Tootfinder

Therapeutic AI and the Hidden Risks of Over-Disclosure: An Embedded AI-Literacy Framework for Mental Health Privacy
Soraya S. Anvari, Rina R. Wehbe
https://arxiv.org/abs/2510.10805

Therapeutic AI and the Hidden Risks of Over-Disclosure: An Embedded AI-Literacy Framework for Mental Health Privacy
Large Language Models (LLMs) are increasingly deployed in mental health contexts, from structured therapeutic support tools to informal chat-based well-being assistants. While these systems increase accessibility, scalability, and personalization, their integration into mental health care brings privacy and safety challenges that have not been well-examined. Unlike traditional clinical interactions, LLM-mediated therapy often lacks a clear structure for what information is collected, how it is …

Between Help and Harm: An Evaluation of Mental Health Crisis Handling by LLMs
Adrian Arnaiz-Rodriguez, Miguel Baidal, Erik Derner, Jenn Layton Annable, Mark Ball, Mark Ince, Elvira Perez Vallejos, Nuria Oliver
https://arxiv.org/abs/2509.24857

Between Help and Harm: An Evaluation of Mental Health Crisis Handling by LLMs
The widespread use of chatbots powered by large language models (LLMs) such as ChatGPT and Llama has fundamentally reshaped how people seek information and advice across domains. Increasingly, these chatbots are being used in high-stakes contexts, including emotional support and mental health concerns. While LLMs can offer scalable support, their ability to safely detect and respond to acute mental health crises remains poorly understood. Progress is hampered by the absence of unified crisis ta…

MakOne: Behavioural Data of University Students' Smart Devices in Uganda
Michael Kizito, Ivan Kayongo, Hawa Nyende, Halimu Chongomweru, Lillian Muyama, Roy Alia Asiku, Alice Mugisha
https://arxiv.org/abs/2509.22334

MakOne: Behavioural Data of University Students' Smart Devices in Uganda
Understanding student behaviour in higher education is essential for improving academic performance, supporting mental well-being, and informing institutional policies. However, most existing behavioural datasets originate from Western institutions and overlook the unique socioeconomic and infrastructural contexts of African institutions, limiting the global applicability of resulting insights. This paper introduces MakOne, a novel multimodal dataset collected over six weeks from 72 students at…