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Budge, S.L., Moore, J.T., Del Re, A.C., Wampold, B.E., Baardseth, T.P., & Nienhuis, J.B. (2013). The effectiveness of evidence-based treatments for personality disorders when comparing treatment-as-usual and bona fide treatments. Clinical Psychology Review, 33, 1057-1066.

Personality disorders (PD) are more stable and enduring than other mental disorders and are characterized by pervasive, serious, and rigid self-destructive patterns in affect, cognition, interpersonal relations, and impulse control that reduce psychological well-being. PD are associated with higher rates of self injury, suicide, and health care costs. The prevalence of PD in the population ranges from 6% to 13%. The presence of PD in a patient often reduces the effectiveness of psychological treatments for Axis I disorders (e.g., depression, anxiety) that the patient may have. Psychotherapy may be more effective than other interventions, such as pharmacotherapy, for treating PD. In their meta analysis, Budge and colleagues (2013) addressed two questions. First, are manualized evidence-based treatments (EBT) as provided in clinical trials superior to treatment as usual (TAU), presumably as offered in naturalistic settings, for treating PD? Second, are there differences between bona fide treatments (i.e., psychotherapy administered by trained therapists and based on sound psychological theories) for PD? (A note about meta analyses: meta analyses are a statistical method to combine the findings of a large number of studies while accounting for the sample sizes, quality of the studies, and size of the effects. Meta analyses provide us with much more dependable results than any single study could provide). Regarding the first question, 30 studies were included in the meta analysis. Evidence-based treatments included psychodynamic therapies, cognitive behavioral therapies, and dialectical behavior therapy, among others. Overall, EBTs were more effective than TAUs, and the effect was medium sized. The positive effects in favor of EBT over TAU were larger for patients with borderline personality disorder. For the second study comparing bona fide treatments, only 12 studies were found and included in the meta analysis. Only three of the studies indicated that one bona fide therapy was more effective than another. It is also important to note that the average duration of treatment in the EBT studies was 1 year and peaked at 40 sessions.

Practice Implications

As Budge and colleagues (2013) concluded, with sufficient training, supervision, and dose hours, it appears that evidence based treatments (EBT) are more effective than treatments as usual (TAU) for personality disorders (PD). The results of the meta analysis suggested that training in evidence based psychotherapies may be necessary to achieve the best possible outcomes for patients with PD, especially those with borderline personality disorder. Are there differences in between EBTs for PD? The literature on this issue is quite small, so that 12 studies are not enough to make many conclusions. There is previous evidence that psychodynamic therapies and CBT yield very large effects for PD. The pervasiveness and complexity of PD symptoms make it so that effective treatments are necessarily longer term, which is consistent with previous research on this topic.

Cuijpers, P., Huibers, M., Ebert, D.D., Koole, S.L., & Andersson, G. (2013). How much psychotherapy is needed to treat depression? A metaregression analysis. Journal of Affective Disorders, 147, 1-13.

The question of the number of psychotherapy sessions and of frequency sessions (i.e., number of sessions per week) that are optimal for good outcomes could have implications for how psychotherapy is practiced and how it is reimbursed. In my August 2013 PPRNet Blog, I reported on research that indicated half of patients recover after 21 sessions of psychotherapy. However, that also means that half do not recover in that number of sessions. Many of those who do not recover require another 29 sessions to recover. Research and practice in psychotherapy is largely based on a “one-session-per-week” model. Some researchers, however, have found that an increase in the frequency sessions per week could improve or speed up outcomes. Cuijpers and colleagues (2013) did a meta-regression to assess these questions for short-term psychotherapies for depression. (Meta-regression is a type of meta-analysis in which predictors from many studies are aggregated and their averaged effects on the aggregated outcome are assessed. This produces much more reliable findings than are possible from a single study.) The authors assessed predictors such as the number and frequency of sessions, and they looked at symptom outcomes for depression. The authors found 70 controlled studies that included 5403 patients. More than two-thirds of the studies included CBT as the psychotherapy. Average length of treatment was 11 sessions, and the maximum number of sessions was 24. The number of sessions across studies ranged from .44 to 2 per week, and the average per week was 1. The overall effect size for the treatment was medium sized (g = .59), though the effect became smaller (g = .40) when publication bias was corrected. (Publication bias refers to the likelihood that some less favorable studies or results were not published thus creating an overestimation of the effect of the treatment. See my May 2013 PPRNet Blog). Cuijper and colleagues’ meta-regression showed a small but significant association between greater number of sessions and outcomes for depression; but more importantly, a greater number of sessions per week had a considerably larger positive influence on the effects of psychotherapy for depression.

Practice Implications

The findings from Cuijpers and colleagues (2013) meta-regression are particularly relevant to time limited treatment of depression with CBT. The total number of sessions was less important than the frequency of sessions per week. The results suggest that increasing the intensity or frequency of CBT sessions per week might result in a more efficient therapy and faster relief for patients with depression.

