Article(id=1324044596199695145, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324044540067328424, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202511367, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1763827200000, receivedDateStr=2025-11-23, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793606431292, onlineDateStr=2026-11-02, pubDate=1777046400000, pubDateStr=2026-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793606431292, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793606431292, creator=13701087609, updateTime=1793606431292, updator=13701087609, issue=Issue{id=1324044540067328424, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='8', pageStart='1345', pageEnd='1536', issueExtLink='null', onlineDate='null', pubDate='1777046400000', pubDateStr='2026-04-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793606417910, creator='13701087609', updateTime=1793606417910, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=1434, endPage=1439, ext={EN=ArticleExt(id=1324044596493296426, articleId=1324044596199695145, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Potential categories, influencing factors, and improvement strategies of traditional Chinese medicine health literacy among Chinese residents: Based on latent profile analysis, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To identify latent classes of traditional Chinese medicine (TCM) health literacy among Chinese residents and examine influencing factors, in order to inform targeted promotion strategies.

Methods

A combined stratified and typical sampling approach was used to survey 1 259 residents from Hangzhou, Hefei, and Sanming. Latent profile analysis (LPA) identified TCM health literacy classes, and logistic regression analyzed influencing factors.

Results

Residents' TCM health literacy has reached 57.9%. Four latent classes were identified: knowledge-belief separation (18.6%), basic deficiency (29.4%), balanced literacy (34.3%), and ideal exemplary (17.7%). Significant influencing factors included age, monthly income, medical payment method, self-rated health, and awareness of TCM health service and insurance reimbursement.

Conclusion

There is significant group heterogeneity in TCM health literacy among Chinese residents. An intervention system covering policy guidance, community implementation and individual participation is required, featuring differentiated strategies based on knowledge popularization, belief cultivation, behavior transformation and role modeling, so as to foster overall improvement in TCM health literacy.

, authors=Wen-ting WANG1, Xiang-qi FU2, Jian-ping REN3, Sheng WANG2, authorsList=Wen-ting WANG, Xiang-qi FU, Jian-ping REN, Sheng WANG, authorCompany=null, correspAuthors=Sheng WANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1324044598837912367, articleId=1324044596199695145, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=基于潜在剖面分析的我国居民中医药健康素养类别、影响因素和提升策略研究, columnId=1228016568014139551, journalTitle=现代预防医学, columnName=卫生政策与管理, runingTitle=null, highlight=null, articleAbstract=
目的

探讨我国居民中医药健康素养的潜在类别及影响因素,为制定素养提升策略提供依据。

方法

采用分层抽样与典型抽样相结合的方法,对浙江杭州、安徽合肥与福建三明共1 259名居民进行问卷调查,运用潜在剖面分析识别居民中医药健康素养的潜在类别,并通过logistic回归分析其影响因素。

结果

居民中医药健康素养具备率为57.9%,分为知信分离型(18.6%)、基础薄弱型(29.4%)、素养均衡型(34.3%)和理想典范型(17.7%)等四个潜在类别,年龄、月收入、医疗费用支付方式、自评健康状况、中医药服务知晓情况及医保报销知晓情况是潜在类别归属的影响因素。

结论

我国居民中医药健康素养存在明显的群体异质性,应构建覆盖“政策引导-社区实施-个体参与”的多层次、差异化干预体系,从知识普及、信念建立、行为转化及榜样示范等方面精准施策,推动健康素养整体提升。

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王文婷(1991—),女,博士,副研究员,研究方向:卫生服务体系与政策研究

