Personalized Medicine and Cognitive Behavioral Therapies for Depression: Small Effects, Big Problems, and Bigger Data

Self-Guided Behavioral Activation Using an Online Single-Session Intervention: Content and Lexical Analyses of Activity Scheduling

The Common Elements Toolbox (COMET) is a self-guided online single-session intervention (SSI) containing cognitive-behavioral elements, including behavioral activation (BA). Little is known about the process of activity scheduling in BA. Using data from an 8-week randomized controlled trial of COMET with 409 online workers with a history of psychopathology, two raters coded the types of activities individuals scheduled during the intervention. Additionally, we compared the activities to a BA dictionary developed from therapist-led psychotherapy. We explored baseline clinical and demographic variables that were predictive of the activity category scheduled and explored the scheduled activity category as a predictor of depression, anxiety, and well-being post-intervention. Results yielded 9 different activity types, most commonly sedentary hobbies (41%), physical activity (29%), and active hobbies (18%). We found a small overlap (17%) between the self-guided BA activities in our COMET sample and those in the existing BA dictionary. Demographic variables were predictive of activity category, but clinical variables were not. The type of activity scheduled was not predictive of post-intervention outcomes. In self-guided BA, individuals, particularly men, less educated participants, and racial-ethnic minorities, tend to pick sedentary activities. Findings underscore the need for adaptive and personalized interventions.

Safety and Efficacy of Modular Digital Psychotherapy for Social Anxiety: Randomized Controlled Trial

BACKGROUND

Social anxiety disorder is a common mental health condition characterized by an intense fear of social situations that can lead to significant impairment in daily life. Cognitive behavioral therapy (CBT) has been recognized as an effective treatment; however, access to therapists is limited, and the fear of interacting with therapists can delay treatment seeking. Furthermore, not all individuals respond. Tailoring modular treatments to individual cognitive profiles may improve efficacy. We developed a novel digital adaptation of CBT for social anxiety that is both modular and fully digital without a therapist in the loop and implemented it in the smartphone app Alena.

OBJECTIVE

This study aimed to evaluate the safety, acceptability, and efficacy of the new treatment in online participants with symptoms of social anxiety.

METHODS

In total, 2 web-based randomized controlled trials (RCTs) comparing individuals with access to the treatment through the app to a waitlist control group were conducted. Participants were recruited on the web and reported Social Phobia Inventory (SPIN) total scores of ≥30. Primary outcomes were safety and efficacy over 6 weeks in 102 women aged 18 to 35 years (RCT 1) and symptom reduction (SPIN scores) after 8 weeks in 248 men and women aged 18 to 75 years (RCT 2).

RESULTS

In RCT 1, active and control arm adverse event frequency and severity were not distinguishable (intervention: 7/52, 13%; waitlist control: 8/50, 16%; χ21=0.007; P=.93). App acceptability was high, with a median completion rate of 90.91% (IQR 54.55%-100%). Secondary outcomes suggested greater symptom reduction in the active arm (mean SPIN score reduction -9.83, SD 12.80) than in the control arm (mean SPIN score reduction -4.13, SD 11.59; t90=-2.23; false discovery rate P=.04; Cohen d=0.47). RCT 2 replicated these findings. Adverse event frequency was comparable across the 2 groups (intervention: 20/124, 16.1%; waitlist control: 21/124, 16.8%; χ21<0.001; P>.99). Despite a longer treatment program, median completion remained high (84.85%, IQR 51.52%-96.97%). SPIN score reduction was greater in the active arm (mean -12.89, SD 13.87) than in the control arm (mean -7.48, SD 12.24; t227=-3.13; false discovery rate P=.008; Cohen d=0.42).

CONCLUSIONS

The web-only, modular social anxiety CBT program appeared safe, acceptable, and efficacious in 2 independent RCTs on online patient groups with self-reported symptoms of social anxiety.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05858294; https://clinicaltrials.gov/study/NCT05858294 (RCT 1) and ClinicalTrials.gov NCT05987969; https://clinicaltrials.gov/study/NCT05987969 (RCT 2).