Author email: p.cuijpers@vu.nl

Handbook of Psychotherapy and Behavior Change: Starting in March 2013 I will review one chapter a month from the Handbook of Psychotherapy and Behavior Change in addition to reviewing psychotherapy research articles. Book chapters have more restrictive copy right rules than journal articles, so I will not provide author email addresses for these chapters. If you are interested, the Handbook table of content and sections of the book can be read on Google Books.

Baldwin, S. & Imel, Z.E. (2013). Therapist effects. In M.E. Lambert (Ed.), Bergin and Garfield’s Handbook of Psychotherapy and Behavior Change, 6^th Edition (pp. 258-297). New York: Wiley.

Does it matter that some therapists are more effective than others? Can less effective therapists be trained to improve their outcomes and relationship quality with patients?  These are important questions not only for our patients’ well-being but also for the long term survival of psychotherapy as a health enterprise. If we do not measure outcomes and help therapists who are less effective, stakeholders (i.e., clients, families, agencies, insurance companies) may stop paying for the services. In the September 2013 blog I discussed a large study that showed that a few therapists were reliably harmful and some therapists were reliably helpful to their patients. That study also reported that most therapists were effective in 5 of 12 problem domains for which their patients sought help. What these findings and the Handbook chapter by Baldwin and Imel (2013) show is that there are significant between-therapist effects (i.e., therapists differed from each other on patient outcomes) and within-therapist effects (i.e., therapist outcomes within their own caseload differed based on the patients’ problems). Baldwin and Imel (2013) reported on their meta analysis in which between-therapist differences accounted for 5% of the outcome variance. That seems small, but it’s not. One study, for example, estimated that for each 100 patients that would be treated, the worst therapist compared to the best therapist would have 6 more patients who deteriorated. I would prefer my loved ones to be seen by the best therapist, even if the difference between best and worst is only 5%. Nevertheless, 95% of the variance in outcomes is within the therapist’s caseload. That is, the patient, other contextual variables, and the therapist-patient relationship are by far the biggest contributors to outcome. As Baldwin and Imel point out, not only are some therapists are more effective for some patients and not others, but also some therapists are better at developing a therapeutic relationship with some patients than with others. Baldwin and Imel reported that, on average, 9% of the variance in the quality of the therapeutic alliance is associated with the therapist – that’s a clinically meaningful effect.

Practice Implications

As Baldwin and Imel (2013) state, ignoring therapist accountability is detrimental to patients and to the mental health field in general. If stakeholders do not see evidence of positive outcomes, then they will withdraw funding, and patients will have even less access to services. Therapists differ in their outcomes, and outcomes also differ within each therapist’s caseload. If a primary goal is to improve therapist performance and patient outcomes, then therapists need to measure outcomes and therapeutic relationship quality. This knowledge about performance with specific patients can help therapists seek continuing education and training to improve outcomes and therapeutic alliances with specific patients for whom the therapist is less effective. This may require continuous outcome monitoring and real-time feedback to therapists regarding their patients’ outcomes (see my September 2013 blog in identifying clients who might deteriorate).

Bell, E. C., Marcus, D. K., & Goodlad, J. K. (2013). Are the parts as good as the whole? A meta-analysis of component treatment studies. Journal of Consulting and Clinical Psychology, 81, 722-736.

Component studies (i.e., dismantling treatments or adding to existing treatments) may provide a method for identifying whether specific active ingredients in psychotherapy contribute to client outcomes. In a dismantling design, at least one element of the treatment is removed and the full treatment is compared to this dismantled version. In additive designs, an additional component is added to an existing treatment to examine whether the addition improves client outcomes. If the dismantled or added component is an active ingredient, then the condition with fewer components should yield less improvement. Among other things, results from dismantling or additive design studies can help clinicians make decisions about which components of treatments to add or remove with some clients who are not responding. For example, Jacobson and colleagues (1996) conducted a dismantling study of cognitive-behavioral therapy (CBT) for depression. They compared: (1) the full package of CBT, (2) behavioral activation (BA) plus CBT modification of automatic thoughts, and (3) BA alone. This study failed to find differences among the three treatment conditions. These findings were interpreted to indicate that BA was as effective as CBT, and there followed an increased interest in behavioral treatments for depression. However, relying on a single study to influence practice is risky because single studies are often statistically underpowered and their results are not as reliable as the collective body of research. One way to evaluate the collective research is by meta analysis, which allows one to assess an overall effect size in the available literature (see my November, 2013 blog on why clinicians should rely on meta analyses). In their meta analysis, Bell and colleagues (2013) collected 66 component studies from 1980 to 2010. For the dismantling studies, there were no significant differences between the full treatments and the dismantled treatments. For the additive studies, the treatment with the added component yielded a small but significant effect at treatment completion and at follow-up. These effects were only found for the specific problems that were targeted by the treatment. Effects were smaller and non-non-significant for other outcomes such as quality of life.