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汪胜,E-mail:
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Development and preliminary application of a residents' TCM Health Literacy Questionnaire[D]. Nanchang: Jiangxi University of Chinese Medicine, 2022. (In Chinese), articleTitle=Development and preliminary application of a residents' TCM Health Literacy Questionnaire, refAbstract=null), Reference(id=1324044605297140584, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[7], rfOrder=12, authorNames=新华社, journalName=null, refType=null, unstructuredReference=新华社. 我国公民中医药健康文化素养水平达26.85%[EB/OL]. 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(In Chinese), articleTitle=The trend and influencing factors of health literacy among residents in Gongshu District, Hangzhou (2019-2023), refAbstract=null)], funds=[Fund(id=1324044603757831003, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, awardId=2024ZF105; 2024ZF114, language=CN, fundingSource=浙江省中医药科技计划项目(2024ZF105; 2024ZF114), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324044599064404784, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, xref=1., ext=[AuthorCompanyExt(id=1324044599072793393, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, companyId=1324044599064404784, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Affiliated Hangzhou First People's Hospital, Westlake University School of Medicine, Hangzhou, Zhejiang 310006, China), AuthorCompanyExt(id=1324044599081182002, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, companyId=1324044599064404784, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.西湖大学医学院附属杭州市第一人民医院,浙江 杭州 310006)]), AuthorCompany(id=1324044599148290867, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, xref=2., ext=[AuthorCompanyExt(id=1324044599156679476, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, companyId=1324044599148290867, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.杭州师范大学公共卫生与护理学院)]), AuthorCompany(id=1324044599240565557, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, xref=3., ext=[AuthorCompanyExt(id=1324044599248954166, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, companyId=1324044599240565557, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.杭州师范大学公共管理学院)])], figs=[ArticleFig(id=1324044602742809427, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, language=EN, label=Fig. 1, caption=Score profiles of the four-class latent profile model, figureFileSmall=Fb0+wMDOj2tf6nfEdug0cw==, figureFileBig=WXkE+uIYedZaxYeF1y24rw==, tableContent=null), ArticleFig(id=1324044602847667028, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, language=CN, label=图1, caption=居民中医药健康素养四类潜在剖面得分分布, figureFileSmall=Fb0+wMDOj2tf6nfEdug0cw==, figureFileBig=WXkE+uIYedZaxYeF1y24rw==, tableContent=null), ArticleFig(id=1324044603111908181, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, language=EN, label=Table 1, caption=

Model fit indices for LPA of residents' TCM health literacy

, figureFileSmall=null, figureFileBig=null, tableContent=
AICBICaBICEntropyLMR(P)BLRT(P)类别概率
124 201.26824 232.09724 213.038
224 003.41324 054.79424 023.0290.626<0.001<0.0010.904/0.866
323 854.04323 925.97623 881.5050.716<0.001<0.0010.847/0.917/0.878
423 780.25323 872.73823 815.5610.8400.0002<0.0010.953/0.922/0.910/0.897
523 712.86823 825.90623 756.0230.7520.0319<0.0010.791/0.808/0.832/0.872/0.917
), ArticleFig(id=1324044603195794262, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, language=CN, label=表1, caption=

居民中医药健康素养潜在剖面分析拟合信息

, figureFileSmall=null, figureFileBig=null, tableContent=
AICBICaBICEntropyLMR(P)BLRT(P)类别概率
124 201.26824 232.09724 213.038
224 003.41324 054.79424 023.0290.626<0.001<0.0010.904/0.866
323 854.04323 925.97623 881.5050.716<0.001<0.0010.847/0.917/0.878
423 780.25323 872.73823 815.5610.8400.0002<0.0010.953/0.922/0.910/0.897
523 712.86823 825.90623 756.0230.7520.0319<0.0010.791/0.808/0.832/0.872/0.917
), ArticleFig(id=1324044603296457559, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, language=EN, label=Table 2, caption=

