基于优劣尺度法的中医针灸民众认识与偏好选择

doi:10.3976/j.issn.1002-4026.20240134

Abstract

Abstract:

The purpose of this study is to use the BWS survey method to investigate the acceptance of acupuncture and moxibustion by the general public and what factors affect their choice of acupuncture and moxibustion therapy，and to investigate the existing problems of acupuncture and moxibustion therapy. A total of 219 respondents participated in this survey，the number of valid questionnaires is 201，the number of invalid questionnaires is 18. The study identified the most important and least important factors influencing acupuncture preferences，the most important being "whether acupuncture is effective" and the least important being "personal traditional beliefs"，BW scores from high to low （influence from high to low） were： Whether the efficacy of acupuncture is significant，whether the overall health can be adjusted，the level of development of acupuncture technology，whether personalized treatment can be performed，the degree of side effects，the extent of acupuncture treatment，other alternative therapies，the identification and trust of acupuncture culture，fear of acupuncture，economic factors，personal traditional ideas.In the future，the development of acupuncture and moxibustion should pay more attention to the curative effect，strengthen the publicity of the scientific nature of acupuncture and moxibustion，and contribute to promoting the development of acupuncture and moxibustion，improving the policies related to acupuncture and moxibustion and strengthening the public's trust in acupuncture and moxibustion.

Key words: acupuncture, best-worst scaling, public awareness, preference survey, traditional Chinese medicine

CLC Number:

R245

LI Dongye, CUI Jingru, ZONG Ruiyu, LI Xin, WANG Siyu, JIA Hongling, SONG Haiyan. Public awareness and preference for traditional Chinese medicine acupuncture based on the best-worst scaling[J].Shandong Science, 2025, 38(5): 131-139.

Figures/Tables 5

Table 1

Name，concept，and abbreviation of the BWS sattribute"

分类	影响因素	缩写	概念
针灸	针灸技术是否发达	技术	有些人可能认为针灸是一种古老且过时的治疗方法，与现代医学相比缺乏科学依据
	针灸治疗面是否广泛	治疗面	部分青年人认为针灸只能治疗一些中老年疾病
	副作用程度	副作用	虽然针灸通常被认为是安全的，但部分人可能担心潜在的副作用，如感染、出血或神经损伤等。这些担忧可能源于对针灸操作不当或个体差异的担忧
	针灸的疗效是否显著	疗效	显著的治疗效果：针灸在许多疾病和症状的治疗上展现出了显著的效果。无论是慢性疼痛、神经性疾病还是消化问题，针灸都能通过调节身体的气血和经络系统，达到缓解病情的目的。许多患者在接受针灸治疗后，都能明显感受到症状的改善
	有其他可替代针灸的疗法	替代物	有其他能与针灸起到相近作用的疗法，比如汤剂，中频等可以替换针灸
	能否进行个性化治疗	个性化	针灸治疗可以根据每个人的体质、病情和年龄等因素进行个性化的调整。这意味着每个患者都能得到最适合自己的治疗方案，从而达到更好的治疗效果
	能否进行整体健康调理	整体性	针灸不仅仅是针对某一症状的治疗，它更注重整体健康的调理。通过刺激经络和穴位，针灸能够调整身体的阴阳平衡，增强免疫力，改善睡眠质量，提高整体健康水平
外界因素	对于针灸的恐惧	恐惧	部分人可能害怕针灸过程中使用的针具，担心疼痛或不适。这种恐惧可能源于对针灸的不了解或过去的负面经历
	经济因素	经济	针灸治疗通常需要多次疗程才能取得显著效果，这可能会对一些经济条件有限的人来说是一个负担
	对针灸的文化认同与信任	文化认同	在一些文化中，针灸被视为一种传统的、自然的疗法，人们对其有着深厚的认同感和信任感。这种文化认同也使得更多的人愿意尝试并接受针灸治疗
	个人传统观念	传统观念	部分人可能更倾向于选择其他治疗方法，如药物治疗或物理治疗，而不是针灸。这可能与个人的信仰、价值观或治疗期望有关