Self-report measures of fear learning and extinction and their association with internet-based cognitive behavioural therapy outcome

Despite the widespread use of cognitive-behavioural therapy (CBT), only about half of patients respond favourably. Understanding whether relevant psychological processes are associated with treatment response could help identify patients at risk of non-response prior to treatment and improve their outcomes by enabling clinicians to tailor interventions accordingly. Fear conditioning tasks are a valuable tool for studying the learning processes associated with anxiety disorders and their treatment. This study examined associations between outcomes from a remote fear conditioning task and responses to internet-based CBT. Anxious adults (n = 112) completed a fear conditioning task before receiving internet-based CBT. Participants rated their expectancy of an aversive noise (unconditioned stimulus; US) in response to a reinforced conditional stimulus (CS+) and a nonreinforced conditional stimulus (CS-) during acquisition, followed by extinction where neither stimulus was reinforced. Anxiety symptoms were assessed before each CBT session. Linear regression models indicated no significant association between mean US-expectancy ratings for 'safe' stimuli (acquisition CS- and extinction CS+) and change in anxiety across treatment. These findings contribute to the mixed literature on fear conditioning's role in treatment outcomes, highlighting the need for further research to elucidate the complex interplay between fear conditioning processes and response to CBT in anxiety disorders.

Next-Generation Cognitive-Behavioral Therapy for Depression: Integrating Digital Tools, Teletherapy, and Personalization for Enhanced Mental Health Outcomes

Background and Objectives: This systematic review aims to present the latest developments in next-generation CBT interventions of digital support tools, teletherapies, and personalized treatment modules in enhancing accessibility, improving treatment adherence, and optimizing therapeutic outcomes for depression. Materials and Methods: This review analyzed 81 PRISMA-guided studies on the efficacy, feasibility, and applicability of NG-CBT approaches. Other important innovations include web-based interventions, AI-operated chatbots, and teletherapy platforms, each of which serves as a critical challenge in delivering mental health care. Key messages have emerged regarding technological readiness, patient engagement, and the changing role of therapists within the digital context of care. Results: Findings indicate that NG-CBT interventions improve treatment accessibility and engagement while maintaining clinical effectiveness. Personalized digital tools enhance adherence, and teletherapy platforms provide scalable and cost-effective alternatives to traditional therapy. Conclusions: Such developments promise great avenues for decreasing the global burden of depression and enhancing the quality of life through novel, accessible, and high-quality therapeutic approaches.

Prediction of individual patient outcomes to psychotherapy vs medication for major depression

Treatments for major depressive disorder (MDD) include antidepressant medications and evidence-based psychotherapies, which are approximately equally efficacious. Individual response to treatment, however, is variable, implying individual differences that could allow for prospective differential prediction of treatment response and personalized treatment recommendation. We used machine learning to develop predictor variables that combined demographic and clinical items from a randomized clinical trial. The variables predicted a meaningful proportion of variance in end-of-treatment depression severity for cognitive behavioral therapy (39.7%), escitalopram (32.1%), and duloxetine (67.7%), leading to a high accuracy in predicting remission (71%). Further, we used these variables to simulate treatment recommendation and found that patients who received their recommended treatment had significantly improved depression severity and remission likelihood. Finally, the prediction algorithms and treatment recommendation tool were externally validated in an independent sample. These results represent a highly promising, easily implemented, potential advance for personalized medicine in MDD treatment.

Moderators of short- and long-term outcomes in panic control treatment and panic-focused psychodynamic psychotherapy

OBJECTIVE

The objective was to test the hypothesis that externalizing and internalizing helpfulness beliefs and learning styles at baseline moderate panic severity and overall mental illness as short-term and long-term outcomes of two panic-focused psychotherapies, Panic Control Treatment (PCT) and Panic-Focused Psychodynamic Psychotherapy (PFPP).

METHOD

Participants were 108 adults with DSM-IV Panic Disorder with or without Agoraphobia (PD/A) who were randomized to treatment in a trial of PCT and PFPP. Piece-wise/segmented multilevel modeling was used to test three-way interactions (Treatments × Moderator × Time), with participants and therapists as random factors. Outcome variables were clinician-rated panic severity and self-rated mental illness post-treatment and during follow-up.

RESULTS

Patients' externalizing (but not internalizing) helpfulness beliefs moderated mental illness outcomes during follow-up (but not during treatment); low levels of Externalization were facilitative for PFPP but not PCT. Internalizing and externalizing helpfulness beliefs and learning style did not moderate clinician-rated panic severity, whether short- or long-term.