Practice Implications

Psychotherapists are sometimes faced with a decision about whether to supplement current treatments with an added component, or whether to remove a component that may not be helping. Adding components to existing treatments leads to modestly improved outcomes at least with regard to targeted symptoms. Removing components appears not to have an impact on outcomes. The findings of Bell and colleagues’ (2013) meta analysis suggest that specific components or active ingredients of current treatments’ have a significant but small effect on outcomes. Some writers, such as Wampold, have argued that the small effects of specific components highlight the greater importance of common factors in psychotherapy (i.e., therapeutic alliance, client expectations, therapist empathy, etc.). This may be especially the case when it comes to improving a patient’s quality of life.

Author email: david.marcus@wsu.edu

Munder, T., Brütsch, O., Leonhart, R., Gerger, H., & Barth, J. (2013). Researcher allegiance in psychotherapy outcome research: An overview of reviews. Clinical Psychology Review, 33, 501-511.

Although evidence for the efficacy of psychotherapy is largely uncontested, there remains debate about whether one type of treatment is more effective than another. This debate continues despite a recent American Psychological Association (APA) resolution on the equivalent efficacy of most systematic psychotherapy approaches. There are many aspects to this debate (e.g., some treatments are more researched than others and so appear to be better; symptom focused measurements are more sensitive to change and so may favour one treatment over another; some treatments are more amenable to manualization and short term application; etc.). One element of the debate that has received a lot of attention is researcher allegiance. Researcher allegiance refers to researchers preferring one treatment approach over another, and this preference may bias comparative outcome trials in favour of the preferred therapy. Researcher allegiance is measured by assessing primary researchers’ publication history or by their self-declared preference for a particular therapy approach. There exist 30 meta analyses that assessed researcher allegiance since the 1980s. These meta analyses focused on different therapy types, client populations (adults, children), and research designs (randomized trials, naturalistic effectiveness studies). However, some meta analyses have reported contradictory results for the researcher allegiance effect. This could be due to the different foci of the meta analyses (i.e., different treatment approaches, patient populations, age groups, etc.), and also possibly due the allegiance of those conducting the meta analyses. Munder and colleagues (2013) conducted a mega analysis of these meta analyses. As the name implies, a mega analysis aggregates the findings of available meta analyses. Munder and colleagues found a significant moderate effect of researcher allegiance. Researcher allegiance was consistent across patient populations, age groups, outcome measures, type of study design, and year of publication.

Practice Implications

As the APA resolution indicates, psychotherapy is the informed and intentional application of clinical methods and interpersonal stances derived from established psychological principles. Evidence-based practice in psychotherapy is "the integration of the best available research with clinical expertise in the context of patient characteristics, culture and preferences". The results of this mega analysis undermine the claim of some comparative outcome studies that suggest that one evidence-based psychotherapy is more effective than another.

Author email: tmunder@uni-kassel.de

McHugh, K.R., Whitton, S.W., Peckham, A.D., Welge, J.A., & Otto, M.W. (2013). Patient preference for psychological vs pharmacological treatment of psychiatric disorders: A meta-analytic review. Journal of Clinical Psychiatry, 74, 595-602.

For the most part psychotherapy and pharmacological interventions have equivalent positive effects on depression in the short term, and psychotherapy has better outcomes in the long term (see my May, 2013 blog).  There is also evidence that the effects of medications for depression are overestimated (also in the May 2013 blog). Despite all of this evidence, psychotherapy use has remained the same or declined slightly over the past 10 years (currently at about 3.4% of the population), whereas medication use for depression has doubled to over 10% of the population. At the same time, guidelines for evidenced based practice emphasize incorporating patient preferences when there is an absence of evidence-based decision rules for treatment selection. Providing patients with their preferred treatment is associated with better treatment uptake and outcomes (see June, 2013 blog). McHugh and colleagues conducted a meta analysis to review the literature on patient preferences for psychological versus pharmacological interventions for mental health disorders among adults. They included studies with treatment and non-treatment seeking samples of patients with a variety of disorders. (A quick note about meta-analysis. Meta analysis is a way of statistically combining the effect sizes from a number of studies into a common metric so that an average effect size can be calculated. Meta analysis is now the standard by which studies are reviewed. Meta analysis results are much more reliable than any single study and so represent the best way to inform clinical practice from research findings). McHugh and colleagues identified 34 studies representing over 90,000 participants. Most studies were of depressive disorders and anxiety disorders. When given a preference, 75% of participants preferred psychotherapy over medication to treat their mental health problem. In treatment seeking samples, the percentage was lower at 69%, but still significantly in favour of psychotherapy. Younger people and women were more likely to prefer psychotherapy, though the findings still showed a preference for psychotherapy among older people and men. The availability of combining psychotherapy and medication did not affect the results, so that even when given the option of both psychotherapy and medication people still preferred psychotherapy alone.

Practice Implications:

In all subsamples, participants were 3 times more likely to prefer psychotherapy to medication for their mental disorder. Patient preference for treatment is a core component of evidence based mental health practice that improves outcome and reduces drop outs. Without evidence for superiority for one treatment over another, patients should be given their preference, and on average patients overwhelmingly prefer psychotherapy. To optimize outcomes in clinical settings, providers should consider patient preferences, including their preference for psychotherapy over medication.

Author email: kmchugh@mclean.harvard.edu