Multimodal Remote Research on Social Anxiety Using a New Teleconferencing Paradigm

Background

Social anxiety is a prevalent mental health concern. Models of social anxiety incorporate multifaceted components from cognitive appraisals to attention as factors maintaining the disorder. Multimodal research investigating multiple facets of social anxiety simultaneously offers an important avenue to advance our understanding of the disorder.

Methods

The current study tested a novel, internet-based simulated teleconferencing interaction social stressor challenge and included the collection of self-report, eye-tracking, and auditory vocal data during the challenge. Participants (N = 262) completed two interactions. The pre-recorded male and female audience members (assigned to display interest or uninterest) discussed a topic and then prompted the participant to speak on that topic.

Results

Fidelity indices revealed that most participants rated the interactions with the simulated audience as realistic; reported heightened subjective distress during the simulated teleconferencing interactions; and correctly rated audience members' level of interest. As predicted, social anxiety predicted participants' subjective distress during the simulated teleconferencing interactions. Findings from audio vocal and eye tracking analyses largely corresponded to prior research - indicating that social anxiety influences audio vocal responses and patterns of attention during social stressors.

Conclusions

Taken together, these findings suggest that the simulated teleconferencing interaction framework introduced here offers a potentially useful approach for the remote investigation of mechanisms underpinning social anxiety.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10608-023-10371-y.

Assessing the dominance behavioral system in early childhood using observational methods

BACKGROUND

The dominance behavioral system (DBS) is a biologically based system that underpins individual differences in motivation for dominance and power. However, little is known about the DBS in childhood. In order to make strong claims about the DBS's trait-like properties and predictive validity, a clearer understanding of its early development is required.

PARTICIPANTS AND PROCEDURE

In a pilot study aimed at developing a behavioral coding system for dominance, a key facet of the DBS, we collected and coded observational data from 58 children, assessed at ages 3 and 5-6. These data were examined in conjunction with measures of child temperament via observational measures, and symptoms of psychopathology.

RESULTS

Dominance was moderately stable in early childhood to a degree comparable to other early child temperament traits. Consistent with the study hypotheses, boys were more dominant than girls, and dominance was negatively associated with children's behavioral inhibition, effortful control, and internalizing symptoms.

CONCLUSIONS

These results provide initial support for the validity and developmental sensitivity of an objective coding system for assessing facets of the DBS in early childhood. Ultimately, the use of this coding system will facilitate future studies of how early DBS predicts psychological adjustment later in life.

The scarring impact of status loss in social anxiety: An evolutionary perspective

Evolutionary models suggest that social anxiety (SA) is associated with sensitivity to status loss. These models make several additional predictions concerning the strength as well as the specificity of the association between post-event distress (PED) following status losses and SA. First, the strength of this association is postulated to be enhanced in men, especially following status losses inflicted by other men (intra-male status losses). Second, given the evolutionary postulated relationship between social status and physical fitness, sensitivity to status loss in SA is expected to extend to physically threatening events. We examined these predictions in four online samples (total N = 1123; 59% females, 27% above the cutoff for clinically elevated SA). In all studies, participants recalled social status-loss events and rated the emotional and distressing impact of these experiences. In two samples, participants also identified and recalled physically threatening events. Our findings were consistent with evolutionary predictions. SA was associated with PED following social status-loss events (β = 0.27). This association was stronger in men than in women (β = 0.40, β = 0.16, respectively). Moreover, the SA-PED association was especially enhanced following intra-male, compared to intra-female and inter-gender, status losses (β = 0.47, β = 0.26, and β = 0.17, respectively). Furthermore, SA was uniquely associated with PED following physically threatening events, over and above PED following social status-loss events (β = 0.21). Our data highlights the significant impact of socially and physically threatening events and delineates the scarring signature of such events in SA.

Evaluating the Feasibility and Acceptability of an Artificial-Intelligence-Enabled and Speech-Based Distress Screening Mobile App for Adolescents and Young Adults Diagnosed with Cancer: A Study Protocol

Simple Summary

Adolescent and young adult (AYA) patients diagnosed with cancer are at a higher risk of psychological distress, which requires regular monitoring throughout their cancer journeys. Paper-and-pencil or digital surveys for psychological stress are often cumbersome to complete during a patient’s visit, and many patients find completing the same survey multiple times repetitive and boring. Recent advances in mobile technology and speech science have enabled flexible and engaging ways of monitoring psychological distress. This paper describes the scientific process we will use to evaluate an artificial intelligence (AI)-enabled mobile app to monitor depression and anxiety among AYAs diagnosed with cancer.

