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.
…I blog about psychotherapy for borderline personality disorder, capacity to metnalize and therapy resistant depression, and negative effects of psychotherapy
Type of Research
- ALL Topics (clear)
- Alliance and Therapeutic Relationship
- Anxiety Disorders
- Attendance, Attrition, and Drop-Out
- Client Factors
- Client Preferences
- Cognitive Therapy (CT) and Cognitive-Behavioural Therapy (CBT)
- Combination Therapy
- Common Factors
- Depression and Depressive Symptoms
- Efficacy of Treatments
- Feedback and Progress Monitoring
- Group Psychotherapy
- Illness and Medical Comorbidities
- Interpersonal Psychotherapy (IPT)
- Long-term Outcomes
- Neuroscience and Brain
- Outcomes and Deterioration
- Personality Disorders
- Placebo Effect
- Practice-Based Research and Practice Research Networks
- Psychodynamic Therapy (PDT)
- Resistance and Reactance
- Self-Reflection and Awareness
- Suicide and Crisis Intervention
- Therapist Factors
- Transference and Countertransference
- Trauma and/or PTSD
- Treatment Length and Frequency
Adapting Therapy to Each Client: Becoming an Evidence-Based Therapist I
Norcross, J.C. & Wampold, B.E. (2018). A new therapy for each patient: Evidence‐based relationships and responsiveness. Journal of Clinical Psychology, Online First, DOI: 10.1002/jclp.22678
Over the next several months, I will review in this blog results of a number of meta-analyses conducted recently on patient factors and relationship factors in psychotherapy. These factors provide evidence-based guidance to psychotherapists on how best to relate to and adapt to clients so that psychotherapy is more effective. This introductory article by Norcross and Wampold is an overview of the nine meta analyses related to transdiagnostic client factors to which therapists can adapt their interpersonal stances and treatment. The goal is to enhance treatment effectiveness by therapists tailoring therapy to individual client characteristics that are related to outcomes. Decades of research indicate that client transdiagnostic characteristics have more influence on outcomes than the particular treatment method, and likely more influence than the particular client diagnosis. The research indicates that giving the identical treatment to every client without adaptation to client characteristics is not an effective approach to providing psychotherapy. These meta analyses of client factors indicate that therapists should select different interventions and relational stances according to the client and the context. What are these client characteristics and therapist adaptations that are reliably related to outcomes? The client factors most strongly related to outcomes include therapist adaptations to: client culture/race/ethnicity (99 studies, g = .50); client preferences for type of therapy (51 studies, g = .28), client religion/spirituality (97 studies, g = .13 to .43), client stage of change (76 studies, g = .41), client reactance/resistance level (13 studies, g = .78), client coping style (32 studies, g = .53), and client attachment style (32 studies, g = .35). Over the next months, I will be reviewing in more detail these meta analyses of client factors and the practice implications of each so that therapists can use this evidence-base to help them to adapt to particular client characteristics.
Practitioners will find that fitting the therapy to clients’ culture, stage of change, religion/spirituality, reactance/resistance, coping style, and attachment style will improve treatment outcomes. Doing so will have a greater impact on outcomes than the particular type of therapy provided or adapting treatment to the particular client diagnosis. The results of this large body of evidence suggests that therapists should no longer ask: “what is my theoretical orientation” but rather they should ask: “what relationship, adaptation, and approach will be most effective with this particular client”.
Psychotherapy Relationships That Work: Becoming an Evidence-Based Therapist II
Norcross, J. C., & Lambert, M. J. (2018). Psychotherapy relationships that work III. Psychotherapy, 55(4), 303-315.
