Practice-Based Psychotherapy Research
To Improve The Wellbeing Of Our Community
PPRNet Blog: November 2016
At the PPRNet conference in November 2012 over 100 psychotherapy clinicians, researchers, and educators were very keen to receive ongoing information about psychotherapy research that is practice-oriented and presented in an easily readable format. And so the PPRNet Blog was born.
About once a month I will review and summarize two or three published psychotherapy research articles. As part of the summary, I will highlight the practice implications of the research.
Because of copyright issues, we cannot post the full text of the articles, but we will provide a link to the abstract on the publisher's web site. I will also post the author's email address. Most authors are very happy to share their work. So if you want a copy of the article send the author an email with a request for a pdf or reprint.
At the bottom of each review you can post a comment, and comment on your colleagues' comments. I will update these as frequently as possible.
If you have ideas for an article to review or a topic you would like to see covered, please send me an email at email@example.com.
Giorgio A. Tasca
Bar-Kalifa, E., Atzil-Slonim, D., Rafaeli, E., Peri, T., Rubel, J., & Lutz, W. (2016, October 24).
Therapist–client agreement in assessments of clients’ functioning. Journal of Consulting and Clinical Psychology. Advance online publication.
There has been a lot of research in the past decade on progress monitoring (i.e., regularly providing reliable feedback to therapists on client outcomes, the alliance, and client functioning). This research indicates that client outcomes can be enhanced if therapists have ongoing information on how their client or the relationship is progressing. In this innovative research by Bar-Kalifa and colleagues, the authors studied 77 therapists who saw a total of 384 clients. The therapists were experienced at providing cognitive-behavioral therapy. Clients for the most part had a depressive or anxiety disorder and were seen for an average of 36 sessions. Client outcomes were measured pre- and post-treatment. Emotional and psychological functioning during the past week was rated by the client before each session, and the same measure was given to the therapist to rate their client at the end of each session. After therapists made their rating, they were given ongoing feedback (i.e., progress monitoring) about how their clients’ rated their own functioning during the past week. Did clients and therapists agree on level of client functioning, was this agreement stable over time, and was this agreement or disagreement related to client outcomes? The authors used sophisticated statistical modeling to separate the effects of client ratings of their functioning from therapists’ ratings, and to examine the impact of the changing relationship between therapist and client ratings over time on client outcomes. The authors found little difference in the level of client and therapist ratings of client functioning, and they found that therapists tended to be accurate (i.e., congruent with clients) in tracking client functioning over time. More importantly, the ability of therapists to accurately track client functioning from session to session was related to better client outcomes in terms of key symptoms of depression and anxiety.
The ability of therapists to accurately track client functioning over time was related to better client outcomes. This means that therapists who were aware of their clients’ functioning through feedback methods were better equipped to help their clients. In particular, information about how client functioning was changing from session to session might have allowed therapists to take corrective action for clients who were not doing well from one session to another. This information might have allowed therapists to reconsider a treatment formulation for a particular client, for example. Therapists should be aware of how a client is doing at a particular session, but more importantly therapists should be sensitive to fluctuations in client functioning across sessions. This might be best achieved with ongoing progress monitoring.
For a copy of the abstract:
Author email: firstname.lastname@example.org
Fried, E.I. (2016). The 52 symptoms of major depression: Lack of content overlap among seven common depression scales. Journal of Affective Disorders.