Univariate analysis of latent classes in residents' TCM health culture literacy [n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
项目分类知信分离型基础薄弱型素养均衡型理想典范型χ2P
性别男85(18.4)79(17.1)145(31.5)152(33.0)1.630.653
女151(18.9)139(17.4)225(28.2)283(35.5)
年龄(岁)≤3029(23.8)14(11.5)51(41.8)28(23.0)77.19<0.001
31~4563(16.5)75(19.7)94(24.7)149(39.1)
46~6090(33.0)37(13.6)68(24.9)78(28.6)
≥6154(11.2)92(19)157(32.5)180(37.3)
文化程度初中及以下91(20.4)68(15.2)139(31.1)149(33.3)24.530.004
高中或中专62(19.6)53(16.7)105(33.1)97(30.6)
大专45(22.1)40(19.6)57(27.9)62(30.4)
本科及以上38(13.1)57(19.6)69(23.7)127(43.6)
月收入(元)≤4 000146(27.9)78(14.9)148(28.3)151(28.9)69.39<0.001
4 001~8 00076(13.4)105(18.5)187(33.0)199(35.1)
>8 00114(8.3)35(20.7)35(20.7)85(50.3)
婚姻状况未婚18(13.0)21(15.2)50(36.2)49(35.5)11.480.244
已婚202(19.3)183(17.5)295(28.2)365(34.9)
离异8(23.5)3(8.8)13(38.2)10(29.4)
丧偶8(19.0)11(26.2)12(28.6)11(26.2)
职业学生22(26.8)12(14.6)24(29.3)24(29.3)84.68<0.001
企业员工42(16.6)46(18.2)74(29.2)91(36.0)
公务员/事业单位41(22.9)40(22.3)41(22.9)57(31.8)
个体工商28(28.6)13(13.3)32(32.7)25(25.5)
自由职业30(23.6)16(12.6)40(31.5)41(32.3)
农业劳动者29(22.1)20(15.3)36(27.5)46(35.1)
离退休44(11.3)71(18.3)123(31.6)151(38.8)
医疗费用支付方式城乡居民基本医保94(24.6)55(14.4)94(24.6)139(36.4)144.33<0.001
城镇职工基本医保69(10.3)138(20.6)213(31.8)249(37.2)
商业医保59(51.8)7(6.1)37(32.5)11(9.6)
新农合医保5(11.4)11(25.0)10(22.7)18(40.9)
自费9(18.0)7(14.0)16(32.0)18(36.0)
慢性病状况无156(21.6)122(16.9)195(27.0)249(34.5)21.600.010
一种50(13.7)71(19.5)107(29.3)137(37.5)
两种24(19.5)18(14.6)47(38.2)34(27.6)
三种及以上6(12.2)7(14.3)21(42.9)15(30.6)
自评健康状况好209(24)144(16.5)236(27.1)283(32.5)70.329<0.001
一般10(5.1)44(22.4)51(26.0)91(46.4)
差17(8.9)30(15.7)83(43.5)61(31.9)
中医药服务知晓度是172(20.8)172(19.8)202(24.4)289(34.9)34.53<0.001
否64(14.8)64(12.5)168(38.9)146(33.8)
医保报销知晓度是155(27.0)113(19.7)132(23.0)175(30.4)61.50<0.001
否81(11.8)105(15.4)238(34.8)260(38.0)
收费情况知晓度是159(23.8)127(19.0)161(24.1)221(33.1)36.20<0.001
否77(13.0)91(15.4)209(35.4)214(36.2)
), ArticleFig(id=1324044603401315160, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, language=CN, label=表2, caption=

居民中医药健康文化素养潜在类别的单因素分析[名(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
项目分类知信分离型基础薄弱型素养均衡型理想典范型χ2P
性别男85(18.4)79(17.1)145(31.5)152(33.0)1.630.653
女151(18.9)139(17.4)225(28.2)283(35.5)
年龄(岁)≤3029(23.8)14(11.5)51(41.8)28(23.0)77.19<0.001
31~4563(16.5)75(19.7)94(24.7)149(39.1)
46~6090(33.0)37(13.6)68(24.9)78(28.6)
≥6154(11.2)92(19)157(32.5)180(37.3)
文化程度初中及以下91(20.4)68(15.2)139(31.1)149(33.3)24.530.004
高中或中专62(19.6)53(16.7)105(33.1)97(30.6)
大专45(22.1)40(19.6)57(27.9)62(30.4)
本科及以上38(13.1)57(19.6)69(23.7)127(43.6)
月收入(元)≤4 000146(27.9)78(14.9)148(28.3)151(28.9)69.39<0.001
4 001~8 00076(13.4)105(18.5)187(33.0)199(35.1)
>8 00114(8.3)35(20.7)35(20.7)85(50.3)
婚姻状况未婚18(13.0)21(15.2)50(36.2)49(35.5)11.480.244
已婚202(19.3)183(17.5)295(28.2)365(34.9)
离异8(23.5)3(8.8)13(38.2)10(29.4)
丧偶8(19.0)11(26.2)12(28.6)11(26.2)
职业学生22(26.8)12(14.6)24(29.3)24(29.3)84.68<0.001
企业员工42(16.6)46(18.2)74(29.2)91(36.0)
公务员/事业单位41(22.9)40(22.3)41(22.9)57(31.8)
个体工商28(28.6)13(13.3)32(32.7)25(25.5)
自由职业30(23.6)16(12.6)40(31.5)41(32.3)
农业劳动者29(22.1)20(15.3)36(27.5)46(35.1)
离退休44(11.3)71(18.3)123(31.6)151(38.8)
医疗费用支付方式城乡居民基本医保94(24.6)55(14.4)94(24.6)139(36.4)144.33<0.001
城镇职工基本医保69(10.3)138(20.6)213(31.8)249(37.2)
商业医保59(51.8)7(6.1)37(32.5)11(9.6)
新农合医保5(11.4)11(25.0)10(22.7)18(40.9)
自费9(18.0)7(14.0)16(32.0)18(36.0)
慢性病状况无156(21.6)122(16.9)195(27.0)249(34.5)21.600.010
一种50(13.7)71(19.5)107(29.3)137(37.5)
两种24(19.5)18(14.6)47(38.2)34(27.6)
三种及以上6(12.2)7(14.3)21(42.9)15(30.6)
自评健康状况好209(24)144(16.5)236(27.1)283(32.5)70.329<0.001
一般10(5.1)44(22.4)51(26.0)91(46.4)
差17(8.9)30(15.7)83(43.5)61(31.9)
中医药服务知晓度是172(20.8)172(19.8)202(24.4)289(34.9)34.53<0.001
否64(14.8)64(12.5)168(38.9)146(33.8)
医保报销知晓度是155(27.0)113(19.7)132(23.0)175(30.4)61.50<0.001
否81(11.8)105(15.4)238(34.8)260(38.0)
收费情况知晓度是159(23.8)127(19.0)161(24.1)221(33.1)36.20<0.001
否77(13.0)91(15.4)209(35.4)214(36.2)
), ArticleFig(id=1324044603497784153, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, language=EN, label=Table 3, caption=

