets requires only a small fraction of time required for session observation and ratings. This project will compare this novel strategy to observer ratings and adherence checklists that are embedded in clinical notes. Furthermore, it will compare the accuracy of worksheet data collected by mobile app to paper-form worksheets, and assess the feasibility and acceptability of these strategies. Because the core elements of CBT and its worksheets are common across many CBTs, this research has broad implications for monitoring fidelity to CBTs in a variety of mental health and healthcare systems and settings. This research will be conducted by a team of investigators with expertise in CBT, training, implementation, psychotherapy process and outcome research, psychometrics, longitudinal data analysis, mobile technologies and healthcare economics, with input from community partners and end-users. The resulting products have the potential to significantly improve efforts to monitor and ensure ongoing high quality implementation of CBT in routine care settings.

Public Health Relevance

This project will compare two methods of assessing the quality of cognitive behavioral therapy (CBT) that do not involve directly observing sessions, adherence checklists embedded in clinical notes, and rating the quality of worksheets that are completed with therapist guidance during sessions. It will also examine whether ratings of worksheets completed on a mobile app are reliable and valid quality measures. This information can inform strategies to monitor and enhance CBT quality, which can ultimately improve the quality of care and clinical outcomes.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH112628-02
Application #
9474211
Study Section
Special Emphasis Panel (ZMH1)
Program Officer
Sherrill, Joel
Project Start
2017-05-01
Project End
2021-03-31
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Palo Alto Veterans Institute for Research
Department
Type
DUNS #
624218814
City
Palo Alto
State
CA
Country
United States
Zip Code
94304