Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual participant data.

BACKGROUND: Internet cognitive behavioural therapy (iCBT) is a viable delivery format of CBT for depression. However, iCBT programmes include training in a wide array of cognitive and behavioural skills via different delivery methods, and it remains unclear which of these components are more efficacious and for whom. METHODS: We did a systematic review and individual participant data component network meta-analysis (cNMA) of iCBT trials for depression. We searched PubMed, PsycINFO, Embase, and the Cochrane Library for randomised controlled trials (RCTs) published from database inception to Jan 1, 2019, that compared any form of iCBT against another or a control condition in the acute treatment of adults (aged ≥18 years) with depression. Studies with inpatients or patients with bipolar depression were excluded. We sought individual participant data from the original authors. When these data were unavailable, we used aggregate data. Two independent researchers identified the included components. The primary outcome was depression severity, expressed as incremental mean difference (iMD) in the Patient Health Questionnaire-9 (PHQ-9) scores when a component is added to a treatment. We developed a web app that estimates relative efficacies between any two combinations of components, given baseline patient characteristics. This study is registered in PROSPERO, CRD42018104683. FINDINGS: We identified 76 RCTs, including 48 trials contributing individual participant data (11 704 participants) and 28 trials with aggregate data (6474 participants). The participants' weighted mean age was 42·0 years and 12 406 (71%) of 17 521 reported were women. There was suggestive evidence that behavioural activation might be beneficial (iMD -1·83 [95% credible interval (CrI) -2·90 to -0·80]) and that relaxation might be harmful (1·20 [95% CrI 0·17 to 2·27]). Baseline severity emerged as the strongest prognostic factor for endpoint depression. Combining human and automated encouragement reduced dropouts from treatment (incremental odds ratio, 0·32 [95% CrI 0·13 to 0·93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. INTERPRETATION: The individual patient data cNMA revealed potentially helpful, less helpful, or harmful components and delivery formats for iCBT packages. iCBT packages aiming to be effective and efficient might choose to include beneficial components and exclude ones that are potentially detrimental. Our web app can facilitate shared decision making by therapist and patient in choosing their preferred iCBT package. FUNDING: Japan Society for the Promotion of Science.

An examination of dysfunctional attitudes and extreme response styles as predictors of relapse in guided internet-based cognitive behavioral therapy for depression.

OBJECTIVES: Internet-based cognitive behavioral therapy (iCBT) is an effective treatment option for depression, but its long-term effects are not well understood. We investigate for whom iCBT may have more enduring effects by evaluating dysfunctional attitudes as predictors of relapse. METHODS: The sample consists of 31 iCBT responders (20 women, average age 31.6) who were followed for 1 year. RESULTS: Higher Dysfunctional Attitudes Scale scores predicted higher risk of relapse (hazard ratio = 1.98). This relation remained significant when controlling for high style (dysfunctional) or content (functional) responses. Having relatively more positive extreme responses on style rather than content items did not predict risk of relapse. CONCLUSIONS: Our results were consistent with the value of differentiating an extreme style of responding from otherwise endorsing belief in dysfunctional attitudes. Research that refines our understanding of patients' individual risk for relapse has the potential to inform how treatment might be individually tailored.

Guided internet CBT versus "gold standard" depression treatments: An individual patient analysis.

OBJECTIVE: Guided, computerized cognitive behavioral therapy delivered over the internet (iCBT) is a promising treatment for depression. However, comparisons to "gold standard" treatments and comparators, such as structured psychotherapy, medications, or pill placebo are rare. We compare the results of an 8-week trial of guided iCBT to outcomes from two trials of depression treatment, Penn-Vandy and U. Washington, using individual patient data. METHOD: We adjusted for sample differences by restricting the iCBT sample to randomised controlled trial (RCT) inclusion criteria and using propensity scores. Three separate samples were included in analyses: iCBT trial (N = 89), Penn-Vandy (N = 240), and U. Washington (N = 241). Continuous outcomes were analyzed with linear-mixed models and noninferiority analyses were conducted for iCBT versus the psychotherapy conditions. The primary outcomes were attrition, remission, and the Hamilton Rating Scale for Depression. RESULTS: Dropout was greater in iCBT than in CT, medications, placebo (Penn-Vandy), and CT and BA (U. Washington), but the rates of remission were similar. In continuous analyses, iCBT was superior to placebo in both RCTs and most analyses indicated no difference between iCBT and the active treatments. CONCLUSIONS: Guided iCBT appears not inferior to "gold standard" treatments for depression and is superior to placebo. Weaknesses include a lack of randomization, unblinded assessments, and a shorter "frame of treatment" in the iCBT sample.

