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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.

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.)

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).

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.)

Implicit cognitive processing is theorized to have a central role in many forms of psychopathology. In the current review, we focus on implicit associations, by which we mean evaluative representations in memory that are difficult to control and do not require conscious reflection to influence affect, cognition, or behavior. We consider definitional and measurement challenges before examining recent empirical evidence for these associations in anxiety, obsessive-compulsive, posttraumatic stress, depressive, and alcohol use disorders. This examination is framed by a brief review of the ways that prominent models of psychopathology represent biased implicit processing of disorder-relevant information. We consider to what extent models reflect more traditional automatic/implicit versus strategic/explicit dual-process perspectives or reflect more recent dynamical systems perspectives in which mental representations are iteratively reprocessed, evolving continuously. Finally, we consider the future research needed to better understand the interactive and temporal dynamics of implicit cognition in psychopathology.

Few replicable genetic variants have been identified in the etiology of heritable anxiety disorders such as panic disorder. Endophenotypic measures that have reduced heterogeneity may provide more powerful targets for gene identification. We assessed hypersensitivity to carbon dioxide (a reliable endophenotype of panic and anxiety) in 174 Caucasian college students, who were genotyped on 26 polymorphic markers from 11 genes previously associated with panic/anxiety. Individual trajectories of respiratory and subjective anxiety response to carbon dioxide were measured and tested for association with these genetic markers. One marker in the acid-sensing ion channel 1 (ASIC1) gene, rs1108923, had a significant association with respiratory rate. No genes had a significant association with subjective anxiety response. Our findings support previously reported associations between ASIC1 and panic/anxiety, but not other genes previously associated with anxiety disorders. The use of endophenotypic markers is a promising avenue for gene identification in anxiety and other complex disorders., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Social anxiety is the most prevalent anxiety disorder of late adolescence, yet current treatments reach only a minority of youth with the disorder. Effective and easy-to-disseminate treatments are needed. This study pilot tested the efficacy of a novel, online cognitive bias modification for interpretation (CBM-I) intervention for socially anxious youth and their parents. The CBM-I intervention targeted cognitive biases associated with early adolescents' maladaptive beliefs regarding social situations, and with parents' intrusive behavior, both of which have been theoretically linked with the maintenance of social anxiety in youth. To investigate the efficacy of intervening with parents and/or children, clinically diagnosed early adolescents (ages 10-15; N=18) and their mothers were randomly assigned to one of three conditions: the first targeted early adolescents' cognitive biases related to social anxiety (Child-only condition); the second targeted parents' biases associated with intrusive behavior (Parent-only condition); and the third targeted both youth and parents' biases in tandem (Combo condition). The use of a multiple baseline design allowed for the efficient assessment of causal links between the intervention and reduction in social anxiety symptoms in youth. Results provided converging evidence indicating modest support for the efficacy of CBM-I, with no reliable differences across conditions. Taken together, results suggest that online CBM-I with anxious youth and/or their parents holds promise as an effective and easily administered component of treatment for child social anxiety that deserves further evaluation in a larger trial., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

In this paper we examine the nature of automatic cognitive processing in anxiety disorders and Major Depressive Disorder (MDD). Rather than viewing automaticity as a unitary construct, we follow a social cognition perspective (Bargh, 1994) that argues for four theoretically independent features of automaticity: unconscious (processing of emotional stimuli occurs outside awareness), efficient (processing emotional meaning uses minimal attentional resources), unintentional (no goal is needed to engage in processing emotional meaning), and uncontrollable (limited ability to avoid, alter or terminate processing emotional stimuli). Our review of the literature suggests that most anxiety disorders are characterized by uncontrollable, and likely also unconscious and unintentional, biased processing of threat-relevant information. In contrast, MDD is most clearly typified by uncontrollable, but not unconscious or unintentional, processing of negative information. For the anxiety disorders and for MDD, there is no sufficient evidence to draw firm conclusions about efficiency of processing, though early indications are that neither anxiety disorders nor MDD are characterized by this feature. Clinical and theoretical implications of these findings are discussed and directions for future research are offered. In particular, it is clear that paradigms that more directly delineate the different features of automaticity are required to gain a more comprehensive and systematic understanding of the importance of automatic processing in emotion dysregulation., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Negative affect measures were evaluated in a cross-sectional community sample of adults aged 18-93 (N = 335) to examine the structure of neuroticism, anxiety, and depressive symptoms in young, middle, and older adult cohorts. Structural equation modeling was used to contrast 3 nested models: a 1-factor general distress model; a 2-factor high negative-low positive affect model; and a 3-factor "tripartite model" reflecting a higher order Negative Affect factor that is common to depression and anxiety problems and 2 lower order factors, Low Positive Affect (mostly specific to depression) and Arousal (specific to anxiety/panic). As expected, the tripartite model fit best for all age groups. Further, multigroup analyses indicated age invariance for the tripartite model, suggesting the model can be effectively applied with older populations., (((c) 2007 APA, all rights reserved).)

