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Discrimination in the evaluation of others is a key cause of social inequality around the world. However, relatively little is known about psychological interventions that can be used to prevent biased evaluations. The limited evidence that exists on these strategies is spread across many methods and populations, making it difficult to generate reliable best practices that can be effective across contexts. In the present work, we held a research contest to solicit interventions with the goal of reducing discrimination based on physical attractiveness using a hypothetical admissions task. Thirty interventions were tested across four rounds of data collection (total N > 20,000). Using a signal detection theory approach to evaluate interventions, we identified two interventions that reduced discrimination by lessening both decision noise and decision bias, while two other interventions reduced overall discrimination by only lessening noise or bias. The most effective interventions largely provided concrete strategies that directed participants' attention toward decision-relevant criteria and away from socially biasing information, though the fact that very similar interventions produced differing effects on discrimination suggests certain key characteristics that are needed for manipulations to reliably impact judgment. The effects of these four interventions on decision bias, noise, or both also replicated in a different discrimination domain, political affiliation, and generalized to populations with self-reported hiring experience. Results of the contest for decreasing attractiveness-based favoritism suggest that identifying effective routes for changing discriminatory behavior is a challenge and that greater investment is needed to develop impactful, flexible, and scalable strategies for reducing discrimination. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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., Competing Interests: Declaration of Competing Interest Lauren S. Hallion and Gordon J. G. Asmundson are Associate Editor and Editor-in-Chief at Journal of Anxiety Disorders, respectively, and receive financial support through payments for their editorial work on the journal. Neither author was involved in the review of the manuscript or the decision regarding its acceptance. We have no additional conflicts of interest to declare., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

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., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: Perceived burdensomeness and thwarted belongingness are considered interpersonal risk factors for suicide. Examining these themes in personal text messages may help identify proximal suicide risk., Method: Twenty-six suicide attempt survivors provided personal text messages and reported dates for past periods characterized by positive mood, depressed mood, suicidal ideation (with no attempt), or the two-week period leading up to suicide attempt(s). Texts were then classified into the applicable period based on matching dates. Texts ( N  = 194,083; including n  = 86,705 outgoing texts) were coded for perceived burdensomeness and thwarted belongingness by masked trained raters. Multilevel models were fit to examine whether the target themes (combined into one overall interpersonal risk variable due to low base rate) were more prevalent in texts sent during higher risk episodes (e.g., suicide attempt vs. depressed mood episodes)., Results: 0.57% of outgoing texts contained either target theme. As hypothesized, logistic models showed participants were more likely to send texts containing the target themes during suicide attempt episodes relative to suicidal ideation (with no attempt) episodes, depressed mood episodes, and positive mood episodes, and during suicidal ideation (with no attempt) episodes relative to positive mood episodes. All contrasts were robust to post-hoc correction except for suicide attempt episodes vs. ideation (with no attempt) episodes. No other significant pairwise differences for episode type emerged., Conclusions: Despite the small sample size and low base rate of target themes in the texts, perceived burdensomeness and thwarted belongingness were associated with intra-individual suicide risk severity in personal text messages.

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).

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., (© 2024 Research Society on Alcohol.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

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. Participants were college students meeting hazardous drinking criteria (N = 328; M age  = 20.15; 59% women, 40% men, 1% gender-diverse; 60% white; 23% Asian; 12% multiple races; 2% other racial groups; 8% identified as Hispanic/Latino/a/x). 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. Outcomes were drinking identity, drinking refusal self-efficacy, alcohol consumption, alcohol-related problems, and craving. Participants completed three writing sessions and online follow-up assessments at 2, 4, and 12 weeks. The study is a registered clinical trial; hypotheses and analyses were preregistered (https://osf.io/vy2ep/). Contrary to predictions, narrative writing about a future self as a low-risk drinker did not significantly impact outcomes. Null results extended to expected interactions with writing perspective and social network instructions. The narrative writing task did not shift drinking or alcohol-related outcomes. Future experimental work may benefit from greater flexibility in conceptualizing a future self, recruiting individuals interested in behavior change, and more sensitive measures of drinking identity., (Copyright © 2023 Elsevier Inc. All rights reserved.)

