Investigation of Active Ingredients Within Internet-Delivered Cognitive Behavioral Therapy for Depression: A Randomized Optimization Trial

Cognitive behavioral therapy skills via a smartphone app for subthreshold depression among adults in the community: the RESiLIENT randomized controlled trial

Subthreshold depression, defined as a depressive status falling short of the diagnostic threshold for major depression, is common, disabling and constitutes a risk factor for future depressive episodes. Cognitive behavioral therapies (CBT) have been shown to be effective but are usually provided as packages of various skills. Little research has been done to investigate whether all their components are beneficial and contributory to mental health promotion. We addressed this issue by developing a smartphone CBT app that implements five representative CBT skills (behavioral activation, cognitive restructuring, problem solving, assertion training and behavior therapy for insomnia), and conducting a master randomized study that included four 2 × 2 factorial trials to enable precise estimation of skill-specific efficacies. Between September 2022 and February 2024, we recruited 3,936 adult participants with subthreshold depression. Among those randomized, the follow-up rate was 97% at week 6 and adherence to the app was 84%. The study showed that all included CBT skills and their combinations differentially beat all three control conditions of delayed treatment, health information or self-check, with effect sizes ranging between -0.67 (95% confidence interval: -0.81 to -0.53) and -0.16 (-0.30 to -0.02) for changes in depressive symptom severity from baseline to week 6, as measured with the Patient Health Questionnaire-9 scores. Knowledge of the active ingredients of CBT can better inform the design of more effective and scalable psychotherapies in the future. (UMIN Clinical Trials Registry UMIN000047124 ).

'Harder to reach' versus reaching harder: Exploring preferred dissemination pathways to a digital binge-eating intervention for adults with or at risk of food insecurity

OBJECTIVE

Individuals from minoritized and under-resourced subpopulations, such as individuals with food insecurity, are sometimes considered "harder to reach." Instead, tailored dissemination pathways may be required to reach them. We sought to learn how best to reach individuals with food insecurity seeking digital intervention for binge eating.

METHOD

As part of continued design work in two ongoing trials testing a digital intervention for binge eating, we conducted a secondary exploratory analysis of individuals' preferred dissemination channels, modes, and materials. We assessed individuals' preferences at baseline via a pre-intervention questionnaire. Adults (n = 90) with binge eating and food insecurity or at risk of food insecurity completed the questionnaire. We also compared their preferences to adults (n = 106) with binge eating and without food insecurity, and highlighted differences of p < 0.10.

RESULTS

Individuals with or at risk of food insecurity preferred dissemination via community organizations and events, healthcare centers, fitness centers, and online sources, more than trusted sources (e.g., clinicians). They preferred websites over other dissemination modes (e.g., videos). They were most interested in useful promotional materials (e.g., grocery bags). Compared to those without food insecurity, individuals with or at risk of food insecurity were more interested in dissemination via community organizations and events, and less interested in dissemination through doctors.

DISCUSSION

Findings indicate tailored dissemination strategies could improve reach to individuals with or at risk of food insecurity. This study is a first step toward better engaging this subpopulation. Future work should disseminate through the preferred channels, assess their reach, and iterate as needed.

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.

Active Components in Internet-Based Cognitive-Behavioral Therapy for Social Anxiety Disorder: A Randomized Full Factorial Trial

INTRODUCTION

Many studies have demonstrated that social anxiety disorder (SAD) can be effectively treated with psychotherapy, particularly cognitive-behavioral therapy (CBT), including internet-based CBT (ICBT). Despite evidence-based treatments, many individuals do not sufficiently benefit from them. Identifying the active components could help improve the effectiveness of SAD treatment. This study tested the effects of four treatment components (psychoeducation, cognitive restructuring, attention training, and exposure) within ICBT for SAD to investigate its active components.

METHODS

This randomized full factorial trial consisted of four factors (i.e., treatment components) and 16 conditions. A total of 464 adults with a diagnosed SAD were recruited from the community. The primary outcome was SAD symptoms at 8 weeks (post-assessment). Secondary outcomes included SAD diagnosis, SAD symptoms at follow-up (4 months after post), depression and anxiety symptoms, quality of life, client satisfaction, and adverse effects.

RESULTS

Conditions including psychoeducation and exposure were significantly more effective in reducing SAD symptoms at post compared to conditions without these components. Conditions including cognitive restructuring and attention training did not show superiority over conditions without them at post. However, all treatment conditions significantly reduced symptoms compared to the condition without a treatment component. At follow-up, the superiority of psychoeducation and exposure was not significant anymore due to the version without the respective components catching up.