CONCLUSIONS

These results suggest that helpfulness beliefs and learning style have limited use in assignment to either PCT or PFPP for PD/A. Although further research is needed, low levels of helpfulness beliefs about externalizing coping may play a role in mental illness outcomes for PFPP.

Advancing the personalized advantage index (PAI): a systematic review and application in two large multi-site samples in anxiety disorders

BACKGROUND

The Personalized Advantage Index (PAI) shows promise as a method for identifying the most effective treatment for individual patients. Previous studies have demonstrated its utility in retrospective evaluations across various settings. In this study, we explored the effect of different methodological choices in predictive modelling underlying the PAI.

METHODS

Our approach involved a two-step procedure. First, we conducted a review of prior studies utilizing the PAI, evaluating each study using the Prediction model study Risk Of Bias Assessment Tool (PROBAST). We specifically assessed whether the studies adhered to two standards of predictive modeling: refraining from using leave-one-out cross-validation (LOO CV) and preventing data leakage. Second, we examined the impact of deviating from these methodological standards in real data. We employed both a traditional approach violating these standards and an advanced approach implementing them in two large-scale datasets, PANIC-net (n = 261) and Protect-AD (n = 614).

RESULTS

The PROBAST-rating revealed a substantial risk of bias across studies, primarily due to inappropriate methodological choices. Most studies did not adhere to the examined prediction modeling standards, employing LOO CV and allowing data leakage. The comparison between the traditional and advanced approach revealed that ignoring these standards could systematically overestimate the utility of the PAI.

CONCLUSION

Our study cautions that violating standards in predictive modeling may strongly influence the evaluation of the PAI's utility, possibly leading to false positive results. To support an unbiased evaluation, crucial for potential clinical application, we provide a low-bias, openly accessible, and meticulously annotated script implementing the PAI.

The next generation of developmental psychopathology research: Including broader perspectives and becoming more precise

The current Special Issue marks a major milestone in the history of developmental psychopathology; as the final issue edited by Cicchetti, we have an opportunity to reflect on the remarkable progress of the discipline across the last four decades, as well as challenges and future directions for the field. With contemporary issues in mind, including rising rates of psychopathology, health disparities, and international conflict, as well as rapid growth and accessibility of digital and mobile technologies, the discipline of developmental psychopathology is poised to advance multidisciplinary, developmentally- and contextually- informed research, and to make substantial progress in supporting the healthy development of individuals around the world. We highlight key future directions and challenges for the next generation of developmental psychopathology research including further investigation of culture at multiple levels of analysis, incorporation of macro-level influences into developmental psychopathology research, methods advances to address heterogeneity in translational research, precision mental health, and the extension of developmental psychopathology research across the lifespan.

Using the 'Leapfrog' Design as a Simple Form of Adaptive Platform Trial to Develop, Test, and Implement Treatment Personalization Methods in Routine Practice

The route for the development, evaluation and dissemination of personalized psychological therapies is complex and challenging. In particular, the large sample sizes needed to provide adequately powered trials of newly-developed personalization approaches means that the traditional treatment development route is extremely inefficient. This paper outlines the promise of adaptive platform trials (APT) embedded within routine practice as a method to streamline development and testing of personalized psychological therapies, and close the gap to implementation in real-world settings. It focuses in particular on a recently-developed simplified APT design, the 'leapfrog' trial, illustrating via simulation how such a trial may proceed and the advantages it can bring, for example in terms of reduced sample sizes. Finally it discusses models of how such trials could be implemented in routine practice, including potential challenges and caveats, alongside a longer-term perspective on the development of personalized psychological treatments.

Leveraging Single-Case Experimental Designs to Promote Personalized Psychological Treatment: Step-by-Step Implementation Protocol with Stakeholder Involvement of an Outpatient Clinic for Personalized Psychotherapy