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. When participants reported not engaging in any recent ER, they indicated their reason for not regulating. Data were collected between 2018 and 2019. Participants reported not regulating in 60.9% of surveys. The most frequently endorsed reason for not regulating was "I was not experiencing any thoughts/feelings that I wanted to change," followed by "I did not want to put in the effort," then "I did not know what to do," and finally, "I did not think I was capable." After controlling for within- and between-person state affect, participants with lower trait-level social anxiety, depression, and emotion dysregulation scores were more likely to report no ER because they were not experiencing any thoughts/feelings that they wanted to change relative to the other three reasons that might reflect barriers to effective regulation. Trait-level generalized worry and alcohol use did not significantly predict between nonregulation reasons. Findings from these preregistered analyses suggest that not regulating-especially among persons higher in social anxiety, depression, and emotion dysregulation-may indicate ER skill or motivation deficits that point to opportunities for intervention. Results may not generalize to more demographically or clinically diverse samples. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

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. unnecessary). Implicit and explicit COVID-19 associations were examined based on individuals' demographic characteristics. Implicit associations were hypothesized to uniquely contribute to individuals' self-reports of mental health., Methods: Participants ( N  = 13,413 US residents; April-November 2020) were volunteers for a COVID-19 study. Participants completed one BIAT and self-report measures. This was a preregistered study with a planned internal replication., Results: Results revealed older age was weakly associated with stronger implicit and explicit associations of COVID-as-dangerous and precautions-as-necessary. Black and Asian individuals reported greater necessity of taking precautions than White individuals (with small-to-medium effects); greater education was associated with greater explicit reports of COVID-19-as-dangerous and precautions-as-necessary with small effects. Replicated relationships between COVID-as-dangerous explicit associations and mental health had very small effects., Conclusions: Implicit associations did not predict mental health but there was evidence that stronger COVID-19-as-dangerous explicit associations are weakly associated with worse mental health.

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)., Methods: The study involved a 3-arm randomized controlled pilot trial in which treatment-seeking young adults (aged 18-30 y) with co-occurring social anxiety and hazardous alcohol use were randomized to receive (1) the "integrated" Re-Train Your Brain program, where each session included both IBM and ApBM (50:50 ratio), plus TAU (35/100, 35%); (2) the "alternating" Re-Train Your Brain program, where each session focused on IBM or ApBM in an alternating pattern, plus TAU (32/100, 32%); or (3) TAU only (33/100, 33%). Primary outcomes included feasibility and acceptability, and secondary efficacy outcomes included changes in cognitive biases, social anxiety symptoms, and alcohol use. Assessments were conducted at baseline, after the intervention period (6 weeks after baseline), and 12 weeks after baseline., Results: Both Re-Train Your Brain program formats were feasible and acceptable for young adults. When coupled with TAU, both integrated and alternating programs resulted in greater self-reported improvements than TAU only in anxiety interpretation biases (at the 6-week follow-up; Cohen d=0.80 and Cohen d=0.89) and comorbid interpretation biases (at the 12-week follow-up; Cohen d=1.53 and Cohen d=1.67). In addition, the alternating group reported larger improvements over the control group in generalized social anxiety symptoms (at the 12-week follow-up; Cohen d=0.83) and alcohol cravings (at the 6-week follow-up; Cohen d=0.81). There were null effects on all other variables and no differences between the intervention groups in efficacy outcomes., Conclusions: Should these findings be replicated in a larger randomized controlled trial, Re-Train Your Brain has the potential to be a scalable, low-cost, and non-labor-intensive adjunct intervention for targeting interpretation and comorbidity biases as well as generalized anxiety and alcohol-related outcomes in the real world., Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12620001273976; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364131., International Registered Report Identifier (irrid): RR2-10.2196/28667., (©Katrina Prior, Elske Salemink, Monique Piggott, Victoria Manning, Reinout W Wiers, Bethany A Teachman, Maree Teesson, Andrew J Baillie, Alison Mahoney, Lauren McLellan, Nicola C Newton, Lexine A Stapinski. Originally published in JMIR Formative Research (https://formative.jmir.org), 25.10.2023.)

