Return of negative interpretation bias after positive interpretation training as a dynamic predictor of treatment outcome in fear of public speaking.

Despite various efforts in the field, no consistent predictors of treatment outcome in anxiety disorders have been identified. Based on the Dynamic System Theory, this study proposes a novel, dynamic predictor of treatment outcome in those with public speaking anxiety. It was assessed whether speed of return to one's interpretation bias equilibrium after an experimentally-induced perturbation (i.

A mobile intervention to reduce anxiety among university students, faculty, and staff: Mixed methods study on users' experiences.

Anxiety is highly prevalent among college communities, with significant numbers of students, faculty, and staff experiencing severe anxiety symptoms. Digital mental health interventions (DMHIs), including Cognitive Bias Modification for Interpretation (CBM-I), offer promising solutions to enhance access to mental health care, yet there is a critical need to evaluate user experience and acceptability of DMHIs. CBM-I training targets cognitive biases in threat perception, aiming to increase cognitive flexibility by reducing rigid negative thought patterns and encouraging more benign interpretations of ambiguous situations.

Early Attrition Prediction for Web-Based Interpretation Bias Modification to Reduce Anxious Thinking: A Machine Learning Study.

Background: Digital mental health is a promising paradigm for individualized, patient-driven health care. For example, cognitive bias modification programs that target interpretation biases (cognitive bias modification for interpretation [CBM-I]) can provide practice thinking about ambiguous situations in less threatening ways on the web without requiring a therapist. However, digital mental health interventions, including CBM-I, are often plagued with lack of sustained engagement and high attrition rates.

Intolerance of uncertainty as a predictor of anxiety severity and trajectory during the COVID-19 pandemic.

Background: Efforts to identify risk and resilience factors for anxiety severity and course during the COVID-19 pandemic have focused primarily on demographic rather than psychological variables. Intolerance of uncertainty (IU), a transdiagnostic risk factor for anxiety, may be a particularly relevant vulnerability factor.

Method: N = 641 adults with pre-pandemic anxiety data reported their anxiety, IU, and other pandemic and mental health-related variables at least once and up to four times during the COVID-19 pandemic, with assessments beginning in May 2020 through March 2021.

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.

Randomized Controlled Trial Evaluating the Effectiveness of a Direct-to-Consumer Marketing Video About Patients' Right to Evidence-Based Mental Health Care.

This study evaluated the impact of a direct-to-consumer (DTC) marketing video designed to educate the public about patients' rights to evidence-based mental health care (EBMHC). Participants ( N = 632) were randomly assigned to an active DTC video condition, a control video condition, or a control condition without a video. Participants who watched the DTC video ( vs .

Detecting Social Contexts from Mobile Sensing Indicators in Virtual Interactions with Socially Anxious Individuals.

Mobile sensing is a ubiquitous and useful tool to make inferences about individuals' mental health based on physiology and behavior patterns. Along with sensing features directly associated with mental health, it can be valuable to detect different features of social contexts to learn about social interaction patterns over time and across different environments. This can provide insight into diverse communities' academic, work and social lives, and their social networks.

Investigating cognitive and motivational proximal outcomes in a randomized clinical trial of writing about the future self to reduce drinking.

Background: Drinking identity (the extent to which one links the self with drinking alcohol) is a unique risk factor for college students' hazardous drinking that is not directly targeted by existing interventions. We conducted a study that aimed to decrease drinking identity among college students with hazardous drinking. We adapted a writing task about the future self and tested whether three writing sessions could decrease drinking identity and change drinking.

Evaluating distress as a moderator of the relationship between drinking identity and hazardous drinking during the post-college transition.

Drinking identity (the extent to which one associates the self with drinking alcohol) is a robust predictor of young adult hazardous drinking (HD; heavy drinking and alcohol-related problems), and decreases in drinking identity have been linked to the decline in HD that often occurs following college graduation. Identifying moderators is key to recognizing who is most at risk for continued HD given a drinking identity vulnerability. Using data from a longitudinal study of graduating college students from the U.

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.

Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and A Machine Learning Pipeline.

Individuals high in social anxiety symptoms often exhibit elevated state anxiety in social situations. Research has shown it is possible to detect state anxiety by leveraging digital biomarkers and machine learning techniques. However, most existing work trains models on an entire group of participants, failing to capture individual differences in their psychological and behavioral responses to social contexts.

State and Trait Emotion Regulation Diversity in Social Anxiety.

Emotion regulation (ER) diversity, defined as the variety, frequency, and evenness of ER strategies used, may predict social anxiety (SA) severity. In a sample of individuals with high (113) or low (=42) SA severity, we tested whether four trait ER diversity metrics predicted group membership. We generalized existing trait ER diversity calculations to repeated-measures data to test if state-level metrics (using two weeks of EMA data) predicted SA severity within the higher severity group.