Logistic regression analysis of the latent profiles for residents' TCM health literacy

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自变量βSEWald χ2POR值(95%CI)
C2vsC1a
年龄≤30岁-1.5850.5179.4080.0020.205(0.074~0.564)
46~60岁-1.3100.33914.906<0.0010.270(0.139~0.525)
月收入/元≤4 000-1.5270.41913.264<0.0010.217(0.096~0.494)
医疗费用支付方式商业医保-1.8730.6987.1980.0070.154(0.039~0.604)
中医药服务知晓度是0.8400.2769.2540.0022.317(1.348~3.981)
医保报销知晓度是-0.5540.2574.6680.0310.575(0.347~0.950)
C3vsC1a
年龄46~60岁-1.1330.29514.765<0.0010.322(0.181~0.574)
月收入/元≤4 000-0.9470.3955.7350.0170.388(0.179~0.842)
自评健康状况好-0.9760.3467.9500.0050.377(0.191~0.743)
C4vsC1a
年龄≤30岁-1.3190.4528.5170.0040.267(0.110~0.648)
46~60岁-0.9220.2939.9190.0020.398(0.224~0.706)
月收入/元≤4 000-1.8710.38224.026<0.0010.154(0.073~0.325)
4 001~8 000-0.9510.3587.0630.0080.386(0.192~0.779)
医疗费用支付方式商业医保-2.3120.59215.261<0.0010.099(0.031~0.316)
自评健康状况一般0.9920.4734.4090.0362.697(1.068~6.810)
中医药服务知晓度是0.5970.2445.9800.0141.817(1.126~2.933)
医保报销知晓度是-0.8430.23313.103<0.0010.431(0.273~0.680)
), ArticleFig(id=1324044603594253146, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044596199695145, language=CN, label=表3, caption=