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 reidentification (ReID) , which is the process of identifying participants' IDs from deidentified digital phenotyping datasets. We propose a machine-learning-based computational pipeline to evaluate and quantify model outcomes under various configurations, such as modality inclusion , window length , and feature type and format , to investigate the factors influencing ReID risks and their predictive trade-offs. This pipeline leverages features extracted from three wearable sensors, resulting in up to 68.43% accuracy in ReID risk for a sample size of N=45 socially anxious participants based on only descriptive features of 10-second observations. Additionally, we explore the trade-offs between privacy risks and predictive benefits by adjusting various settings (e.g., the ways to process extracted features). Our findings highlight the importance of privacy in digital phenotyping and suggest potential future directions.

We present a novel method for quantifying transitions within multivariate binary time series data, using a sliding series of transition matrices, to derive metrics of stability and spread. We define stability as the trace of a transition matrix divided by the sum of all observed elements within that matrix. We define spread as the number of all non-zero cells in a transition matrix divided by the number of all possible cells in that matrix. We developed this method to allow investigation into high-dimensional, sparse data matrices for which existing binary time series methods are not designed. Results from 1728 simulations varying six parameters suggest that unique information is captured by both metrics, and that stability and spread values have a moderate inverse association. Further, simulations suggest that this method can be reliably applied to time series with as few as nine observations per person, where at least five consecutive observations construct each overlapping transition matrix, and at least four time series variables compose each transition matrix. A pre-registered application of this method using 4 weeks of ecological momentary assessment data (N = 110) showed that stability and spread in the use of 20 emotion regulation strategies predict next timepoint affect after accounting for affect and anxiety's auto-regressive and cross-lagged effects. Stability, but not spread, also predicted next timepoint anxiety. This method shows promise for meaningfully quantifying two unique aspects of switching behavior in multivariate binary time series data., (© 2022. The Psychonomic Society, Inc.)

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 ( n= 113) or low ( n =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. As hypothesized (osf.io/xadyp), higher trait ER diversity within avoidance-oriented strategies predicted greater likelihood of belonging to the higher severity group. At the state-level, higher diversity across all ER strategies, and within and between avoidance- and approach-oriented strategies, predicted higher SA severity (but only after controlling for number of submitted EMAs). Only diversity within avoidance-oriented strategies was significantly correlated across trait and state levels. Findings suggest that high avoidance-oriented ER diversity may co-occur with higher SA severity.

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).

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. Accuracy in choosing the more rewarding face was also analyzed., Results: No significant group differences were found for learning rates. Contrary to hypotheses, participants high in social anxiety showed impaired punishment learning accuracy; they were more accurate at choosing the most rewarding face than they were at avoiding the most punishing face, and their punishment learning accuracy was lower than that of participants low in social anxiety. Secondary analyses found that high (vs. low) social anxiety participants were less accurate at selecting the more rewarding face on more (vs. less) punishing face pairs., Limitations: Stimuli were static, White, facial images, which lack important social cues (e.g., movement, sound) and diversity, and participants were largely non-Hispanic, White undergraduates, whose social reinforcement learning may differ from individuals at different developmental stages and those holding more marginalized identities., Conclusions: Socially anxious individuals may be less accurate at learning to avoid social punishment, which may maintain negative beliefs through an interpersonal stress generation process., Competing Interests: Declaration of competing interest The authors have no conflicts of interest., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

