Web-based interpretation bias training to reduce anxiety: A sequential, multiple-assignment randomized trial.

OBJECTIVE: Web-based cognitive bias modification for interpretation (CBM-I) can improve interpretation biases and anxiety symptoms but faces high rates of dropout. This study tested the effectiveness of web-based CBM-I relative to an active psychoeducation condition and the addition of low-intensity telecoaching for a subset of CBM-I participants. METHOD: 1,234 anxious community adults (Mage = 35.09 years, 81.2% female, 72.1% white, 82.6% not Hispanic) were randomly assigned at Stage 1 of a sequential, multiple-assignment randomized trial to complete five weekly sessions of CBM-I or psychoeducation on our team's public research website. After the first session, for Stage 2, an algorithm attempted to classify CBM-I participants as higher (vs. lower) risk for dropping out; those classified as higher risk were then randomly assigned to complete four brief weekly telecoaching check-ins (vs. no coaching). RESULTS: As hypothesized (https://doi.org/j2xr; Daniel, Eberle, & Teachman, 2020), CBM-I significantly outperformed psychoeducation at improving positive and negative interpretation biases (Recognition Ratings, Brief Body Sensations Interpretation Questionnaire) and anxiety symptoms (Overall Anxiety Severity and Impairment Scale, Anxiety Scale from Depression Anxiety Stress Scales-Short Form), with smaller treatment gains remaining significant at 2-month follow-up. Unexpectedly, CBM-I had significantly worse treatment dropout outcomes than psychoeducation, and adding coaching (vs. no coaching) did not significantly improve efficacy or dropout outcomes (notably, many participants chose not to interact with their coach). CONCLUSIONS: Web-based CBM-I appears effective, but supplemental coaching may not mitigate the challenge of dropout. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Online cognitive bias modification for interpretation to reduce anxious thinking during the COVID-19 pandemic.

Anxiety disorders are highly prevalent, and rates increased during the COVID-19 pandemic. However, most individuals with elevated anxiety do not access treatment due to barriers such as stigma, cost, and availability. Digital mental health programs, such as cognitive bias modification for interpretation (CBM-I), hold promise in increasing access to care. Before widely disseminating CBM-I, we must rigorously test its effectiveness and determine whom it is best positioned to benefit. The present study (which is a substudy of a parent trial) compared CBM-I against psychoeducation offered through the public website MindTrails, and also tested whether baseline anxiety tied to COVID-19 influenced the rate of change in anxiety and interpretation bias during and after each intervention. Adults with moderate-to-severe anxiety symptoms were randomly assigned to complete five sessions of either CBM-I or psychoeducation as part of a larger trial, and 608 enrolled in this substudy after Session 1. As predicted (https://osf.io/2dyzr), CBM-I was superior to psychoeducation at reducing anxiety symptoms (on the OASIS but not the DASS-21-AS: d = -0.31), reducing negative interpretation bias (d range = -0.34 to -0.43), and increasing positive interpretation bias (d = 0.79) by the end of treatment. Results also indicated that individuals higher (vs. lower) in baseline COVID-19 anxiety had stronger decreases in anxiety symptoms while receiving CBM-I but weaker decreases in anxiety symptoms (on the DASS-21-AS) while receiving psychoeducation. These findings suggest that CBM-I may be a useful anxiety-reduction tool for individuals experiencing higher anxiety tied to uncertain events such as the COVID-19 pandemic.

Minimal Effect of Messaging on Engagement in a Digital Anxiety Intervention.

This study evaluated the effectiveness of different recruitment messages for encouraging enrollment in a digital mental health intervention (DMHI) for anxiety among 1,600 anxious patients in a large healthcare system. Patients were randomly assigned to receive a standard message, or one of five messages designed to encourage enrollment: Three messages offered varying financial incentives, one message offered coaching, and one message provided consumer testimonials. Patients could then click a link in the message to visit the DMHI website, enroll, and start the first session. We examined the effects of message features and message length (short vs. long) on rates of site clicks, enrollment, and starting the first session. We also tested whether demographic and clinical factors derived from patients' electronic health records were associated with rates of enrollment and starting the first session to understand the characteristics of patients most likely to use DMHIs in this setting. Across messages, 19.4% of patients clicked a link to visit the DMHI website, but none of the messages were significantly associated with rates of site clicks, enrollment, or starting the first session. Females (vs. males) had a greater probability of enrollment. No other demographic or clinical variables were significantly associated with enrollment or starting the first session. Findings provide guidance for resource allocation decisions in larger scale DMHI implementations in healthcare settings.

Shifting Episodic Prediction With Online Cognitive Bias Modification: A Randomized Controlled Trial.

