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Negative emotions and associated avoidance behaviors are core symptoms of anxiety. Current treatments aim to resolve dysfunctional coupling between them. However, precise interactions between emotions and avoidance in patients' everyday lives and changes from pre- to post-treatment remain unclear. We analyzed data from a randomized controlled trial where patients with anxiety disorders underwent 16 sessions of cognitive behavioral therapy (CBT). Fifty-six patients (68 % female, age: M = 33.31, SD = 12.45) completed ecological momentary assessments five times a day on 14 consecutive days before and after treatment, rating negative emotions and avoidance behaviors experienced within the past 30 min. We computed multilevel vector autoregressive models to investigate contemporaneous and time-lagged associations between anxiety, depression, anger, and avoidance behaviors within patients, separately at pre- and post-treatment. We examined pre-post changes in network density and avoidance centrality, and related these metrics to changes in symptom severity. Network density significantly decreased from pre- to post-treatment, indicating that after therapy, mutual interactions between negative emotions and avoidance were attenuated. Specifically, contemporaneous associations between anxiety and avoidance observed before CBT were no longer significant at post-treatment. Effects of negative emotions on avoidance assessed at a later time point (avoidance instrength) decreased, but not significantly. Reduction in avoidance instrength positively correlated with reduction in depressive symptom severity, meaning that as patients improved, they were less likely to avoid situations after experiencing negative emotions. Our results elucidate mechanisms of successful CBT observed in patients' daily lives and may help improve and personalize CBT to increase its effectiveness., Competing Interests: Declaration of Competing Interest TK is affiliated with the Centre for Digital Health Interventions, a joint initiative of the Institute for Implementation Science in Health Care, University of Zurich, the Department of Management, Technology, and Economics at ETH Zurich, and the Institute of Technology Management and School of Medicine at the University of St. Gallen. Centre for Digital Health Interventions is funded in part by CSS, a Swiss health insurer. TK is also a cofounder of Pathmate Technologies, a university spin-off company that creates and delivers digital clinical pathways. However, neither CSS nor Pathmate Technologies was involved in this research. All other authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Psychotherapies, such as cognitive behavioral therapy (CBT), currently have the strongest evidence of durable symptom changes for most psychological disorders, such as anxiety disorders. Nevertheless, only about half of individuals treated with CBT benefit from it. Predictive algorithms, including digital assessments and passive sensing features, could better identify patients who would benefit from CBT, and thus, improve treatment choices., Objective: This study aims to establish predictive features that forecast responses to transdiagnostic CBT in anxiety disorders and to investigate key mechanisms underlying treatment responses., Methods: This study is a 2-armed randomized controlled clinical trial. We include patients with anxiety disorders who are randomized to either a transdiagnostic CBT group or a waitlist (referred to as WAIT). We index key features to predict responses prior to starting treatment using subjective self-report questionnaires, experimental tasks, biological samples, ecological momentary assessments, activity tracking, and smartphone-based passive sensing to derive a multimodal feature set for predictive modeling. Additional assessments take place weekly at mid- and posttreatment and at 6- and 12-month follow-ups to index anxiety and depression symptom severity. We aim to include 150 patients, randomized to CBT versus WAIT at a 3:1 ratio. The data set will be subject to full feature and important features selected by minimal redundancy and maximal relevance feature selection and then fed into machine leaning models, including eXtreme gradient boosting, pattern recognition network, and k-nearest neighbors to forecast treatment response. The performance of the developed models will be evaluated. In addition to predictive modeling, we will test specific mechanistic hypotheses (eg, association between self-efficacy, daily symptoms obtained using ecological momentary assessments, and treatment response) to elucidate mechanisms underlying treatment response., Results: The trial is now completed. It was approved by the Cantonal Ethics Committee, Zurich. The results will be disseminated through publications in scientific peer-reviewed journals and conference presentations., Conclusions: The aim of this trial is to improve current CBT treatment by precise forecasting of treatment response and by understanding and potentially augmenting underpinning mechanisms and personalizing treatment., Trial Registration: ClinicalTrials.gov NCT03945617; https://clinicaltrials.gov/ct2/show/results/NCT03945617., International Registered Report Identifier (irrid): DERR1-10.2196/42547., (©Miriam Müller-Bardorff, Ava Schulz, Christina Paersch, Dominique Recher, Barbara Schlup, Erich Seifritz, Iris Tatjana Kolassa, Tobias Kowatsch, Aaron Fisher, Isaac Galatzer-Levy, Birgit Kleim. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 14.05.2024.)