Relationship factors in psychotherapy are some of the most important predictors of patient outcomes. They outweigh factors like the type of therapy provided in determining whether patients get better after psychotherapy. In this second overview article, Norcross and Lambert provide a review of 17 meta-analyses of relationship factors in psychotherapy that contribute to positive outcomes. Like the review of patient factors also found in this blog and E-Newsletter, this article briefly outlines those evidence-based relationship factors that reliably predict patient outcomes in psychotherapy. The therapeutic relationship refers to how the therapist and patient relate to each other, or their interpersonal behaviors. By contrast, techniques or interventions refer to what is done by the therapist. Practice guidelines typically focus on interventions or therapeutic orientation. As the authors argue, what is missing from treatment guidelines are the person of the therapist and the therapeutic relationship – evidence for which is backed up by 5 decades of research. Even in studies of highly structured manualized psychotherapy for a specific disorder in which efforts were made to reduce the effect of individual therapist, up to 18% of outcomes (a moderate to large effect) could be attributed to the person of the therapist. By contrast somewhere between 0% and 10% of outcomes (a small to moderate effect) is attributable to specific treatment methods. So, which therapeutic relationship factors are reliably related to patient outcomes? These include: the therapeutic alliance in individual therapy (306 studies, g = .57) couple therapy (40 studies, g = .62), and adolescent psychotherapy (43 studies, g = .40), collaboration (53 studies, g = .61) and goal consensus (54 studies, g = .49), cohesion in group therapy (55 studies, g = .56), therapist empathy (82 studies, g = .58), collecting and delivering client feedback or progress monitoring (24 studies, g = .14 to .49), managing countertransference (9 studies, g = .84), and repairing therapeutic alliance ruptures (11 studies, g = .62) among others. Over the next few months, I will be reviewing these meta analyses in more detail to discuss how therapists can use this evidence base to improve their patients’ outcomes.
The research as a whole indicates that therapists should make the creation and cultivation of the therapeutic relationship a primary goal of therapy. Factors such as managing the therapeutic alliance, repairing alliance ruptures, engaging in ongoing progress monitoring, managing countertransference and others should be used to modify treatments and interpersonal stances in order to maximize outcomes. When seeking out professional development and training, practitioners should focus on evidence-based relationship factors (managing the alliance, judicious self disclosure, managing emotional expression, promoting credibility of the treatment, collecting formal feedback, managing countertransference) in addition to focusing on evidence-based treatments.
Psychotherapy for Eating Disorders
Grenon, R., Carlucci, S., Brugnera, A., Schwartze, D., … Tasca, G. A. (2018). Psychotherapy for eating disorders: A meta-analysis of direct comparisons, Psychotherapy Research, DOI: 10.1080/10503307.2018.1489162
Eating disorders can cause a great deal of physical and mental impairment because of the severity of the symptoms and because of comorbid conditions like depression, anxiety, substance use, and others. Anorexia nervosa (AN) occurs in about 0.5% of the population, bulimia nervosa (BN) occurs in about 1.5% of the population, and binge-eating disorder (BED) occurs in about 3.5% of the population. Treatment guidelines include both cognitive behavioral therapy (CBT) and interpersonal psychotherapy (IPT) as front line interventions for BN and BED. However, results from previous meta analyses of psychological treatments for eating disorders were confounded by not focusing exclusively on randomized controlled trials, mixing studies of adult and adolescent samples, combining an array of outcomes rather than separately reporting primary (eating disorder symptoms) and secondary (interpersonal problems, depression) outcomes, and not distinguishing between bona fide psychotherapies (like CBT, IPT, psychodynamic therapy, and others) from non-bona fide treatments (like self help, behavioral weight loss supportive counseling). Grenon and colleagues conducted a meta analysis of psychotherapies for eating disorders to examine if: psychotherapy is effective compared to a wait list, if bona fide psychotherapy and non-bona fide treatment differ in outcomes, and if one type of psychotherapy (i.e., CBT) was more effective than other bona fide psychotherapies (like IPT, behavior therapy, psychodynamic therapy, dialectical behavior therapy). Their meta analysis included 35 randomized controlled trials of direct comparisons. Psychotherapy was significantly more effective than a wait-list control at post treatment, so that 53.89% of patients were abstinent of symptoms after psychotherapy compared to only 8.92% who were abstinent in the wait-list group. Bona fide psychotherapies (51% abstinent) were significantly more effective than non-bona fide treatments (40% abstinent) at post treatment, and dropout in bona fide psychotherapies (17.5%) was significantly lower than in non-bona fide treatment (29.1%). Further, the difference between CBT and other bona fide psychotherapies was not significant.
Psychotherapy for eating disorders are effective for patients with BN or BED. There were too few studies of those with AN to come to any conclusions about their treatment. Patients with BN or BED are best treated with a bona fide psychotherapy that involves face to face psychological therapy like CBT, IPT, psychodynamic therapy, dialectical behavior therapy, or behavior therapy. Non-bona fide treatments like self help, behavioral weight loss, and supportive counseling should only be used as an adjunct to bona fide psychotherapy for eating disorders.