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. This study focused on 2 types of social reinforcement learning relevant to social anxiety: learning about other people and learning about one's own social performance., Methods: Participants (N=106) completed 2 laboratory sessions, separated by 5 weeks of ecological momentary assessment tracking emotion regulation strategy use and affect. Approximately half (n=51, 48.1%) of the participants completed up to 6 brief daily sessions of CBM-I in week 3. Participants completed a task that assessed social reinforcement learning about other people in both laboratory sessions and a task that assessed social reinforcement learning about one's own social performance in the second session. Behavioral data from these tasks were computationally modeled using Q-learning and analyzed using mixed effects models., Results: After the CBM-I intervention, participants updated their beliefs about others more slowly (P=.04; Cohen d=-0.29) but used what they learned to make more accurate decisions (P=.005; Cohen d=0.20), choosing rewarding faces more frequently. These effects were not observed among participants who did not complete the CBM-I intervention. Participants who completed the CBM-I intervention also showed less-biased updating about their social performance than participants who did not complete the CBM-I intervention, learning similarly from positive and negative feedback and from feedback on items related to poor versus good social performance. Regardless of the intervention condition, participants at session 2 versus session 1 updated their expectancies about others more from rewarding (P=.003; Cohen d=0.43) and less from punishing outcomes (P=.001; Cohen d=-0.47), and they became more accurate at learning to avoid punishing faces (P=.001; Cohen d=0.20)., Conclusions: Taken together, our results provide initial evidence that there may be some beneficial effects of both the CBM-I intervention and self-tracking of emotion regulation on social reinforcement learning in individuals who are socially anxious, although replication will be important., (©Miranda L Beltzer, Katharine E Daniel, Alexander R Daros, Bethany A Teachman. Originally published in JMIR Formative Research (https://formative.jmir.org), 09.08.2023.)

Although the vast majority of people with mental illness (PWMI) are not violent, Americans tend to think they are more dangerous than the general population. Because negative media portrayals may contribute to stigma, we used time-series analyses to examine changes in the public's perceived dangerousness of PWMI around six mass shootings whose perpetrators were reported to have a mental illness. From 2011 to 2019, 38,094 U.S. participants completed an online study assessing implicit and explicit perceived dangerousness of PWMI. There were large, upward spikes in perceived dangerousness the week of the Sandy Hook mass shooting that were relatively short-lived. However, there was not a consistent pattern of effects for other events analyzed, and any other spikes observed were smaller. Effects tended to be larger for explicit versus implicit perceived dangerousness. Sandy Hook seemed to temporarily worsen perceived dangerousness of PWMI, but this pattern was not observed for other mass shootings.

Uncertainty about the future often leads to worries about what the future will bring, which can have negative consequences for health and well-being. However, if worry can act as a motivator to promote efforts to prevent undesirable future outcomes, those negative consequences of worry may be mitigated. In this article, we apply a novel model of uncertainty, worry, and perceived control to predict psychological and physical well-being among four samples collected in China (Study 1; during the early COVID-19 outbreak in China) and the United States (Studies 2-4, during 4 weeks in May 2020, 4 weeks in November 2020, and cross-sectionally between April and November 2020). Grounded in the feeling-is-for-doing approach to emotions, we hypothesized (and found) that uncertainty about one's COVID-19 risk would predict greater worry about the virus and one's risk of contracting it, and that greater worry would in turn predict poorer well-being. We also hypothesized, and found somewhat mixed evidence, that perceptions of control over 1's COVID-19 risk moderated the relationship between worry and well-being such that worry was related to diminished well-being when people felt they lacked control over their risk for contracting the virus. This study is one of the first to demonstrate an indirect path from uncertainty to well-being via worry and to demonstrate the role of control in moderating whether uncertainty and worry manifest in poor well-being. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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. To address this concern, in Study 1, we collected linguistic data from N=35 high socially anxious participants in a variety of social contexts, finding that digital linguistic biomarkers significantly differ between evaluative vs. non-evaluative social contexts and between individuals having different trait psychological symptoms, suggesting the likely importance of personalized approaches to detect state anxiety. In Study 2, we used the same data and results from Study 1 to model a multilayer personalized machine learning pipeline to detect state anxiety that considers contextual and individual differences. This personalized model outperformed the baseline's F1-score by 28.0%. Results suggest that state anxiety can be more accurately detected with personalized machine learning approaches, and that linguistic biomarkers hold promise for identifying periods of state anxiety in an unobtrusive way.

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., Competing Interests: Conflict of interest: None to report.