CONCLUSION

The findings suggest that while all treatment components of ICBT for SAD are beneficial compared to no treatment, psychoeducation and exposure include specific active components that significantly improve treatment outcomes more quickly in ICBT for SAD.

INTRODUCTION

Many studies have demonstrated that social anxiety disorder (SAD) can be effectively treated with psychotherapy, particularly cognitive-behavioral therapy (CBT), including internet-based CBT (ICBT). Despite evidence-based treatments, many individuals do not sufficiently benefit from them. Identifying the active components could help improve the effectiveness of SAD treatment. This study tested the effects of four treatment components (psychoeducation, cognitive restructuring, attention training, and exposure) within ICBT for SAD to investigate its active components.

METHODS

This randomized full factorial trial consisted of four factors (i.e., treatment components) and 16 conditions. A total of 464 adults with a diagnosed SAD were recruited from the community. The primary outcome was SAD symptoms at 8 weeks (post-assessment). Secondary outcomes included SAD diagnosis, SAD symptoms at follow-up (4 months after post), depression and anxiety symptoms, quality of life, client satisfaction, and adverse effects.

RESULTS

Conditions including psychoeducation and exposure were significantly more effective in reducing SAD symptoms at post compared to conditions without these components. Conditions including cognitive restructuring and attention training did not show superiority over conditions without them at post. However, all treatment conditions significantly reduced symptoms compared to the condition without a treatment component. At follow-up, the superiority of psychoeducation and exposure was not significant anymore due to the version without the respective components catching up.

CONCLUSION

The findings suggest that while all treatment components of ICBT for SAD are beneficial compared to no treatment, psychoeducation and exposure include specific active components that significantly improve treatment outcomes more quickly in ICBT for SAD.

Mechanisms of change in digital interventions for depression: A systematic review and meta-analysis of six mediator domains

BACKGROUND

While the efficacy of digital interventions for the treatment of depression is well established, comprehensive knowledge on how therapeutic changes come about is still limited. This systematic review aimed to provide an overview of research on change mechanisms in digital interventions for depression and meta-analytically evaluate indirect effects of potential mediators.

METHODS

The databases CENTRAL, Embase, MEDLINE, and PsycINFO were systematically searched for randomized controlled trials investigating mediators of digital interventions for adults with depression. Two reviewers independently screened studies for inclusion, assessed study quality and categorized potential mediators. Indirect effects were synthesized with a two-stage structural equation modeling approach (TSSEM).

RESULTS

Overall, 25 trials (8110 participants) investigating 84 potential mediators were identified, of which attentional (8 %), self-related (6 %), biophysiological (6 %), affective (5 %), socio-cultural (2 %) and motivational (1 %) variables were the scope of this study. TSSEM revealed significant mediation effects for combined self-related variables (ab = -0.098; 95 %-CI: [-0.150, -0.051]), combined biophysiological variables (ab = -0.073; 95 %-CI: [-0.119, -0.025]) and mindfulness (ab = -0.042; 95 %-CI: [-0.080, -0.015]). Meta-analytical evaluations of the other three domains were not feasible.

LIMITATIONS

Methodological shortcomings of the included studies, the considerable heterogeneity and the small number of investigated variables within domains limit the generalizability of the results.

CONCLUSION

The findings further the understanding of potential change mechanisms in digital interventions for depression and highlight recommendations for future process research, such as the consideration of temporal precedence and experimental manipulation of potential mediators, as well as the application of network approaches.

Identifying Active Ingredients that Cause Change in Digital Parent Training Programs for Child Behavior Problems: A Qualitative Exploration

Digital parent training programs (DPTs) aimed at treating child behavior problems have shown efficacy in a number of trials, but less is known about the active ingredients parents find helpful while using DPTs. We analyzed data from users of self-guided DPTs within a randomized controlled trial setting: a standard program (DPT-STD) and an enhanced program (DPT-TP). Thematic analysis of interviews (n = 16) reveals that users of both programs endorsed the "content", "content presentation", "accessibility", and "therapeutic context" as beneficial. However, only DPT-TP users identified the "therapeutic persuasiveness" as helpful, attributing this to features embedded exclusively in the enhanced program, including call-to-action reminders and assessment-based feedback. Findings were reinforced by the analysis of responses to open-ended questions from a larger sample of users (n = 31 DPT-STD users and n = 34 DPT-TP users). These findings underscore the importance of utilizing features that help parents make positive changes in their home.

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.

