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Background: Common mental disorders, including depression and anxiety, are leading causes of disability worldwide. Digital mental health interventions, such as web-based self-help and other low-intensity treatments (LITs) that are not digital (eg, bibliotherapy), have the potential to reach many individuals by circumventing common barriers present in traditional mental health care. It is unclear how often LITs are used in clinical practice, or whether providers would be interested in their use for treatment waiting lists. Objective: The aims of this study were to (1) describe current practices for treatment waiting lists, (2) describe providers’ attitudes toward digital and nondigital LITs for patients on a waiting list, and (3) explore providers’ willingness to use digital and nondigital LITs and their decisions to learn about them. Methods: We surveyed 141 practicing mental health care providers (eg, therapists and psychologists) and provided an opportunity for them to learn about LITs. Results: Most participants reported keeping a waiting list. Few participants reported currently recommending digital or nondigital LITs, though most were willing to use at least one for patients on their waiting list. Attitudes toward digital and nondigital LITs were neutral to positive. Guided digital and nondigital LITs were generally perceived to be more effective but less accessible, and unguided interventions were perceived to be less effective but more accessible. Most participants selected to access additional information on LITs, with the most popular being web-based self-help. Conclusions: Results suggest providers are currently not recommending LITs for patients on treatment waiting lists but would be willing to recommend them. Future work should explore barriers and facilitators to implementing digital and nondigital LITs for patients on treatment waiting lists. [ABSTRACT FROM AUTHOR]

Although effective treatments for common mental health problems are available, individual responses to treatments are difficult to predict. Treatment efficacy could be optimized by targeting interventions using individual predictions of treatment outcomes. The aim of this study was to develop a prediction algorithm using data from one of the largest randomized controlled trials on psychological interventions for common mental health problems. This is a secondary analysis of the Enhancing Recovery in Coronary Heart Disease study investigating the effectiveness of cognitive behavioral therapy (CBT) and care as usual (CAU) for depression and low perceived social support following acute myocardial infarction. 2481 participants were randomly assigned to CBT and CAU. Baseline social-demographics, depression characteristics, comorbid symptoms, and stress and adversity measures were used to build an algorithm predicting post-treatment depression severity using elastic net regularization. Performance and generalizability of this algorithm were determined in a hold-out sample (n = 1203). Treatment matching based on predictions in the hold-out sample resulted in inconsistent and small effects (d = 0.15), that were more pronounced for individuals matched to CBT (d = 0.22). We identified a small subgroup of individuals for which CBT did not appear more efficacious than CAU. Limitations are a poorly defined CAU condition, a low-severity sample, specific exclusion criteria and unavailability of certain baseline variables. Small matching effects are likely a realistic representation of the performance and generalizability of multivariable prediction algorithms based on clinical measures. Results indicate that future work and new approaches are needed. • Machine learning predictions were made for targeted psychological interventions. • Predictions relied on self-report and clinical observation. • Predictions were developed and tested in a large dataset. • Predictions resulted in small matching effects. • Improvements are needed to guarantee clinical relevance of these prediction models. [ABSTRACT FROM AUTHOR]

Cognitive-behavioral therapies (CBTs) are the most widely studied form of psychotherapy for disorders like depression and anxiety. Nonetheless, there is heterogeneity in response to CBTs vs. other treatments. Researchers have become increasingly interested in using pre-treatment individual differences (i.e., moderators) to match patients to the most effective treatments for them. Several methods to combine multiple variables to create precision treatment rules (PTRs) that identify subgroups have been proposed. We review the rationale behind multivariable PTRs as well as the findings of studies that have used different PTRs. We identify conceptual and methodological issues in the literature. Multivariable treatment assignment is a promising avenue of research. Nonetheless, effect sizes appear to be small and most of the samples that have been used to study these questions have been grossly underpowered to detect small effects. We recommend researchers explore multivariable treatment selection strategies, particularly those resembling risk stratification, in heterogeneous samples of patients undergoing low-intensity CBTs vs. realistic minimal controls. [ABSTRACT FROM AUTHOR]