居民中医药健康素养潜在类别的logisitic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
自变量βSEWald χ2POR值(95%CI)
C2vsC1a
年龄≤30岁-1.5850.5179.4080.0020.205(0.074~0.564)
46~60岁-1.3100.33914.906<0.0010.270(0.139~0.525)
月收入/元≤4 000-1.5270.41913.264<0.0010.217(0.096~0.494)
医疗费用支付方式商业医保-1.8730.6987.1980.0070.154(0.039~0.604)
中医药服务知晓度是0.8400.2769.2540.0022.317(1.348~3.981)
医保报销知晓度是-0.5540.2574.6680.0310.575(0.347~0.950)
C3vsC1a
年龄46~60岁-1.1330.29514.765<0.0010.322(0.181~0.574)
月收入/元≤4 000-0.9470.3955.7350.0170.388(0.179~0.842)
自评健康状况好-0.9760.3467.9500.0050.377(0.191~0.743)
C4vsC1a
年龄≤30岁-1.3190.4528.5170.0040.267(0.110~0.648)
46~60岁-0.9220.2939.9190.0020.398(0.224~0.706)
月收入/元≤4 000-1.8710.38224.026<0.0010.154(0.073~0.325)
4 001~8 000-0.9510.3587.0630.0080.386(0.192~0.779)
医疗费用支付方式商业医保-2.3120.59215.261<0.0010.099(0.031~0.316)
自评健康状况一般0.9920.4734.4090.0362.697(1.068~6.810)
中医药服务知晓度是0.5970.2445.9800.0141.817(1.126~2.933)
医保报销知晓度是-0.8430.23313.103<0.0010.431(0.273~0.680)
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基于潜在剖面分析的我国居民中医药健康素养类别、影响因素和提升策略研究
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王文婷 1 , 傅相绮 2 , 任建萍 3 , 汪胜 2
现代预防医学 | 卫生政策与管理 2026,53(8): 1434-1439
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现代预防医学 |卫生政策与管理 2026 , 53 (8) : 1434 -1439
基于潜在剖面分析的我国居民中医药健康素养类别、影响因素和提升策略研究
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王文婷1, 傅相绮2, 任建萍3, 汪胜2
作者信息
  • 1.西湖大学医学院附属杭州市第一人民医院,浙江 杭州 310006
  • 2.杭州师范大学公共卫生与护理学院
  • 3.杭州师范大学公共管理学院
通讯作者:
汪胜,E-mail:
作者简介:

王文婷(1991—),女,博士,副研究员,研究方向:卫生服务体系与政策研究

Potential categories, influencing factors, and improvement strategies of traditional Chinese medicine health literacy among Chinese residents: Based on latent profile analysis
Wen-ting WANG1, Xiang-qi FU2, Jian-ping REN3, Sheng WANG2
Affiliations
  • Affiliated Hangzhou First People's Hospital, Westlake University School of Medicine, Hangzhou, Zhejiang 310006, China
出版时间: 2026-04-25 doi: 10.20043/j.cnki.MPM.202511367
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目的

探讨我国居民中医药健康素养的潜在类别及影响因素,为制定素养提升策略提供依据。

方法

采用分层抽样与典型抽样相结合的方法,对浙江杭州、安徽合肥与福建三明共1 259名居民进行问卷调查,运用潜在剖面分析识别居民中医药健康素养的潜在类别,并通过logistic回归分析其影响因素。

结果

居民中医药健康素养具备率为57.9%,分为知信分离型(18.6%)、基础薄弱型(29.4%)、素养均衡型(34.3%)和理想典范型(17.7%)等四个潜在类别,年龄、月收入、医疗费用支付方式、自评健康状况、中医药服务知晓情况及医保报销知晓情况是潜在类别归属的影响因素。

结论

我国居民中医药健康素养存在明显的群体异质性,应构建覆盖“政策引导-社区实施-个体参与”的多层次、差异化干预体系,从知识普及、信念建立、行为转化及榜样示范等方面精准施策,推动健康素养整体提升。

中医药  /  健康素养  /  潜在剖面分析  /  提升策略
Objective

To identify latent classes of traditional Chinese medicine (TCM) health literacy among Chinese residents and examine influencing factors, in order to inform targeted promotion strategies.

Methods

A combined stratified and typical sampling approach was used to survey 1 259 residents from Hangzhou, Hefei, and Sanming. Latent profile analysis (LPA) identified TCM health literacy classes, and logistic regression analyzed influencing factors.

Results

Residents' TCM health literacy has reached 57.9%. Four latent classes were identified: knowledge-belief separation (18.6%), basic deficiency (29.4%), balanced literacy (34.3%), and ideal exemplary (17.7%). Significant influencing factors included age, monthly income, medical payment method, self-rated health, and awareness of TCM health service and insurance reimbursement.

Conclusion

There is significant group heterogeneity in TCM health literacy among Chinese residents. An intervention system covering policy guidance, community implementation and individual participation is required, featuring differentiated strategies based on knowledge popularization, belief cultivation, behavior transformation and role modeling, so as to foster overall improvement in TCM health literacy.

