Publications

Abstract Marketers across a variety of contexts have increasingly turned to social media influencers (SMIs) to take advantage of their robust social networks to promote products and services. While research has focused on the perceived social relationship between SMIs and their followers, little attention has been given to the influence of social engagement cues, such […]

Abstract The experimental study examined automatic and volitional attention processes as function of social comparison priming (directional: upward differences, downward differences, similarities; and non-directional control) and the valence of information (i.e., positive vs. negative feature) about an unfamiliar person. A total of 209 individuals, including those clinically depressed and without the diagnosis, were exposed to […]

The underlying factors governing why pedestrians interact with pedestrian signals and pushbuttons the way they do can inform design guidance and modifications which encourage pedestrians to use infrastructure more safely and efficiently. Therefore, a recruited participant experiment using eye tracking technology was performed to explore pedestrian signal compliance and pushbutton use. A total of 48 […]

BACKGROUND AND OBJECTIVES: Managing substance use disorders (SUDs) is limited by the lack of longitudinal clinical data during active use and recovery. Wearable devices may help address this gap by capturing physiological and behavioral data in real-world settings. This review evaluated the feasibility and acceptability of wearable devices among individuals with SUDs. METHODS: A systematic […]

Technostress is the mental strain experienced when digital technologies feel demanding or difficult to manage. Despite growing interest in technostress research, existingdatasets provide limited biometric emotional data from code-mediated activities. Thisarticle presents TIDE, a novel multimodal biometric dataset designed to supporttechnostress research during IDE-based programming. TIDE captures facial expressionbased emotional responses, gaze coordinates, programming phases, […]

Depression, as a mental health condition, often manifests through diverse verbal, non-verbal, and behavioral signals. Early and accurate detection of these indicators is critical to ensuring timely and effective intervention. This work introduces a multimodal Integrated AI framework for depression detection that uses: audio, visual, and textual data to improve classification performance. The proposed framework […]

Abstract We present an information-theoretic framework for identifying which physiological and eye-gaze-based indicators, and at what temporal scales, are most informative of cognition-related reliance behavior during conditionally automated (SAE Level 3) driving. We analyze data collected from an in-person driving simulator study in which participants interact with a conditionally automated vehicle in a single continuous […]

Abstract This study examined whether AI-powered chatbot-based training was associated with changes in university students’ Facial and Vocal Emotional Reaction Time Proportions during simulated job interviews. A one-group pretest–posttest design was conducted with 54 third- and fourth-year students enrolled in a Human Talent Management course at a private Latin American university. This study was implemented […]

Abstract This study examined whether AI-powered chatbot-based training was associated with changes in university students’ Facial and Vocal Emotional Reaction Time Proportions during simulated job interviews. A one-group pretest–posttest design was conducted with 54 third- and fourth-year students enrolled in a Human Talent Management course at a private Latin American university. This study was implemented […]

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by challenges in communication, social interaction, and behavioral patterns. While early diagnosis remains crucial, there is a critical need for effective screening methods for school-age children, as many cases with nuanced presentations often go undetected during early childhood. This research presents a facial morphology-based computational […]