Depression is a leading cause of disability in the world and an important reason why people seek psychotherapy. Depression is also the most commonly studied disorder in psychological treatment studies. Measuring depression with self-report or clinician rating scales seems straight forward, but it turns out that it is not. This is important for clinicians because we assume that scales assess depressive symptoms in a reliable way, and that this measurement gives a valid indicator of a patient’s level of depression and improvements in the depressive symptoms. In this review Fried examined the content of the seven of the most common measures of depression including: the Beck Depression Inventory (BDI), the Centre for Epidemiological Studies Depression Scale (CESD), and the Hamilton Rating Scale for Depression (HRDS). Many might assume depression to represent a single construct – meaning depression is sometimes thought to represent one unitary thing that is consistent across individuals. Because of that assumption, some might consider depression scales to be interchangeable. But according to Fried, these seven scales listed a total of 52 different symptoms. Using a statistical approach called a Jaccard Index, Fried found that the overlap in symptoms among the different depression scales was low (i.e., different scales seemed to be tapping into different symptoms). When he reviewed the content of each scale, this low overlap seemed clear. For example, the BDI (developed by the founder of CBT) emphasizes cognitive symptoms of depression, the CESD has a number of items that are only indirectly related to depressive symptoms (like interpersonal sensitivity), and the HRDS (often used in medication trials to evaluate side effects) emphasizes somatic symptoms like insomnia, fatigue, and sexual dysfunction. Perhaps this lack of overlap is not so surprising given that the concept of depression is likely multidimensional and not representative of a single uniform construct.
So what does this mean for clinical practice? Many clinicians use a depression scale to assess their patients and monitor their outcomes. Which scale one uses seems to make a difference in terms of what is being measured and what outcomes are monitored. Using the BDI will emphasize the cognitive aspects of depression, whereas ratings with the HRDS may emphasize the somatic aspects of depression. Fried recommends that researchers use more than one scale, and if the findings differ across scales, then that provides more nuanced information about the effects and outcomes of depression and its treatment. Perhaps the same can be said for clinical practice – if clinicians use only one depression scale, then they should be aware of what aspects of depression or what kind of information about their patent’s depression that the scale is providing.
For a copy of the article, click here:
Author email: email@example.com
Hall, G.C.N., Ibarak, A.Y., Huang, E.R., Marti, C.N., & Stice, E. (2016). A meta-analysis of cultural adaptations of psychological interventions. Behavior Therapy,
Cultural adaptation of psychological interventions involves identifying cultural contexts of behaviors and developing constructs of mental health functioning relevant to the cultural context. Most cultural adaptation of psychotherapies involves taking existing treatments originally developed for those of European ancestry and adapting them for another specific cultural group or context. However, a few efforts exist in which new treatments were developed within a particular culture to address culture-specific concerns. Eight dimensions along which interventions could be culturally adapted include: language, people, metaphors, content, concepts, goals, methods, and context. Some researchers have expressed concern that cultural adaptation could distance an intervention from its evidence-base, and reduce its effectiveness. In this meta analysis by Hall and colleagues, the researchers look closely at the effects all culturally adapted treatments and prevention methods. They reviewed 78 studies that included nearly 14,000 participants. All studies included culturally adapted interventions for individuals of non-European ancestry. For example, these included studies that adapted CBT interventions for various disorders (mainly depression and anxiety disorders), or studies that match therapist to client in terms of ethnicity. Only 5% of studies created a new intervention developed within a particular culture, whereas the vast majority of studies adapted an existing treatment initially developed for clients of European ancestry. The average effect size was g = .67 (confidence intervals not reported), indicating that culturally adapted interventions produced better outcomes than comparison conditions. Culturally adapted interventions were also more likely to result in better outcomes than the same interventions that were not adapted (g = .52). Effect sizes for cultural adaptation in treatment studies (g = .72) were larger than for prevention studies (g = .25), likely because participants in treatment studies had higher levels of initial psychopathology. There was little evidence that matching therapist and client on ethnicity was helpful.
This meta analysis provides compelling evidence that cultural adaptation of existing treatments can result in more positive outcomes compared to not adapting the same treatment. The effect sizes may even underestimate the true effects of cultural adaptation because the outcome variables like measures of depression were rarely adapted to a specific culture (e.g., depression among Chinese participants may be expressed differently than depression among European participants, and most depression measures were created by and for Europeans).
For a copy of the abstract:
Author email: firstname.lastname@example.org