[Digital Beacons of Hope? The Challenges and Potentials of Digital Health Applications for Children and Adolescents with Mental Disorders in Germany]

Digital Beacons of Hope? The Challenges and Potentials of Digital Health Applications for Children and Adolescents with Mental Disorders in Germany Abstract: With the Digital Healthcare Act, Germany has taken a decisive step toward promoting high-quality, evidence-based digital health applications (DiHAs). Presently, there is a significant gap in the provision of mental health services throughout Germany, particularly regarding children and adolescents and especially in the aftermath of the COVID-19 pandemic. DiHAs as low-threshold, location- and time-independent additional mental health services - may offer a way to address this situation. Particularly in the emerging generation of digital natives, there is a high demand for digital mental health services. However, despite the rapidly growing supply of DiHAs for adults, there is a lack of approved DiHAs for children and adolescents with mental disorders. Rather, the demand for care is left to the unregulated market of diverse internet- and mobile-based interventions; early studies have questioned the evidence base, safety, and quality. This discrepancy arises from various specific challenges and risks that reduce incentives to develop DiHAs for this particularly vulnerable target group, including (1) limited evidence, (2) high complexity in study execution, (3) high complexity in the development of applications, (4) poorly researched specific risks, and (5) high regulatory requirements. This article discusses these challenges and risks and outlines the perspectives for a high-quality, safe, and evidence-based digital mental healthcare for children and adolescents.

Intervention Optimization: A Paradigm Shift and Its Potential Implications for Clinical Psychology

To build a coherent knowledge base about what psychological intervention strategies work, develop interventions that have positive societal impact, and maintain and increase this impact over time, it is necessary to replace the classical treatment package research paradigm. The multiphase optimization strategy (MOST) is an alternative paradigm that integrates ideas from behavioral science, engineering, implementation science, economics, and decision science. MOST enables optimization of interventions to strategically balance effectiveness, affordability, scalability, and efficiency. In this review we provide an overview of MOST, discuss several experimental designs that can be used in intervention optimization, consider how the investigator can use experimental results to select components for inclusion in the optimized intervention, discuss the application of MOST in implementation science, and list future issues in this rapidly evolving field. We highlight the feasibility of adopting this new research paradigm as well as its potential to hasten the progress of psychological intervention science.

Heterogeneity of Treatment Effects in Internet- and Mobile-Based Interventions for Depression: A Systematic Review and Meta-Analysis

Importance

While the effects of internet- and mobile-based interventions (IMIs) for depression have been extensively studied, no systematic evidence is available regarding the heterogeneity of treatment effects (HTEs), indicating to what extent patient-by-treatment interactions exist and personalized treatment models might be necessary.

Objective

To investigate the HTEs in IMIs for depression as well as their efficacy and effectiveness.

Data Sources

A systematic search in Embase, MEDLINE, Central, and PsycINFO for randomized clinical trials and supplementary reference searches was conducted on October 13, 2019, and updated March 25, 2022. The search string included various terms related to digital psychotherapy, depression, and randomized clinical trials.

Study Selection

Titles, abstracts, and full texts were reviewed by 2 independent researchers. Studies of all populations with at least 1 intervention group receiving an IMI for depression and at least 1 control group were eligible, if they assessed depression severity as a primary outcome and followed a randomized clinical trial (RCT) design.

Data Extraction and Synthesis

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines. Risk of bias was evaluated using the Cochrane Risk of Bias Tool. HTE was investigated using logarithmic variance ratios (lnVR) and effect sizes using Hedges g. Three-level bayesian meta-regressions were conducted.

Main Outcomes and Measures

Heterogeneity of treatment effects was the primary outcome of this study; magnitudes of treatment effect sizes were the secondary outcome. Depression severity was measured by different self-report and clinician-rated scales in the included RCTs.

Results

The systematic review of 102 trials included 19 758 participants (mean [SD] age, 39.9 [10.58] years) with moderate depression severity (mean [SD] in Patient Health Questionnaire-9 score, 12.81 [2.93]). No evidence for HTE in IMIs was found (lnVR = -0.02; 95% credible interval [CrI], -0.07 to 0.03). However, HTE was higher in more severe depression levels (β̂ = 0.04; 95% CrI, 0.01 to 0.07). The effect size of IMI was medium (g = -0.56; 95% CrI, -0.46 to -0.66). An interaction effect between guidance and baseline severity was found (β̂ = -0.24, 95% CrI, -0.03 to -0.46).

Conclusions and Relevance

In this systematic review and meta-analysis of RCTs, no evidence for increased patient-by-treatment interaction in IMIs among patients with subthreshold to mild depression was found. Guidance did not increase effect sizes in this subgroup. However, the association of baseline severity with HTE and its interaction with guidance indicates a more sensitive, guided, digital precision approach would benefit individuals with more severe symptoms. Future research in this population is needed to explore personalization strategies and fully exploit the potential of IMI.

