Blog

Torous, J., Lipschitz, J., Ng, M., & Firth, J. (2020). Dropout rates in clinical trials of smartphone apps for depressive symptoms: A systematic review and meta-analysis. Journal of Affective Disorders, 263, 413-419.

Depression is a leading cause of disability worldwide, and yet more than 50% of people do not have access to adequate therapy. One solution might be to provide individuals with smartphone apps to help screen, monitor, or provide treatment. Smart phones are ubiquitous, and depression apps are one of the most downloaded categories of apps by the public. Research seems to suggest that smartphone apps provide some positive results for members of the public, but these findings are compromised by the high drop-out rates reported in the primary studies. Further, one study found that although many people download the apps, only about 4% actually use them. Whereas smartphone apps appear attractive to the consumer, very few actually make use of and therefore benefit from them. In this systematic review, Torous and colleagues conduct a meta-analysis of drop-out rates from studies that test the use of smart phone apps. They found 18 independent studies representing data from 3,336 participants who received a psychological intervention for depression via a cell phone app, or who were in a placebo control condition. A total of 22 different apps were tested in the studies. Initially, the pooled drop-out rate from the depression app treatment arms appeared to be about 26.2% (95% C.I.=11.34% to 46.75%), which would be in line with average drop-out rates from randomized controlled trials of face to face psychotherapy. But, the authors noted two things. First, the drop-out rate from the placebo control conditions (14.2%; 95% C.I. = 8.236 to 23.406) was almost half as high as that found for the apps. Second, through some sophisticated statistical analyses, they found evidence of “publication bias” in this research area. This means that a number of studies testing these apps likely were completed but never published (i.e., these might be studies funded by an app manufacturer that demonstrated negative findings or high drop-out rates). When the authors statistically adjusted for publication bias, they found that the actual drop-out rate from the apps was about 47.8%. That is, almost half of users did not complete or dropped out of the studies. There were no differences in drop-out between types of interventions (CBT, mindfulness, or others), and studies with larger sample sizes (i.e., better quality studies) had higher drop-out rates.

Practice Implications

Although smartphone apps appear really attractive and may be potentially useful as an adjunct to face to face psychotherapy for depression, their utility is plagued by extremely low usage rates (4%) and high drop-out rates from studies (almost 50%). Leading writers and researchers define psychotherapy as primarily a healing relationship that also includes specific interventions. The key ingredient is the human relationship. Depressed or otherwise troubled individuals cannot (because of feeling demoralized) or will not interact with a machine for healing. One way or another, when it comes to smartphone apps, depressed individuals are voting with their feet. Given these findings, health care providers should consider the ethics of giving a depressed individual only e-therapy as the primary mode of treatment.

Cuijpers, P., Noma, H., Karyotaki, E.,  Vinkers, C.H., Cipriani, A., & Furukawa, T.A. (2020). A network meta‐analysis of the effects of psychotherapies, pharmacotherapies and their combination in the treatment of adult depression. World Psychiatry, 19, 92-107.

Mental disorders represent a significant health burden worldwide, with over 350 million people affected. Depression is the second leading cause of disease burden. There is ample evidence that psychotherapies and pharmacotherapies are effective in the treatment of depression. There is also evidence for the efficacy of different types of psychotherapy (CBT, IPT, PDT), and for different types of antidepressant medications. Some research suggests that combining psychotherapy and medications is better than either intervention alone, but the evidence is inconclusive. Existing meta analyses only compare two existing treatments directly to each other at a time: psychotherapy vs medications, psychotherapy vs combined treatments, medications vs combined treatments. In this meta-analysis, Cuijpers and colleagues use a method called “network meta-analysis” to study the relative impact of medications, psychotherapy, or their combination. Network meta-analysis is controversial because it relies on indirect comparisons to estimate effects. For example, let’s say one study compared medications (A) to psychotherapy (B), and another study compared medication (A) to combination treatment (C), then a network meta-analysis would estimate the effects of psychotherapy vs combination treatment by using the transitive principle (if A = B, and B = C, then A = C). This logic relies on everything being equivalent across studies. However, in treatment trials one cannot assume that the different studies comparing A, B, and C are equivalent in terms of quality and bias (in fact, we know they are not). In any case, Cuijpers and colleagues found that combined treatment was superior to ei­ther psychotherapy alone or pharmacotherapy alone in terms of standardized effect sizes (0.30, 95% CI: 0.14-0.45 and 0.33, 95% CI: 0.20-0.47). No significant difference was found between psychotherapy alone and pharmacotherapy alone (0.04, 95% CI: –0.09 to 0.16). Interestingly, acceptability (defined as lower patient drop-out rate and better patient adherence to the treatment) was significantly better for combined treatment compared with pharmacotherapy (RR=1.23, 95% CI:

1.05-1.45), as well as for psychotherapy compared with pharmacotherapy (RR=1.17, 95% CI: 1.02-1.32). In other words, pharmacotherapy alone was less acceptable to patients than another treatment approach that included psychotherapy.