Predictors of Dropout in Internet-Based Cognitive Behavioral Therapy for Depression.

Internet-based cognitive behavioral therapy (iCBT), provided with guidance, has been shown to outperform wait-list control conditions and appears to perform on par with face-to-face psychotherapy. However, dropout remains an important problem. Dropout rates for iCBT programs for depression have ranged from 0% to 75%, with a mean of 32%. Drawing from a recent study in which 117 people participated in iCBT with support, we examined participant characteristics, participants' use of iCBT skills, and their experience of technical difficulties with iCBT as predictors of dropout risk. Educational level, extraversion, and participant skill use predicted lower risk of dropout; technical difficulties and openness predicted higher dropout risk. We encourage future research on predictors of dropout in the hope that greater understanding of dropout risk will inform efforts to promote program engagement and retention.

Dysfunctional attitudes or extreme response style as predictors of depressive relapse and recurrence after mobile cognitive therapy for recurrent depression.

BACKGROUND: According to previous research, dysfunctional attitudes and/or scoring extreme on the end-point anchors of questionnaires of dysfunctional thinking predict depressive relapse/recurrence. Evidence that these two methods represent a risk for depressive relapse/recurrence is however mixed, due to differential or poorly defined concepts. The current study aimed to test the two methods. METHODS: Remitted recurrently depressed patients with low residual depressive symptoms (N = 264) were recruited as part of a randomized controlled trial of the effectiveness of mobile Cognitive Therapy for recurrent depression versus treatment as usual. In the current secondary analysis, Cox regression models were conducted to test dysfunctional attitudes and extreme responding variables (assessed on the Dysfunctional Attitudes Scale [DAS]) as predictors of depressive relapse/recurrence within two years after randomization. RESULTS: Data from 255 participants were analyzed. Results showed that DAS total scores at baseline significantly predicted depressive relapse/recurrence (Hazard Ratio [HR] = 1.01, p = .042). An index that reflects endorsement of habitual relative to functional responses was a significant predictor of depressive relapse/recurrence (HR = 2.11, p = .029). LIMITATIONS: The current study employed a single measure to identify extreme responses and dysfunctional attitudes. Secondly, various statistical analyses were performed without correcting for multiple testing, which in turn increased the likelihood to finding significant results. CONCLUSIONS: Current study confirmed both methods: People who scored higher on the DAS or had relatively more habitual than functional responses on the extreme positive ends of the DAS had a decreased time to depressive relapse/recurrence.

Efficacy of Guided iCBT for Depression and Mediation of Change by Cognitive Skill Acquisition.

Guided internet CBT (iCBT) is a promising treatment for depression; however, it is less well known through what mechanisms iCBT works. Two possible mediators of change are the acquisition of cognitive skills and increases in behavioral activation. We report results of an 8-week waitlist controlled trial of guided iCBT, and test whether early change in cognitive skills or behavioral activation mediated subsequent change in depression. The sample was 89 individuals randomized to guided iCBT (n = 59) or waitlist (n = 30). Participants were 75% female, 72% Caucasian, and 33 years old on average. The PHQ9 was the primary outcome measure. Mediators were the Competencies of Cognitive Therapy Scale-Self Report and the Behavioral Activation Scale for Depression-Short Form. Treatment was Beating the Blues plus manualized coaching. Outcomes were analyzed using linear mixed models, and mediation with a bootstrap resampling approach. The iCBT group was superior to waitlist, with large effect sizes at posttreatment (Hedges' g = 1.45). Dropout of iCBT was 29% versus 10% for waitlist. In the mediation analyses, the acquisition of cognitive skills mediated subsequent depression change (indirect effect = -.61, 95% bootstrapped biased corrected CI: -1.47, -0.09), but increases in behavioral activation did not. iCBT is an effective treatment for depression, but dropout rates remain high. Change in iCBT appears to be mediated by improvements in the use of cognitive skills, such as critically evaluating and restructuring negative thoughts.