Our objective is to implement a single-case experimental design (SCED) infrastructure in combination with experience-sampling methods (ESM) into the standard diagnostic procedure of a German outpatient research and training clinic. Building on the idea of routine outcome monitoring, the SCED infrastructure introduces intensive longitudinal data collection, individual effectiveness measures, and the opportunity for systematic manipulation to push personalization efforts further. It aims to empower psychotherapists and patients to evaluate their own treatment (idiographic perspective) and to enable researchers to analyze open questions of personalized psychotherapy (nomothetic perspective). Organized around the principles of agile research, we plan to develop, implement, and evaluate the SCED infrastructure in six successive studies with continuous stakeholder involvement: In the project development phase, the business model for the SCED infrastructure is developed that describes its vision in consideration of the context (Study 1). Also, the infrastructure's prototype is specified, encompassing the SCED procedure, ESM protocol, and ESM survey (Study 2 and 3). During the optimization phase, feasibility and acceptability are tested and the infrastructure is adapted accordingly (Study 4). The evaluation phase includes a pilot implementation study to assess implementation outcomes (Study 5), followed by actual implementation using a within-institution A-B design (Study 6). The sustainability phase involves continuous monitoring and improvement. We discuss to what extent the generated data could be used to address current questions of personalized psychotherapy research. Anticipated barriers and limitations during the implementation processes are outlined.

Data-driven personalized medicine approaches to cognitive-behavioral therapy allocation in a large sample: A reanalysis of the ENRICHED study

BACKGROUND

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.

METHODS

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).

RESULTS

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

Limitations are a poorly defined CAU condition, a low-severity sample, specific exclusion criteria and unavailability of certain baseline variables.

CONCLUSIONS

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.

Commentary: Holy grails, personalized medicine, and the public health burden of psychopathology - a reflection on Ahuvia et al. (2023)

Clinical psychology and psychiatry have many 'holy grails' or research findings that are widely sought after but remain elusive. The use of machine learning (ML) models for treatment selection is one of these holy grails. Ahuvia et al. (Journal of Child Psychology and Psychiatry, 2023) recently analyzed a large trial (n = 996) of two distinct single-session interventions (SSIs) for internalizing distress and found little evidence that an ML model could predict differential treatment response. I discuss potential avenues for advancing SSI research. One avenue is the dissemination and implementation of SSIs, including how they interact with other treatments in routine care. Quantifying and critically questioning the promises of holy grails like ML models is sorely needed. Using simulation modeling to evaluate the relative merits of using ML models for treatment selection or using SSIs versus other treatment strategies may be another path forward.

A 12-Month Follow-Up of PROCARE+, a Transdiagnostic, Selective, Preventive Intervention for Adolescents At-Risk for Emotional Disorders

Few studies have reported long-term follow-up data on selective preventive interventions for adolescents. No follow-up selective preventive transdiagnostic studies for adolescents at-risk for emotional disorders, such as anxiety and depression, have been reported. To fill this gap, this study aims to provide the first follow-up assessment of a randomized controlled trial (RCT) studying selective transdiagnostic prevention in at-risk adolescents. A 12-month follow-up assessment was conducted with subjects who originally received either PROCARE (Preventive transdiagnostic intervention for Adolescents at Risk for Emotional disorders), PROCARE+, which includes the PROCARE protocol along with personalized add-on modules or an active control condition (ACC) based on emotional psychoeducation, and their respective booster session for each experimental condition. 80 subjects (47.5% girls) aged between 12 and 18 years (M = 14.62; SD 1.43) who completed these treatment conditions were available for the 12-month follow-up. The results demonstrate the superior long-term efficacy of the PROCARE+ intervention in mitigating emotional symptoms and obsessive-compulsive symptomatology compared to the PROCARE and ACC conditions, with effect sizes notably exceeding those commonly observed in preventive programs. While the three treatments demonstrated beneficial impacts, the pronounced results associated with PROCARE+ at the 12-month follow-up emphasized the importance of personalized treatment modules and the sustained benefits of booster sessions in the realm of preventive psychological interventions. The findings also highlight the potential role of add-on modules in enhancing the effects of the PROCARE+ condition.

Evaluating a treatment selection approach for online single-session interventions for adolescent depression

BACKGROUND

The question 'what works for whom' is essential to mental health research, as matching individuals to the treatment best suited to their needs has the potential to maximize the effectiveness of existing approaches. Digitally administered single-session interventions (SSIs) are effective means of reducing depressive symptoms in adolescence, with potential for rapid, large-scale implementation. However, little is known about which SSIs work best for different adolescents.

OBJECTIVE

We created and tested a treatment selection algorithm for use with two SSIs targeting depression in high-symptom adolescents from across the United States.

