Why this topic?
The purpose of this project is to enhance the integration of culturally-relevant information in therapy sessions, aiming to improve mental health outcomes for racial and ethnic minority groups. By developing a taxonomy and training a text classifier, the project will systematically identify and analyze culturally-relevant content in therapy notes. This will provide valuable insights into how cultural competence can influence treatment outcomes, such as reducing dropout rates among minority patients. The project’s role is to create a structured coding scheme, build an accurate text classifier, and analyze the impact of cultural content on therapy effectiveness, ultimately contributing to more equitable and effective mental health care.
Why is this important?
We need to find better ways to understand and use cultural information from diverse patients to improve mental health treatment. When healthcare providers consider a patient’s cultural background, treatments are more successful. Ignoring culture can lead to patients quitting therapy early or not getting better.
Experts agree that good mental health care should include understanding different cultures, being aware of cultural differences, and having skills to work with diverse patients. This approach is thought to help people from various racial and ethnic backgrounds have better outcomes in therapy. However, there’s still debate about the best ways to help therapists become more culturally aware and responsive.
Artificial intelligence (AI) and machine learning (ML) have been used in mental health to help bridge the gap between what therapists know and how they apply that knowledge. These tools have helped therapists better identify symptoms. But right now, there aren’t any AI tools to help identify important cultural information.
Project Status
We have collected the data and are currently coding
Some initial results presented at the AIM-AHEAD annual meeting can be found Here
If you are a [George Mason Student] interested in getting involved in research in the lab, please contact [Dr. Tonge] about openings for research assistants.
If you are a person interested in our results: we’re carefully analyzing the data to ensure our findings are accurate and meaningful. We’re excited about the potential insights this project may offer to the mental health community and look forward to sharing more as our research progresses. Subscribe for updates below or leave a comment!
TIDL@GMU 