Table 1

Table 2

Table 3

Table 4

Table 5

References 32

[1]	LIU B Y, DENG L Y, YANG Y Y. World acupuncture and moxibustion:an investigation and analysis of global application[M]. Beijing: Beijing Science and Technology Press, 2014.
[2]	INC E. Acupuncture: review and analysis of reports on controlled clinical trials[M]. Geneva: World Health Organization, 2002.
[3]	YANG F M, YANG Y, WATANABE D, et al. A summary of acupuncture standardization in Australia, Korea, Japan and the USA[J]. World Journal of Acupuncture - Moxibustion, 2017, 27(4): 20-26. DOI:10.1016/S1003-5257(18)30007-2.
[4]	CHEN Z J, HUO J, WANG X Y, et al. Investigation and analysis of the key objectives of WFAS “technical specifications of acupuncture and moxibustion: General rules for the drafting”[J]. Evidence-Based Complementary and Alternative Medicine, 2021, 2021: 9508061. DOI:10.1155/2021/9508061.
[5]	CAO H J, LI X, et al. Factors influencing participant compliance in acupuncture trials: An in-depth interview study[J]. PLoS One, 2020, 15(4): e0231780. DOI:10.1371/journal.pone.0231780.
[6]	郭盛楠, 刘志顺, 唐乐. 关于针灸科门诊患者针刺刺激接受程度的初步调查分析[J]. 辽宁中医杂志, 2012, 39(7): 1266-1268. DOI:10.13192/j.ljtcm.2012.07.73.guoshn.002.
[7]	史宏扬, 赵娟. 大学生针灸认知现状及其影响因素的调查研究[J]. 中国医药指南, 2014, 12(10): 252-253. DOI:10.15912/j.cnki.gocm.2014.10.014.
[8]	HOLLIN I L, PASKETT J, SCHUSTER A L R, et al. Best-worst scaling and the prioritization of objects in health: A systematic review[J]. PharmacoEconomics, 2022, 40(9): 883-899. DOI:10.1007/s40273-022-01167-1. pmid: 35838889
[9]	FLYNN T N, LOUVIERE J J, PETERS T J, et al. Best-worst scaling: What it can do for health care research and how to do it[J]. Journal of Health Economics, 2007, 26(1): 171-189. DOI:10.1016/j.jhealeco.2006.04.002.
[10]	张录法, 黄姣姣, 王慧, 等. 优劣尺度法理论及应用研究述评[J]. 统计与信息论坛, 2019, 34(3): 24-30. DOI:10.3969/j.issn.1007-3116.2019.03.004.
[11]	SEVERIN F, SCHMIDTKE J, MÜHLBACHER A, et al. Eliciting preferences for priority setting in genetic testing: A pilot study comparing best-worst scaling and discrete-choice experiments[J]. European Journal of Human Genetics, 2013, 21(11): 1202-1208. DOI:10.1038/ejhg.2013.36. pmid: 23486538
[12]	POTOGLOU D, BURGE P, FLYNN T, et al. Best-worst scaling vs. discrete choice experiments: An empirical comparison using social care data[J]. Social Science & Medicine, 2011, 72(10): 1717-1727. DOI:10.1016/j.socscimed.2011.03.027.
[13]	CHEUNG K L, WIJNEN B F M, HOLLIN I L, et al. Using best-worst scaling to investigate preferences in health care[J]. PharmacoEconomics, 2016, 34(12): 1195-1209. DOI:10.1007/s40273-016-0429-5. pmid: 27402349
[14]	TAYLOR G, ADDIE Y O, BURCHETT J, et al. “Miracle” or “medicine”: A turning-point analysis of patients' and physicians' shifting views on acupuncture[J]. Medical Acupuncture, 2020, 32(5): 263-271. DOI:10.1089/acu.2020.1428.
[15]	ROCKERS P, RYAN M, KOLSTAD J R, et al. How to conduct a discrete choice experiment for health workforce recruitment and retention in remote and rural areas: A user guide with case studies[M]. Geneva: World Health Organization, 2012