In this conceptual paper, we outline the many challenges on the road to personalized psychotherapy, using the example of cognitive behavior therapy (CBT) for depression. To optimize psychotherapy for the individual patient, we need to find out how therapy works (identification of mechanisms of change) and for whom it works (identification of moderators). To date, psychotherapy research has not resulted in compelling evidence for or against common or specific factors that have been proposed as mechanisms of change. Our central proposition is that we need to combine the "how does it work?"-question with the "for whom does it work?"-question in order to advance the field. We introduce the personalized causal pathway hypothesis that emphasizes the links and distinction between individual patient differences, therapeutic procedures and therapy processes as a paradigm to facilitate und understand the concept of personalized psychotherapy. We review the mechanism of change literature for CBT for depression to see what we have learned so far, and describe preliminary observational evidence supporting the personalized causal pathway hypothesis. We then propose a research agenda to push the ball forward: exploratory studies into the links between individual differences, therapeutic procedures, therapy processes and outcome that constitute a potential causal pathway, making use of experience sampling, network theory, observer ratings of therapy sessions, and moderated mediation analysis; testing and isolation of CBT procedures in experiments; and testing identified causal pathways of change as part of a personalized CBT package against regular CBT, in order to advance the application of personalized psychotherapy. [ABSTRACT FROM AUTHOR]

Introduction: Researchers have proposed that predicting who is a likely placebo responder may help guide treatment allocations to treatment regimens that differ in intensity. Methods: We used data from the Treatment of Adolescent Depression Study (TADS) in which adolescents (n = 439) were randomized 1:1:1:1 to placebo, cognitive-behavioral therapy (CBT), medications (MEDs), or their combination (COMB). We developed a prognostic index (PI) in the placebo group to predict self-reported (RADS) and observer-rated (CDRS) depression outcomes using elastic net regularization. We explored whether the PIs moderated outcomes in the treatment conditions. Results: PI-CDRS was predicted by multiple variables but it did not moderate outcomes. PI-RADS was predicted by baseline severity, age, sleep problems, expectations, maternal depression, and the action stage of change. It moderated outcomes such that there were treatment differences for less placebo-responsive patients. For participants prone to placebo response, type of treatment had no statistically significant impact on outcomes. Baseline depression severity accounted for this effect: treatment differences were small and non-significant for patients with milder depression but larger in more severely depressed patients. Discussion: Future work should investigate whether multiple variable explain outcomes beyond severity as well as complex interactions between severity and other variables. [ABSTRACT FROM AUTHOR]

Identifying differences in the clinical response to specific interventions is an important challenge in the field of Clinical Psychology. This is especially true in the treatment of depression where many treatments appear to have comparable outcomes. In a controlled trial, we compared a positive psychology group intervention, the Integrative Positive Psychological Intervention for Depression (IPPI-D; n = 62) to a cognitive-behavioral therapy group intervention (CBT; n = 66) for depression. No statistically or clinically-significant differences between the treatments were found, but a slight advantage was observed, on average, for IPPI-D. The aim of the present study was to identify and combine moderators of the differential efficacy of these two psychological interventions for clinical depression. For this purpose, a secondary analysis using the Personalized Advantage Index (PAI) was performed to identify the intervention predicted to produce the better outcome for each patient. Six of the 21 potential moderators were found to predict differential efficacy between the treatments. IPPI-D was predicted to be the optimal treatment for 73% of the sample. Baseline features that characterized these individuals were: mental and physical comorbidity, prior antidepressant medication, higher levels of negative thoughts, and higher personal growth. The 27% who were predicted to achieve better outcomes in CBT than in IPPI-D tended to have these baseline features: no comorbidities, no prior antidepressant medication, lower levels of negative thoughts, and lower personal growth. [ABSTRACT FROM AUTHOR]

Identifying active ingredients of psychological interventions is a major goal of psychotherapy researchers that is often justified by the promise that it will lead to improved patient outcomes. Much of this "active ingredients" research is conducted within randomized controlled trials (RCTs) with patient populations, putting it in Phase T2 of the clinical-translational spectrum. I argue that RCTs in patient populations are very "messy laboratories" in which to conduct active ingredient work and that T0 and T1 research provide more controlled contexts. However, I call attention to the long road from identifying active ingredients of CBTs, whether in T0, T1, or T2 research, to improving outcomes. Dissemination and implementation research (T3 and T4 approaches) may be conceptually closer to improving outcomes. Given how common and disabling mental health symptoms are, I argue that if researchers want to improve patient outcomes, these research programs must receive more attention including work on the uptake of psychological interventions as well as work on optimal ordering of existing interventions. • Research on active ingredients is criticized. • Identifying active ingredients of CBTs may be slow to improve treatment outcomes. • Other research programmes have more immediate potential to improve outcomes. • Researchers should study the entire clinical-translational spectrum to advance CBTs. [ABSTRACT FROM AUTHOR]