Objective: This study evaluated implicit associations (i.e., associations in memory that are automatically activated and difficult to control consciously) related to trauma and one's self in the context of a clinical trial for active duty service members seeking treatment for posttraumatic stress disorder (PTSD). Previous studies with nontreatment-seeking community samples found that implicit trauma identity associations were associated with PTSD symptoms even after controlling for amount of trauma exposure and self-reported negative cognitions about the self. This study extended prior work by evaluating whether trauma-related implicit associations were associated with PTSD and depressive symptoms in a clinical sample seeking treatment for PTSD, predicted PTSD treatment response, or changed over the course of treatment., Method: This secondary analysis examined implicit trauma identity associations using data from a clinical trial evaluating a variable-length adaptation of cognitive processing therapy for military personnel. Participants were 127 active duty U.S. military personnel (13.4% women) seeking PTSD treatment. Implicit trauma identity associations were evaluated at baseline and posttreatment. Study hypotheses and data analysis plan were preregistered., Results: Contrary to predictions, baseline implicit trauma identity associations were not significantly associated with baseline PTSD or depressive symptoms and did not predict treatment response. Implicit trauma identity associations did not change significantly in response to treatment., Conclusions: More tailoring of implicit trauma measures for military personnel and/or treatment-seeking patients may be needed. The measure may lack sensitivity to change in response to treatment and have reduced utility in treatment-seeking samples with high symptom burden and less variability in symptoms. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Objectives: This study developed and pilot-tested an adaptation of Cognitive Bias Modification (CBM) to target two aspects of relational flexibility in couples: the ability to generate alternative perspectives, and the ability to respond nondefensively when alternative partner perspectives are raised within challenging relationship situations (referred to as flexibility in partner perspectives)., Methods: CBM-FlexC training materials were developed in Phase 1, and expert users (N = 4) and end-point users (N = 7) provided qualitative feedback. Feasibility and preliminary efficacy of CBM-FlexC were evaluated in Phase 2, using an online sample of distressed couples (N = 18). Using a multiple baseline design, participants completed three baseline assessments, six CBM-FlexC sessions over 2 weeks, and a 1-month follow-up., Results: CBM-FlexC training resulted in greater flexibility in partner perspectives, relationship satisfaction, and general psychological flexibility compared to baseline, and improvements were maintained 1-month after training when using mixed-effects models. However, analyses of reliable change (based on graphical inspection and the Reliable Change Index) indicated that most participants did not experience reliable improvement in flexibility in partner perspectives, or relationship satisfaction., Conclusion: This pilot study provides some positive signals regarding the potential efficacy of CBM-FlexC, while pointing to the need for further development to strengthen its effects., (© 2022 Wiley Periodicals LLC.)

Objective: Identifying digital markers of sleep disturbance-a known suicide risk factor-may aid in the detection of imminent suicide risk. This study examined sleep-related communication and texting patterns in personal text messages (N = 86,705) of suicide attempt survivors., Method: Twenty-six participants provided dates of past suicide attempts and 2-week periods of positive mood, depressed mood, or suicidal ideation. Linguistic Inquiry Word Count was used to identify sleep-related texts via a custom dictionary. Mixed effect models were fitted to test the association between suicide/mood episode type (e.g., attempt versus ideation) and three outcomes: likelihood of a text including sleep-related content, nightly count of texts sent from midnight to 5:00 AM, and sum of unique hour bins from midnight to 5:00 AM with outgoing texts., Results: Analyses with a sleep dictionary that was manually revised to be more accurate (but not the original unedited dictionary) showed sleep-related communication was more likely during depressed mood episodes than positive mood episodes. Otherwise, there were no significant differences in sleep-related communication or objective texting patterns across episode type., Conclusions: Although we did not detect differences in sleep-related communication tied to suicidal thoughts or behaviors, sleep-related communication may differ as a function of within-person mood level., (© 2022 The Authors. Suicide and Life-Threatening Behavior published by Wiley Periodicals LLC on behalf of American Association of Suicidology.)

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. A sample of 422 undergraduates reporting HD was followed from six months before until two years after graduation. Their drinking, drinking identity, and social networks were assessed online. Within-person changes in drinking identity did not mediate the relationship between within-person changes in social network drinking and personal HD, though significant positive between-person associations among all constructs were found. Instead, there was some evidence that within-person changes in drinking identity followed changes in HD, suggesting that drinking identity may function as a marker versus mechanism of "natural" HD reduction during transition out of college.

