Mental health researchers have recently turned to websites and mobile applications to deliver inexpensive, automated cognitive behavioral therapy (CBT), a depression treatment usually administered in-person by a trained mental health professional, to anyone with an Internet connection. By studying the social practices involved in the development, marketing, and testing of these treatments, this research, which trains a graduate student in anthropology in the methods of empirical, scientific data collection and analysis, seeks to understand how this e-mental health turn influences popular distinctions between normal and abnormal low mood. In addition, it explores what impact automated CBT has in producing new kinds of mental health knowledge, and the relationship between therapist and patient. The findings of this research will be disseminated in such a way to aid researchers and policy-makers to innovate treatment modalities for mental health. The project also builds infrastructural capacity in basic science through international scholarly cooperation.

Aaron Neiman, under the supervision of Dr. Duana Fullwiley of Stanford University, will explore the impact e-mental health technology on depression treatment modalities. The project will investigate one of the most prominent sites of this e-mental health research, asking how it navigates the many technical and ethical challenges raised by taking depression treatment online. Employing laboratory ethnographic methods such as interviews, embedded observation, and textual analysis of scientific documents, the site of this year-long research is the Black Dog Institute in Sydney, Australia, a nonprofit mood disorder research center pioneering this new form of therapy. Under the leadership of its executive director, the Institute has refashioned itself in recent years from a forward-thinking mental health clinic into a world-class research institute developing novel depression treatments. This reflects a broader digital turn in mental health research globally, largely led by the Australian government. The ethnographic data gathered in this study will shed light on a possible future of automated therapy, and how these new human-computer interactions change popular understandings of what constitutes depression.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Behavioral and Cognitive Sciences (BCS)
Type
Standard Grant (Standard)
Application #
1917569
Program Officer
Jeffrey Mantz
Project Start
Project End
Budget Start
2019-09-01
Budget End
2021-06-30
Support Year
Fiscal Year
2019
Total Cost
$12,335
Indirect Cost
Name
Stanford University
Department
Type
DUNS #
City
Stanford
State
CA
Country
United States
Zip Code
94305