Transdiagnostic cognitive behavioural psychotherapy (TD-CBT) may facilitate the treatment of emotional disorders. Here we investigate short- and long-term efficacy of TD-CBT for emotional disorders in individual, group and internet-based settings in randomized controlled trials (PROSPERO CRD42019141512). Two independent reviewers screened results from PubMed, MEDLINE, PsycINFO, Google Scholar, medRxiv and OSF Preprints published between January 2000 and June 2023, selected studies for inclusion, extracted data and evaluated risk of bias (Cochrane risk-of-bias tool 2.0). Absolute efficacy from pre- to posttreatment and relative efficacy between TD-CBT and control treatments were investigated with random-effects models. Of 56 identified studies, 53 (6,705 participants) were included in the meta-analysis. TD-CBT had larger effects on depression (g = 0.74, 95% CI = 0.57-0.92, P < 0.001) and anxiety (g = 0.77, 95% CI = 0.56-0.97, P < 0.001) than did controls. Across treatment formats, TD-CBT was superior to waitlist and treatment-as-usual. TD-CBT showed comparable effects to disorder-specific CBT and was superior to other active treatments for depression but not for anxiety. Different treatment formats showed comparable effects. TD-CBT was superior to controls at 3, 6 and 12 months but not at 24 months follow-up. Studies were heterogeneous in design and methodological quality. This review and meta-analysis strengthens the evidence for TD-CBT as an efficacious treatment for emotional disorders in different settings., (© 2023. The Author(s).)

Background: The Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) are widely used self-report questionnaires to assess symptoms of social anxiety. While SPS measures social performance anxiety, SIAS measures social interaction anxiety. They are mostly reported simultaneously, but there have not been consistent results of the joint factor structure and therefore no consistent recommendations on how to use and evaluate the questionnaires. This study aimed (1) to evaluate the underlying joint factor structure of the SPS and SIAS and (2) to test whether SPS and SIAS are reliable scales to assess two different aspects of social anxiety., Methods: The one-factor, two-factor, and bifactor models were tested in a clinical sample recruited from the community and diagnosed with a social anxiety disorder. Exploratory and confirmatory factor analyses were conducted, bifactor-specific indices were calculated, and the content of the less fitting items was examined., Results: Confirmatory factor analyses showed that the best-fitting model was the bifactor model with a reduced set of items. The bifactor-specific indices showed that the factor structure cannot be considered unidimensional and that SPS and SIAS are reliable subscales. A closer examination of the less fitting item content and implications for future studies are discussed., Conclusions: In conclusion, SPS and SIAS can be reported together as an overall score of social anxiety and are separately reliable measures to assess different aspects of social anxiety., Trial Registration: This is a secondary analysis of data from two trials registered under ISRCTN75894275 and ISRCTN10627379., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Self-efficacy is a key construct in behavioral science with significant impact on mental health and wellbeing. A growing body of work has shown that perceptions of self-efficacy can be increased through recall of autobiographical episodes (AEs) of mastery ("self-efficacy memories") in experimental settings. Doing so contributes to improvements in clinically relevant processes, such as emotion regulation and problem solving. Here we examine whether the recall of self-efficacy AEs contributes to more adaptive appraisals for personally experienced negative memories. Seventy-five healthy individuals each identified an idiosyncratic personal negative memory that was screened for emotional attributes. Participants were then asked to either recall self-efficacy (SE, n = 25) or positive (POS, n = 25) autobiographical episodes. We investigated induction effects on subsequent reappraisals of the personal negative memories. The SE induction was associated with significant reductions in distress, and subjective physiological responses as compared to the POS induction. No significant induction effects emerged in autonomic regulation. These findings suggest that recalling self-efficacy episodes may promote adaptive self-appraisals for negative memories, which in turn may contribute to recovery from stressful events and, with further research, may prove to be a useful adjunctive strategy for treatments such as CBT. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Unified Protocol (UP) as a transdiagnostic intervention has primarily been applied in the treatment of anxiety disorders and in face-to-face-settings. The current study investigated the efficacy of a 10-week Internet-based adaptation of the UP for anxiety, depressive, and somatic symptom disorders. The trial was registered under DRKS00014820 at the German Clinical Trial Registry, DRKS. Participants (n = 129) were randomized to treatment or waitlist control. Significant treatment effects were found for symptom distress, satisfaction with life, positive/negative affect and markers of anxiety, depression, and somatic symptom burden (within-group Hedges' g = 0.32-1.38 and between-group g = 0.20-1.11). Treatment gains were maintained at 1- and 6-month-follow-up. Subgroup analyses showed comparable effects in participants with anxiety and depressive disorders. 26.6% dropped out of treatment and 35.38% did not provide post-treatment assessments. The results strengthen the application of the UP as an Internet-based treatment for alleviating symptom distress across emotional disorders. More research on the applicability for single disorders is needed and avenues to improve adherence and attrition rates should be explored., Competing Interests: The authors have declared that no competing interests exist.