METHODS

Using data from a large-scale RCT comparing two evidence-based SSIs (N = 996; ClinicalTrials.gov: NCT04634903), we utilized a Personalized Advantage Index approach to create and evaluate a treatment-matching algorithm for these interventions. The two interventions were Project Personality (PP; N = 482), an intervention teaching that traits and symptoms are malleable (a 'growth mindset'), and the Action Brings Change Project (ABC; N = 514), a behavioral activation intervention.

RESULTS

Results indicated no significant difference in 3-month depression outcomes between participants assigned to their matched intervention and those assigned to their nonmatched intervention. The relationship between predicted response to intervention (RTI) and observed RTI was weak for both interventions (r = .39 for PP, r = .24 for ABC). Moreover, the correlation between a participants' predicted RTI for PP and their predicted RTI for ABC was very high (r = .79).

CONCLUSIONS

The utility of treatment selection approaches for SSIs targeting adolescent depression appears limited. Results suggest that both (a) predicting RTI for SSIs is relatively challenging, and (b) the factors that predict RTI for SSIs are similar regardless of the content of the intervention. Given their overall effectiveness and their low-intensity, low-cost nature, increasing youths' access to both digital SSIs may carry more public health utility than additional treatment-matching efforts.

Identifying active ingredients in cognitive-behavioral therapies: What if we didn't?

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.

Efficacy of an Unguided, Digital Single-Session Intervention for Internalizing Symptoms in Web-Based Workers: Randomized Controlled Trial

BACKGROUND

The Common Elements Toolbox (COMET) is an unguided digital single-session intervention (SSI) based on principles of cognitive behavioral therapy and positive psychology. Although unguided digital SSIs have shown promise in the treatment of youth psychopathology, the data are more mixed regarding their efficacy in adults.

OBJECTIVE

This study aimed to investigate the efficacy of COMET-SSI versus a waiting list control in depression and other transdiagnostic mental health outcomes for Prolific participants with a history of psychopathology.

METHODS

We conducted an investigator-blinded, preregistered randomized controlled trial comparing COMET-SSI (n=409) with an 8-week waiting list control (n=419). Participants were recruited from the web-based workspace Prolific and assessed for depression, anxiety, work and social functioning, psychological well-being, and emotion regulation at baseline and at 2, 4, and 8 weeks after the intervention. The main outcomes were short-term (2 weeks) and long-term (8 weeks) changes in depression and anxiety. The secondary outcomes were the 8-week changes in work and social functioning, well-being, and emotion regulation. Analyses were conducted according to the intent-to-treat principle with imputation, without imputation, and using a per-protocol sample. In addition, we conducted sensitivity analyses to identify inattentive responders.

RESULTS

The sample comprised 61.9% (513/828) of women, with a mean age of 35.75 (SD 11.93) years. Most participants (732/828, 88.3%) met the criteria for screening for depression or anxiety using at least one validated screening scale. A review of the text data suggested that adherence to the COMET-SSI was near perfect, there were very few inattentive respondents, and satisfaction with the intervention was high. However, despite being powered to detect small effects, there were negligible differences between the conditions in the various outcomes at the various time points, even when focusing on subsets of individuals with more severe symptoms.

CONCLUSIONS

Our results do not support the use of the COMET-SSI in adult Prolific participants. Future work should explore alternate ways of intervening with paid web-based participants, including matching individuals to SSIs they may be most responsive to.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05379881, https://clinicaltrials.gov/ct2/show/NCT05379881.

Why is it so hard to identify (consistent) predictors of treatment outcome in psychotherapy? - clinical and research perspectives

BACKGROUND

Anxiety and depression are two of the most debilitating psychological disorders worldwide today. Fortunately, effective treatments exist. However, a large proportion of patients do not recover from treatment, and many still have symptoms after completing treatment. Numerous studies have tried to identify predictors of treatment outcome. So far, researchers have found few or no consistent predictors applicable to allocate patients to relevant treatment.

METHODS

We set out to investigate why it is so hard to identify (consistent) predictors of treatment outcome for psychotherapy in anxiety and depression by reviewing relevant literature.

