Project Type: Ongoing

A study that is currently collecting or analyzing data

Leveraging AI/ML to Improve Cultural Preparedness of Mental Health Professionals

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!

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Leveraging AI/ML to Improve Cultural Preparedness of Mental Health Professionals

Photo by Google DeepMind on Pexels.com

Why this topic?

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.

Our project aims to address this gap by using AI to find culturally important information in therapy notes. We’ll use data from several hundred patients who have agreed to participate in our research. We will be using Natural Language Processing to examine patterns in unstructured notes, then using those findings to make predictions.

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 are early in this research and looking for help with coding and data entry

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 still very early in the process of research in this area! It may be more than a year before we have results to share. Subscribe for updates below or leave a comment!

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Mental Health Help-Seeking Study

Photo by RDNE Stock project on Pexels.com

Why this topic?

The mental health help-seeking study aims to understand how people make decisions about seeking help for emotional or personal problems, including who they turn to first and why. This research is important because rates of anxiety and depression are rising, but many people, especially young adults and those from minoritized backgrounds, may not seek help from traditional sources like mental health professionals.

We use a cross-sectional survey (we ask people questions just one time) to try to understand parts of their identity, their experience, and their preferences for seeking help for mental health concerns.

Why is this important?

  1. Identify which sources (e.g., friends, family, professionals) people are most likely to disclose mental health symptoms to
  2. Determine the order in which people prefer to seek help for personal/emotional concerns or suicidal thoughts
  3. Explore how factors like demographics, personality traits, and clinical symptoms influence help-seeking preferences

By understanding these patterns, we can develop more accessible and effective support systems that align with people’s preferences. This knowledge can help healthcare providers, policymakers, and community organizations better address the growing need for mental health support, especially among underserved populations.

Project Status

We have collected the data and concluded 2 projects.
1 – a project (PhD milestone) by Gracie Kelly on stigma and mental health help-seeking from different targets
2 – a project (honors thesis) by Kayleigh Fenton on identity, trust, and stigma among racial/ethnic minorities

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 are currently submitting this work for publication. When accepted, we will provide summaries of our findings. Subscribe for updates below or leave a comment!

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Exploring Therapy Experiences Through Reddit Discussions

Photo by Brett Jordan on Pexels.com

Why this topic?

Therapists and clients are in a bind when it comes to giving and getting feedback. Therapists can be reluctant to ask for honest feedback and patients can have a difficult time giving honest feedback to their therapists. The question of how people express their thoughts and experiences of therapy over social media, a place that can be honest and importantly, anonymous, lead us to developing this ongoing research project.

Our research project aims to shed light on this question by analyzing discussions on Reddit centered around the phrase “My Therapist.”

Using topic modeling techniques, we’re examining Reddit posts and comments to uncover common themes and concerns shared by individuals who are likely therapy consumers. This approach allows us to explore authentic conversations about mental health and therapy in a unique way.

Why is this important?

By understanding what people are discussing about their therapy experiences, we hope to:

  • Gain insights into the concerns and experiences of therapy consumers/patients
  • Explore how online platforms like Reddit are being used for mental health support
  • Identify potential areas for improvement in mental health support and services

Project Status

Ongoing!

We have collected the data and are currently coding

If you are a George Mason Student interested in getting involved in research in the lab, please contact Dr. Tonge about availability for research assistants.

If you are a person interested in our results and 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 to project updates