Abstract

Adolescents and young adults (AYAs) diagnosed with cancer are an age-defined population, with studies reporting up to 45% of the population experiencing psychological distress. Although it is essential to screen and monitor for psychological distress throughout AYAs’ cancer journeys, many cancer centers fail to effectively implement distress screening protocols largely due to busy clinical workflow and survey fatigue. Recent advances in mobile technology and speech science have enabled flexible and engaging methods to monitor psychological distress. However, patient-centered research focusing on these methods’ feasibility and acceptability remains lacking. Therefore, in this project, we aim to evaluate the feasibility and acceptability of an artificial intelligence (AI)-enabled and speech-based mobile application to monitor psychological distress among AYAs diagnosed with cancer. We use a single-arm prospective cohort design with a stratified sampling strategy. We aim to recruit 60 AYAs diagnosed with cancer and to monitor their psychological distress using an AI-enabled speech-based distress monitoring tool over a 6 month period. The primary feasibility endpoint of this study is defined by the number of participants completing four out of six monthly distress assessments, and the acceptability endpoint is defined both quantitatively using the acceptability of intervention measure and qualitatively using semi-structured interviews.

Measuring neuropsychiatric symptoms in patients with early cognitive decline using speech analysis

BACKGROUND

Certain neuropsychiatric symptoms (NPS), namely apathy, depression, and anxiety demonstrated great value in predicting dementia progression, representing eventually an opportunity window for timely diagnosis and treatment. However, sensitive and objective markers of these symptoms are still missing. Therefore, the present study aims to investigate the association between automatically extracted speech features and NPS in patients with mild neurocognitive disorders.

METHODS

Speech of 141 patients aged 65 or older with neurocognitive disorder was recorded while performing two short narrative speech tasks. NPS were assessed by the neuropsychiatric inventory. Paralinguistic markers relating to prosodic, formant, source, and temporal qualities of speech were automatically extracted, correlated with NPS. Machine learning experiments were carried out to validate the diagnostic power of extracted markers.

RESULTS

Different speech variables are associated with specific NPS; apathy correlates with temporal aspects, and anxiety with voice quality-and this was mostly consistent between male and female after correction for cognitive impairment. Machine learning regressors are able to extract information from speech features and perform above baseline in predicting anxiety, apathy, and depression scores.

CONCLUSIONS

Different NPS seem to be characterized by distinct speech features, which are easily extractable automatically from short vocal tasks. These findings support the use of speech analysis for detecting subtypes of NPS in patients with cognitive impairment. This could have great implications for the design of future clinical trials as this cost-effective method could allow more continuous and even remote monitoring of symptoms.

Social dominance and multiple dimensions of psychopathology: An experimental test of reactivity to leadership and subordinate roles

Background

Theory and research suggest that social dominance is important for multiple forms of psychopathology, and yet few studies have considered multiple dimensions of psychopathology simultaneously, and relatively few have used well-validated behavioral indices.

Method

Among 81 undergraduates, we used a well-validated experimental approach of assigning participants to a leadership or subordinate position, and we examined how self-rated severity of depression, social anxiety, manic tendencies, and psychopathy relate to psychophysiological and affective reactivity to this role.

Results

Consistent with hypotheses, manic symptoms related to more discomfort in the subordinate role compared to the leadership role, as evidenced by more decline in positive affect, more discomfort, and a larger RSA decline, while depression symptoms related to a more positive response to the subordinate role than the leadership role, including more positive affect and more comfort in the assigned role. Social anxiety was related to discomfort regardless of the assigned role, and those with higher psychopathy symptoms did not show differential response to assigned roles.

Limitations

Findings are limited by the mild symptom levels and absence of hormonal data.

Conclusions

Findings provide novel transdiagnostic evidence for the importance of social dominance to differentiate diverse forms of psychopathology.