Prognosis moderates the engagement-outcome relationship in unguided cCBT for depression: A proof of concept for the prognosis moderation hypothesis.

OBJECTIVE: Understanding how treatments work is a goal of psychotherapy research, however the strength of relationships between therapy processes and outcomes is inconsistent. DeRubeis, Cohen, et al. (2014) proposed that process-outcome relationships are moderated by patient characteristics. These "patient response patterns" (PRPs) indicate individuals' responsiveness to the active ingredients of treatment. Given the same quality of therapy, one individual may receive more benefit than another depending on their PRP. The "prognosis moderation hypothesis" states that PRPs can be defined by pretreatment prognostic indicators. Medium prognosis groups ("pliant-like") will have stronger process-outcome relationships than good ("easy-like") or poor ("challenging-like") groups. METHOD: N = 190 individuals received unguided computerized CBT. They were 58% women, aged 44.7 years. Engagement with the cCBT program was the process variable. PRPs were defined by predicted scores from a prognostic regression model. Outcomes were BDI scores at 3, 6, and 12 months. "Easy-like," "pliant-like" and "challenging-like" groups were created and the engagement-outcome relationship was assessed as a function of group. RESULTS: Engagement-outcome correlations by PRP were: easy-like, r = -.27 (p < .05); pliant-like, r = -.36 (p < .01); and challenging-like, r = .05 (p = .70). The pliant-like group was found to be the only moderator of the engagement-outcome relationship. Results were similar at 6 months but faded at 12. CONCLUSIONS: The engagement-outcome relationship varied as a function of prognosis, providing support for the prognosis moderation hypothesis. The "pliant-like" group appeared most sensitive to treatment procedures. Future research is needed to refine the methods for identifying PRPs. (PsycINFO Database Record

Positive extreme responding after cognitive therapy for depression: Correlates and potential mechanisms.

"Extreme responding" is the tendency to endorse extreme responses on self-report measures (e.g., 1s and 7s on a 7-point scale). It has been linked to depressive relapse after cognitive therapy (CT), but the mechanisms are unknown. Moreover, findings of positive extreme responding (PER) predicting depressive relapse do not support the original hypothesis of "extreme" negative thinking leading to extreme negative emotional reactions. We assessed the relationships between post-treatment PER on the Dysfunctional Attitudes Scale (DAS) and Attributional Style Questionnaire (ASQ) and these constructs: coping skills, in-session performance of cognitive therapy skills, age, and estimated IQ. Significant correlates were entered into a model predicting rate of relapse to determine whether these constructs explained the relationship between PER and relapse. The sample consisted of 60 individuals who participated in CT for moderate to severe depression. Results indicated the following relationships: a negative correlation between ASQ PER and IQ, negative correlations between DAS PER and performance of CT skills and planning coping, and a positive correlation between DAS PER and behavioral disengagement coping. IQ scores fully accounted for the relationship between ASQ PER and relapse. These results suggest two potential mechanisms linking PER to relapse: cognitive limitations and coping deficits/cognitive avoidance.

Extreme response style and symptom return after depression treatment: the role of positive extreme responding.