Negative future thinking pervades emotional disorders. This hybrid efficacy-effectiveness trial tested a four-session, scalable online cognitive bias modification program for training more positive episodic prediction. 958 adults (73.3% female, 86.5% White, 83.4% from United States) were randomized to positive conditions with ambiguous future scenarios that ended positively, 50/50 conditions that ended positively or negatively, or a control condition with neutral scenarios. As hypothesized (preregistration: https://osf.io/jrst6), positive training participants improved more than control participants in negative expectancy bias (d = -0.58), positive expectancy bias (d = 0.80), and self-efficacy (d = 0.29). Positive training was also superior to 50/50 training for expectancy bias and optimism (d = 0.31). Training gains attenuated yet remained by 1-month follow-up. Unexpectedly, participants across conditions improved comparably in anxiety and depression symptoms and growth mindset. Targeting a transdiagnostic process with a scalable program may improve bias and outlook; however, further validation of outcome measures is required.

Mechanisms of change in treatments for transdiagnostic emotion dysregulation: The roles of skills use, perceived control and mindfulness.

Emotion dysregulation (ED) is a key target for change among empirically supported treatments for emotional disorders, including dialectical behaviour therapy skills training (DBT-ST), yet how treatments improve ED is poorly understood. Using data from a randomised trial of DBT-ST versus supportive group therapy for transdiagnostic ED, we tested whether three mechanistic variables-behavioural skills use, mindfulness, and perceived control-explain variability in ED within people over time. We additionally explored the mediating roles of these variables between conditions. Adults with transdiagnostic ED (N = 44) participated in weekly groups for 4 months, with assessments at pre-, mid- and post-treatment and at 2-month follow-up. As hypothesised, multilevel models disaggregating within- and between-person effects indicated that skills use, mindfulness, and perceived control each had significant total and unique within-person associations with ED at concurrent time points, net the effect of time. Unexpectedly, these within-person relations were not significant for mechanistic variables predicting ED 2 months later. Further, unique between-person variability in skills use, mindfulness, and perceived control did not significantly mediate the relationship between condition and ED improvements. The present study is an important step in clarifying ED mechanisms of change, both within and between persons.

Multilevel associations of daily skill use and effectiveness with anxiety, depression, and stress in a transdiagnostic sample undergoing dialectical behavior therapy skills training.

Dialectical Behavior Therapy (DBT) is effective at treating disorders of emotion dysregulation. However, it is unclear which mechanisms contribute to these effects. The aim of this study was to characterize the within-person associations of two theoretically relevant mechanisims of change, skill use and skill effectiveness, with anxiety, stress, and depression. Participants (n = 19, Mage = 31.8, 68% female) with a primary anxiety or depressive disorder completed daily reports (N = 1344) of DBT skill use, perceived effectiveness, anxiety, stress, and depression during a 16-session DBT skills training group. DBT skill use increased across treatment, p < .01, but effectiveness did not, p = .64. Within persons, participants used more skills on days with greater stress and anxiety, p < .01, which predicted next-day decreases in stress and anxiety, p = .03. On days when participants reported higher effectiveness, they used more skills than their personal average when experiencing more intense negative affect, p < .01. These results suggest using more skills, especially when used more effectively, is a mechanism by which DBT skills groups address emotional dysfunction for those with transdiagnostic emotional disorders.

Anxiety sensitivity, distress intolerance, and negative interpretation bias strengthen the relationship between trait anxiety and depersonalization.

BACKGROUND OBJECTIVES: Depersonalization is common in anxiety disorders, but little is known about factors that influence co-occurring anxiety and depersonalization. DESIGN: We investigated trait moderators of the relationships between state and trait anxiety and depersonalization to better understand their co-occurrence and to identify potential points of intervention. METHODS: Adults recruited on Amazon Mechanical Turk (N = 303) completed two computer tasks designed to increase variability in state anxiety and depersonalization as well as several self-report questionnaires. RESULTS: As hypothesized, anxiety positively predicted depersonalization at both a state level and trait level. Moreover, as hypothesized, the trait anxiety-trait depersonalization relationship was strengthened by greater anxiety sensitivity; distress intolerance; and negative interpretation bias for anxiety sensations, and for depersonalization sensations. None of these hypothesized trait moderators significantly strengthened the state anxiety-state depersonalization relationship. CONCLUSIONS: These findings suggest that, on a trait level, anxiety and depersonalization more frequently co-occur when people catastrophically misinterpret their symptoms or have lower emotional distress tolerance.

Adapting cognitive bias modification to train healthy prospection.