Traditional Chinese medicine  /  Health literacy  /  Latent profile analysis  /  Improvement strategies
王文婷, 傅相绮, 任建萍, 汪胜. 基于潜在剖面分析的我国居民中医药健康素养类别、影响因素和提升策略研究. 现代预防医学, 2026 , 53 (8) : 1434 -1439 . DOI: 10.20043/j.cnki.MPM.202511367
Wen-ting WANG, Xiang-qi FU, Jian-ping REN, Sheng WANG. Potential categories, influencing factors, and improvement strategies of traditional Chinese medicine health literacy among Chinese residents: Based on latent profile analysis[J]. Modern Preventive Medicine, 2026 , 53 (8) : 1434 -1439 . DOI: 10.20043/j.cnki.MPM.202511367
中医药健康素养指获取、理解中医药基本理念、中医药健康生活方式、中医药公众适宜方法、中医药文化常识,以维护和促进自身健康、提高文化素质的能力[1],该素养水平的提升对公民自身个人健康、国家卫生健康事业与中医药事业高质量发展均具有重要意义[2]。近年来,国家持续强化政策引导,先后在《中医药发展战略规划纲要(2016-2030年)》(国发〔2016〕15号)、《“十四五”中医药发展规划》(国办发〔2022〕5号)等政策文件中强调提升公民中医药健康文化素养。国家卫生健康委印发《全民健康素养提升三年行动方案(2024-2027年)》进一步将其列为重要目标[3]。然而,现实中我国居民对中医药知识的掌握程度、信念认同度以及行为转化能力仍普遍偏低,整体素养水平亟待提升。
潜在剖面分析(Latent profile analysis,LPA)是一种基于个体观测指标进行群体异质性识别与同质性分类的统计方法,能够揭示不同潜在类别的特征差异[4]。目前国内中医药健康素养研究多局限于整体描述或单维比较,缺乏对人群内在异质结构的深入剖析,样本也多来源于单一地区,缺乏跨区域、多层次的抽样支持,制约了结论的推广价值。基于此,本研究采用分层抽样方法,选取浙江、安徽、福建三省居民为研究对象,采用潜在剖面分析法,识别我国居民中医药健康素养的潜在类别,分析不同类别群体的典型特征及其影响因素,以期为构建分层、精准的中医药健康素养提升策略提供实证依据。
本研究采用分层抽样与典型抽样相结合的方法,综合考虑区域经济发展与中医药事业发展差异,选取浙江杭州、安徽合肥与福建三明作为样本城市,每个城市选取8家街道社区卫生服务中心及所辖社区,共24个调查单位。调查对象纳入标准:①社区居住时间≥6个月;②年龄≥18岁且无认知障碍。本研究经西湖大学医学院附属杭州市第一人民医院伦理委员会审批(【2023】科研医伦审第453号),所有调查对象均知情同意。
在文献回顾基础上,结合专家意见自行设计,包括性别、年龄、文化程度、月收入、婚姻状况、职业、医疗费用支付方式、慢性病状况、自评健康状况以及中医药服务知晓情况等共12个条目。
借鉴相关政策和文献[5-6],以天人合一整体观和知信行理论为指导,构建包含中医药文化知识、认知态度、行为转化三个维度的问卷框架。条目设计参考《中国公民中医药健康文化素养调查问卷》《中国公民中医药卫生保健素养》《中国公民健康素养66条》,涵盖饮食、作息、运动、心理、文化常识等方面。经6名专家两轮修订,遵循“少而精”原则,最终形成包含20个条目的中医药健康素养问卷,适用于大规模快速调查。
评分标准如下:文化维度(Q1-Q10),分值范围0-50分,答对计5分,错误计0分;态度维度(Q11-Q15),分值范围0-25分,采用1-5分Likert式评分(1=非常不愿意,5=非常愿意);行为维度(Q16-Q20),分值范围0-25分,Q16-Q19按频率计1-5分(1=从不,5=总是),Q20答“是”计5分,“否”计0分。总得分≥60判定为具备中医药健康素养;各维度得分达到其总分60%及以上判定具备该维度素养。预调研显示,Cronbach α为0.911,KMO=0.850,Bartlett检验P<0.01,累计方差贡献率76.649%,信效度良好。