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. College students ( N  = 128; 65.6% female; 54.7% White) completed an in-person lab visit followed by a 2-week ecological momentary assessment protocol with six randomly timed survey prompts per day for up 2 weeks. At baseline, participants completed measures assessing past-week depression symptoms, social anxiety-related traits, and trait emotion dysregulation. During each randomly timed prompt, participants reported up to eight strategies used to change their thoughts or feelings, negative and positive affect, motivation to change emotions, their social context, and how well they felt they were managing their emotions. In pre-registered analyses examining the 1,423 survey responses collected, polyregulation was more likely when participants were feeling more intensely negative and when their motivation to change their emotions was stronger. Neither sex, psychopathology-related symptoms and traits, social context, nor subjective effectiveness was associated with polyregulation, and state affect did not moderate these associations. This study helps address a key gap in the literature by assessing emotion polyregulation in daily life., Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-022-00166-x., Competing Interests: Conflicts of InterestThe authors declare no competing interests., (© The Society for Affective Science 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

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.

Objective: This study examined whether variables related to unequal access to mental health resources (including Black and Latinx racial-ethnic group membership, lower education level, and lower number of community-level treatment providers, and facilities) were associated with current mental health treatment use; and, whether these variables moderated the likelihood that individuals would receive their preferred effective treatment., Methods: In a preregistered (osf.io/z28wr) study, 5626 individuals completed a mental health history form and measures of implicit and explicit beliefs about the effectiveness of therapy versus medication., Results: Individuals with more (vs. less) education were more likely to report current treatment use. Individuals who were Black/Latinx (vs. non-Latinx White) or who lived in a community with fewer (vs. more) providers sometimes had a lower probability of accessing preferred effective treatment, though results varied across implicit and explicit measures., Conclusions: Findings highlight the need to increase access to mental health resources among marginalized groups., (© 2022 Wiley Periodicals LLC.)

Introduction: Most previous studies have examined the effects of acute psychological stress in humans based on select gene panels. The genomic approach may help identify novel genes that underline biological mechanisms of acute psychological stress responses., Objective: This exploratory study aimed to investigate genome-wide transcriptional activity changes in response to acute psychological stress., Methods: The sample included 40 healthy women (mean age 31.4 ± 11.6 years). Twenty-two participants had a stress experience induced by the Trier Social Stress Test (experimental group) and 18 did not (control group). Psychological stress levels and hemodynamic changes were assessed before and after the Trier Social Stress Test. Peripheral blood samples obtained before and after the Trier Social Stress Test were processed for mRNA sequencing., Results: Psychological and hemodynamic stress parameters indicated that the Trier Social Stress Test induced moderate levels of stress in the experimental group. Six genes (HCG26, HCP5, HLA-F, HLA-F-AS1, LOC1019287, and SLC22A16) were up-regulated, and fi ve genes (CA1, FBXO9, SNCA, STRADB, and TRMT12) were down-regulated among those who experienced stress induction, compared with the control group. Nine genes of eleven were linked to endocrine system disorders, neurological disease, and organismal injury and abnormalities., Conclusions: Of the genes identifi ed in this study, HCP5, SLC22A16, and SNCA genes have previously been proposed as therapeutic targets for cancer and Parkinson disease. Further studies are needed to examine pathological mechanisms through which these genes mediate eff ects of psychological stress on adverse health outcomes. Such studies may ultimately identify therapeutic targets that enhance biological resilience to adverse eff ects of psychological stress.

