Toward a mechanistic understanding of the role of error monitoring and memory in social anxiety.

Cognitive models state that social anxiety (SA) involves biased cognitive processing that impacts what is learned and remembered within social situations, leading to the maintenance of SA. Neuroscience work links SA to enhanced error monitoring, reflected in error-related neural responses arising from mediofrontal cortex (MFC). Yet, the role of error monitoring in SA remains unclear, as it is unknown whether error monitoring can drive changes in memory, biasing what is learned or remembered about social situations. Motivated by the longer-term goal of identifying mechanisms implicated in SA, in the current study we developed and validated a novel paradigm for probing the role of error-related MFC theta oscillations (associated with error monitoring) and incidental memory biases in SA. Electroencephalography (EEG) data were collected while participants completed a novel Face-Flanker task, involving presentation of task-unrelated, trial-unique faces behind target/flanker arrows on each trial. A subsequent incidental memory assessment evaluated memory biases for error events. Severity of SA symptoms were associated with greater error-related theta synchrony over MFC, as well as between MFC and sensory cortex. Social anxiety also was positively associated with incidental memory biases for error events. Moreover, greater error-related MFC-sensory theta synchrony during the Face-Flanker predicted subsequent incidental memory biases for error events. Collectively, the results demonstrate the potential of a novel paradigm to elucidate mechanisms underlying relations between error monitoring and SA.

Future Directions in Clinical Trials and Intention-To-Treat Analysis: Fulfilling Admirable Intentions Through the Right Questions.

We call for clinical trials researchers to carefully consider questions about use of intention-to-treat (ITT) analysis and per protocol analysis. We discuss how questions about efficacy and mechanisms of efficacy are appropriately answered through the application of per protocol analysis. ITT analysis is well-suited and appropriate for addressing questions related to treatment effectiveness, typically adherence to the treatment with respect to an outcome. While guided by admirable intentions, ITT analysis is often not guided by the right questions, leading to ITT misapplication. We address additional misconceptions that often lead to ITT misapplication, including issues relating to treatment noncompletion and violation of random assignment. We further highlight future directions and implications, particularly that future clinical child and adolescent research trial designs will be increasingly characterized by hybrid trials that combine elements of efficacy, effectiveness, and implementation research, where ITT and per protocol analysis will be appropriately applied to answer the right questions.

Back to the roots of perceived burdensomeness: The potential role of perceived contribution.

BACKGROUND: The Interpersonal-Psychological Theory of Suicide (IPTS), identifies perceived burdensomeness as a critical factor in the development of suicidal ideation. Measurement of perceived burdensomeness using the INQ in research has predominantly focused on liability toward others. Recent studies have demonstrated the role of perceived contribution toward others as an aspect of perceived burdensomeness. This study proposes a hypothesized transactional model of perceived burdensomeness, in which perceived burdensomeness can be viewed as the balance between perceived contributions and perceived liability to others. METHOD: Participants (n = 1112) were college students (M age = 18.86 years, SD = 1.50) who completed survey measures. Participants were predominantly cisgender women (73.6%), heterosexual (78.8%), and white (58.3%). RESULTS: Perceived contribution was negatively associated with perceived burdensomeness, suicidal ideation, and psychological pain after controlling for perceived liability. Further, the difference between perceived contributions and perceived liability accounted for variability in suicidal ideation after controlling for INQ perceived burdensomeness. DISCUSSION: The inclusion of perceived contribution as an element of perceived burdensomeness may offer new opportunities for clinical formulation and intervention. Future research is needed to further evaluate the proposed transactional model of perceived burdensomeness.

Attention Training for Child Anxiety and Its Disorders: Moving from Research to Clinical Implementation.

Attention training is an evidence-based, computerized treatment for anxiety and its disorders rooted in cognitive neuroscience. Though experimental research and clinical trials data on attention training in children span two decades, the literature has focused on attention training's anxiety reduction effects, with little guidance on its implementation in clinical practice. Guidance on implementation is needed given recent efforts to increase accessibility of attention training in clinical practice settings. In this article, we move from research to clinical implementation, providing guidelines with pragmatic clinical steps. We include guidance on psychoeducation, setting and delivery of sessions, potential challenges, and frequently asked questions regarding implementation.

