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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.

This month...

Giorgio A. Tasca

…I blog about content from the updated edition of the Handbook of Psychotherapy and Behavior Change, published in 2021: the effectiveness of psychotherapist training, the therapist effect, and therapist responsiveness to patient interpersonal behaviours.

Type of Research

Topics

September 2018

  • Is Psychotherapy Effective? Revisited.

    Munder, T., Fluckiger, C., Leichsenring, F, Abbass, A.A., Hilsenroth, M.J., … Wampold, B.E. (2018). Is psychotherapy effective? A re-analysis of treatments for depression. Epidemiology and Psychiatric Sciences, 1-7.

    Based on a deeply flawed review in 1952, Hans Eysenck declared that psychotherapy was no more effective than custodial care for treating mental disorders. Later, he qualified this by stating that behaviour therapy was effective and other forms of psychotherapy were not. These statements touched off decades of angst and debate in the psychotherapy community, and also resulted in a great deal of research about psychotherapy’s effectiveness. By the 1970s the new research technique of meta-analysis was developed and was applied to psychotherapy research. In their seminal meta analysis of controlled studies, Smith and Glass found that psychotherapy was useful and with large effects compared to no treatment. And yet the debate continues. In 2018, Cuijpers argued that waitlist control groups (i.e., a common control condition in psychotherapy studies in which patients receive no treatment) are an inappropriate comparison leading to exaggerated estimates of the effects of psychotherapy. Recently, Munder and colleagues argued that waitlist controls are a way of estimating the natural course of the disorder (what would happen with no treatment) plus the effect of expecting to receive treatment (client expectations of receiving treatment tend to have a positive impact on symptoms). In fact, research shows that pre- to post-study effect sizes for the waiting period is approximately g = .40, or a medium effect. In other words, waiting for therapy in a study results in a moderate proportion of individuals getting better on their own without treatment. Therefore, Munder and colleagues argued that comparing psychotherapy to a waitlist control is appropriate and may be a conservative estimate of psychotherapy’s effects (i.e., psychotherapy has to outperform the effects of clients expecting treatment to help them). In their meta analysis, Munder and colleagues re-analysed 71 studies of psychotherapy for depression compared to a waitlist control condition. They found that the effect size in favour of psychotherapy was g = 0.75 (SE = 0.09) indicating a moderate to large effect. Psychotherapy was also more effective than care as usual (i.e., compared to another intervention that was not psychotherapy), g = 0.31 (SE = 0.11). There were no differences between types of psychotherapy (CBT, IPT, PDT, etc.) for depression outcomes.

    Practice Implications

    Despite various attempts during the history of psychotherapy to downplay or disparage its efficacy, research continues to show that psychotherapy is in fact effective. The average effect size compared to the natural history of depression is moderate to large (and that is likely an under-estimate). Again, there is no evidence that one type of psychotherapy is superior to another for treating depression. It is time for the field to move beyond questions of efficacy of psychotherapy and of the relative efficacy of different treatments, and look to understanding therapist interpersonal stances, client characteristics, and relationship factors that may improve outcomes from psychotherapy.

July 2018

  • Placebo Response in Transcranial Magnetic Stimulation for Depression

    Razza, L. B., Moffa, A. H., Moreno, M. L., Carvalho, A. F., Padberg, F., Fregni, F., & Brunoni, A. R. (2018). A systematic review and meta-analysis on placebo response to repetitive transcranial magnetic stimulation for depression trials. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 81, 105-113.

    Transcranial magnetic stimulation (TMS) is a new treatment for depression thought to modulate brain activity through electromagnetic pulses delivered by a coil placed over the patient’s scalp. A meta analysis shows that TMS may be effective in treating depressive disorders when compared to a placebo control, although only 18.6% of those receiving TMS were no longer depressed at the end of treatment. The placebo control condition usually involves a sham version of TMS in which the coil is placed over the scalp but no magnetic stimulation is applied. In antidepressant trials, the placebo response is quite high such that approximately 40% of patients respond to the placebo condition (in antidepressant trials, the placebo condition includes an identical pill that is inert). In this meta analysis, Razza and colleagues assess the placebo response in TMS. They included only double blind randomized controlled trials (i.e., trials in which both the patient and physician were not aware if the treatment was real or a sham). The authors estimated the placebo response based on pre- to post-sham TMS scores of common measures of depression. The meta analysis included 61 studies of over 1300 patients. The main result showed that sham response was large (g = 0.80; 95%CI = 0.65–0.95). Trials including patients with only one episode of depression or who were not treatment resistant (g =0.67, 95%CI = 0.06–1.28, p= 0.03) had higher placebo responses than those trials in which patients previously had two or more failed antidepressant treatments (g = 0.5, 95%CI = 0.03–0.99, p = 0.048).

    Practice Implications

    The results of this meta analysis demonstrates a high placebo response in trials testing TMS. This is similar to the high level of placebo response commonly seen in patients in antidepressant medication trials. It appears that psychological factors like attention, instillation of hope, patient expectations of receiving benefit, and perhaps working alliance may account for an important portion of why pharmacological and other medical interventions appear to work for those with depressive disorders. This is particularly true for patients who are receiving treatment for the first time or for whom previous medical treatment was successful.