Automated assessment of psychiatric disorders using speech: A systematic review

OBJECTIVE

There are many barriers to accessing mental health assessments including cost and stigma. Even when individuals receive professional care, assessments are intermittent and may be limited partly due to the episodic nature of psychiatric symptoms. Therefore, machine-learning technology using speech samples obtained in the clinic or remotely could one day be a biomarker to improve diagnosis and treatment. To date, reviews have only focused on using acoustic features from speech to detect depression and schizophrenia. Here, we present the first systematic review of studies using speech for automated assessments across a broader range of psychiatric disorders.

METHODS

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We included studies from the last 10 years using speech to identify the presence or severity of disorders within the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). For each study, we describe sample size, clinical evaluation method, speech-eliciting tasks, machine learning methodology, performance, and other relevant findings.

RESULTS

1395 studies were screened of which 127 studies met the inclusion criteria. The majority of studies were on depression, schizophrenia, and bipolar disorder, and the remaining on post-traumatic stress disorder, anxiety disorders, and eating disorders. 63% of studies built machine learning predictive models, and the remaining 37% performed null-hypothesis testing only. We provide an online database with our search results and synthesize how acoustic features appear in each disorder.

CONCLUSION

Speech processing technology could aid mental health assessments, but there are many obstacles to overcome, especially the need for comprehensive transdiagnostic and longitudinal studies. Given the diverse types of data sets, feature extraction, computational methodologies, and evaluation criteria, we provide guidelines for both acquiring data and building machine learning models with a focus on testing hypotheses, open science, reproducibility, and generalizability.

LEVEL OF EVIDENCE

3a.

Social anxiety and sensitivity to social-rank features in male faces

BACKGROUND AND OBJECTIVES

Evolutionary theories propose that socially anxious individuals are especially sensitive to social-rank signals, presumably at the expense of the attunement to signals of affiliation. Despite this theoretical claim, few empirical attempts examined the association between social anxiety (SA) and sensitivity to specific features of social-rank and affiliation. This study aims to fill this gap.

METHOD

Participants (N = 67) completed two tasks in which two emotionally neutral computer-generated male faces of the same character were presented side-by-side. In the Social-Rank-Sensitivity Task, the faces within each pair differed in their level of dominance and, in the Affiliation-Sensitivity Task, the faces differed in their level of trustworthiness. The participants' task was to decide which of the two faces looked more dominant or friendly.

RESULTS

There were no differences in accuracy between high- and low-SA participants in the Affiliation-Sensitivity Task. In contrast, high-SA participants were more accurate than low-SA participants in the Social-Rank-Sensitivity Task. No group differences were found in decision latencies in either task.

LIMITATIONS

Limitations of the study are that a non-clinical sample was used and that only computer-generated male faces were considered.

CONCLUSIONS

Our findings suggest that SA is related to an enhanced ability to discriminate faces based on social-rank features. Examining sensitivity to facial cues signaling social-rank and affiliation may help to specify the nature of social threat sensitivity in SA.

"Fear guides the eyes of the beholder": Assessing gaze avoidance in social anxiety disorder via covert eye tracking of dynamic social stimuli

Gaze avoidance is an important feature of social anxiety disorder (SAD) and may serve as a biobehavioral marker of SAD. The purpose of the present study was to replicate and extend findings on gaze avoidance in SAD via eye tracking during a computerized social simulation. Patients with SAD (n = 27) and a (sub)sample of demographically-matched healthy controls (HC; n = 22) completed a computerized, dynamic social simulation task involving video clips of actors giving positive and negative social feedback to the participant. All participants were unknowingly eye tracked during the simulation, and post-study consent was obtained to examine responses. Consistent with the bivalent fear of evaluation (BFOE) model of social anxiety, fear of positive evaluation related systematically to state anxiety in response to positive social feedback, and fear of negative evaluation related systematically to state anxiety in response to negative social feedback. Moreover, compared to HCs, SAD patients exhibited significantly greater global gaze avoidance in response to both the positive and negative video clips. Our results provide strong additional support for gaze avoidance as a biobehavioral marker of SAD, as well as additional support for the BFOE model. Implications for the assessment and treatment of SAD are discussed.