Doctor of Philosophy, The Ohio State University, 2007, Family Resource Management
This study used Grossman's model of demand for health to examine demand for Complementary and Alternative Medicine (CAM) in the U.S. The main purpose of this study was to identify the predictors of demand for CAM. An important objective was to examine whether CAM and conventional care are economic substitutes or complements. In this study, demand for three CAM modalities including chiropractic, acupuncture, and massage was examined. Data used for this study were from the 2002 and the 2004 Medical Expenditure Panel Survey. CAM demand was estimated using a two-part model. In the first part, likelihood of CAM use is estimated using logit analysis. In the second part, level of use is estimated using an OLS regression. Propositions of Grossman's model are partially supported by this study. Health insurance coverage, time factors, health status, health behavior, gender, marital status, race and region of residence have significant effect on likelihood of CAM use. Risk tolerance, MSA status and preferred language of communication have a significant effect on likelihood of chiropractic use only. Price of chiropractic, unearned family income, and level of education are significant only in the first stage model for acupuncture and/or massage. Time factors, wages, age and self-perceived mental health status are significant predictors of number of acupuncture and/or massage visits but not of chiropractic visits. Own-price of chiropractic, Medicaid coverage, gender, region and preferred language of communication are significant predictors of level of use of chiropractic. Although the magnitude of demand elasticities is small, the positive total cross-price elasticities of chiropractic and physician visits and acupuncture and/or massage and physician visits suggest that CAM and physician care are substitutes. Based on the results, theoretical, research, and policy implications are drawn. Deviations from Grossman's model suggest that augmenting economic models with other relevant (open full item for complete abstract)
Committee: Gong-Soog Hong (Advisor)
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