Current treatments for disorders of emotion, such as pathological anxiety, are often less effective in older adults than in younger adults and have poorly understood mechanisms, pointing to the need for psychopathology models that better account for age-related changes in normative emotional functioning and the expression of disordered emotion. This article describes ways in which the healthy aging and emotion literature can enhance understanding and treatment of symptoms of anxiety and depression in later life. We offer recommendations on how to integrate the theories and findings of healthy aging literature with psychopathology research and clinical practice and highlight opportunities for future research.

Objective: Cognitive models of panic disorder suggest that change in catastrophic misinterpretations of bodily sensations will predict symptom reduction. To examine change processes, we used a repeated measures design to evaluate whether the trajectory of change in misinterpretations over the course of 12-week cognitive behavior therapy is related to the trajectory of change in a variety of panic-relevant outcomes. Method: Participants had a primary diagnosis of panic disorder (N = 43; 70% female; mean age = 40.14 years). Race or ethnicity was reported as 91% Caucasian, 5% African American, 2.3% biracial, and 2.3% "other." Change in catastrophic misinterpretations (assessed with the Brief Body Sensations Interpretation Questionnaire; Clark et al., 1997) was used to predict a variety of treatment outcomes, including overall panic symptom severity (assessed with the Panic Disorder Severity Scale [PDSS]; Shear et al., 1997), panic attack frequency (assessed with the relevant PDSS item), panic-related distress/apprehension (assessed by a latent factor, including peak anxiety in response to a panic-relevant stressor--a straw breathing task), and avoidance (assessed by a latent factor, which included the Fear Questionnaire-Agoraphobic Avoidance subscale; Marks & Mathews, 1979). Results: Bivariate latent difference score modeling indicated that, as expected, change in catastrophic misinterpretations predicted subsequent reductions in overall symptom severity, panic attack frequency, distress/apprehension, and avoidance behavior. However, change in the various symptom domains was not typically a significant predictor of later interpretation change (except for the distress/apprehension factor). Conclusions: These results provide considerable support for the cognitive model of panic and speak to the temporal sequence of change processes during therapy. (Contains 5 footnotes, 1 table and 1 figure.)

Depersonalization is common in anxiety disorders, but little is known about factors that influence co-occurring anxiety and depersonalization. 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. 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. 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. 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. [ABSTRACT FROM AUTHOR]

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. This pre-registered study () assesses the impact of a brief, online cognitive training intervention for threat interpretations using passively-collected mobile sensing data. 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. The brief intervention was not reliably associated with changes to participant mobility patterns. 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. [ABSTRACT FROM AUTHOR]

The tendency for individuals to interpret ambiguous information in a threatening way is theorised to maintain anxiety disorders. Recent findings suggest that positive and negative interpretation biases may have unique effects. This study tested the relationships between threat and benign biases with state and trait anxiety and quality of life, and whether individual differences moderate these relationships. N = 699 individuals with elevated trait anxiety symptoms completed web-based measures of interpretation bias, trait anxiety, state anxiety, and quality of life. Results demonstrated that threat interpretations predicted state anxiety, trait anxiety, and quality of life. Benign interpretations also predicted quality of life. However, benign interpretations only weakly (or not at all) predicted state and trait anxiety. Individual differences (e.g. gender, race, ethnicity, age) did not moderate findings. Results emphasise the need to consider benign and threat biases separately, both in cognitive models of anxiety and experimental designs. [ABSTRACT FROM AUTHOR]