RESULTS

Four challenges stand out; a) the complexity of human lives, b) sample size and statistical power, c) the complexity of therapist-patient relationships, and d) the lack of consistency in study designs. Together these challenges imply there are a countless number of possible predictors. We also consider ethical implications of predictor research in psychotherapy. Finally, we consider possible solutions, including the use of machine learning, larger samples and more realistic complex predictor models.

CONCLUSIONS

Our paper sheds light on why it is so hard to identify consistent predictors of treatment outcome in psychotherapy and suggest ethical implications as well as possible solutions to this problem.

Advanced methods and implementations for the meta-analyses of animal models: Current practices and future recommendations

Meta-analytic techniques have been widely used to synthesize data from animal models of human diseases and conditions, but these analyses often face two statistical challenges due to complex nature of animal data (e.g., multiple effect sizes and multiple species): statistical dependency and confounding heterogeneity. These challenges can lead to unreliable and less informative evidence, which hinders the translation of findings from animal to human studies. We present a literature survey of meta-analysis using animal models (animal meta-analysis), showing that these issues are not adequately addressed in current practice. To address these challenges, we propose a meta-analytic framework based on multilevel (linear mixed-effects) models. Through conceptualization, formulations, and worked examples, we illustrate how this framework can appropriately address these issues while allowing for testing new questions. Additionally, we introduce other advanced techniques such as multivariate models, robust variance estimation, and meta-analysis of emergent effect sizes, which can deliver robust inferences and novel biological insights. We also provide a tutorial with annotated R code to demonstrate the implementation of these techniques.

Acceptability and Outcomes of Transdiagnostic Guided Self-help Bibliotherapy for Internalizing Disorder Symptoms in Adults: A Fully Remote Nationwide Open Trial

Introduction

Doing What Matters in Times of Stress (DWM) is a five-module transdiagnostic guided self-help (GSH) intervention developed by the World Health Organization, originally in a group-based format. In a sample of individuals recruited from across the United States, we conducted an open trial to study the feasibility and acceptability of an adaptation of DWM in which guidance was provided individually and remotely via phone and videoconferencing.

Methods

We assessed internalizing symptoms, psychological well-being, work and social functioning, usability of the intervention, and emotion regulation over the course of 6 weeks.

Results

A total of 263 individuals completed our screening. Of those, 75.29% (n = 198) qualified for the intervention. We reached most participants who qualified (71.21%, n = 141) via phone to schedule a GSH session. Most of those scheduled attended a study session (84.4%, n = 119), and most of those who attended a session completed more than half the treatment (84.03%, n = 100). Retention rates were comparable to meta-analytic estimates of dropout rates in GSH. Participants showed improvement on internalizing symptoms, psychological well-being, work and social functioning, usability of the intervention, and emotion regulation.

Conclusion

DWM is a freely available, seemingly efficacious transdiagnostic intervention for internalizing disorder symptoms.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10608-022-10338-5.

Is it worth it to personalize the treatment of PTSD? - A variance-ratio meta-analysis and estimation of treatment effect heterogeneity in RCTs of PTSD

Several evidence-based treatments for posttraumatic stress disorder (PTSD) are recommended by international guidelines (e.g., APA, NICE). While their average effects are in general high, non-response rates indicate differential treatment effects. Here, we used a large database of RCTs on psychotherapy for PTSD to determine a reliable estimate of this heterogeneity in treatment effects (HTE) by applying Bayesian variance ratio meta-analysis. In total, 66 studies with a total of 8803 patients were included in our study. HTE was found for all psychological treatments, with varying degrees of certainty, only slight differences between psychological treatments, and active control groups yielding a smaller variance ratio compared to waiting list control groups. Across all psychological treatment and control group types, the estimate for the intercept was 0.12, indicating a 12% higher variance of posttreatment values in the intervention groups after controlling for differences in treatment outcomes. This study is the first to determine the maximum increase in treatment effects of psychological treatments for PTSD by personalization. The results indicate that there is comparatively high heterogeneity in treatment effects across all psychological treatment and control groups, which in turn allow personalizing psychological treatments by using treatment selection approaches.