Background: Social anxiety disorder is associated with distinct mobility patterns (e.g., increased time spent at home compared to non-anxious individuals), but we know little about if these patterns change following interventions. The ubiquity of GPS-enabled smartphones offers new opportunities to assess the benefits of mental health interventions beyond self-reported data., Objectives: This pre-registered study (https://osf.io/em4vn/?view_only=b97da9ef22df41189f1302870fdc9dfe) assesses the impact of a brief, online cognitive training intervention for threat interpretations using passively-collected mobile sensing data., Design: Ninety-eight participants scoring high on a measure of trait social anxiety completed five weeks of mobile phone monitoring, with 49 participants randomly assigned to receive the intervention halfway through the monitoring period., Results: The brief intervention was not reliably associated with changes to participant mobility patterns., Conclusions: Despite the lack of significant findings, this paper offers a framework within which to test future intervention effects using GPS data. We present a template for combining clinical theory and empirical GPS findings to derive testable hypotheses, outline data processing steps, and provide human-readable data processing scripts to guide future research. This manuscript illustrates how data processing steps common in engineering can be harnessed to extend our understanding of the impact of mental health interventions in daily life.

Technology-delivered interventions have the potential to help address the treatment gap in mental health care but are plagued by high attrition. Adding coaching, or minimal contact with a nonspecialist provider, may encourage engagement and decrease dropout, while remaining scalable. Coaching has been studied in interventions for various mental health conditions but has not yet been tested with anxious samples. This study describes the development of and reactions to a low-intensity coaching protocol administered to N = 282 anxious adults identified as high risk to drop out of a web-based cognitive bias modification for interpretation intervention. Undergraduate research assistants were trained as coaches and communicated with participants via phone calls and synchronous text messaging. About half of the sample never responded to coaches' attempts to schedule an initial phone call or did not answer the call, though about 30% completed the full intervention with their coach. Some anxious adults may choose technology-delivered interventions specifically for their lack of human contact and may fear talking to strangers on the phone; future recommendations include taking a more intensive user-centered design approach to creating and implementing a coaching protocol, allowing coaching support to be optional, and providing users with more information about how and why the intervention works., (Copyright © 2022. Published by Elsevier Ltd.)

Accumulated findings from studies in which implicit-bias measures correlate with discriminatory judgment and behavior have led many social scientists to conclude that implicit biases play a causal role in racial and other discrimination. In turn, that belief has promoted and sustained two lines of work to develop remedies: (a) individual treatment interventions expected to weaken or eradicate implicit biases and (b) group-administered training programs to overcome biases generally, including implicit biases. Our review of research on these two types of sought remedies finds that they lack established methods that durably diminish implicit biases and have not reproducibly reduced discriminatory consequences of implicit (or other) biases. That disappointing conclusion prompted our turn to strategies based on methods that have been successful in the domain of public health. Preventive measures are designed to disable the path from implicit biases to discriminatory outcomes. Disparity-finding methods aim to discover disparities that sometimes have obvious fixes, or that at least suggest where responsibility should reside for developing a fix. Disparity-finding methods have the advantage of being useful in remediation not only for implicit biases but also systemic biases. For both of these categories of bias, causes of discriminatory outcomes are understood as residing in large part outside the conscious awareness of individual actors. We conclude with recommendations to guide organizations that wish to deal with biases for which they have not yet found solutions.

Temporal complexity refers to qualities of a time series that are emergent, erratic, or not easily described by linear processes. Quantifying temporal complexity within a system is key to understanding the time based dynamics of said system. However, many current methods of complexity quantification are not widely used in psychological research because of their technical difficulty, computational intensity, or large number of required data samples. These requirements impede the study of complexity in many areas of psychological science. A method is presented, tangle, which overcomes these difficulties and allows for complexity quantification in relatively short time series, such as those typically obtained from psychological studies. Tangle is a measure of how dissimilar a given process is from simple periodic motion. Tangle relies on the use of a three-dimensional time delay embedding of a one-dimensional time series. This embedding is then iteratively scaled and premultiplied by a modified upshift matrix until a convergence criterion is reached. The efficacy of tangle is shown on five mathematical time series and using emotional stability, anxiety time series data obtained from 65 socially anxious participants over a 5-week period, and positive affect time series derived from a single participant who experienced a major depression episode during measurement. Simulation results show tangle is able to distinguish between different complex temporal systems in time series with as few as 50 samples. Tangle shows promise as a reliable quantification of irregular behavior of a time series. Unlike many other complexity quantification metrics, tangle is technically simple to implement and is able to uncover meaningful information about time series derived from psychological research studies. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The papers in this special issue make a compelling case for the value of digital mental health services (DMHS; including technology-based interventions, assessments, and prevention programs) to help address some of the currently unmet needs in mental health care. At the same time, the papers highlight the work that needs to be accomplished for DMHS to fulfill their promise. We review the papers' contributions in terms of (a) the imperative to increase access to evidence-informed, high-quality care, especially for underserved populations, both in the United States and globally; (b) ways to use DMHS to improve the ways that clinical care is provided to make treatment provision more effective and efficient; and (c) the current state of the research on DMHS for emotional disorders. We then consider lessons learned and recommendations to move the field forward, such as increasing (and making transparent) the research base on DMHS, adopting regulatory standards for DMHS, attending carefully to training issues for DMHS and best practices for dissemination and implementation, designing specifically for digital platforms, and being intentional about efforts to reduce disparities regarding who benefits from DMHS.