OBJECTIVE: Evidence linking extreme response style (ER) to depressive relapse has been mixed. One reason might be high levels of extreme responses that are positive in nature (ER-Ps) compared with those negative in nature (ER-Ns) at posttreatment. ER-Ps likely consist of both maladaptive "style" responses and adaptive "content" responses (i.e., legitimate denials of dysfunction). The composition of ER-Ps might confound measures of total extreme responding as well as conventional scores on cognitive questionnaires. In the current study, we assessed ER in a new sample by (a) disambiguating ER-Ps that reflect style from those that reflect content and (b) assessing the contribution of ER-Ps to the prediction of relapse/recurrence. METHOD: Responders (N = 104) to a randomized controlled trial of cognitive therapy versus medications for moderate to severe depression had an average age of 40 years (SD = 12), and they were 58% female, 38% married/cohabitating, and 85% Caucasian. ER variables were calculated using the Dysfunctional Attitudes Scale (DAS; Weissman, 1979), with ER-Ps categorized as either content or style responses. ER indices and DAS scores were used to predict symptom return over 2 years. RESULTS: No standard extreme responding variables (e.g., an index of total extreme responding) predicted symptom return, but higher relative levels of style ER-P predicted relapse/recurrence. Total DAS scores also predicted relapse/recurrence but only when high levels of style ER-P responses were controlled. CONCLUSIONS: ER-Ps, at least on the DAS, appear to contain indicators of both adaptive and maladaptive positive responses. Future research should attend to the valence of the extreme responses as well as to the content of extreme positive responses, which may reflect either healthy or unhealthy tendencies.

The Personalized Advantage Index: translating research on prediction into individualized treatment recommendations. A demonstration.

BACKGROUND: Advances in personalized medicine require the identification of variables that predict differential response to treatments as well as the development and refinement of methods to transform predictive information into actionable recommendations. OBJECTIVE: To illustrate and test a new method for integrating predictive information to aid in treatment selection, using data from a randomized treatment comparison. METHOD: Data from a trial of antidepressant medications (N = 104) versus cognitive behavioral therapy (N = 50) for Major Depressive Disorder were used to produce predictions of post-treatment scores on the Hamilton Rating Scale for Depression (HRSD) in each of the two treatments for each of the 154 patients. The patient's own data were not used in the models that yielded these predictions. Five pre-randomization variables that predicted differential response (marital status, employment status, life events, comorbid personality disorder, and prior medication trials) were included in regression models, permitting the calculation of each patient's Personalized Advantage Index (PAI), in HRSD units. RESULTS: For 60% of the sample a clinically meaningful advantage (PAI≥3) was predicted for one of the treatments, relative to the other. When these patients were divided into those randomly assigned to their "Optimal" treatment versus those assigned to their "Non-optimal" treatment, outcomes in the former group were superior (d = 0.58, 95% CI .17-1.01). CONCLUSIONS: This approach to treatment selection, implemented in the context of two equally effective treatments, yielded effects that, if obtained prospectively, would rival those routinely observed in comparisons of active versus control treatments.

Understanding processes of change: how some patients reveal more than others-and some groups of therapists less-about what matters in psychotherapy.

OBJECTIVE: We identify difficulties researchers encounter in psychotherapy process-outcome investigations, and we describe several limitations of the popular "variance accounted for" approach to understanding the effects of psychotherapy. METHODS & RESULTS: Using data simulations, we show how the expected correlation between an excellent measure of therapy quality and outcome would be surprisingly small (approximately .25) under conditions likely to be common in psychotherapy research. Even when we modeled conditions designed to increase the likelihood that strong process-outcome relationships would be observed, we found that the expected correlations were still only in the modest range (.38-.51). CONCLUSIONS: We discuss the implications of our analysis for the interpretation of process-outcome findings as well as for design considerations in future investigations.

Pretreatment anxiety predicts patterns of change in cognitive behavioral therapy and medications for depression.

OBJECTIVE: Some studies report that initial anxiety is associated with equivocal or negative effects in depression treatment. In contrast, at least 4 studies of cognitive behavioral therapy (CBT) report that anxiety predicts greater or more rapid change in depression. Further exploration is needed to clarify the relationship between initial anxiety and depression change. Questions include the relationship between anxiety and patterns of change and time to relapse, as well as the specificity effects to CBT. METHOD: The study assessed the relation of Beck Anxiety Inventory anxiety scores to early rapid change and overall change in Beck Depression Inventory-II depression scores during acute depression treatment. Participants were 178 individuals enrolled in a randomized controlled trial of CBT versus antidepressant medications (ADMs) for moderate to severe depression. They were 58% female and 83% Caucasian, with an average age of 40 (SD = 11.5). Thirty-four percent (34%) were married or cohabitating. Hierarchical linear models, including quadratic growth parameters, were used to model change. The relation of anxiety to the probability of posttreatment relapse was also examined. RESULTS: Findings indicate that higher levels of anxiety predict early rapid change, but not overall change, in both CBT and ADM. However, patients with higher levels of intake anxiety evidenced increased risk for relapse after CBT. CONCLUSIONS: Early rapid change predicted by anxiety occurs across different treatment conditions, but this early rapid response is not indicative of positive overall outcome in all cases. These findings might indicate that anxiety predicts a response to nonspecific "common factors" of treatment.