Background: A growing number of psychological interventions are delivered via smartphones with the aim of increasing the efficacy and effectiveness of these treatments and providing scalable access to interventions for improving mental health. Most of the scientifically tested apps are based on cognitive behavioral therapy (CBT) principles, which are considered the gold standard for the treatment of most mental health problems., Objective: This review investigates standalone smartphone-based ecological momentary interventions (EMIs) built on principles derived from CBT that aim to improve mental health., Methods: We searched the MEDLINE, PsycINFO, EMBASE, and PubMed databases for peer-reviewed studies published between January 1, 2007, and January 15, 2020. We included studies focusing on standalone app-based approaches to improve mental health and their feasibility, efficacy, or effectiveness. Both within- and between-group designs and studies with both healthy and clinical samples were included. Blended interventions, for example, app-based treatments in combination with psychotherapy, were not included. Selected studies were evaluated in terms of their design, that is, choice of the control condition, sample characteristics, EMI content, EMI delivery characteristics, feasibility, efficacy, and effectiveness. The latter was defined in terms of improvement in the primary outcomes used in the studies., Results: A total of 26 studies were selected. The results show that EMIs based on CBT principles can be successfully delivered, significantly increase well-being among users, and reduce mental health symptoms. Standalone EMIs were rated as helpful (mean 70.8%, SD 15.3; n=4 studies) and satisfying for users (mean 72.6%, SD 17.2; n=7 studies)., Conclusions: Study quality was heterogeneous, and feasibility was often not reported in the reviewed studies, thus limiting the conclusions that can be drawn from the existing data. Together, the studies show that EMIs may help increase mental health and thus support individuals in their daily lives. Such EMIs provide readily available, scalable, and evidence-based mental health support. These characteristics appear crucial in the context of a global crisis such as the COVID-19 pandemic but may also help reduce personal and economic costs of mental health impairment beyond this situation or in the context of potential future pandemics., (©Marta Anna Marciniak, Lilly Shanahan, Judith Rohde, Ava Schulz, Carolin Wackerhagen, Dorota Kobylińska, Oliver Tuescher, Harald Binder, Henrik Walter, Raffael Kalisch, Birgit Kleim. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 12.11.2020.)

Background: Social anxiety disorder (SAD) is highly prevalent among university students, but the majority of affected students remain untreated. Internet- and mobile-based self-help interventions (IMIs) may be a promising strategy to address this unmet need. This study aims to investigate the efficacy and cost-effectiveness of an unguided internet-based treatment for SAD among university students. The intervention is optimized for the treatment of university students and includes one module targeting fear of positive evaluations that is a neglected aspect of SAD treatment., Methods: The study is a two arm randomized controlled trial in which 200 university students with a primary diagnosis of SAD will be assigned randomly to either a wait-list control group (WLC) or the intervention group (IG). The intervention consists of 9 sessions of an internet-based cognitive-behavioral treatment, which also includes a module on fear of positive evaluation (FPE). Guidance is delivered only on the basis of standardized automatic messages, consisting of positive reinforcements for session completion, reminders, and motivational messages in response to non-adherence. All participants will additionally have full access to treatment as usual. Diagnostic status will be assessed through Structured Clinical Interviews for DSM Disorders (SCID). Assessments will be completed at baseline, 10 weeks and 6-month follow-up. The primary outcome will be SAD symptoms at post-treatment, assessed via the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS). Secondary outcomes will include diagnostic status, depression, quality of life and fear of positive evaluation. Cost-effectiveness and cost-utility analyses will be evaluated from a societal and health provider perspective., Discussion: Results of this study will contribute to growing evidence for the efficacy and cost-effectiveness of unguided IMIs for the treatment of SAD in university students. Consequently, this trial may provide valuable information for policy makers and clinicians regarding the allocation of limited treatment resources to such interventions., Trial Registration: DRKS00011424 (German Clinical Trials Register (DRKS)) Registered 14/12/2016.