[16]	MÜHLBACHER A C, ZWEIFEL P, KACZYNSKI A, et al. Experimental measurement of preferences in health care using best-worst scaling (BWS): Theoretical and statistical issues[J]. Health Economics Review, 2016, 6(1): 5. DOI:10.1186/s13561-015-0077-z. pmid: 26822869
[17]	CHEUNG K L, MAYER S, SIMON J, et al. Comparison of statistical analysis methods for object case best-worst scaling[J]. Journal of Medical Economics, 2019, 22(6): 509-515. DOI:10.1080/13696998.2018.1553781. pmid: 30482068
[18]	SCHMID T, GANDRA S R, et al. Erratum to: ‘costs of treating cardiovascular events in Germany: A systematic literature review'[J]. Health Economics Review, 2016, 6(1): 1. DOI:10.1186/s13561-016-0080-z.
[19]	许越, 李雨畅, 陈星宇, 等. 基于优劣尺度法的老年人居家照护服务选择偏好及支付意愿分析[J]. 中国卫生质量管理, 2024, 31(8): 23-29. DOI:10.13912/j.cnki.chqm.2024.31.8.05.
[20]	MEARA A, CROSSNOHERE N L, BRIDGES J F P. Methods for measuring patient preferences: An update and future directions[J]. Current Opinion in Rheumatology, 2019, 31(2): 125-131. DOI:10.1097/BOR.0000000000000587. pmid: 30624283
[21]	SUN T, CHEN H L, GAO Y, et al. Best-worst scaling survey of inpatients' preferences in medical decision-making participation in China[J]. Healthcare, 2023, 11(3): 323. DOI:10.3390/healthcare11030323.
[22]	BEUSTERIEN K, KENNELLY M J, BRIDGESJ F P, et al. Use of best-worst scaling to assess patient perceptions of treatments for refractory overactive bladder[J]. Neurourology and Urodynamics, 2016, 35(8): 1028-1033. DOI:10.1002/nau.22876. pmid: 26370222
[23]	BAUTISTA D C, XIN X H, et al. Using best-worst scaling choice experiments to elicit the most important domains of health for health-related quality of life in Singapore[J]. PLoS One, 2018, 13(2): e0189687. DOI:10.1371/journal.pone.0189687.
[24]	刘保延. 从历史看未来:针灸标准发展脉络与展望[J/OL]. World Journal of Acupuncture-Moxibustion, 2024, 10(4):1-6. [2025-01-17]. http://kns.cnki.net/kcms/detail/11.2892.R.20240711.1538.002.html.
[25]	转化中医学在我国的形成与发展:摘自《转化中医学-中药复方新药创制转化思路与方法》(人民卫生出版社,2021年)[J]. 中药药理与临床, 2023, 39(2):2.
[26]	景向红, 朱兵. 针灸的转化医学之路[J]. 针刺研究, 2023, 48(1): 14-17. DOI:10.13702/j.1000-0607.20221127.
[27]	刘世蒙, 杨毅, 孙辉, 等. 患者偏好证据应用于卫生技术评估的价值、方法及挑战[J]. 中国卫生政策研究, 2022, 15(5): 52-58. DOI:10.3969/j.issn.1674-2982.2022.05.008.
[28]	陶颖, 刘世蒙, 陈英耀. 优化陈述性偏好研究的属性确定过程:基于优劣尺度法[J]. 中国循证医学杂志, 2024, 24(9):1079-1084. DOI:10.7507/1672-2531.202312099.
[29]	HAGHANI M, BLIEMER M C J, HENSHER D A. The landscape of econometric discrete choice modelling research[J]. Journal of Choice Modelling, 2021, 40: 100303.DOI:10.1016/j.jocm.2021.100303.
[30]	CLARK M D, DETERMANN D, PETROU S, et al. Discrete choice experiments in health economics: A review of the literature[J]. PharmacoEconomics, 2014, 32(9): 883-902. DOI:10.1007/s40273-014-0170-x. pmid: 25005924
[31]	SOEKHAI V, DE BEKKER-GROB E W, ELLIS A R, et al. Discrete choice experiments in health economics: Past, present and future[J]. PharmacoEconomics, 2019, 37(2): 201-226. DOI:10.1007/s40273-018-0734-2. pmid: 30392040
[32]	ROGERS H J, MARSHMAN Z, RODD H, et al. Discrete choice experiments or best-worst scaling? A qualitative study to determine the suitability of preference elicitation tasks in research with children and young people[J]. Journal of Patient-Reported Outcomes, 2021, 5(1): 26. DOI:10.1186/s41687-021-00302-4. pmid: 33689059

