Jeffrey M. Girard’s research while affiliated with University of Kansas and other places

Young adults typically drink socially, yet most lab studies testing alcohol responses have administered alcohol in isolation. This is the first study to examine alcohol responses and social reward in a group setting among a young-adult at-risk sample. Heavy-drinking young adults ( N = 393; 50% female) were grouped in threes and drank a moderate dose of alcohol or a placebo beverage. These social interactions were recorded, and the duration and sequence of facial expressions, speech, and laughter were coded. Results revealed a comprehensive, multimodal, positive effect of alcohol on socioemotional experiences across self-report (e.g., increased positive affect and social bonding, greater relief of unpleasant feelings) and behavioral outcomes at both the individual (e.g., more rapid increases in Duchenne smiling) and group levels (e.g., more three-way conversations). Findings underscore the potential for group-formation paradigms to yield valuable data regarding etiological mechanisms underlying alcohol use disorder. All data and code are available ( https://osf.io/3q42z /).

Objective: Emotion measurement is central to capturing acute alcohol reinforcement and so to informing models of alcohol use disorder etiology. Yet our understanding of how alcohol impacts emotion as assessed across diverse response modalities remains incomplete. The present study leverages a social alcohol-administration paradigm to assess drinking-related emotions, aiming to elucidate impacts of intoxication on self-reported versus behaviorally expressed emotion. Method: Participants (N = 60; Mage = 22.5; 50% male; 55% White) attended two counterbalanced laboratory sessions, on one of which they were administered an alcoholic beverage (target blood alcohol content .08%) and on the other a nonalcoholic control beverage. Participants in both conditions were accurately informed of beverage contents and consumed study beverages in assigned groups of three while their behavior was videotaped. Emotion was assessed via self-report as well as continuous coding of facial muscle movements. Results: The relationship between self-reported and behaviorally expressed emotion diverged significantly across beverage conditions: positive affect: b = −0.174, t = −2.36, p = .022; negative affect, b = 0.4319, t = 2.37, p = .021. Specifically, self-reports and behavioral displays converged among sober but not intoxicated participants. Further, alcohol’s effects on positive facial displays remained significant in models controlling for self-reported positive and negative emotion, with alcohol enhancing Duchenne smiles 20% beyond effects captured via self-reports, pointing to unique effects of alcohol on behavioral indicators of positive emotion. Conclusions: Findings highlight effects of acute intoxication on the convergence and divergence of emotion measures, thus informing our understanding of measures for capturing emotions that are most proximal to drinking and thus most immediately reinforcing of alcohol consumption.

This study introduces LlaMADRS, a novel framework leveraging open-source Large Language Models (LLMs) to automate depression severity assessment using the Montgomery-Asberg Depression Rating Scale (MADRS). We employ a zero-shot prompting strategy with carefully designed cues to guide the model in interpreting and scoring transcribed clinical interviews. Our approach, tested on 236 real-world interviews from the Context-Adaptive Multimodal Informatics (CAMI) dataset, demonstrates strong correlations with clinician assessments. The Qwen 2.5--72b model achieves near-human level agreement across most MADRS items, with Intraclass Correlation Coefficients (ICC) closely approaching those between human raters. We provide a comprehensive analysis of model performance across different MADRS items, highlighting strengths and current limitations. Our findings suggest that LLMs, with appropriate prompting, can serve as efficient tools for mental health assessment, potentially increasing accessibility in resource-limited settings. However, challenges remain, particularly in assessing symptoms that rely on non-verbal cues, underscoring the need for multimodal approaches in future work.

Prevailing factor models of psychosis are centered on schizophrenia-related disorders defined by the Diagnostic and Statistical Manual of Mental Disorders and International Classification of Diseases, restricting generalizability to other clinical presentations featuring psychosis, even though affective psychoses are more common. This study aims to bridge this gap by conducting exploratory and confirmatory factor analyses, utilizing clinical ratings collected from patients with either affective or nonaffective psychoses (n = 1,042). Drawing from established clinical instruments, such as the Positive and Negative Syndrome Scale, Young Mania Rating Scale, and Montgomery-Åsberg Depression Rating Scale, a broad spectrum of core psychotic symptoms was considered for the model development. Among the candidate models considered, including correlated factors and multifactor models, a model with seven correlated factors encompassing positive symptoms, negative symptoms, depression, mania, disorganization, hostility, and anxiety was most interpretable with acceptable fit. The seven factors exhibited expected associations with external validators, were replicable through cross-validation, and were generalizable across affective and nonaffective psychoses.

Research supports the premise that greater substance use is associated with fewer sources of environmental reinforcement. However, it remains unclear whether types of environmental reinforcement (e.g., social or work) may differentially influence use. This study tested the association between types of environmental reinforcement and engagement in multiple health risk behaviors (alcohol use, binge eating, and nicotine use). Cross-sectional data were collected from a general population sample of US adults (N = 596). The Pleasant Events Schedule (PES) was used to measure sources of reinforcement. Exploratory structural equation modeling (ESEM) characterized different areas of environmental reinforcement and correlations with alcohol consumption, binge eating, and nicotine use. A four-factor structure of the PES demonstrated a conceptually cohesive model with acceptable fit and partial strict invariance. Social-related reinforcement was positively associated with alcohol consumption (β = 0.30, p < 0.001) and binge eating (β = 0.26, p < 0.001). Work/school-related reinforcement was negatively associated with binge eating (β = −0.14, p = 0.006). No areas of reinforcement were significantly associated with nicotine use (p values = 0.069 to 0.755). Social-related activities may be associated with engagement in multiple health risk behaviors (more binge eating and alcohol use), whereas work/school-related activities may be preventative against binge eating. Understanding these relationships can inform prevention efforts targeting health risk behaviors.

Prevailing factor models of psychosis are centered on schizophrenia-related disorders defined by the DSM and ICD, restricting generalizability to other clinical presentations featuring psychosis, even though affective psychoses are more common. This study aims to bridge this gap by conducting exploratory and confirmatory factor analyses, utilizing clinical ratings collected from patients with either affective or non-affective psychoses (n = 1042). Drawing from established clinical instruments, such as the Positive and Negative Syndrome Scale, Young Mania Rating Scale, and Montgomery-Åsberg Depression Rating Scale, a broad spectrum of core psychotic symptoms was considered for the model development. Among the candidate models considered, including correlated factors and multifactor models, a model with seven correlated factors encompassing positive symptoms, negative symptoms, depression, mania, disorganization, hostility, and anxiety was most interpretable with acceptable fit. The seven factors exhibited expected associations with external validators, were replicable through cross- validation, and were generalizable across affective and non-affective psychoses.