现场一对一调查社区居民。2024年中医药健康文化素养水平为26.85%[7],按照样本量公式,设定Z=1.96,E=0.03,最低样本量为839人。为提高信效度,适当扩大样本规模,每个社区随机调查50~60人,共回收有效问卷1 259份。
数据分析采用Mplus 8.3及SPSS 27.0软件。最优模型判断标准如下:赤池信息准则(AIC)、贝叶斯信息准则(BIC)和校正后贝叶斯信息准则(aBIC)越小表明拟合越好;熵(Entropy)≥0.80提示分类精准性较高;似然比检验(LMR)与Bootstrap似然比检验(BLRT)P<0.05,支持k类模型优于k-1类[8]。定性资料以频数和百分比表示,组间比较采用Pearson χ2检验、Fisher精确检验或蒙特卡洛检验;采用logistic回归分析潜在类别的影响因素,以P<0.05为差异有统计学意义。
共调查1 259例居民,其中杭州市482例,合肥市465例,三明市312例。人口学特征显示,男性461例(36.6%),女性798例(63.3%);年龄集中于31-45岁(30.2%)和≥61岁(38.3%);学历以初中及以下(35.5%)和高中或中专(25.1%)为主;月收入以4 001–8 000元(45.0%)为主;婚姻状况以已婚为主(82.8%)。在健康与医疗相关特征方面,53.1%者为城镇职工基本医疗保险;57.3%者未患有慢性病;69.2%者自评健康状况为“好”;知晓中医药服务者占65.6%。
居民中医药健康素养总分为(62.07±12.25)分,具有中医药健康素养者729例(57.9%)。各维度标准化得分及达标情况如下:知识维度(63.71±16.78)分,达标681例(54.0%);态度维度(67.92±21.18)分,达标890例(70.6%);行为维度(52.95±18.98)分,达标581例(41.1%)。
单因素分析显示,地区、年龄、职业、医疗费用支付方式、患慢性病情况、自评健康状况、中医药服务知晓度对中医药健康素养有显著影响(P<0.05)。多因素分析显示,杭州、合肥的居民健康素养高于三明;≤30岁的居民素养低于≥61岁居民;初中及以下学历者显著低于本科及以上学历者;城乡居民医保或商业医保群体高于自费群体;自评健康“好/比较好/一般”者高于自评健康“差”者;知晓中医药服务者高于不知晓者。
从单类别模型开始逐步拟合。随着模型数增加,AIC、BIC、aBIC值均逐渐降低,且LMR和BLRT均达显著水平(P<0.01)。当剖面数为4时,Entropy值(0.840)最接近1,分类精准性最高。结合模型可解释的实际意义,选取模型4为最佳潜在剖面模型。见表1。
结果显示,四类别在中医药知识、态度与行为三个维度得分均具有显著差异(P<0.05)。基于各类别的特征,分别命名描述如下:(1)知信分离型(18.6%):健康素养总分及态度得分均最低,但知识得分较高,呈现出“高知识、低信念”的知信分离特征。(2)基础薄弱型(29.4%):知识与行为得分均最低,整体素养基础薄弱。(3)素养均衡型(34.3%):三个维度得分较均衡,整体表现居中,无明显短板但仍有提升空间。(4)理想典范型(17.7%):三个维度得分均最高,展现出知识全面、信念稳定、行为积极的理想状态。见图1。
结果显示,不同潜在类别居民在年龄、文化程度、月收入、职业、医疗费用支付方式、慢性病状况、自评健康状况、中医药服务知晓度、医保报销知晓度、收费情况知晓度方面差异均具有统计学意义(P<0.01)。见表2。
以中医药健康素养潜在类别为因变量,单因素分析有意义者为自变量进行多因素logistics回归分析。结果显示,年龄、月收入、医疗费用支付方式、自评健康状况、中医药服务知晓度和医保报销知晓度是潜在类别的影响因素(P<0.05)。见表3。
居民中医药健康素养整体水平较既往研究[9]有所提升,反映出近年来政策推动与宣传教育已见成效。但各维度存在差异:知识与态度得分较高,健康行为得分明显偏低,且受地区、年龄、教育、经济水平与健康感知等多重因素影响。