How Reliable is the Association Between Therapeutic Alliance and Patient Outcomes?
Flückiger, C., Del Re, A. C., Wampold, B. E., & Horvath, A. O. (2018). The alliance in adult psychotherapy: A meta-analytic synthesis. Psychotherapy. Advance online publication. http://dx.doi.org/10.1037/pst0000172
The therapeutic alliance is one of the most researched concepts in psychotherapy. The alliance, also called the working alliance or therapeutic alliance, consists of the collaborative agreement between patient and therapist on the tasks (what to do) and goals (what to achieve) of their therapeutic work together. Alliance also includes the relational or emotional bond between therapist and patient. It is different from therapist empathy, transference, countertransference, the real relationship and other concepts related to the therapeutic relationship. Researchers and clinicians have known for years about the importance of developing and maintaining an alliance to achieving patient outcomes. The growing research in this area now allows one to see how stable this finding is. Fluckiger and colleagues conducted a meta analysis of 306 studies with over 30,000 patients that assessed the alliance-outcome relationship. The research occurred in naturalistic settings (during regular clinical practice) and in randomized controlled trials. The overall effect size based on 295 independent comparisons was r = .278 (95% CI: .256, .299), indicating a statistically significant medium-sized association accounting for about 8% of treatment outcomes. To put this in perspective, this effect is as large as or larger than the effects of many common medical interventions. The type of therapy made no difference to this finding - the alliance was just as important to CBT as it was to psychodynamic, interpersonal, and emotionally focused therapies. The alliance-outcome correlation was somewhat smaller, though still significant among those with substance-use disorders, but otherwise was consistent for all other disorders tested (depression, anxiety, PTSD, borderline personality disorder). The alliance measure used, who rated the alliance, when it was assessed, and the outcome that was measured tended to have a small or no impact on the results. The alliance-outcome relationship was just as important to everyday clinical practice as it was in randomized controlled trials.
The alliance-outcome association is highly reliable or stable across a number of therapies, diagnoses, measurements, and study designs. This very large body of research suggests that therapists should: (1) build and maintain an emotional bond, and agreement on tasks and goals with patients throughout therapy; (2) develop the alliance early by focusing on agreement on treatment and goals; (3) address ruptures in the alliance early and immediately; and (4) assess the strength and quality of the alliance regularly throughout treatment from the patient’s perspective using a well-known brief alliance measure.
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).
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.
Are E-Health Interventions Useful for Weight Loss?
Podina, I. R., & Fodor, L. A. (2018). Critical review and meta-analysis of multicomponent behavioral e-health interventions for weight loss. Health Psychology, 37(6), 501-515.
Over 35% of Americans are overweight or obese, and this poses significant health-related challenges. Obesity likely contributes to heart disease, Type II diabetes, and some forms of cancer. Also, obesity is often co-morbid with mental health conditions including depression and binge-eating disorder. Practice guidelines list multicomponent behavioural interventions as state of the art treatment for weight loss. These include dietary counselling, increased physical activity, and behavioural methods to support behaviour change. However, such interventions often require direct in-person contact with a health or mental health professional, which can be expensive and create a barrier to accessing treatment for some. An option to increase access is to deliver the multicomponent behavioural intervention by internet or by another electronic format such as DVD. In this meta analysis, Podina and Fodor reviewed 47 randomized controlled studies representing over 1500 participants in which e-health interventions for weight loss in overweight or obese individuals were tested against in-person treatment or a control condition (no treatment or treatment as usual). E-health interventions were more effective than control conditions for weight loss outcomes at post-treatment, g = 0.34 (95% CI [0.24 to 0.44]). Similar results were found at follow-up. However, e-health interventions were significantly less effective than active in-person treatments, g = -0.31 (95% CI [-0.43 to -0.20]) for weight loss in overweight or obese individuals.
E-health interventions (mostly internet delivered treatment) of multicomponent behavioral treatment for weight loss was more effective than no treatment or treatment as usual. However, e-health was significantly less effective than traditional face to face behavioral interventions to help people reduce their body weight. The authors raised concerns about the use of e-health interventions for weight loss as the first line treatment as the effects were small and the approach was less effective than in-person interventions.