Outcome feedback uses routine monitoring of a client’s progress with treatment goals as compared to a normative treatment sample. Past research has demonstrated benefits to using outcome feedback to adjust or modify a clinician’s interventions during treatment or to indicate the need for additional supervision. The current study is a randomised controlled trial to observe and measure treatment outcomes when outcome feedback is used to inform treatment decision-making.
This course is based on the article, Feedback-informed Treatment versus Usual Psychological Treatment for Depression and Anxiety created by Jamie Delgadillo, PhD et al. in 2018.
Publication Date:
2018
Course Material Authors
Course Material Authors authored the material only, and were not involved in creating this CE course. They are identified here for your own evaluation of the relevancy of the material this course is based on.
Jamie Delgadillo, PhD Health Sciences Research
Dr. Delgadillo is a Clinical Research Fellow in the Clinical Psychology Unit, Department of Psychology, University of Sheffield, Sheffield, UK. His research primarily focuses on the development of methods to predict and prevent poor treatment outcomes (i.e. dropout, persistent distress after therapy, relapse) and to optimally match patients to specific interventions. His work has been published in multiple peer reviewed journals.
Kim de Jong
Kim currently works as an Assistant Professor of Clinical Psychology at Leiden University. She is a board member of the Dutch Association for Cognitive Behavioral Therapy. Previously she has worked as an applied researcher in a mental health organization, where she performed studies in a wide variety of patients and settings
Mike Lucock
Mike Lucock is Professor of Clinical Psychology at the University of Huddersfield and Associate Director of Research in the South West Yorkshire Partnership NHS Foundation. His main research activity has been focused on self-help/self management in mental health and psychological therapies process and outcome research in routine NHS service settings. This includes the development and evaluation of self-help support for people with common mental health problems and self-management support for people with more severe and long term mental health problems. His research has involved a range of methodological approaches, including RCTs, generating practice based evidence and qualitative research. Trust.
Paul Pawlicki, PsyD, received his degree in clinical psychology from the Chicago School of Professional Psychology in Chicago, IL, in 2005. From 2004-2006, he taught courses in general psychology, abnormal psychology, and human sexuality at Collin College in Plano, TX. He currently practices individual therapy at the Department of Sexual Medicine at Park Nicollet Health Health Services near Minneapolis, MN.
Recommended For:
Counselors, marriage and family therapists, psychologists and social workers. This course is appropriate for all levels of knowledge.
Course Objectives:
After taking this course, you should be able to:
Identify results of past studies of outcome feedback on the quality of treatment outcomes
List participant population characteristics for which outcome feedback is most valuable
Describe environmental factors that aid outcome feedback in improving treatment outcomes
Disclosure to Learners
Disclosure of Relevant Financial Relationships
CE Learning Systems adheres to the ACCME's Standards for Integrity and Independence in Accredited
Continuing Medical Education. Any individuals in a position to control the content of a CE activity –
including faculty, planners, reviewers, or others ― are required to disclose all relevant financial
relationships with ineligible entities (formerly known as commercial interests).
The following relevant financial relationships have been disclosed by this activity's planners, faculty, and
the reviewer:
Planners and Reviewers
The planners of this activity have reported that they have no relevant financial relationships.
Commercial support
There is no commercial support for this distance-learning course.
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