March 2018

  • Therapeutic Alliance Predicts Client Outcomes in CBT

    Cameron, S. K., Rodgers, J., & Dagnan, D. (2018). The relationship between the therapeutic alliance and clinical outcomes in cognitive behaviour therapy for adults with depression: A meta‐analytic review. Clinical Psychology and Psychotherapy, DOI: 10.1002/cpp.2180.

    The therapeutic alliance refers to the collaborative agreement between therapist and client on the tasks of therapy (homework, treatment approach, intervention style) and goals of therapy (to reduce depressive symptoms, to improve interpersonal relationships, to cope better with stress), plus the emotional bond between therapist and client. The alliance is part of a larger concept of therapeutic relationship that also includes the real relationship between client and therapist and the transference relationship (maladaptive relational patterns in the client based on a history of relationships with parental figures). The alliance is thought to be a common factor across different therapeutic orientations, including cognitive behavioral therapy (CBT), time-limited psychodynamic psychotherapy (TLPP), and interpersonal psychotherapy (IPT). In fact, the alliance is known to have a moderate and robust relationship to client outcomes regardless of who rates the alliance (therapist, client, observer), which measure is used, and when in therapy the alliance is rated (early, middle, late). Although Beck emphasized the alliance as a key therapeutic principle in CBT, some CBT writers argue that the alliance is not so important. In this study, Cameron and colleagues conducted a meta analysis of 13 randomized controlled trials that assessed the relationship between therapeutic alliance and CBT outcomes for depression in adult clients. The overall mean correlation between therapeutic alliance and outcome was r = 0.26 (95% CI [.19–.32]), which indicates a moderate and significant relationship. This is very close to the value found in a larger meta analysis of over 200 alliance – outcome studies.

    Practice Implications

    The study demonstrates the importance of the therapeutic alliance to client outcomes in CBT. The association was at similar levels to those found in other types of therapy. Therapists conducting CBT should attend to building and maintaining an alliance, which provides a context to facilitate CBT interventions. If a client is not completing homework for example, it is likely that there is a lack of agreement on tasks of therapy, and this part of the alliance may need to be renegotiated. Therapists may also benefit from routinely assessing the alliance in therapy with their clients on a session by session basis using short and easy to use measures. Reviewing these scales regularly can alert a therapist to potential problems in the alliance and the need to repair any tensions or ruptures.

  • Effects of Computerized CBT May be Overestimated

    So, M., Yamaguchi, S., Hashimoto, S., Sado, M., Furukawa, T.A., & McCrone, P. (2013). Is computerised CBT really helpful for adult depression?-A meta-analytic re-evaluation of CCBT for adult depression in terms of clinical implementation and methodological validity. BMC Psychiatry, 13, 113. 

    Depression is a major cause of disability in the world, and so efforts to improve access to its treatment have been ongoing for several decades. In particular, many researchers and clinicians propose cognitive behavioural therapy (CBT) as an effective treatment with a good evidence-base. There have been many clinical trials showing the efficacy of CBT. In recent years, there have also been attempts to computerize CBT (CCBT) as a self help intervention in order to increase its accessibility for those with depression, and perhaps also to improve its cost effectiveness. In fact, the Increasing Accessibility to Psychotherapy (IAPT) program in the UK provides CCBT as the most common first treatment for depression. However there remain questions about the longer term effectiveness of CCBT to reduce symptoms of depression, its potentially high patient dropout rate (a negative outcome), and its effects on quality of life of those burdened by depression. In this meta analysis, the largest of its kind, So and colleagues assess these issues with regard to CCBT. They reviewed 14 direct comparison randomized controlled trials that provided 16 comparisons of CCBT versus a control condition (wait list or treatment as usual) for adults with depression. At post-treatment, CCBT was more effective than controls in reducing depression −0.48 [95% CI −0.63 to −0.33]. However, at follow up (up to 6 months), the effects of CCBT disappeared −0.05 [95% CI −0.19 to 0.09]. Also improvement in functioning and quality of life were not significantly different between CCBT and control conditions, −0.05 [95% CI −0.31 to 0.22]. The rate of drop out from CCBT (32%) was almost double that of control conditions (17%), RR = 1.68 [95% CI 1.31 to 2.16]. There was also evidence of publication bias (i.e., a tendency for some researchers not to publish non-significant findings), so that the positive post-treatment results in favour of CCBT might be inflated.

    Practice Implications

    Although CCBT may be touted as a way to increase access to treatment for depression, this meta analysis indicates some concerns about the widespread implementation of CCBT. The effects of CCBT appear to be limited to a short-term reduction of depressive symptoms that may not be sustained in the longer run. There was no appreciable impact of CCBT on quality of life relative to controls, and so CCBT may have a limited impact on the burden of depression. Most troubling was a high drop out rate of 32%. Drop out from CCBT in the IAPT program in the UK is about 50%, and this may be indicative of the actual drop out rate in real world practice.

