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

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 nat...

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Autores principales: Eigenschink, Michael, Bellach, Luise, Leonard, Sebastian, Dablander, Tom Eric, Maier, Julian, Dablander, Fabian, Sitte, Harald H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9990654/
https://www.ncbi.nlm.nih.gov/pubmed/36863740
http://dx.doi.org/10.1136/bmjopen-2021-060644
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author Eigenschink, Michael
Bellach, Luise
Leonard, Sebastian
Dablander, Tom Eric
Maier, Julian
Dablander, Fabian
Sitte, Harald H
author_facet Eigenschink, Michael
Bellach, Luise
Leonard, Sebastian
Dablander, Tom Eric
Maier, Julian
Dablander, Fabian
Sitte, Harald H
author_sort Eigenschink, Michael
collection PubMed
description 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.
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spelling pubmed-99906542023-03-08 Cross-sectional survey and Bayesian network model analysis of traditional Chinese medicine in Austria: investigating public awareness, usage determinants and perception of scientific support Eigenschink, Michael Bellach, Luise Leonard, Sebastian Dablander, Tom Eric Maier, Julian Dablander, Fabian Sitte, Harald H BMJ Open Complementary Medicine 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. BMJ Publishing Group 2023-03-02 /pmc/articles/PMC9990654/ /pubmed/36863740 http://dx.doi.org/10.1136/bmjopen-2021-060644 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Complementary Medicine
Eigenschink, Michael
Bellach, Luise
Leonard, Sebastian
Dablander, Tom Eric
Maier, Julian
Dablander, Fabian
Sitte, Harald H
Cross-sectional survey and Bayesian network model analysis of traditional Chinese medicine in Austria: investigating public awareness, usage determinants and perception of scientific support
title Cross-sectional survey and Bayesian network model analysis of traditional Chinese medicine in Austria: investigating public awareness, usage determinants and perception of scientific support
title_full Cross-sectional survey and Bayesian network model analysis of traditional Chinese medicine in Austria: investigating public awareness, usage determinants and perception of scientific support
title_fullStr Cross-sectional survey and Bayesian network model analysis of traditional Chinese medicine in Austria: investigating public awareness, usage determinants and perception of scientific support
title_full_unstemmed Cross-sectional survey and Bayesian network model analysis of traditional Chinese medicine in Austria: investigating public awareness, usage determinants and perception of scientific support
title_short Cross-sectional survey and Bayesian network model analysis of traditional Chinese medicine in Austria: investigating public awareness, usage determinants and perception of scientific support
title_sort cross-sectional survey and bayesian network model analysis of traditional chinese medicine in austria: investigating public awareness, usage determinants and perception of scientific support
topic Complementary Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9990654/
https://www.ncbi.nlm.nih.gov/pubmed/36863740
http://dx.doi.org/10.1136/bmjopen-2021-060644
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