Objectives: Internet- and mobile-based interventions (IMIs) offer the opportunity to deliver mental health treatments on a large scale. This randomized controlled trial evaluated the efficacy of an unguided IMI (StudiCare SAD) for university students with social anxiety disorder (SAD)., Methods: University students (N = 200) diagnosed with SAD were randomly assigned to an IMI or a waitlist control group (WLC) with full access to treatment as usual. StudiCare SAD consists of nine sessions. The primary outcome was SAD symptoms at posttreatment (10 weeks), assessed via the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS). Secondary outcomes included depression, quality of life, fear of positive evaluation, general psychopathology, and interpersonal problems., Results: Results indicated moderate to large effect sizes in favor of StudiCare SAD compared with WLC for SAD at posttest for the primary outcomes (SPS: d = 0.76; SIAS: d = 0.55, p < 0.001). Effects on all secondary outcomes were significant and in favor of the intervention group., Conclusion: StudiCare SAD has proven effective in reducing SAD symptoms in university students. Providing IMIs may be a promising way to reach university students with SAD at an early stage with an effective treatment., (© 2019 John Wiley & Sons, Ltd.)

Increased levels of self-criticism and a lack of self-compassion have been associated with the development and maintenance of a range of psychological disorders. In the current study, we tested the efficacy of an online version of a compassion-focused intervention, mindfulness-based compassionate living (MBCL), with guidance on request. A total of 122 self-referred participants with increased levels of self-criticism were randomly assigned to care as usual (CAU) or the intervention group (CAU + online intervention). Primary endpoints were self-reported depressive, anxiety and distress symptoms (DASS-21) and self-compassion (SCS) at 8 weeks. Secondary endpoints were self-criticism, mindfulness, satisfaction with life, fear of self-compassion, self-esteem, and existential shame. At posttreatment, the intervention group showed significant changes with medium to large effect sizes compared to the control group regarding primary outcomes (Cohen's d: 0.79 [DASS] and -1.21 [SCS]) and secondary outcomes (Cohen's ds: between 0.40 and 0.94 in favor of the intervention group). The effects in the intervention group were maintained at 6-months postrandomization. Adherence measures (number of completed modules, self-reported number of completed exercises per week) predicted postintervention scores for self-compassion but not for depressive, anxiety, and distress symptoms in the intervention group. The current study shows the efficacy of an online intervention with a transdiagnostic intervention target on a broad range of measures, including depressive and anxiety symptoms and self-compassion., (Copyright © 2018. Published by Elsevier Ltd.)

Objective: Internet-based cognitive-behavioral treatments (ICBT) have shown promise for various mental disorders, including social anxiety disorder (SAD). Most of these treatments have been delivered on desktop computers. However, the use of smartphones is becoming ubiquitous and could extend the reach of ICBT into users' everyday life. Only a few studies have empirically examined the efficacy of ICBT delivered through a smartphone app and there is no published study on mobile app delivered ICBT for SAD. This three-arm randomized-controlled trial (RCT) is the first to compare the efficacy of guided ICBT for smartphones (app) and conventional computers (PC) with a wait list control group (WL)., Method: A total of 150 individuals meeting the diagnostic criteria for SAD were randomly assigned to one of the three conditions. Primary endpoints were self-report measures and diagnostic status of SAD., Results: After 12 weeks of treatment, both active conditions showed superior outcome on the composite of all SAD measures (PC vs. WL: d = 0.74; App vs. WL: d = 0.89) and promising diagnostic response rates (NNTPC = 3.33; NNTApp = 6.00) compared to the WL. No significant between-groups effects were found between the two active conditions on the composite score (Cohen's d = 0.07). Treatment gains were maintained at 3-month follow-up. Program use was more evenly spread throughout the day in the mobile condition, indicating an integration of the program into daily routines., Conclusions: ICBT can be delivered effectively using smartphones. (PsycINFO Database Record, ((c) 2018 APA, all rights reserved).)