One of the main debates in the study of psychotherapy is whether specific techniques are best indicated for different problems or whether “common factors” better account for the efficacy of psychotherapy. Evidence for the superiority of specific techniques is mixed and limited to a handful of diagnoses. By contrast, evidence for the importance of common factors is riddled with methodological weaknesses and may be of limited clinical utility. The stagnation in this debate may reflect that the research methods heretofore employed have reached a plateau in their ability to advance knowledge regarding psychotherapy processes. The articles of the special issue move beyond simple bivariate relationship and attempt to model the real-world complexity involved in the process of psychotherapy. It is argued that these types of investigations, which model the interactions of patient characteristics as well as multiple specific and “common factors,” are the best way to advance the state of knowledge regarding psychotherapy processes. [ABSTRACT FROM AUTHOR]

Prior studies have suggested that the association between the alliance and depression improvement varies as a function of prior history of depression. We sought to replicate these findings and extend them to short-term psychodynamic supportive psychotherapy (SPSP) in a sample of patients who were randomized to one of these treatments and were administered the Helping Alliance Questionnaire (N=282) at Week 5 of treatment. Overall, the alliance was a predictor of symptom change (d=0.33). In SPSP, the alliance was a modest but robust predictor of change, irrespective of prior episodes (d=0.25-0.33). By contrast, in CBT, the effects of the alliance on symptom change were large for patients with 0 prior episodes (d=0.86), moderate for those with 1 prior episode (d=0.49), and small for those with 2+ prior episodes (d=0.12). These findings suggest a complex interaction between patient features and common vs. specific therapy processes. In CBT, the alliance relates to change for patients with less recurrent depression whereas other CBT-specific processes may account for change for patients with more recurrent depression. [ABSTRACT FROM AUTHOR]

Background: Prognostic indices (PIs) combining variables to predict future depression risk may help guide the selection of treatments that differ in intensity. We develop a PI and show its promise in guiding treatment decisions between treatment as usual (TAU), treatment starting with a low-intensity treatment (brief therapy (BT)), or treatment starting with a high-intensity treatment intervention (cognitive-behavioral therapy (CBT)).Methods: We utilized data from depressed patients (N=622) who participated in a randomized comparison of TAU, BT, and CBT in which no statistically significant differences in the primary outcomes emerged between the three treatments. We developed a PI by predicting depression risk at follow-up using a LASSO-style bootstrap variable selection procedure. We then examined between-treatment differences in outcome as a function of the PI.Results: Unemployment, depression severity, hostility, sleep problems, and lower positive emotionality at baseline predicted a lower likelihood of recovery across treatments. The PI incorporating these variables produced a fair classification accuracy (c=0.73). Among patients with a high PI (75% percent of the sample), recovery rates were high and did not differ between treatments (79-86%). Among the patients with the poorest prognosis, recovery rates were substantially higher in the CBT condition (60%) than in TAU (39%) or BT (44%).Limitations: No information on additional treatment sought. Prospective tests needed.Conclusion: Replicable PIs may aid treatment selection and help streamline stepped models of care. Differences between treatments for depression that differ in intensity may only emerge for patients with the poorest prognosis. [ABSTRACT FROM AUTHOR]

Since the introduction of Beck's cognitive theory of emotional disorders, and their treatment with psychotherapy, cognitive-behavioral approaches have become the most extensively researched psychological treatment for a wide variety of disorders. Despite this, the relative contribution of cognitive to behavioral approaches to treatment are poorly understood and the mechanistic role of cognitive change in therapy is widely debated. We critically review this literature, focusing on the mechanistic role of cognitive change across cognitive and behavioral therapies for depressive and anxiety disorders. [ABSTRACT FROM AUTHOR]