Web-Based Cognitive Bias Modification Program for Young People With Social Anxiety and Hazardous Alcohol Use: Feasibility, Acceptability, and Preliminary Efficacy Study.

Background: Interpretation bias modification (IBM) and approach bias modification (ApBM) cognitive retraining interventions can be efficacious adjunctive treatments for improving social anxiety and alcohol use problems. However, previous trials have not examined the combination of these interventions in a young, comorbid sample.

Objective: This study aims to describe the feasibility, acceptability, and preliminary efficacy of a web-based IBM+ApBM program for young adults with social anxiety and hazardous alcohol use ("Re-Train Your Brain") when delivered in conjunction with treatment as usual (TAU).

Writing about the future self to shift drinking identity: An experimental investigation.

College student drinking is prevalent and costly to public and personal health, leading to calls to identify and target novel mechanisms of behavior change. We aimed to manipulate drinking identity (a cognitive risk factor for hazardous drinking) via three sessions of narrative writing about a future self. We tested whether writing could shift drinking identity and would be accompanied by changes in alcohol consumption and problems.

Understanding Privacy Risks versus Predictive Benefits in Wearable Sensor-Based Digital Phenotyping: A Quantitative Cost-Benefit Analysis.

Wearable devices with embedded sensors can provide personalized healthcare and wellness benefits in digital phenotyping and adaptive interventions. However, the collection, storage, and transmission of biometric data (including processed features rather than raw signals) from these devices pose significant privacy concerns. This quantitative, data-driven study examines the privacy risks associated with wearable-based digital phenotyping practices, with a focus on user , which is the process of identifying participants' IDs from deidentified digital phenotyping datasets.

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.

Changes in Learning From Social Feedback After Web-Based Interpretation Bias Modification: Secondary Analysis of a Digital Mental Health Intervention Among Individuals With High Social Anxiety Symptoms.

Background: Biases in social reinforcement learning, or the process of learning to predict and optimize behavior based on rewards and punishments in the social environment, may underlie and maintain some negative cognitive biases that are characteristic of social anxiety. However, little is known about how cognitive and behavioral interventions may change social reinforcement learning in individuals who are anxious.

Objective: This study assessed whether a scalable, web-based cognitive bias modification for interpretations (CBM-I) intervention changed social reinforcement learning biases in participants with high social anxiety symptoms.

Investigating psychiatric symptoms as predictors of the reasons people do not regulate their emotions in daily life.

Investigations into emotion dysregulation predominantly focus on ineffective strategy selection and implementation. However, little empirical attention has been given to the possibility that failure to engage in emotion regulation (ER) may also indicate emotion dysregulation, especially when the reason for not regulating suggests skill or motivational deficits. We randomly sampled ER strategy use up to six times per day for 5 weeks in 113 adults with elevated social anxiety.

Assessing Emotion Polyregulation in Daily Life: Who Uses It, When Is It Used, and How Effective Is It?

Unlabelled: Most research on emotion regulation has focused on understanding individual emotion regulation strategies. Preliminary research, however, suggests that people often use several strategies to regulate their emotions in a given emotional scenario (polyregulation). The present research examined who uses polyregulation, when polyregulation is used, and how effective polyregulation is when it is used.

Examining social reinforcement learning in social anxiety.

Background And Objectives: Reinforcement learning biases have been empirically linked to anhedonia in depression and theoretically linked to social anhedonia in social anxiety disorder, but little work has directly assessed how socially anxious individuals learn from social reward and punishment.

Methods: N = 157 individuals high and low in social anxiety symptoms completed a social probabilistic selection task that involved selecting between pairs of neutral faces with varying probabilities of changing to a happy or angry face. Computational modeling was performed to estimate learning rates.

Maturing Out: Between- and Within-Persons Changes in Social-Network Drinking, Drinking Identity, and Hazardous Drinking Following College Graduation.

Many college students reduce hazardous drinking (HD) following graduation without treatment. Identifying cognitive mechanisms facilitating this "natural" reduction in HD during this transition is crucial. We evaluated drinking identity as a potential mechanism and tested whether within-person changes in one's social network's drinking were linked to within-person changes in drinking identity and subsequent within-person changes in HD.

Implicit and explicit COVID-19 associations and mental health in the United States: a large-scale examination and replication.

Background: Given the sensitive nature of COVID-19 beliefs, evaluating them explicitly and implicitly may provide a fuller picture of how these beliefs vary based on identities and how they relate to mental health.

Objective: Three novel brief implicit association tests (BIATs) were created and evaluated: two that measured COVID-19-as-dangerous (vs. safe) and one that measured COVID-19 precautions-as-necessary (vs.