November 2017

  • Psychotherapy for Depression Also Reduces Interpersonal Problems

    McFarquhar, T., Luyten, P., & Fonagy, P. (2018). Changes in interpersonal problems in the psychotherapeutic treatment of depression as measured by the Inventory of Interpersonal Problems: A systematic review and meta-analysis. Journal of Affective Disorders, 226, 108-123.

    Interpersonal problems are commonly reported by depressed people. Interpersonal problems are seen by many as both a cause of depressive symptoms and as a result of depression. Depression may be the result of lacking basic human needs like social supports, stable relationships, and intimacy. One of the most important ways of assessing interpersonal problems is with the Inventory of Interpersonal Problems (IIP). The IIP is based on a circumplex model of two independent dimensions: affiliation (friendliness vs hostility) and status (dominance vs submissiveness). Greater problems in any of these domains or any combination of these domains may lead to interpersonal distress that result in or are the result of depression. Many psychotherapies target interpersonal problems in their treatment of depression: Interpersonal Psychotherapy (IPT), Short Term Dynamic Psychotherapy (STDP), and Emotion Focused Therapy (EFT). In this meta-analysis, McFarquhar and colleagues evaluated whether psychotherapy for depression is related to changes in interpersonal distress and whether specific types of interpersonal problems at baseline are related to treatment outcomes for depression at post-treatment. The authors looked at both randomized and non-randomized trials of psychotherapy for adults with depression. They found 10 studies that met inclusion criteria, six of which were randomized controlled trials. Psychotherapy for depression resulted large positive changes in interpersonal problems (overall pre- to post-treatment ES g=0.74, 95% CI=0.56–0.93). Unfortunately, there were too few studies (k = 3) that met meta-analytic criteria to do an analysis of pre-treatment interpersonal distress as a predictor of depression outcomes. However, of 8 studies that looked at this question, six showed that higher interpersonal distress was associated with poorer outcomes for depression at post-treatment.

    Practice Implications

    Given that interpersonal problems both cause and are caused by depressive symptoms, targeting relationship difficulties (lack of social support, conflict in relationships, low intimacy, relationship avoidance) in psychotherapy should be a priority. This meta-analysis showed that interpersonal distress improves after psychotherapy for depression, and there was some evidence that higher interpersonal problems at the outset may reduce the effects of the therapy for depressive symptoms.

August 2017

  • Interventions for PTSD for Survivors of Mass Violence

    Morina, N., Malek, M., Nickerson, A., & Bryant, R.A. (2017). Meta-analysis of interventions for posttraumatic stress disorder and depression in adult survivors of mass violence in low- and middle-income countries. Depression and Anxiety, DOI: 10.1002/da.22618

    There is a high prevalence of post-traumatic stress disorder (PTSD) in countries that have experienced civil war and mass violence, and given the number of open conflict, the prevalence is likely increasing. Most people affected are from low- to middle-income countries. Both PTSD and depression confer a large personal, social, health, and economic burden especially when untreated. Research in Western countries show that psychological treatment of PTSD is effective, but there are practical barriers to transporting and adapting these interventions to low- and middle-income countries. In this meta-analysis, Morina and colleagues do a systematic review of psychological interventions for PTSD conducted of adult survivors of war in low- and middle-income countries. Treatments included trauma-focused cognitive-behavioral therapy, interpersonal psychotherapy, eye movement desensitization and reprocessing and several others. In total, 2,124 treated participants and 934 participants in the waitlist condition were included in the analyses. In the 18 trials that were included, symptoms of PTSD and depression were measured. The average drop-out rate was 11.5%. Across all active interventions (k = 16), a large pre–post effect size was found, g = 1.29; 95% CI = [0.99; 1.59] for PTSD. The average between-group effect size comparing active treatments versus control conditions at post-treatment was small to medium, g = 0.39; 95% CI = [0.249; 0.55], and at follow-up was large, g = 0.93; 95% CI = [0.56; 1.31], k = 10. Pre-post effect size for depression was equally large g = 1.28; 95% CI = [0.96; 1.61]. The effect size comparing active treatments versus control conditions for depression at posttreatment (k = 11) was large, g = 0.86; 95% CI = [0.54; 1.18], and at follow-up was medium to large, g = 0.90; 95% CI = [0.49; 1.33], k = 5.

    Practice Implications

    Evidence-based psychological treatments developed in high-income countries are also effective in reducing symptoms of PTSD and depression in adults who experienced war-time conditions in low- and middle-income countries. Although not directly tested, the evidence suggests that different evidence-based treatments were equally effective. Even if drop-out rates were low, practical barriers still existed, including the number of sessions of these treatments (average was 10 sessions), the need for trained personnel, and the need for face to face meetings. The authors suggested that collaborative care models should be evaluated and tested which aim to enhance the reach of efficacious treatments within primary care to optimize the number of patients who can benefit from these interventions.

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