Predicting therapeutic outcome in the mental health domain is of utmost importance to enable therapists to provide the most effective treatment to a patient. Using information from the writings of a patient can potentially be a valuable source of information, especially now that more and more treatments involve computer-based exercises or electronic conversations between patient and therapist. In this paper, we study predictive modeling using writings of patients under treatment for a social anxiety disorder. We extract a wealth of information from the text written by patients including their usage of words, the topics they talk about, the sentiment of the messages, and the style of writing. In addition, we study trends over time with respect to those measures. We then apply machine learning algorithms to generate the predictive models. Based on a dataset of 69 patients, we are able to show that we can predict therapy outcome with an area under the curve of 0.83 halfway through the therapy and with a precision of 0.78 when using the full data (i.e., the entire treatment period). Due to the limited number of participants, it is hard to generalize the results, but they do show great potential in this type of information.

A growing body of evidence suggests that internet-based cognitive behavioural treatments (ICBT) are effective to treat social anxiety disorder (SAD). Whereas the efficacy of clinician-guided ICBT has been established, ICBT in a group format has not yet been systematically investigated. This three-arm RCT compared the efficacy of clinician-guided group ICBT (GT) with clinician guided individual ICBT (IT) and a wait-list (WL). A total of 149 individuals meeting the diagnostic criteria for SAD were randomly assigned to one of three conditions. Primary endpoints were self-report measures of SAD and diagnostic status taken at baseline, after the twelve-week intervention and at six-month follow-up. Secondary endpoints were symptoms of depression, interpersonal problems and general symptomatology. At post-treatment, both active conditions showed superior outcome regarding SAD symptoms (GT vs. WL: d = 0.84-0.74; IT vs. WL: d = 0.94-1.22). The two active conditions did not differ significantly in symptom reduction (d = 0.12-0.26, all ps > 0.63), diagnostic response rate or attrition. Treatment gains were maintained at follow-up. The group format reduced weekly therapist time per participant by 71% (IT: 17 min, GT: 5 min). Findings indicate that a clinician-guided group format is a promising approach in treating SAD., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Background: Social anxiety disorder (SAD) is one of the most common mental disorders and causes subjective suffering and economic burden worldwide. Although effective treatments are available, a lot of cases go untreated. Internet-based self-help is a low-threshold and flexible treatment alternative for SAD. Various studies have already shown that internet-based self-help can be effective to reduce social phobic symptoms significantly. Most of the interventions tested include therapist support, whereas the role of peer support within internet-based self-help has not yet been fully understood. There is evidence suggesting that patients' mutual exchange via integrated discussion forums can increase the efficacy of internet-based treatments. This study aims at investigating the added value of therapist-guided group support on the treatment outcome of internet-based self-help for SAD., Methods/design: The study is conducted as a randomized controlled trial. A total of 150 adults with a diagnosis of SAD are randomly assigned to either a waiting-list control group or one of the active conditions. The participants in the two active conditions use the same internet-based self-help program, either with individual support by a psychologist or therapist-guided group support. In the group guided condition, participants can communicate with each other via an integrated, protected discussion forum. Subjects are recruited via topic related websites and links; diagnostic status will be assessed with a telephone interview. The primary outcome variables are symptoms of SAD and diagnostic status after the intervention. Secondary endpoints are general symptomology, depression, quality of life, as well as the primary outcome variables 6 months later. Furthermore, process variables such as group processes, the change in symptoms and working alliance will be studied., Discussion: The results of this study should indicate whether group-guided support could enhance the efficacy of an internet-based self-help treatment for SAD. This novel treatment format, if shown effective, could represent a cost-effective option and could further be modified to treat other conditions, as well., Trial Registration: ISRCTN75894275.