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. RESULTS: In preregistered analyses using latent growth models, higher IU at the first pandemic timepoint predicted more severe anxiety, but also a sharper decline in anxiety, across timepoints. This finding was robust to the addition of pre-pandemic anxiety and demographic predictors as covariates (in the full sample) as well as pre-pandemic depression severity (in participants for whom pre-pandemic depression data were available). Younger age, lower self/parent education, and self-reported history of COVID-19 illness at the first pandemic timepoint predicted more severe anxiety across timepoints with strong model fit, but did not predict anxiety trajectory. CONCLUSIONS: IU prospectively predicted more severe anxiety but a sharper decrease in anxiety over time during the pandemic, including after adjustment for covariates. IU therefore appears to have unique and specific predictive utility with respect to anxiety in the context of the COVID-19 pandemic.

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).

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

ABSTRACT: 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 . both control conditions) had significantly greater knowledge of patients' rights to EBMHC. Further, individuals who watched the DTC ( vs . control) video reported significantly greater comfort with accessing care and perceived their assigned video as significantly more culturally sensitive. However, participants who watched the DTC video were not significantly different from both control conditions on self-report measures of self-efficacy in working with a provider, likelihood of asking a provider about one's rights, treatment-seeking intentions, and self-stigma. Findings suggest the potential for a DTC video to promote knowledge of EBMHC, though its impact on help-seeking perceptions and intentions was less promising.

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. We also investigated whether two additional factors (writing perspective and inclusion of participants' social networks) would enhance task impact. The present study evaluated whether posited proximal cognitive and motivational outcomes (drinking identity, self-efficacy, readiness to change, and drinking intentions) changed immediately after each writing session. METHOD: The study is a randomized clinical trial in which hypotheses and analyses were pre-registered. Participants were 328 college students who met hazardous drinking criteria. The study had a 2 (narrative writing topic: low-risk drinker vs. reduced smartphone use) × 2 (writing perspective: first-person vs. non-first-person) × 2 (social network instruction: instructed to include vs. not) factorial design. Proximal outcomes were drinking identity, self-efficacy, readiness to change, and drinking intentions. The clinical outcome was alcohol consumption. Participants completed three laboratory sessions at weekly intervals that included the writing task and pre- and post-task assessments. RESULTS: Results were largely null, except that readiness to reduce drinking was higher in the low-risk drinker condition and increased over the lab sessions. Time effects indicated that reductions in drinking identity, drinking intentions, and alcohol consumption, and increases in self-efficacy were observed but did not change above and beyond control conditions. CONCLUSIONS: Findings indicate the need to strengthen the writing task and select a more appropriate control task to target proposed proximal outcomes. Future studies might try personalizing the task, evaluating its efficacy with individuals motivated to change their drinking, and using a control task that does not involve imagining a future self.

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.

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.S., we evaluated distress (depression, anxiety, stress symptoms) as a potential moderator. Between- and within-person components of drinking identity and distress were evaluated to consider both individual differences and variations within a person across time and changing contexts. Study hypotheses and data analysis plan were preregistered. Graduating college students who met HD criteria (N = 422) completed implicit and explicit drinking identity measures (assessed using reaction time and self-report measures, respectively), distress symptom questionnaires, and self-reported alcohol consumption and problems at four-month intervals for 2.5 years. Results supported moderation at the between-person level for alcohol consumption, with higher levels of implicit drinking identity and distress linked to greater subsequent alcohol consumption. Only between-person main effects for (explicit) identity and distress were linked to more subsequent alcohol-related problems. Though moderation findings were mixed, having a stronger drinking identity and/or greater distress was linked to continued HD risk in this sample. Individuals with these risk factors may benefit from enhanced prevention efforts to help graduates transition out of HD post-college.

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. We posit that passively detecting social contexts can be particularly useful for social anxiety research, as it may ultimately help identify changes in social anxiety status and patterns of social avoidance and withdrawal. To this end, we recruited a sample of highly socially anxious undergraduate students (N=46) to examine whether we could detect the presence of experimentally manipulated virtual social contexts via wristband sensors. Using a multitask machine learning pipeline, we leveraged passively sensed biobehavioral streams to detect contexts relevant to social anxiety, including (1) whether people were in a social situation, (2) size of the social group, (3) degree of social evaluation, and (4) phase of social situation (anticipating, actively experiencing, or had just participated in an experience). Results demonstrated the feasibility of detecting most virtual social contexts, with stronger predictive accuracy when detecting whether individuals were in a social situation or not and the phase of the situation, and weaker predictive accuracy when detecting the level of social evaluation. They also indicated that sensing streams are differentially important to prediction based on the context being predicted. Our findings also provide useful information regarding design elements relevant to passive context detection, including optimal sensing duration, the utility of different sensing modalities, and the need for personalization. We discuss implications of these findings for future work on context detection (e.g., just-in-time adaptive intervention development).