Prospection, the mental simulation of future events, has been theoretically linked to physical and mental health. Prior studies have found that prospection is malleable; however, no research to our knowledge has tested whether a scalable intervention explicitly targeting the simulation of positive future outcomes can lead to more generalized positive prospection, and enhance positive outlook and reduce distress. The current study tested a novel, web-based cognitive bias modification for interpretation (CBM-I) program designed to shift prospective bias towards more positive (as opposed to negative) representations of future outcomes among 172 participants selected for having a relatively negative baseline expectancy bias. Results showed that following CBM-I, participants in active training conditions exhibited more positive expectations about the future, and increased self-efficacy and growth mindset. Also, optimism increased and depression and anxiety symptoms decreased following active training, but this also occurred for the control condition. Analyses did not suggest that changes in positive expectations mediated changes in positive outlook outcomes. Results suggest that an online prospection intervention can lead to more positive expectations about future events and improve positive outlook, though open questions remain about what accounts for the training effects.

Changes in Problematic Anger, Shame, and Disgust in Anxious and Depressed Adults Undergoing Treatment for Emotion Dysregulation.

Emotion dysregulation, the pervasive difficulty managing negative emotions, is a core problem across mood and anxiety disorders. Anger, shame, and disgust are particularly problematic emotions, impacting both disorder severity and treatment outcome. We previously found that a 16-week dialectical behavior therapy skills training group (DBT-ST) was superior to an activities-based support group (ASG) in decreasing emotion dysregulation in 44 adults with high emotion dysregulation who met diagnostic criteria for an anxiety or depressive disorder. We presently examine these participants' changes in anger, shame, disgust, and distress using self-reports collected over 6 months during and after treatment. Hierarchical linear modeling analyses show that DBT-ST was superior to ASG in decreasing anger suppression (d = 0.93) and distress (d = 1.04). Both conditions significantly reduced shame, disgust propensity, and disgust sensitivity, but neither was superior for these outcomes. The treatments did not significantly reduce anger expression. Mediation analyses suggest that condition indirectly influenced 4-month anger suppression, shame, and distress through its effect on 2-month emotion dysregulation. These findings suggest that DBT-ST is efficacious for certain problematic emotions and distress in depressed and anxious adults and that common factors may account for some, but not all, of its benefits.

A Weakly Supervised Learning Framework for Detecting Social Anxiety and Depression.

Although social anxiety and depression are common, they are often underdiagnosed and undertreated, in part due to difficulties identifying and accessing individuals in need of services. Current assessments rely on client self-report and clinician judgment, which are vulnerable to social desirability and other subjective biases. Identifying objective, nonburdensome markers of these mental health problems, such as features of speech, could help advance assessment, prevention, and treatment approaches. Prior research examining speech detection methods has focused on fully supervised learning approaches employing strongly labeled data. However, strong labeling of individuals high in symptoms or state affect in speech audio data is impractical, in part because it is not possible to identify with high confidence which regions of a long speech indicate the person's symptoms or affective state. We propose a weakly supervised learning framework for detecting social anxiety and depression from long audio clips. Specifically, we present a novel feature modeling technique named NN2Vec that identifies and exploits the inherent relationship between speakers' vocal states and symptoms/affective states. Detecting speakers high in social anxiety or depression symptoms using NN2Vec features achieves F-1 scores 17% and 13% higher than those of the best available baselines. In addition, we present a new multiple instance learning adaptation of a BLSTM classifier, named BLSTM-MIL. Our novel framework of using NN2Vec features with the BLSTM-MIL classifier achieves F-1 scores of 90.1% and 85.44% in detecting speakers high in social anxiety and depression symptoms.

Dialectical behavior therapy skills for transdiagnostic emotion dysregulation: a pilot randomized controlled trial.

Difficulties with emotions are common across mood and anxiety disorders. Dialectical behavior therapy skills training (DBT-ST) reduces emotion dysregulation in borderline personality disorder (BPD). Preliminary evidence suggests that use of DBT skills mediates changes seen in BPD treatments. Therefore, we assessed DBT-ST as a stand-alone, transdiagnostic treatment for emotion dysregulation and DBT skills use as a mediator of outcome. Forty-four anxious and/or depressed, non-BPD adults with high emotion dysregulation were randomized to 16 weeks of either DBT-ST or an activities-based support group (ASG). Participants completed measures of emotion dysregulation, DBT skills use, and psychopathology every 2 months through 2 months posttreatment. Longitudinal analyses indicated that DBT-ST was superior to ASG in decreasing emotion dysregulation (d = 1.86), increasing skills use (d = 1.02), and decreasing anxiety (d = 1.37) but not depression (d = 0.73). Skills use mediated these differential changes. Participants found DBT-ST acceptable. Thirty-two percent of DBT-ST and 59% of ASG participants dropped treatment. Fifty-nine percent of DBT-ST and 50% of ASG participants complied with the research protocol of avoiding ancillary psychotherapy and/or medication changes. In summary, DBT-ST is a promising treatment for emotion dysregulation for depressed and anxious transdiagnostic adults, although more assessment of feasibility is needed.