Many attempts have been made to discover and characterize the mechanisms of change in psychotherapies for depression, yet no clear, evidence-based account of the relationship between therapeutic procedures, psychological mechanisms, and symptom improvement has emerged. Negatively-biased thinking plays an important role in the phenomenology of depression, and most theorists acknowledge that cognitive changes occur during successful treatments. However, the causal role of cognitive change procedures in promoting cognitive change and alleviating depressive symptoms has been questioned. We describe the methodological and inferential limitations of the relevant empirical investigations and provide recommendations for addressing them. We then develop a framework within which the possible links between cognitive procedures, cognitive change, and symptom change can be considered. We conclude that cognitive procedures are effective in alleviating symptoms of depression and that cognitive change, regardless of how it is achieved, contributes to symptom change, a pattern of findings that lends support to the cognitive theory of depression. [ABSTRACT FROM AUTHOR]

The authors comment on the article by Wampold and colleagues in the 2017 issue if the journal which criticizes three meta-analysis suggesting superior effects of cognitive behavior therapy (CBT) over other psychotherapy strategies for general psychopathology and social phobia. They explore arguments by Wampold and colleagues on the effectiveness of CBT than other psychotherapies and concerns over the use of the term CBT in medical literature.

Objective: Little is known about the variability of the alliance-outcome correlation across identifiable client subsets. This question was explored in a sample of 60 clients receiving cognitive therapy for depression, from which an overall correlation of .23 was observed between alliance ratings and subsequent symptom change. Method: We examined interactions between the observer-rated version of the Working Alliance Inventory-Short Observer-Rated version (WAI-O; Tracey & Kokotovic, 1989) and client demographics, features of depression, personality, and other clinical features in predicting subsequent symptom change. Results: After correcting for multiple comparisons, interactions between the WAI-0 and the number of prior depressive episodes, as well as the severity of baseline anxiety symptoms, were significant predictors of symptom change. When both interactions were controlled for, number of prior depressive episodes emerged as a statistically significant moderator. The alliance predicted outcome in the subgroup of clients with 0-2 prior episodes (r = .52), but not in those with 3 or more prior episodes (r = -.02). These findings were obtained despite similar univariate distributions on the alliance and symptom change in the 2 subgroups. Discussion: Differences that were observed in the predictive relation of alliance to outcome as a function of number of prior episodes suggest that different therapy processes may account for change in these subgroups. If the pattern observed in the present study is replicated, it would suggest that the alliance-outcome association has been both under-and overestimated. [ABSTRACT FROM AUTHOR]

It has been reported that approximately one of out of every ten Puerto Rican adolescents has serious suicidal ideation. In this study we evaluated the predictive value of some cognitive, behavioral, and affective variables to explain suicidal ideation from a cognitive-behavioral perspective. The sample was comprised of 179 adolescents (ages 13-18) who filled self-report surveys. Approximately 17% of the sample reported thinking about suicide 'sometimes' or 'very frequently'. These adolescents were more depressed, had more dysfunctional thoughts, lower self-concept, and less healthy coping strategies than those who did not report suicidal ideation. These variables also predicted suicidal ideation. These results evidence the large prevalence of suicidal ideation in Puerto Rican adolescents. [ABSTRACT FROM AUTHOR]

Studies suggest that depression severity and duration interact to predict outcomes in depression treatment. To our knowledge, no study has explored this question in a sample with a placebo control, two therapies, and their combination nor with adolescents. We used data from the Treatment of Adolescent Depression Study (N = 439), in which adolescent were randomized to placebo (PBO), cognitive-behavioral therapy (CBT), antidepressants medications (MEDs), or their combination (COMB). We explore the interaction between depression severity, chronicity, and treatments (vs. placebo) in predicting outcomes. There was interaction between severity and chronicity when comparing COMB and CBT with PBO, but not MEDs. In non-chronic depression, the effects of CBT were inversely related to severity to the point that CBT appeared iatrogenic with more severe depression. In chronic depression, the effects of CBT did not vary by severity, but the relative effects of COMB grew, being smallest in milder, more dysthymic-like depression, and largest in chronic-severe depression. These findings support calls to classify depression by severity and chronicity as well efforts to risk stratify patients to different intensity of care according to these variables. • Depression severity and chronicity may interact to predict treatment outcomes. • We explored this question in the Treatment for Adolescent Depression Study (TADS). • In non-chronic depression, greater severity predicted lower response to CBT (vs. placebo). • In chronic depression, greater severity predicted better response to combination treatment. • Adding medications to CBT may potentiate its efficacy in high risk depression subgroups. [ABSTRACT FROM AUTHOR]