Background: Effective emotion regulation (ER) is important to long-term healthy functioning, but little is known about what constitutes effective ER in the moment or how social anxiety symptoms and different strategies influence short-term effectiveness outcomes.Methods: Intensive ecological momentary data from N = 124 college students illustrate how different ways of operationalizing ER effectiveness leads to different conclusions about the short-term effectiveness of different strategies in daily life.Results: When effectiveness is operationalized as the degree to which participants judged that their ER attempts made them feel better, social anxiety severity was negatively associated with effectiveness, and avoidance-oriented strategies were judged to be less effective than engagement-oriented strategies. In contrast, when effectiveness is operationalized as the degree of change in self-reported affect following ER attempts, social anxiety severity was not related to effectiveness, and avoidance-oriented strategies were more effective than engagement-oriented strategies. Social anxiety and ER strategy type did not interact in either model, regardless of how effectiveness was measured.Conclusions: The study highlights discrepancies when examining two common but distinct ways of measuring the same overarching effectiveness construct, and raises intriguing questions about how forms of psychopathology that are intimately tied to emotion dysregulation, like social anxiety, moderate different ways of measuring the effectiveness of ER attempts. [ABSTRACT FROM AUTHOR]

Socially anxious individuals exhibit cognitive performance impairments; it is unclear whether this is due to trait differences in abilities or effects of the experimental context. This study sought to determine how social context, individual differences in fear of negative evaluation (FNE), and task difficulty interact to influence working memory performance as indicated by effectiveness (accuracy) and efficiency (reaction times). Participants (N = 61) performed the n-back task at 2-back and 3-back difficulty levels under three conditions: alone ("Anonymous"), in presence of a non-evaluative experimenter ("Presence"), and under explicit performance evaluation by the experimenter ("Threat"). Overall, participants showed improved accuracy during Threat, but only on 2-back trials. FNE was positively associated with longer reaction times during Threat on 3-back trials. FNE did not relate to accuracy, suggesting that threat-related impairments tied to social anxiety may alter efficiency rather than effectiveness. Thus, social anxiety may elicit cognitive performance impairments even in minimally evaluative environments. [ABSTRACT FROM AUTHOR]

This case features an adult male with moderate social anxiety disorder and mild depressive symptoms who showed an initial positive response to an earlier experience of cognitive behavior therapy, but then relapsed when he started avoiding social situations again because of continuing beliefs that experiencing anxiety was unacceptable. His treatment at our clinic focused on shifting unhelpful thinking about the likelihood and consequences of becoming anxious and reengaging in avoided social situations so he could learn to tolerate negative affect and uncertainty. The treatment approach draws from cognitive behavioral models of social anxiety and highlights advances in clinical science, especially recent work on the causal role of interpretation biases (the tendency to assign negative or threatening meaning to ambiguous situations) in the maintenance and reduction of anxiety. [ABSTRACT FROM AUTHOR]

Little is known about how to predict which individuals with known temperament vulnerabilities will go on to develop social anxiety problems. Adolescents (N = 185) were followed from age 13 to 18 to evaluate psychosocial, prospective predictors of social anxiety symptoms and fears of negative evaluation (FNE), after accounting for pre-existing social withdrawal symptoms. Results from structural equation modeling suggest that lack of perceived social acceptance predicts subsequent explicit social anxiety and FNE, whereas the emotional intensity of close peer interactions predicts subsequent implicit FNE. Results are discussed in terms of the importance of peer interaction in the development of social anxiety, and the value of measuring both implicit and explicit FNE. [ABSTRACT FROM AUTHOR]