Practice Implications

This network meta-analysis by a renowned researcher and in a prestigious journal adds to the controversy around the relative efficacy of psychotherapy vs medications vs their combination. What is clear is that patients find medication alone to be less acceptable as a treatment option, and previous research shows that patients are 4 times more likely to prefer psychotherapy over medications. Unfortunately, most people with depression receive medications without psychotherapy.

Negative Effects of Psychotherapy

Cuijpers, P., Reijnders, M., Karyotaki, E., de Wit, L., & Ebert, D.D. (2018). Negative effects of psychotherapy for adult depression: A meta-analysis of deterioration rates. Journal of Affective Disorders, 239, 138-145.

Several types of psychotherapy are effective to treat depression, and there appears to be very little difference among the treatments in term of their effectiveness. Despite the documented effectiveness of psychotherapies to treat depression, there is also a growing interest in the clinical and research community about negative effects. Negative effects refer to the deterioration or worsening of depressive symptoms during treatment. Some may also refer to drop-out or non-response as a negative effect because these events are demoralizing and may prevent a patient from seeking more adequate care. Some researchers estimated that 5% to 10% of patients deteriorate during therapy. Deteriorations may not be due solely to the therapy itself, but instead may reflect the natural course of depression. In this meta-analysis, Cuijpers and colleagues examined studies in which a psychotherapy for depression was compared to a control condition in which patients did not receive an active treatment. In such studies, one might expect the control condition to represent what would happen in terms of symptoms if the patient received no treatment. Despite over 100 randomized controlled trials of a psychotherapy versus a non-active treatment control condition for depression, only 18 studies reported enough information to estimate negative effects. There was a median deterioration rate in the psychotherapy groups of about 4%, whereas the risk of deterioration in the control groups was about 11%. There were no differences in deterioration rates among types of psychotherapy (CBT vs others), treatment format (group vs individual), or type of control group (wait-list vs care as usual).

Practice Implications

Only 6.2% of research studies reported enough information to estimate negative effects, making it difficult to get a good estimate that represents all studies and patients. Nevertheless, receiving psychotherapy reduced deterioration rates by more than 61% compared to untreated control conditions, suggesting that psychotherapy can help some patients who might get worse with no treatment. Therapists should work to recognize and evaluate deterioration rates in therapy because they do occur for an important minority of patients. Some have suggested ongoing progress monitoring as a means of reducing the number of patients who might get worse during psychotherapy.

Jennissen, S., Huber, J., Ehrenthal, J.C., Schauenburg, H., & Dinger, U. (2018). Association between insight and outcome of psychotherapy: Systematic review and meta-analysis. The American Journal of Psychiatry. Published Online: https://doi.org/10.1176/appi.ajp.2018.17080847

For many authors, one of the purported mechanisms of change in psychotherapy is insight. In fact, the utility of insight for clients with mental health problems was first proposed over 120 years ago by Freud and Breuer. Briefly, insight refers to higher levels of self-understanding that might result in fewer negative automatic reactions to stress and other challenges, more positive emotions, and greater flexibility in cognitive and interpersonal functioning. Although insight is a key factor in some psychodynamic models, it also plays a role in other forms of psychotherapy. Experiential psychotherapy emphasises gaining a new perspective through experiencing, and for CBT insight relates to becoming more aware of automatic thoughts. Jennissen and colleagues defined insight as patients understanding: the relationship between past and present experiences, their typical relationship patterns, and the associations between interpersonal challenges, emotional experiences, and psychological symptoms. In this study, Jennissen and colleagues conducted a systematic review and meta analysis of the insight-outcome relationship, that is the relationship between client self-understanding and symptom reduction. They reviewed studies of adults seeking psychological treatment including individual or group therapy. The predictor variable was an empirical measure of insight assessed during treatment but prior to when final outcomes were evaluated. The outcome was some reliable and empirical measure related to symptom improvement, pre- to post- treatment. The review turned up 22 studies that included over 1100 patients mostly with anxiety or depressive disorders who attended a median of 20 sessions of therapy. The overall effect size of the association between insight and outcome was r = 0.31 (95% CI=0.22–0.40, p < 0.05), which represents a medium effect. Moderator analyses found no effect of type of therapy or diagnosis on this mean effect size, though the power of these analyses was low.

Practice Implications

The magnitude of the association between insight and outcome is similar to the effects of other therapeutic factors such as the therapeutic alliance. When gaining insight, patients may achieve a greater self-understanding, which allows them to reduce distorted perceptions of themselves, and better integrate unpleasant experiences into their conscious life. Symptoms may be improved by self-understanding because of the greater sense of control and master that it provides, and by the new solutions and adaptive ways of living that become available to clients.

Author email: Simone.Jennissen@med.uni-heidelberg.de

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.

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.