Increased quality of life (QoL) is rated by patients as a primary factor in determining recovery from psychopathology. Cognitive behavioral therapies (CBTs) are the most well-researched psychotherapies for internalizing disorders and appear effective at reducing symptoms even when delivered by trainees. Existing research suggests that the effects of CBTs on QoL are more modest than their effects on symptoms. However, little is known about the effects of trainee-delivered CBT on life satisfaction, a subjective measure of QoL. We analyzed data from 93 clients treated by students (n = 23) in a graduate-level training clinic using an intent-to-treat approach, completers case analyses, and random forest imputation. Across methods of handling missing data, improvements in anxiety, depression, and CBT skills were more marked than improvements in QoL. Exploratory analyses suggested baseline life satisfaction was the strongest predictor of end-of-treatment life satisfaction. Future research should explore alternatives to "standard" CBT for clients with low life satisfaction. [ABSTRACT FROM AUTHOR]

Background: Self-guided internet-based cognitive behavioral therapies (iCBTs) for depressive symptoms may substantially increase accessibility to mental health treatment. Despite this, questions remain as to the generalizability of the research on self-guided iCBT.Objective: We sought to describe the clinical entry criteria used in studies of self-guided iCBT, explore the criteria's effects on study outcomes, and compare the frequency of use of these criteria with their use in studies of face-to-face psychotherapy and antidepressant medications. We hypothesized that self-guided iCBT studies would use more stringent criteria that would bias the sample toward those with a less complex clinical profile, thus inflating treatment outcomes.Methods: We updated a recently published meta-analysis by conducting a systematic literature search in PubMed, MEDLINE, PsycINFO, and EMBASE. We conducted a meta-regression analysis to test the effect of the different commonly used psychiatric entry criteria on the treatment-control differences. We also compared the frequency with which exclusion criteria were used in the self-guided iCBT studies versus studies of face-to-face psychotherapy and antidepressants from a recently published review.Results: Our search yielded 5 additional studies, which we added to the 16 studies identified by Karyotaki and colleagues in 2017. Few self-guided iCBT studies excluded patients with severe depressive symptoms (6/21, 29%), but self-guided iCBT studies were more likely than antidepressant (14/170, 8.2%) studies to use this criterion. However, self-guided iCBT studies did not use this criterion more frequently than face-to-face psychotherapy studies (6/16, 38%). Beyond this, we found no evidence that self-guided iCBTs used more stringent entry criteria. Strong evidence suggested that they were actually less likely to use most entry criteria, especially exclusions on the basis of substance use or personality pathology. None of the entry criteria used had an effect on outcomes.Conclusions: A conservative interpretation of our findings is that the patient population sampled in the literature on self-guided iCBT is relatively comparable with that of studies of antidepressants or face-to-face psychotherapy. Alternatively, studies of unguided cognitive behavioral therapy may sample from a more heterogeneous and representative patient population. Until evidence emerges to suggest otherwise, the patient population sampled in self-guided iCBT studies cannot be considered as less complex than the patient population from face-to-face psychotherapy or antidepressant studies. [ABSTRACT FROM AUTHOR]

• Most RCT-tested iCBTs are not accessible to the public. • A significant number of RCT-tested iCBTs are geographically restricted. • iCBTs are more likely to contain evidence-based components, than popular MH apps. We examined the availability and components of internet-based cognitive-behavioral therapies (iCBTs) for depression tested in randomized-controlled trials (RCTs). The objectives of this literature review were to determine the extent to which research-validated iCBTs were available to the public, as well as to determine their therapeutic content. A literature review of RCTs for iCBTs was conducted on July 30, 2021. For each iCBT, interventions were rated by content and compared to commercially available smartphone apps. Our search yielded 80 studies using 41 unique iCBTs. Of these, only 6 (15%) were completely available to the public, more than half were not publicly available (46%), and the remaining 39% were available to the public with some restrictions (e.g., those based on the user's geographical location). When comparing iCBTs evaluated in RCTs to commercially available smartphone apps, we found that iCBTs were more likely to contain psychoeducation, cognitive restructuring, behavioral activation, problem solving, and interpersonal communication components. iCBTs from RCTs contain evidence-based content but few are available to the public. Extending beyond efficacy, attention should be paid to the dissemination of iCBTs. [ABSTRACT FROM AUTHOR]