ChatGPT for Us: Preserving Data Privacy in ChatGPT via Dialogue Text Ambiguation to Expand Mental Health Care Delivery

Large language models have been useful in expanding mental health care delivery. ChatGPT, in particular, has gained popularity for its ability to generate human-like dialogue. However, data-sensitive domains -- including but not limited to healthcare -- face challenges in using ChatGPT due to privacy and data-ownership concerns. To enable its utilization, we propose a text ambiguation framework that preserves user privacy. We ground this in the task of addressing stress prompted by user-provided texts to demonstrate the viability and helpfulness of privacy-preserved generations. Our results suggest that chatGPT recommendations are still able to be moderately helpful and relevant, even when the original user text is not provided

Analysis of Smartphone Text Data Related to mpox from a U.S. Sample of Gay, Bisexual, and Other Men Who Have Sex with Men During the 2022 Outbreak.

Purpose: We sought to understand technology-based communication regarding mpox (monkeypox) among gay, bisexual, and other men who have sex with men (GBMSM) during the global outbreak in 2022. Methods: Forty-four GBMSM (Mage = 25.3 years, 68.2% cisgender, 43.2% non-White) living in the United States participated. From May 2022 to August 2022, all text data related to mpox (174 instances) were downloaded from the smartphones of GBMSM. Text data and smartphone app usage were analyzed. Results: Content analysis revealed 10 text-based themes and 7 app categories. GBMSM primarily used search and browser, texting, and gay dating apps to share vaccine updates, seek mpox vaccination, find general mpox information, share mpox information with other GBMSM, and discuss links between mpox and gay culture. Data visualizations revealed that changes in communication themes and app usage were responsive to major milestones in the mpox outbreak. Conclusion: GBMSM used apps to facilitate a community-driven mpox response