Blog

The Psychotherapy Practice Research Network (PPRNet) blog began in 2013 in response to psychotherapy clinicians, researchers, and educators who expressed interest in receiving regular information about current practice-oriented psychotherapy research. It offers a monthly summary of two or three published psychotherapy research articles. Each summary is authored by Dr. Tasca and highlights practice implications of selected articles. Past blogs are available in the archives. This content is only available in English.

January 2017

Individual versus Group Psychotherapy

Burlingame, G.M., Seebeck, J.D., Janis, R.A., Whitcomb, K.E., Barkowski, S., Rosendahl, J., & Strauss, B. (2016). Outcome differences between individual and group formats when identical and nonidentical treatments, patients, and doses are compared: A 25-year meta-analytic perspective. Psychotherapy, 53, 446-461.

With increasing service demands being put on mental health systems, clinicians and administrators are looking to more efficient ways of providing care to more patients. One option is group therapy in which more patients can be treated with fewer resources. However, are groups as effective as individual therapy for mental disorders? This meta-analysis by Burlingame and colleagues addresses this question by examining 67 studies in which group and individual therapy were directly compared within the same study. The majority of studies included adults with anxiety, mood, or substance use disorders, with some studies focusing on medical conditions, eating or personality disorders. Two-thirds of studies were of cognitive-behavioral therapy, but other treatment types like interpersonal, psychodynamic, and supportive therapy were also tested. Groups were defined as having at least 3 patients per group. The average number of sessions for group and individual therapy were equivalent (group M = 14.67, SD = 8.75; individual 15.94, SD = 14.37)), and as expected group therapy sessions were longer in minutes (M = 100.39, SD = 30.87) than individual therapy sessions (M = 56.55, SD = 14.37) given the multi-person demands of groups. Groups were primarily closed to new members after starting, they tended to have homogenous membership based on diagnosis, and groups tended to be co-led by 2 therapists. Individual and group therapy were not significantly different for all disorders and outcomes at post-treatment (g = -0.03; 95%CI = -0.10, 0.04), short-term follow-up (g = 0.01; 95% CI = -0.13, 0.11), and long-term follow-up (g = 0.00; 95% CI= -0.12, 0.13). Drop out rates for group therapy (17.28%) and individual therapy (14.96%) were not significantly different (OR = 1.10; 95% CI = 0.90, 1.33), and patients were likely to accept group therapy (88.76%) as often as they accepted individual therapy (84.83%) when one or the other was offered. Pre- to post-treatment effect sizes were moderately large for both interventions (group: g = 0.60, 95% CI = 0.48, 0.72; individual: g = 0.53, 95% CI = 0.42, 0.65). Patients presenting with depression, substance us, anxiety, or eating disorders had the highest level of improvement.

Practice Implications

When identical treatments, patients, and doses are compared, individual and group therapy resulted in equivalent outcomes across of a variety of disorders. This is good news for clinicians and agencies looking to maximize resources to treat more patients. However, running a group is more complex than providing individual therapy. Finding a sufficient number of patients to start a group, assessing and preparing each patient prior to starting a group, writing a note per patient per session, and managing attrition is logistically more challenging. Further, most therapists are not formally trained to provide group interventions and so they may find the task of managing a substantially larger amount of within-session group process information to be complex. Finally, as Burlingame and colleagues indicate, there are institutional considerations so that group programs require a milieu that supports group referrals and flexibility in scheduling. Nevertheless the findings of this meta analysis indicate the potential for group therapy to provide efficacious treatments for mental disorders.

December 2016

Effects of Combining Psychotherapy and Pharmacotherapy on Quality of Life in Depression

Kamenov, K., Twomey, C., Cabello, M., Prina, A.M., & Ayuso-Mateos, J.L. (2016). The efficacy of psychotherapy, pharmacotherapy, and their combination on functioning and quality of life in depression: A meta-analysis. Psychological Medicine, doi: 10.1017/S0033291716002774.

Both psychotherapy and pharmacotherapy are efficacious for reducing symptoms of depression. Some studies suggest that functioning (i.e., the ability to engage in work, school, and social activities) and quality of life (i.e., satisfaction with these activities and perception of one’s health) are just as important to depressed patients as is reducing their symptoms. In fact, many patients place greater priority on improving functioning compared to reducing symptoms. In this meta analysis, Kamenov and colleagues assess the relative efficacy of psychotherapy vs pharmacotherapy in improving functioning and quality of life. They also evaluate if combining psychotherapy and pharmacotherapy is efficacious relative to either treatment alone. The meta analysis included k = 153 studies of over 29,000 participants. Psychotherapies often included CBT and interpersonal psychotherapy. Compared to control groups (k = 37 to 52) both psychotherapy (g = 0.35, 95% CI = 0.24, 0.46) and medications (g = 0.27, 95% CI = 0.21, 0.32) significantly improved functioning. Also, compared to controls both psychotherapy (g = 0.35, 95% CI = 0.26, 0.44) and medications (g = 0.31, 95% CI = 0.24, 0.38) significantly improved quality of life in depressed participants. In studies that directly compared psychotherapy and medications, there were no significant differences when it came to improving functioning, but there was a small significant advantage to psychotherapy over medication for improving quality of life (g = 0.21, 95% CI = 0.01, 0.43). Combined psychotherapy and medications (k = 19) was more effective to improve functioning compared to pharmacotherapy alone (g = 0.34, 95% CI = 0.18, 0.50) and compared to psychotherapy alone (g = 0.32, 95% CI = 0.14, 0.49). Combined treatment was also more efficacious for improved quality of life compared to medications alone (g = 0.36, 95% CI = 0.11, 0.62) and to psychotherapy alone (g = 0.39, 95% CI = 0.19, 0.58).