Identifying Person-Specific Drivers of Depression in Adolescents: Protocol for a Smartphone-Based Ecological Momentary Assessment and Passive Sensing Study.

BACKGROUND: Adolescence is marked by an increasing risk of depression and is an optimal window for prevention and early intervention. Personalizing interventions may be one way to maximize therapeutic benefit, especially given the marked heterogeneity in depressive presentations. However, empirical evidence that can guide personalized intervention for youth is lacking. Identifying person-specific symptom drivers during adolescence could improve outcomes by accounting for both developmental and individual differences. OBJECTIVE: This study leverages adolescents' everyday smartphone use to investigate person-specific drivers of depression and validate smartphone-based mobile sensing data against established ambulatory methods. We describe the methods of this study and provide an update on its status. After data collection is completed, we will address three specific aims: (1) identify idiographic drivers of dynamic variability in depressive symptoms, (2) test the validity of mobile sensing against ecological momentary assessment (EMA) and actigraphy for identifying these drivers, and (3) explore adolescent baseline characteristics as predictors of these drivers. METHODS: A total of 50 adolescents with elevated symptoms of depression will participate in 28 days of (1) smartphone-based EMA assessing depressive symptoms, processes, affect, and sleep; (2) mobile sensing of mobility, physical activity, sleep, natural language use in typed interpersonal communication, screen-on time, and call frequency and duration using the Effortless Assessment of Risk States smartphone app; and (3) wrist actigraphy of physical activity and sleep. Adolescents and caregivers will complete developmental and clinical measures at baseline, as well as user feedback interviews at follow-up. Idiographic, within-subject networks of EMA symptoms will be modeled to identify each adolescent's person-specific drivers of depression. Correlations among EMA, mobile sensor, and actigraph measures of sleep, physical, and social activity will be used to assess the validity of mobile sensing for identifying person-specific drivers. Data-driven analyses of mobile sensor variables predicting core depressive symptoms (self-reported mood and anhedonia) will also be used to assess the validity of mobile sensing for identifying drivers. Finally, between-subject baseline characteristics will be explored as predictors of person-specific drivers. RESULTS: As of October 2023, 84 families were screened as eligible, of whom 70% (n=59) provided informed consent and 46% (n=39) met all inclusion criteria after completing baseline assessment. Of the 39 included families, 85% (n=33) completed the 28-day smartphone and actigraph data collection period and follow-up study visit. CONCLUSIONS: This study leverages depressed adolescents' everyday smartphone use to identify person-specific drivers of adolescent depression and to assess the validity of mobile sensing for identifying these drivers. The findings are expected to offer novel insights into the structure and dynamics of depressive symptomatology during a sensitive period of development and to inform future development of a scalable, low-burden smartphone-based tool that can guide personalized treatment decisions for depressed adolescents. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/43931.

Towards implementation of cognitive bias modification in mental health care: State of the science, best practices, and ways forward.

Cognitive bias modification (CBM) has evolved from an experimental method testing cognitive mechanisms of psychopathology to a promising tool for accessible digital mental health care. While we are still discovering the conditions under which clinically relevant effects occur, the dire need for accessible, effective, and low-cost mental health tools underscores the need for implementation where such tools are available. Providing our expert opinion as Association for Cognitive Bias Modification members, we first discuss the readiness of different CBM approaches for clinical implementation, then discuss key considerations with regard to implementation. Evidence is robust for approach bias modification as an adjunctive intervention for alcohol use disorders and interpretation bias modification as a stand-alone intervention for anxiety disorders. Theoretical predictions regarding the mechanisms by which bias and symptom change occur await further testing. We propose that CBM interventions with demonstrated efficacy should be provided to the targeted populations. To facilitate this, we set a research agenda based on implementation frameworks, which includes feasibility and acceptability testing, co-creation with end-users, and collaboration with industry partners.