Providing mental health support for loved ones across a geographic distance creates unique challenges for the remote caregivers, who sometimes turn to online communities for peer support. We qualitatively analyzed 522 Reddit threads to understand what drives remote caregivers' online help-seeking behaviors and the responses they receive from the community. Their purposes of posting included requesting guidance, expressing emotions, and seeking validation. Community responses included providing emotional support, suggesting informational strategies, and sharing personal experiences. While certain themes in posts (emotional toll, monitoring symptoms, and prioritizing caregiver well-being) are shared across remote and non-remote contexts, remote caregivers' posts surfaced nuanced experiences. For example, they often rely on digital cues, such as voice, to interpret care receivers' well-being while struggling with digital silence during crises. We discuss the need for supporting communication and information sharing between remote caregivers and receivers, care coordination for crisis management, and design recommendations for caregiver communities.

Misinformation on private messaging platforms like WhatsApp and LINE is a global concern. However, research has primarily focused on combating misinformation on public social media. Misinformation in private messaging platforms is difficult to challenge due to social norms, interpersonal relationships, and technological affordances. This study investigates Auntie Meiyu, a fact-checking chatbot integrated into LINE, a popular private messaging service in Taiwan. We interviewed 27 users who adopted Auntie Meiyu in their messaging groups to understand their motivations and perceptions of the chatbot, and to assess its influence on interpersonal interactions. Participants indicated that they primarily adopted the chatbot to protect close family members from misleading news. Nevertheless, they experienced mixed feelings due to the chatbot's robotic style and errors in detecting misinformation. We conclude that conversational agents present a promising approach for tackling misinformation, particularly when conversational participants disagree, and offer design recommendations for leveraging AI-enabled conversational agents in countering misinformation.

Family members and close friends often step in to provide crucial emotional and practical support to individuals with mental health conditions, even from far away. While much of the existing research on mental health support focuses on those living in the same household, remote supporters' unique practices and challenges remain underexplored. To fill this gap, we interviewed 22 individuals who provide remote support for family and friends with mental health conditions. Remote supporters face significant challenges, including difficulties in maintaining open communication and coordinating care from a distance, struggles with preserving well-being and boundaries, inadequate institutional support, and social stigma. Our findings also highlight specific expectations for technology-facilitated support, pointing to design opportunities that can improve both the practices and well-being of remote supporters.

Economically disadvantaged migrant workers are one of the most vulnerable groups in healthcare. Studies have shown that chatbots can help patients and health professionals in healthcare settings. However, the design of health chatbots for migrant workers has not been thoroughly investigated. Scenario-based interviews with nineteen participants, including ten economically disadvantaged Thai migrant workers and nine relevant stakeholders, were conducted to examine how they seek healthcare, obtain health information, and communicate with health professionals to gain a deeper understanding of the barriers that migrant workers encounter in healthcare. The findings of the interview show that migrant workers face a variety of barriers, such as a lack of familiarity with the healthcare system in the host country, language barriers, cultural barriers to seeking healthcare, and communication barriers with health professionals. Then, the technological design strategies and the benefits of health chatbots from the perspective of migrant workers were discussed, including their potential to help migrant workers navigate the healthcare system step-by-step, obtain reliable health information, improve their health literacy, and facilitate communication with health professionals. Finally, five design implications for chatbots were proposed to guide future development of health chatbots to help migrant workers. Policymakers and health professionals can benefit from the design implications of migrant worker-centered health chatbots when they develop health chatbots that promote the health and well-being of migrant workers.