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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Differences in demographics and complementary and alternative medicine use between patients attending integrative
Melissa K Melby1, Tetsuhiro Yoshino2, Dunia Tonob3
1Department of Anthropology, College of Arts and Sciences and College of Health Sciences, University of Delaware, Newark, DE, 19716, United States; Member, CIFAR.
Objectives:
Growing interest in integrative medicine motivates examination of who seeks integrative care, and why. By examining differences in demographics and complementary and alternative medicine (CAM) use between patients recruited from Japanese Kampo (traditional herbal medicine) versus biomedical clinics, this study aimed to identify whether integrative medicine options might attract different patients.
Design And Setting:
In this cross-sectional, observational study we administered the International Complementary and Alternative Medicine-Questionnaire (I-CAM-Q) to 209 patients recruited from four hospital clinics. Demographics, use of different types of CAM (self-help CAM, CAM practitioners, CAM products), and motivations were compared between Kampo and Non-Kampo patients and by gender. Factors influencing attendance at the Kampo clinic and CAM use were identified using logistic regression.
Results:
While some demographic characteristics, CAM provider and total CAM use differed between Kampo and non-Kampo patients, self-help CAM use did not. Motivations (for acute, long-term, health maintenance, or other reasons) differed between Kampo and non-Kampo clinic patients for going to non-Kampo physicians (P = 0.02) and Kampo physicians (P = 0.1). Logistic regression results for 'any CAM' use showed odds ratio of 0.32 (95%CI 0.15-0.67) for self-rated health, and 1.60 (95%CI 1.10-2.32) for Macarthur subjective social status scale. Attendance at the Kampo clinic showed odds ratios of 1.50 (95%CI 1.11-2.02) for education and 0.56 (95%CI 0.39-0.80) for employment status.
Conclusions:
Better understanding of factors such as motivation, self-rated health, and socioeconomic conditions that influence patients' CAM use and integrative clinic attendance may enable more effective targeting of populations and integration of CAM into biomedical settings.
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