Abstract: To examine the causal relationship between cognitive biases and anxiety, a bias modification paradigm was used to reduce negative interpretation biases in participants with high anxiety sensitivity (AS). Participants (N =75) were assigned to a Positive training condition or to one of two Control conditions (Neutral or No training). During training, participants imagined themselves in ambiguous scenarios related to AS. Positive training required participants to resolve the scenarios’ ambiguity positively and was hypothesized to result in more positive and less negative subsequent interpretations related to AS, fewer self-reported AS symptoms, and less emotional vulnerability on AS stressors (compared to the Control conditions). As expected, Positive training shifted interpretations of novel scenarios and self-reported AS symptoms in the anticipated direction. Evidence was mixed for the effect of Positive training on emotional vulnerability (small effect for less fear, but not for avoidance). Findings support the causal premise underlying cognitive models of anxiety. [Copyright &y& Elsevier]

Abstract: Body dysmorphic disorder (BDD) is characterized by imagined or slight defects in one''s appearance. We evaluated implicit and explicit biases among individuals diagnosed with BDD (n =21), individuals with subclinical BDD symptoms (n =21), and healthy control participants (n =21). Specifically, we used the Implicit Association Test [IAT; Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: the implicit association test. Journal of Personality and Social Psychology, 74, 1464–1480] to examine automatic associations related to self-esteem, associations between attractive and important, and a physical attractiveness stereotype (associations between attractive and competent). BDD participants had significantly lower implicit self-esteem, relative to control participants, and the subclinical BDD participants were intermediate between these groups. Although no group differences were observed on the implicit Attractive Important IAT; as predicted, BDD participants had significantly stronger implicit associations between attractive and competent than the other groups, in line with a common stereotype about physical attractiveness. Both the Attractive Competent IAT and Self-Esteem IAT were significant predictors of BDD symptom severity, and distress and avoidance during a mirror exposure task. Findings are discussed in light of cognitive-behavioral models of BDD. [Copyright &y& Elsevier]

To evaluate a causal relationship between biased information processing and fear responding, as posited by many cognitive models of anxiety disorders, spider-relevant interpretations were trained to be non-threatening in an analog phobic sample. Participants high in spider fear ( N = 61) were randomly assigned to a ‘Positive training’ condition, or to a ‘Neutral training’ or ‘No training’ control condition. ‘Positive training’ involved learning to ascribe non-threatening meanings to emotionally ambiguous scenarios. Results suggested this training was successful at inducing interpretation biases to be non-threatening, as indicated by faster responses to positive (versus negative) word fragments, as well as more positive and less negative interpretations of novel scenarios (relative to control conditions). Notwithstanding, the impact of training on subsequent avoidance and fear when presented with a live spider was minimal. No differences across training conditions were found; however, faster responding to positive word fragments predicted less avoidance and fear for participants receiving ‘Positive training’. [ABSTRACT FROM AUTHOR]

There is inconsistent evidence for memory biases in anxiety disorders, perhaps because memory biases require activation of the relevant fear schema to be observable. Cognitive theories predict this will occur when exposure to the feared stimulus is combined with semantic and affective activation. The current study examined the impact of priming (having a live spider present) on explicit memory among individuals who were low ( N = 53) or high ( N = 51) in spider fear. As predicted, only participants who were both high in spider fear and primed (spider present) exhibited preferential recall of spider words (but not of other words). Findings are discussed in terms of how priming may enhance the expression of information processing biases among vulnerable individuals. [ABSTRACT FROM AUTHOR]

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. • Cognitive bias modification for interpretation (CBM-I) was superior to psychoeducation at reducing anxiety symptoms (on our primary measure) among adults with moderate-to-severe anxiety. • CBM-I was also superior to psychoeducation at increasing flexible interpretations of ambiguity. • Individuals higher (vs. lower) in baseline anxiety about COVID-19 anxiety may especially benefit from CBM-I as an anxiety-reduction tool. [ABSTRACT FROM AUTHOR]

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. 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. 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. 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. Socially anxious individuals may be less accurate at learning to avoid social punishment, which may maintain negative beliefs through an interpersonal stress generation process. • Participants completed a social probabilistic selection task with emotional faces. • Social reinforcement learning was modeled with Q-learning. • Learning rates were not different for participants high vs. low in social anxiety. • High (vs. low) social anxiety Ps were less accurate at avoiding angry faces. • This learning bias may contribute to maintenance of negative social beliefs. [ABSTRACT FROM AUTHOR]