Cross-sectional survey and Bayesian network model analysis of traditional Chinese medicine in Austria: investigating public awareness, usage determinants and perception of scientific support

Michael Eigenschink; Luise Bellach; Sebastian Leonard; Tom Eric Dablander; Julian Maier; Fabian Dablander; Harald H Sitte

doi:10.1136/bmjopen-2021-060644

Cross-sectional survey and Bayesian network model analysis of traditional Chinese medicine in Austria: investigating public awareness, usage determinants and perception of scientific support

BMJ Open. 2023 Mar 2;13(3):e060644. doi: 10.1136/bmjopen-2021-060644.

Authors

Michael Eigenschink¹, Luise Bellach¹, Sebastian Leonard², Tom Eric Dablander¹, Julian Maier¹, Fabian Dablander³, Harald H Sitte⁴

Affiliations

¹ Center for Physiology and Pharmacology, Institute of Pharmacology, Medical University of Vienna, Wien, Austria.
² Institute of Microbiology and Infection, University of Birmingham School of Dentistry, Birmingham, UK.
³ Department of Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands.
⁴ Center for Physiology and Pharmacology, Institute of Pharmacology, Medical University of Vienna, Wien, Austria harald.sitte@meduniwien.ac.at.

Abstract

Objectives: Despite the paucity of evidence verifying its efficacy and safety, traditional Chinese medicine (TCM) is expanding in popularity and political support. Decisions to include TCM diagnoses in the International Classification of Diseases 11th Revision and campaigns to integrate TCM into national healthcare systems have occurred while public perception and usage of TCM, especially in Europe, remains undetermined. Accordingly, this study investigates TCM's popularity, usage and perceived scientific support, as well as its relationship to homeopathy and vaccinations.

Design/setting: We performed a cross-sectional survey of the Austrian population. Participants were either recruited on the street (in-person) or online (web-link) via a popular Austrian newspaper.

Participants: 1382 individuals completed our survey. The sample was poststratified according to data derived from Austria's Federal Statistical Office.

Outcome measures: Associations between sociodemographic factors, opinion towards TCM and usage of complementary medicine (CAM) were investigated using a Bayesian graphical model.

Results: Within our poststratified sample, TCM was broadly known (89.9% of women, 90.6% of men), with 58.9% of women and 39.5% of men using TCM between 2016 and 2019. Moreover, 66.4% of women and 49.7% of men agreed with TCM being supported by science. We found a positive relationship between perceived scientific support for TCM and trust in TCM-certified medical doctors (ρ=0.59, 95% CI 0.46 to 0.73). Moreover, perceived scientific support for TCM was negatively correlated with proclivity to get vaccinated (ρ=-0.26, 95% CI -0.43 to -0.08). Additionally, our network model yielded associations between TCM-related, homeopathy-related and vaccination-related variables.

Conclusions: TCM is widely known within the Austrian general population and used by a substantial proportion. However, a disparity exists between the commonly held public perception that TCM is scientific and findings from evidence-based studies. Emphasis should be placed on supporting the distribution of unbiased, science-driven information.

Keywords: complementary medicine; health & safety; health policy; herbal medicine; public health; quality in health care.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Austria
Bayes Theorem
Cross-Sectional Studies
Female
Humans
Male
Medicine, Chinese Traditional*
Perception*