Removing Mental Health Stigma in Higher Education Through Remote Monitoring and Telehealth Counseling
Mental health counseling is a growing application space in higher education. Research has consistently shown a rapid growth in the number and severity of psychological problems among university students. A survey of 274 counseling centers showed that overall 85% of university students in U.S. exhibit severe types of mental issues including anxiety, and depression. According to Suicide Prevention Resource Center, approximately 8% of university students in U.S. have seriously considered suicide. Recently, the use of remote health monitoring and communication technologies has shown promise in improving quality of care. In particular, the prevalence of sensor-enabled devices such as smartphones have the potential to increase access to and continuity of care by extending treatment beyond scheduled office visits. The absence of a reliable, usable, and integrated information systems to connect patients and clinicians will continue to present challenges in the treatment of mental health issues among university students. When symptoms are known, telehealth counseling has the potential to improve mental health outcomes, especially in higher education student bodies in which many students have a limited capacity to travel long distances to receive mental health counseling services that traditionally take place in a centralized office complex. In addition, the facilitation of large-scale dialogues on mental health between students, faculty, and staff has the potential to alleviate the stigma surrounding mental health as well as promote development of effective student-centered interventions. Our interdisciplinary team will address this research gap by utilizing a mixed methods pilot study utilizing facilitated dialogues on mental health, remote monitoring using a novel wearable tool, and telehealth counseling sessions. Our goal is to establish a complex sociotechnical infrastructure that uses proactive counseling as well as ubiquitous computing capabilities to detect changes in mental state. This will allow us to interact with students to triage or provide support, as well as to facilitate data collection and monitoring between students and therapists. In collaboration with TAMU student counseling services, the proposed pilot study will establish the feasibility of a user-based, easy-to-use and efficient mental health information system that monitors mental state change indicators of heightened stress or depression symptoms through the use of mobile sensors on a cohort of 200 students stratified across different programs and levels. The system will use mobile sensors (e.g., heart rate, perspiration) to monitor key mental state change indicators (e.g., heart rate variability), detect and monitor anxiety and depression among the student study population, and will trigger clinician-student communication events through a telehealth counseling platform.
This contribution is expected to be significant because it will provide focus for subsequent lines of investigation on improved health tools for anxiety and depression with remote capabilities that enable the integration of information from these tools with on-going treatment plans. The continuous monitoring of students is expected to contribute to decreased depression and anxiety levels and improve the quality of life among university students and facilitate evidence-based diagnostic or treatment decisions based on real-time data and have implications in the design of clinical decision-support systems for mental health therapists.
The status quo as it pertains to mental health diagnosis and treatment is in-person counseling which in most cases is initiated by the student. This proposed research is innovative, in our opinion, because it represents a substantive departure from the status quo by enabling real-time monitoring and documentation of mental health and student-clinician interaction and care. The system will use mobile sensors to monitor key mental state change indicators, identify mental state changes using personalized machine learning algorithms, which will trigger counseling communication events. We plan a joint effort between student, faculty, and staff from the Student Counseling Services, Office of the Dean of Faculties, Division of Student Affairs, Bush School of Government and Public Service, College of Education, School of Public Health, and College of Engineering, among others. The research proposed here is expected to open new research horizons, particularly in the area of smart and connected continuous monitoring systems that are integrated with healthcare infrastructure.