Cognitive behavioral therapy in practice: treatment delivered by trainees at an outpatient clinic is clinically effective.

Cognitive-behavioral therapy (CBT) is known to be effective for a number of disorders, and can be delivered effectively by trainees in controlled settings. However, the effectiveness of trainee therapists in general practice compared to that of more experienced therapists is unknown. In this study, the authors used a benchmarking strategy to compare the outcomes of naturalistic CBT delivered by trainee therapists to those of efficacy and effectiveness studies using primarily professional therapists. Patients (N=249) with mood and anxiety disorders were treated by trainees (primarily by interns and postdocs) using nonstandardized nonmanualized CBT at an outpatient clinic in an urban academic medical center. Changes in anxiety and depression were assessed using effect sizes, reliable and clinically significant change, and benchmarked to efficacy and effectiveness studies. Symptoms of anxiety and depression significantly improved from start to end of treatment. Rates of improvement and recovery compared favorably to those achieved in other studies, with the exception of recovery rates in severe depression. Effect sizes were in the medium to large range, but generally lower than those achieved in other studies. Results suggest that CBT can be delivered effectively by trainees in an outpatient setting.

Demystifying the Postdoctoral Experience: A Guide for Applicants.

Obtaining a postdoctoral position is a common and sometimes necessary step for psychologists' career development. However, in contrast to the internship application process, there is little formal guidance for postdoctoral applicants. By using professional resources and the experiences of individuals familiar with the postdoctoral process, we provide a detailed look at the process of obtaining a postdoctoral position. We cover the search, application, interview, and acceptance process, and provide some advice for dealing with common problems.

The influence of dysphoria on reactivity to naturalistic fluctuations in anger.

We used an experience sampling methodology to explore the relationship between current symptoms of dysphoria and momentary mood fluctuations following everyday experiences of anger. Using PDA devices, participants rated their mood, ruminative cognitions, feelings of dependency, and stressful events 4 times per day for 1 week. We hypothesized and found that those higher in dysphoria would demonstrate a stronger link between anger and depressed mood than those who were lower in dysphoria. Those participants who reported higher initial dysphoria indicated more anger over the course of the week, a stronger within-person association between anger and depressed mood, and a slower recovery from anger experiences. Multilevel moderated mediation analyses indicated that the link between anger and depressed mood for those high in dysphoria is largely explained by a stronger carryover of anger from one assessment to the next and partially explained by greater increases in ruminative cognitions and feelings of dependency. The change in depressed mood appears to occur with increases in anger, specifically, and not other negative mood states. Our results extend previous research on the anger-depression relationship by investigating the short-term relationships between anger and depressed mood among those with varying levels of dysphoria.

Influence of dysphoria on positive and negative cognitive reactivity to daily mood fluctuations.

We used an experience sampling design to investigate the influence of dysphoria on positive and negative cognitive reactivity. Participants recorded their thoughts and mood four times per day on PDA devices for one week. We hypothesized that those higher in dysphoria would demonstrate a greater increase in negative thinking in response to negative mood, and a weaker increase in positive cognitions in response to positive mood. These hypotheses were largely supported. For those participants who reported higher initial dysphoria, there was a stronger association between negative mood and thinking and a weaker link between positive mood and thinking. Regression analyses indicated that positive and negative cognitive reactivity were independently related to dysphoria, suggesting that they represent distinct processes. Our results highlight the importance of understanding levels of both negative and positive cognitive reactivity and underscore the benefits of assessing mood and cognition with repeated measurements in "real-time," in order to better understand the antecedent effects of mood on thinking.