Distributive randomization: a pragmatic fractional factorial design to screen or evaluate multiple simultaneous interventions in a clinical trial

BACKGROUND

In some medical indications, numerous interventions have a weak presumption of efficacy, but a good track record or presumption of safety. This makes it feasible to evaluate them simultaneously. This study evaluates a pragmatic fractional factorial trial design that randomly allocates a pre-specified number of interventions to each participant, and statistically tests main intervention effects. We compare it to factorial trials, parallel-arm trials and multiple head-to-head trials, and derive some good practices for its design and analysis.

METHODS

We simulated various scenarios involving 4 to 20 candidate interventions among which 2 to 8 could be simultaneously allocated. A binary outcome was assumed. One or two interventions were assumed effective, with various interactions (positive, negative, none). Efficient combinatorics algorithms were created. Sample sizes and power were obtained by simulations in which the statistical test was either difference of proportions or multivariate logistic regression Wald test with or without interaction terms for adjustment, with Bonferroni multiplicity-adjusted alpha risk for both. Native R code is provided without need for compiling or packages.

RESULTS

Distributive trials reduce sample sizes 2- to sevenfold compared to parallel arm trials, and increase them 1- to twofold compared to factorial trials, mostly when fewer allocations than for the factorial design are possible. An unexpectedly effective intervention causes small decreases in power (< 10%) if its effect is additive, but large decreases (possibly down to 0) if not, as for factorial designs. These large decreases are prevented by using interaction terms to adjust the analysis, but these additional estimands have a sample size cost and are better pre-specified. The issue can also be managed by adding a true control arm without any intervention.

CONCLUSION

Distributive randomization is a viable design for mass parallel evaluation of interventions in constrained trial populations. It should be introduced first in clinical settings where many undercharacterized interventions are potentially available, such as disease prevention strategies, digital behavioral interventions, dietary supplements for chronic conditions, or emerging diseases. Pre-trial simulations are recommended, for which tools are provided.

Beyond mediators: A critical review and methodological path forward for studying mechanisms in alcohol use treatment research

Understanding how treatments for alcohol use disorder (AUD) facilitate behavior change has long been recognized as an important area of research for advancing clinical care. However, despite decades of research, the specific mechanisms of change for most AUD treatments remain largely unknown because most prior work in the field has focused only on statistical mediation. Statistical mediation is a necessary but not sufficient condition to establish evidence for a mechanism of change. Mediators are intermediate variables that account statistically for the relationship between independent and dependent variables, whereas mechanisms provide more detailed explanations of how an intervention leads to a desired outcome. Thus, mediators and mechanisms are not equivalent. To advance mechanisms of behavior change research, in this critical review we provide an overview of methodological shortfalls of existing AUD treatment mechanism research and introduce an etiologically informed precision medicine approach that facilitates the testing of mechanisms of behavior change rather than treatment mediators. We propose a framework for studying mechanisms in alcohol treatment research that promises to facilitate our understanding of behavior change and precision medicine (i.e., for whom a given mechanism of behavior change operates and under what conditions). The framework presented in this review has several overarching goals, one of which is to provide a methodological roadmap for testing AUD recovery mechanisms. We provide two examples of our framework, one pharmacological and one behavioral, to facilitate future efforts to implement this methodological approach to mechanism research. The framework proposed in this critical review facilitates the alignment of AUD treatment mechanism research with current theories of etiologic mechanisms, precision medicine efforts, and cross-disciplinary approaches to testing mechanisms. Although no framework can address all the challenges related to mechanisms research, our goal is to help facilitate a shift toward more rigorous and falsifiable behavior change research.

The latest developments with internet-based psychological treatments for depression

INTRODUCTION

Internet-based psychological treatments for depression have been around for more than 20 years. There has been a continuous line of research with new research questions being asked and studies conducted.

AREAS COVERED

In this paper, the author reviews studies with a focus on papers published from 2020 and onwards based on a Medline and Scopus search. Internet-based cognitive behavior therapy (ICBT) programs have been developed and tested for adolescents, older adults, immigrant groups and to handle a societal crisis (e.g. COVID-19). ICBT works in regular clinical settings and long-term effects can be obtained. Studies on different treatment orientations and approaches such as acceptance commitment therapy, unified protocol, and tailored treatments have been conducted. Effects on quality-of-life measures, knowledge acquisition and ecological momentary assessment as a research tool have been reported. Factorial design trials and individual patient data meta-analysis are increasingly used in association with internet intervention research. Finally, prediction studies and recent advances in artificial intelligence are mentioned.

EXPERT OPINION

Internet-delivered treatments are effective, in particular if therapist guidance is provided. More target groups have been covered but there are many remaining challenges including how new tools like artificial intelligence will be used when treating depression.