11 citations · 14 across the 11 of their papers we have counts for
13 papers
AI-Assisted Submissions in Online Research Are Rare and Highly Concentrated but Routinely Approved
Neil K. R. Sehgal, Manuel Tonneau, Dunigan Folk +2
Online research platforms underpin much of what science claims about people, on the assumption that a human produced each response. Generative AI threatens that assumption by letti…
"We Are Tired of Explaining": Communication Practice and AI Roleplay Training for Community Health Workers in Rural India
Neil K. R. Sehgal, Sunny Rai, Sai Preethi Matam +4
Community health workers (CHWs) in the Global South increasingly encounter AI-powered tools, yet the counseling work central to their role remains largely unsupported. We study com…
LLMs Mirror Country-Specific Gender Patterns If Asked, but Skew Male When Generating Media in Local Languages
Sharif Kazemi, Tanya Popli, Neil K. R. Sehgal +7
Large language models (LLMs) are increasingly used to generate media, but whether their content perpetuates gender stereotypes is unknown: standard benchmarks rely on selection-bas…
Predictors of Loneliness in Older Adults Using Multimodal Analysis of Speech and Language
Vinmay Khandode, Sai Karthik Kosuri, Neil K. R. Sehgal +6
Loneliness is a critical public health issue among older adults, linked to higher risks of depression, cognitive decline, and mortality. Scalable, objective methods for its detecti…
Depression Symptoms and Relational Patterns in 187k ChatGPT Histories
Neil K. R. Sehgal, Dunigan Folk, Lyle Ungar +1
Large language models are increasingly used as private, always-available conversational systems, but little is known about how people with depressive symptoms use them. Building on…
Self-Reported Side Effects of Semaglutide and Tirzepatide in Online Communities
Neil K. R. Sehgal, Jena Shaw Tronieri, Lyle Ungar +1
Social media can reveal patient experiences with glucagon-like peptide-1 receptor agonists (GLP-1 RAs) that extend beyond clinical trial data. We analyzed 410,198 Reddit posts (May…
Real-Time Deadlines Reveal Fragile Temporal Adaptation in LLM Strategic Dialogues
Neil K. R. Sehgal, Sharath Chandra Guntuku, Lyle Ungar
Large Language Models (LLMs) generate text token-by-token in discrete time, yet real-world communication, from therapy sessions to business negotiations, critically depends on cont…
Designing Mental-Health Chatbots for Indian Adolescents: Mixed-Methods Evidence, a Boundary-Object Lens, and a Design-Tensions Framework
Neil K. R. Sehgal, Hita Kambhamettu, Sai Preethi Matam +2
Mental health challenges among Indian adolescents are shaped by unique cultural and systemic barriers, including high social stigma and limited professional support. We report a mi…
Effects of Static and Conversational AI-Generated Messages on Colorectal Cancer Screening Intent: a Randomized Clinical Trial
Neil K. R. Sehgal, Manuel Tonneau, Andy SL Tan +6
Large language model chatbots show increasing promise in persuasive communication, but their clinical utility remains uncertain, particularly in settings where sustained conversati…
PAL: Designing Conversational Agents as Scalable, Cooperative Patient Simulators for Palliative-Care Training
Neil K. R. Sehgal, Hita Kambhamettu, Allen Chang +3
Effective communication in serious illness and palliative care is essential but often under-taught due to limited access to training resources like standardized patients. We presen…
Large Language Model Chatbot Conversations vs Public Health Materials and Parental HPV Vaccination Intentions: A Randomized Clinical Trial
Neil K. R. Sehgal, Sunny Rai, Manuel Tonneau +6
Health care systems are increasingly considering large language model (LLM)-based chatbots for vaccine communication, but evidence that they improve durable, behaviorally relevant…
Exploring Socio-Cultural Challenges and Opportunities in Designing Mental Health Chatbots for Adolescents in India
Neil K. R. Sehgal, Hita Kambhamettu, Sai Preethi Matam +2
Mental health challenges among Indian adolescents are shaped by unique cultural and systemic barriers, including high social stigma and limited professional support. Through a mixe…
Race Discrimination in Internet Advertising: Evidence From a Field Experiment
Neil K. R. Sehgal, Dan Svirsky
We present the results of an experiment documenting racial bias on Meta's Advertising Platform in Brazil and the United States. We find that darker skin complexions are penalized,…