Date of Graduation
Spring 5-21-2022
Document Type
Thesis
Degree Name
Master of Science in Applied Economics (MSAE)
College/School
College of Arts and Sciences
Department/Program
Economics
First Advisor
Bruce Wydick
Abstract
Human figure drawings are a well-studied diagnostic tool for emotional distress in children. Cleft lip/palate is one of the most common birth defects in the world, and has been shown to negatively impact emotional well-being in childhood which can have negative economic consequences in adulthood. Utilizing a dataset of human figure drawings from children in India and survey data on mental health, this paper will assess the impact of corrective surgery on mental health outcomes, as well as assess the validity of the drawing emotional indicators themselves. The results indicate that while the emotional indicators may not be valid in predicting emotional distress in this sample, there is a positive relationship between corrective surgery and mental health outcomes.
Recommended Citation
Lawrie, Nicholas R., "Using Machine Learning to Analyze Children’s Drawings as Indicators of Mental Well-Being" (2022). Master's Theses. 1416.
https://repository.usfca.edu/thes/1416
Included in
Growth and Development Commons, Health Economics Commons, Psychiatric and Mental Health Commons