Cognitive Processes during Recovery: Moving toward Personalized Spine Surgery Outcomes

This paper focuses on a novel application of personalized medicine: the ways one thinks about health (i.e., appraisal processes) as relevant predictors of spine-surgery response. This prospective longitudinal cohort study (n = 235) investigated how appraisal processes relate to outcomes of spinal decompression and/or fusion surgery, from pre-surgery through one-year post-surgery. Patient-reported outcomes assessed spine-specific disability (Oswestry Disability Index (ODI)), mental health functioning (Rand-36 Mental Component Score (MCS)), and cognitive appraisal processes (how people recall past experiences and to whom they compare themselves). Analysis of Variance examined the appraisal-outcomes association in separate models at pre-surgery, 3 months, and 12 months. We found that appraisal processes explained less variance at pre-surgery than later and were differentially relevant to health outcomes at different times in the spine-surgery recovery trajectory. For the ODI, recall of the seriousness of their condition was most prominent early in recovery, and comparing themselves to positive standards was most prominent later. For the MCS, not focusing on the negative aspects of their condition and/or on how others see them was associated with steady improvement and higher scores at 12 months. Appraisal processes are relevant to both spine-specific disability and mental-health functioning. Such processes are modifiable objects of attention for personalizing spine-surgery outcomes.

Praxisorientierte Forschung in der Psychotherapie

Zusammenfassung. In den letzten Jahrzehnten hat sich durch randomisiert-kontrollierte Studien (RCTs) eine breite Evidenzbasis von Psychotherapie mit mittleren bis großen Effekten für verschiedene psychische Störungen gebildet. Neben der Bestimmung dieser Wirksamkeit („Efficacy“) ebneten Studien zur Wirksamkeit unter alltäglichen Routinebedingungen („Effectiveness“) historisch den Weg zur Entwicklung eines praxisorientierten Forschungsparadigmas. Im Beitrag wird argumentiert, dass im Rahmen dieses Paradigmas praxisbasierte Studien eine wertvolle Ergänzung zu RCTs darstellen, da sie existierende Probleme in der Psychotherapieforschung adressieren können. In der gegenwärtigen praxisorientierten Forschung liefern dabei neue Ansätze aus der personalisierten Medizin und Methoden aus der ‚Computational Psychiatry‘ wichtige Anhaltspunkte zur Optimierung von Effekten in der Psychotherapie. Im Kontext der Personalisierung werden bspw. klinische multivariable Prädiktionsmodelle entwickelt, welche durch Rückmeldeschleifen an Praktiker_innen kurzfristig ein evidenzbasiertes Outcome-Monitoring ermöglicht und langfristig das Praxis-Forschungsnetzwerk in Deutschland stärkt. Am Ende des Beitrags werden zukünftige Richtungen für die praxisorientierte Forschung im Sinne des ‘Precision Mental Health Care’ -Paradigmas abgeleitet und diskutiert.

Evolutionary theory and the treatment of depression: It is all about the squids and the sea bass

According to the analytical rumination hypothesis, depression is an evolved adaptation (like pain or anxiety) that served in our ancestral past to keep people focused on complex interpersonal problems until they could arrive at a resolution (spontaneous remission). If this is true, then those clinical treatments that most facilitate the functions that depression evolved to serve are likely to be more advantageous in the long run than others that simply relieve distress. For example, antidepressant medications may be efficacious in the treatment of depression but only work for so long as they are taken. They may also have an iatrogenic effect that prolongs the duration of the underlying episode. Cognitive and behavioral interventions are as efficacious as medications in terms of reducing acute distress and also appear to have an enduring effect that protects against the return of subsequent symptoms. However, the bulk of the evidence for this effect comes from comparisons to prior medication treatment and it remains unclear whether these psychosocial interventions are truly preventative, or antidepressant medications iatrogenic. A study is described that could resolve this issue and test evolutionary theory with respect to the purported role of rumination in bringing about spontaneous remission.

Cognitive Behavior Therapy at the Crossroads

The early development of cognitive behavior therapy (CBT) can be characterized by the coming together of behavioral and cognitive traditions. However, the past decades have arguably seen more divergences than convergences within the field. The 9th World Congress of Behavioural and Cognitive Therapies was held in Berlin in July 2019 with the congress theme "CBT at the Crossroads." This title reflected in part the coming together of people from all over the world, but also the fact that recent developments raise important questions about the future of CBT, including whether we can in fact treat it as a unified field. In this paper, we briefly trace the history of CBT, then introduce a special issue featuring a series of articles exploring different aspects of the past, present, and future of CBT. Finally, we reflect on the possible routes ahead.