最重要的因素	影响因素	最不重要的因素
	针灸治疗面的广泛度
√	副作用的大小
	针灸的疗效是否显著
	有其他可替代针灸的疗法
	能否进行个性化治疗	√

维度	项数	Cornbach'α系数
最重要的因素	11	0.759
最不重要的因素	11	0.814

特征	类别	数量/人	占比/%
性别	女	121	60.20
性别	男	80	30.80
年龄	18~<30岁	55	27.36
	30~<40岁	36	17.91
	40~<50岁	31	15.42
	50~<60岁	28	13.93
	≥60岁	51	25.37
最高学历	未上学或小学未毕业	13	6.47
	小学	11	5.47
	初中或中专	25	12.44
	高中	33	16.42
	大专	19	9.45
	本科	78	38.81
	硕士及以上	22	10.95
常住地类型	城市	159	79.1
常住地类型	农村	42	20.9
家庭年收入	<3万元	39	19.4
	（3~<8）万元	62	30.85
	（8~<15）万元	55	27.36
	（15~<25）万元	27	13.43
	≥25万元	18	8.96
健康状况	非常健康	47	23.38
	健康	93	46.27
	亚健康	45	22.39
	疾病缠身	16	7.96

影响因素	B	W	BW总分	平均BW得分	缩放BW得分	排名
针灸技术的发展水平	268	114	154	0.939	1.533	3
针灸治疗面的广泛度	210	139	71	0.480	1.229	6
副作用程度	250	146	104	0.638	1.309	5
针灸的疗效是否显著	587	69	518	2.656	2.917	1
有其他可替代针灸的疗法	118	197	-79	-0.476	0.774	7
能否进行个性化治疗	230	109	121	0.712	1.453	4
能否进行整体健康调理	347	91	256	1.354	1.953	2
对于针灸的恐惧	114	362	-248	-1.393	0.561	9
经济因素	68	416	-348	-2.035	0.404	10
对针灸文化的认同与信任	104	217	-113	-0.706	0.692	8
个人传统观念	36	472	-436	-2.396	0.276	11

Public awareness and preference for traditional Chinese medicine acupuncture based on the best-worst scaling

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 5

References 32

Related Articles 13

Metrics

Comments

Recommended 0

[1]	LIU Kechun, WANG Yongcheng, ZANG Xiaohan, XIA Qing, ZHANG Yun, ZHANG Shanshan, SUN Chen. Advancements in network pharmacology and zebrafish modeling for studying traditional Chinese medicine’s effective substances and mechanisms of action [J]. Shandong Science, 2024, 37(2): 29-35.
[2]	YANG Guohong, ZHOU Bingqian, LU Heng, SONG Xiangyun, ZHU Heng, WANG Xiao, LIU Qian, LIU Wei. Investigation and analysis of the current situation of traditional Chinese medicine resources in Gangcheng District, Jinan City, Shandong Province [J]. Shandong Science, 2024, 37(1): 1-8.
[3]	WANG Hui, HUANG Xuan, ZHANG Chenggang, ZENG Wen, ZHOU Tao, JIANG Weike. Diversity analysis and comprehensive value evaluation of wild medicinal plant resources in the fourth national survey of traditional Chinese medicine resources in Weining County,Guizhou Province [J]. Shandong Science, 2024, 37(1): 9-16.
[4]	LI Wanying, DUAN Wanying, LI Rui, RAN Zhifang, ZHOU Jie, FANG Lei. A survey on the current status of traditional Chinese medicine resources in Shizhong District, Jinan, Shandong Province [J]. Shandong Science, 2023, 36(6): 22-27.
[5]	LIANG Jiahao, ZHANG Xinhui, WANG Hai. Exploringtrait genes and predicting the targeted Chinese medicine for ulcerative colitis based on bioinformatics and machine learning [J]. Shandong Science, 2023, 36(6): 56-67.
[6]	SUN Tiefeng, DONG Limin, JIAO Ziqi, WANG Ping. Exploration of the dosing pattern and anti-respiratory syncytial virus mechanism of traditional Chinese medicine based on data mining and network pharmacology [J]. Shandong Science, 2023, 36(3): 1-9.
[7]	HAN Li-wen, CHEN Shan-jun, DONG Rong, ZHANG You-gang, WANG Xiao-jing. Progress of network pharmacology applications in studying the complex mechanisms of action of traditional Chinese medicine [J]. Shandong Science, 2021, 34(6): 22-31.
[8]	WU Xiao-Min, HAN Li-Wen, YANG Guan-E, LIU Ke-Chun. Application of metabonomics in security assessment of traditional Chinese medicine [J]. J4, 2014, 27(2): 34-38.
[9]	NI Chen, QIU Feng, CAO Hui. B/S structure based information collection system for traditional chinese medicine [J]. J4, 2013, 26(4): 56-59.
[10]	CHENG Wei, HOU En-Guang, LI Ke, LI Shu-Bin, ZHAO Bo-Nian, XU Zong-Yuan. Research on principle component analysis based pharmacological effect evaluation method for a kind of Chinese herbal medicine, Baikal skullcap root [J]. J4, 2012, 25(1): 47-50.
[11]	LI Zhen-Yang, CAO Hui, MA Jin-Gang, SONG Xiao-Rui. Application of RBAC model in a traditional Chinese medicine information resources management platform [J]. Shandong Science, 2011, 24(6): 84-87.
[12]	LAI Jian-Mei, CAO Hui, MA Jin-Gang. The research and application of information extraction in the field of traditional Chinese medicine [J]. Shandong Science, 2011, 24(6): 88-91.
[13]	HOU En-Guang, LI Shu-Bin, LI Ke, DING Xiao-Yan, LV Ling, LIU Qing, ZHAO Bo-Nian, XU Zong-Yuan. Neural network based assessment of pharmacological effects of traditional Chinese medicine [J]. J4, 2011, 24(1): 72-76.