Objectives: Poor emotion regulation (ER) has been implicated in many mental illnesses, including social anxiety disorder. To work towards a scalable, low-cost intervention for improving ER, we developed a novel contextual recommender algorithm for ER strategies., Design: N = 114 socially anxious participants were prompted via a mobile app up to six times daily for five weeks to report their emotional state, use of 19 different ER strategies (or no strategy), physical location, and social context. Information from passive sensors was also collected., Methods: Given the large number of ER strategies, we used two different approaches for variable reduction: (1) grouping ER strategies into categories based on a prior meta-analysis, and (2) considering only the ten most frequently used strategies. For each approach, an algorithm that recommends strategies based on one's current context was compared with an algorithm that recommends ER strategies randomly, an algorithm that always recommends cognitive reappraisal, and the person's observed ER strategy use. Contextual bandits were used to predict the effectiveness of the strategies recommended by each policy., Results: When strategies were grouped into categories, the contextual algorithm was not the best performing policy. However, when the top ten strategies were considered individually, the contextual algorithm outperformed all other policies., Conclusions: Grouping strategies into categories may obscure differences in their contextual effectiveness. Further, using strategies tailored to context is more effective than using cognitive reappraisal indiscriminately across all contexts. Future directions include deploying the contextual recommender algorithm as part of a just-in-time intervention to assess real-world efficacy., Practitioner Points: Emotion regulation strategies vary in their effectiveness across different contexts. An algorithm that recommends emotion regulation strategies based on a person's current context may one day be used as an adjunct to treatment to help dysregulated individuals optimize their in-the-moment emotion regulation. Recommending flexible use of emotion regulation strategies across different contexts may be more effective than recommending cognitive reappraisal indiscriminately across all contexts., (© 2021 The British Psychological Society.)

Background and Objectives: Intolerance of uncertainty (IU) is an individual difference factor that reflects difficulty tolerating emotional distress in the context of uncertainty and is a robust transdiagnostic risk factor for emotional disorders. A limitation of prior research on IU is the heavy reliance on self-report measures to assess this construct. The aim of the present study was to examine the validity of a brief, computerized anagram task modified to assess IU (the PACT Anagram Task; PAT)., Methods: Participants were 221 unselected undergraduate students (71% female; M age  = 19; 89% Caucasian) who completed the PAT and a series of self-report measures of convergent, discriminant, and incremental validity, and measures of anxiety and depression symptoms online for course credit., Results: Greater PAT-Distress was positively correlated measures of convergent validity and demonstrated incremental validity in relation to self-reported IU above and beyond attentional control. None of the PAT indicators were associated with compassion or empathic concern, evidencing discriminant validity. PAT-Distress and PAT-Answers were each associated with greater worry above and beyond self-reported IU., Limitations: Study limitations include the cross-sectional design and lack of diversity in terms of sample demographics. Furthermore, we did not examine convergence between this task and other behavioral measures of IU., Conclusion: Subjective distress following completion of the PAT may serve as one indicator of IU. Further research is needed in order to replicate these results and validate the use of the PAT in clinical samples., (Copyright © 2021 Elsevier Ltd. All rights reserved.)