CMIPS

Last updated on November 6, 2022
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Photo from the CMIPS Visual Consent form.

Computational Methods Investigating Psychosocial Stressors (CMIPS)

The aim of this project is to use machine learning and natural language processing to model psychosocial stressors among LGBTQ+ people using their Facebook and/or Twitter data. In other words, to apply artificial intelligence to understand how LGBTQ+ people talk about stressful experiences on Facebook and/or Twitter.

Results will help support the development of technology-delivered mental health tools (e.g., digital mental health apps) specifically designed for LGBTQ+ people.

Check out the visual consent form to learn more.

CMIPS Visual Consent Form 1
CMIPS Visual Consent Form 2

Project Funding

  • NIH Minority Biomedical Research Support (MBRS) Research Training Initiative for Student Enhancement (RISE) Fellowship (R25GM061222, PI Houston, Trainee Cascalheira)
Machine Learning NLP
Cory J. Cascalheira
Cory J. Cascalheira
Doctoral Candidate in Counseling Psychology

Research interests include (1) the examination of stress-based, multilevel determinants and mechanisms conferring risk for LGBTQ+ health disparities (e.g., substance misuse); and (2) the use of computational methods (i.e., artificial intelligence) and big data to understand LGBTQ+ health behaviors and outcomes. Clinical interests include ACT, CBT, CPT, and MI.