What is the problem that needs to be addressed? Please describe how it is related to mental health.
Anxiety and depression are the top causes of disease burden in the United States and cost tens of billions of dollars a year. Although current treatment strategies such as cognitive behavior therapy and community-based peer support groups have been successfully used to improve symptoms of anxiety and depression, these treatments require a great deal of time and economic resources. Cost-effective treatment for anxiety and depression can be especially difficult in large institutions where psychologists receive an overwhelming number of patients, reducing treatment effectiveness and leading patients to feel neglected.
To learn how to improve the effectiveness of mental health interventions, researchers have attempted to collect data on the needs of patients with anxiety and depression, such as through interviews, surveys, and tracking patient cases/reports. However, these methods suffer from a number of limitations including a long lag-time in reporting, as it often takes years for government agencies and researchers to collect interview and survey data. New methods are needed to address the lack of data, and the need for higher quality data to improve the lives of people suffering from these mental health issues.
Why is this a concern for Orange County? What can Orange County and other counties learn from this project?
Orange County has a large number of individuals with anxiety, depression, and related mental health disorders, including a growing number of veterans suffering from anxiety, depression, and post-traumatic stress (PTSD), a growing homeless population suffering from similar mental and behavioral health issues, and a growing number of youth suffering from these mental health issues and at high risk for suicide. New methods are needed to prevent these growing risks for Orange County residents and these important populations.
What is currently being done to resolve this problem in our county and throughout the United States? If applicable: Is it working; why or why not?
A number of methods are being used to both collect data as well as intervene to reduce anxiety and depression, both broadly, as well as more focused among veterans, homeless populations, and youth. For example, a large number of social services already exist that can provide therapy (e.g., CBT), outreach, skills training, and class such as yoga/meditation. Many of these are also available online, such as through mobile apps for CBT. Data collection methods can help inform these interventions. For example, the typical methods used to better understand the needs of people with anxiety and depression include interviews, surveys, and patient case reports. Although these methods are working to some extent, they also suffer from limitations. For example, the methods used to collect data on the needs of patients with anxiety and depression are not real-time or near real-time. Collecting interview and survey data, aggregating it, and analyzing it can take years. It is difficult to understand the needs of people with anxiety and depression, and to tailor interventions toward them, if the data are based on reports from years ago. New methods are needed to better monitor in real-time, or better yet predict, the people at risk for anxiety and depression as well as their mental health-related needs.
What is new or different about this project idea? Please describe how this differs from what is already being done (Question 6). Please list any research that was done on this topic.
No known mental health research/interventions are incorporating the proposed methods.
What is the project idea? Please describe how this project will operate.
This project will leverage the growing amount of data from people’s social media and smartphones and use it to monitor and predict people’s anxiety and depression, and related mental health needs. The ultimate goal of the project will be to collect data in real-time, in an organic comfortable environment, that can help inform tailored interventions for OC residents suffering from and/or at risk for anxiety and depression. We will invite OC participants from a variety of high-risk populations (e.g., veterans, college students, homeless populations) to complete depression and anxiety screening assessments to identify those with anxiety and/or depression. These individuals will be invited to participate in a study where they can choose to provide access to their social media data (e.g., Facebook, Twitter, etc). They will read about their risks of participation (e.g., informed consent; this will be approved by our university ethical review board). Among those who allow access, we will collect and analyze their real-time social media/smartphone data while having them complete periodic surveys to assess their mental health-related behaviors and outcomes. We will use advanced computer science/artificial intelligence methods to “train” machines to learn how to identify patterns from their social media data that can be used to predict their anxiety and depression risk and related mental health outcomes. We will also study their comfort in us using these methods to track their mental health to better understand how to safely and ethically collect real-time social media data and tailor it for personalized interventions.
For more information on these types of research methods: predictiontechnology.ucla.edu