Chatbots supporting #HPV vaccine promotion matched public health materials for short-term intent but showed less durable effects and did not increase vaccination uptake. ja.ma/4uTd50g

Demographic cues (eg, names, dialect) are widely used to study how LLM behavior may change depending on user demographics. Such cues are often assumed interchangeable. 🚨 We show they are not: different cues yield different model behavior for the same group and different conclusions on LLM bias. 🧵👇

🚨 New study! We tested whether AI-generated messages – single static messages vs. conversations – can boost intent to screen for colorectal cancer. Turns out: short, tailored AI messages outperform expert-written materials & match conversations, at a fraction of the time! 🧵👇

🚨 New preprint on AI persuasion and public health 🚨 A 3-min conversation with GPT-4o nudged HPV-vax-hesitant parents (who obv knew it was AI & consented!)—BUT reading standard public-health material still outperformed chatbots in impact and longevity. Details below 👇

🚨 New CHI'25 EA paper! 🚨 How can we design culturally sensitive mental health chatbots for Indian adolescents? 🇮🇳📱 Our mixed-methods study reveals key design insights—from stigma to personalization. Read it here: arxiv.org/abs/2503.08562 #CHI2025 #HCI #MentalHealth #AIforGood #India

Exploring Socio-Cultural Challenges and Opportunities in Designing Mental Health Chatbots for Adolescents in India

Mental health challenges among Indian adolescents are shaped by unique cultural and systemic barriers, including high social stigma and limited professional support. Through a mixed-methods study invo...

arxiv.org

LDI Senior Fellows Neil Sehgal, Anish Agarwal, Raina Merchant, Sharath Chandra Guntuku, and colleagues analyzed Yelp reviews of health care facilities to asses how patient sentiment toward changed before and after COVID-19.