Practice Implications

Combined treatment of medications and psychotherapy is more effective than either treatment alone for improving functioning and quality of life. However, most patients prefer psychotherapy to medications, and some studies indicate that many patients choose not to get treated at all rather than receive medications. Further, quality of life can be substantially compromised by medication side effects. Clinicians should take these factors into account when considering monotherapy with antidepressant medications or combined treatment of pharmacotherapy and psychotherapy for depression.
Placebo Response Rates in Antidepressant Trials

Furukawa, T.A., Cipriani, A., Atkinson, L.A., Leucht, S., Ogawa, Y., … Salanti, G. (2016). Placebo response rates in antidepressant trials: A systematic review of published and unpublished double-blind randomised controlled studies. Lancet Psychiatry, 3, 1059-1066.

The placebo response in medication trials is an interesting and important phenomenon. Placebo response refers to improvement in clients that is due to therapeutically powerful factors like client’s expectations that an intervention will be effective and to the therapeutic relationship with the health care provider. In medication trials, placebo is seen as problematic because researchers typically want to demonstrate the effectiveness of the active medication (e.g., selective serotonin re-uptake inhibitors) independent of any other factors. For this reason, randomized clinical trials of medications are often double-blind and placebo controlled (i.e., clients and clinicians are unaware of who received the active medication and who received the inert placebo pill). It has widely been suspected that over the years the placebo response has been increasing in antidepressant trials possibly due to the types of patients included in trials (i.e., more recently, patients with more severe symptoms are included) and to other methodological issues (e.g., use of multi-centre trials, dosing schedule). An increasing placebo response is suspected of contributing to the growing number of failed anti-depressant trials (i.e., trials that show little or no effectiveness of the medication). Using advanced statistical methods, Furukawa and colleagues evaluated in a meta analysis if placebo response in medication trials was increasing over time. They defined a response as a 50% or greater reduction in observer-rated depression scale scores from baseline to 8 weeks. Their review included 252 placebo controlled trials of antidepressants from 1978 to 2015. Placebo response rates ranged widely from 0% to 70% (I² = 74.1%) with a mean placebo response of 35% to 40%. Year of publication was not significantly related to placebo response rate after controlling for methodological variables like length of the trial, multi-centre trials, and dose regimen. That is, once change in the methodology of conducting trials over time was accounted for, the placebo response appeared to remain largely the same from year to year.

Practice Implications

The placebo response is very real and complicates our understanding of how and why antidepressants might work for some patients. About 35% to 40% of patients who benefit from antidepressants may be benefitting largely because of the expectation of getting better. Greater treatment response to antidepressants for a large proportion of patients appears to be dependent on the therapeutic features of supportive contact with a caring health professional.

November 2016

When Clients and Therapists Agree on Client Functioning

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. http://dx.doi.org/10.1037/ccp0000157.

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.

Practice Implications

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.
Do All Depression Scales Do a Good Job of Measuring Depression?

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.

Practice Implications

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.

October 2016

The Quality of Psychotherapy Research Affects The Size of Treatment Effects for CBT

Cuijpers, P., Cristea, I.A., Karyotaki, E., Reijnders, M., Huibers, M.J.J. (2016). How effective are cognitive behavior therapies for major depression and anxiety disorders? A meta-analytic update of the evidence. World Psychiatry, 15, 245-258.

You might think that an esoteric topic like study quality should not really be of interest or concern to clinicians – but it is an important topic with practice implications. In this meta analysis Pim Cuijpers and his research group updated the meta analytic evidence for the efficacy of cognitive behavioral therapy (CBT) for a variety of disorders (major depressive disorder [MDD], generalized anxiety disorder [GAD], panic disorder [PAD], and social anxiety disorder [SAD]). The important thing about meta analyses is that the method combines the effect sizes from all relevant studies into a single metric – an average effect size. These average effect sizes are much more reliable than findings from any one single study. In fact, whenever possible, clinical decision-making should be based on a meta analysis and systematic review and not on a single study. Meta analyses also allow one to give more weight to those studies that have larger sample sizes, and that employ better methodologies. Even more, meta analytic techniques allow one to adjust the averaged effect size by taking into account publication bias (i.e., an indication of the effects from studies that might have been completed but were never published, likely because they had unfavorable findings). Usually, average effect sizes are lower when they are adjusted for study quality and publication bias. Cuijpers and colleagues’ meta analyses found that the unadjusted average effects of CBT were large for each of the disorders (ranging from g = .75 to .88 [confidence intervals not reported]). However adjusting for publication bias reduced the effects to medium-sized for MDD (g = .65) and GAD (g = .59). Only 17.4% of the individual studies of CBT were considered to be of “high quality” (i.e., studies that use the best methodology to reduce bias, like random allocation, blinding, using all the available data, etc.). After adjusting for study quality, the effects of CBT for SAD (g = .61) and PAD (g = .76) were also reduced to medium-sized. Not surprisingly, the effects of CBT were largest when the treatment was compared to a wait-list no-treatment control group. The effects were small to moderate when CBT was compared to treatment as usual or to a placebo.

Practice Implications

Even when adjusting for study quality and publication bias, the average effects of CBT were medium-sized for a variety of common disorders compared to control conditions. Unfortunately, the quality of the studies was not high for most trials, reducing the effect sizes and lowering our confidence in the efficacy of the treatment. Nevertheless, the findings of this meta analysis suggest that CBT will likely have moderate effects for the average patient with MDD, SAD, PAD, and GAD.

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January 2017

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December 2016

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November 2016

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October 2016

Practice Implications

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