我国居民中医药健康素养可分为四个类别。“知信分离型”居民专业知识掌握较好,但尚未形成稳定信念,健康行为转化不足,符合“知-信-行”理论中从知识获取到信仰形成,再到行为改变是一个渐进过程,信念确立与行为转化需要更长时间的积累与持续推动[10]。“基础薄弱型”居民虽认同中医药价值,但因知识储备不足,限制了行为转化,反映出“知”的欠缺是关键瓶颈。“素养均衡型”占比最高,知识、信念与行为三个维度发展相对均衡,但行为维度仍偏低,表明即使在认知与态度协调的群体中,将健康信念有效转化为稳定、持续的行为路径仍不畅通。“理想典范型”具备较完整的知识-信念-行为结构,展现出良好的主动性与行为执行力,但占比最低,表明当前具备全面中医药健康素养者仍属少数。
多因素分析揭示了年龄、月收入、医疗费用支付方式等对中医药健康素养类别的影响。其中,46~60岁的人群归属于“知信分离型”的概率更高,与既有研究[11]一致。原因在于,该年龄段个体虽获取中医药知识渠道广泛,但行为转化前常综合评估时间、经济成本与健康收益,决策更为审慎,信念形成更缓慢,知识难以迅速转化为实际行动。
经济收入是影响居民能否突破“知信分离”状态的关键因素,月收入≤4 000元者归属为“理想典范型”的概率仅为“知信分离型”的15.4%,且与其他类别均成负相关,与既有研究[12]相似。收入较高者通常能获取更优质的医疗资源与健康信息,具备更强的健康意识,从而更易实现从认知态度到行为的完整转化。
研究发现,商业保险或知晓医保报销政策的群体更倾向于“知信分离型”,这一发现对传统认知形成补充。其原因可能如下:一是该群体受现代医学观念影响,对中医存在“经验医学”等刻板印象,对其在整体调节与慢病防治中的独特价值认知不足;二是尽管支付能力较强,但现有保险体系对中医服务覆盖有限、报销门槛较高,客观上抑制了其行为转化。
值得注意的是,自评健康为“一般”者多属于“理想典范型”,其潜在的“健康危机感”可能促使其采取积极行动。相反,自评健康为“好”的居民,其“健康优越感”反而可能弱化其改善动力,使其更易停留于“知信分离型”状态。此外,知晓中医药服务与“基础薄弱型”或“理想典范型”均呈正相关。这一看似矛盾的结果提示,若健康传播仅注重知识普及而忽视行为转化设计,反而可能加剧群体素养差距。这也反映出当前健康促进工作仍重“知”轻“行”,实践教学相对滞后[13]。
宏观层面应建立分类施策的政策支持体系。针对“知信分离型”人群,将可感知、易操作的中医药适宜技术项目纳入医保报销范围,通过政策杠杆降低体验门槛,破解“疗效疑虑”;同时,鼓励商业保险开发覆盖中医药健康服务的产品,增强服务包容性,提升该群体的信念认同与行为转化动力。对于“基础薄弱型”群体,特别是低收入居民,需完善公益性服务供给机制,逐步将中医药基础保健产品(如保健茶饮、食疗包等)、简易保健技能培训纳入基本公共卫生服务,通过专项补贴降低使用成本,配合发放中医药科普手册,提高其认知与接受度。此外,应同步建立健康素养动态监测评估体系,为持续优化分类干预提供依据。
社区层面应建设多维、友好的中医药健康支持平台。针对“基础薄弱型”人群,可设立中医药健康驿站,通过图文展示、短视频播映、方言讲座等多元化科普降低理解门槛;组织线下讲座、线上跟练、技能工作坊等,指导居民掌握穴位按压、保健操、节气养生等实用技能,促进其从认知到行为的转化。对于“素养均衡型”人群,应侧重行为巩固和风险意识提升,开展八段锦、太极剑、五禽戏等传统功法的公益培训,并结合中医体质辨识及知识竞赛等活动,帮助建立更清晰的健康认知,增强行为维持的内在动力。
社区应倡导科学、融合的中西医健康观念。例如开设“中西医协同防病”专栏,结合案例对比等形式,传递“中西医并重、优势互补”理念;在体质辨识、功法培训中融入血压、血糖等西医指标监测,引导居民建立整合的健康观,促进合理选择。
个人层面应着力提升居民的健康主体责任意识,引导其从被动接受转向主动参与。针对“知信分离型”居民,需通过持续、贴近生活的健康教育和情境体验,帮助其跨越从知晓到信任的鸿沟,认识到自身在健康管理中的主导角色。对于“素养均衡型”居民,引导其参与社区健康自测、知识竞赛、互助小组等活动,提升其自我评估能力,增强行为维持的自觉性与持续性。同时,应充分发挥“理想典范型”居民的榜样引领和同伴教育作用,鼓励其分享养生功法、善用药食同源食材等实践经验,塑造可模仿、可复制的“行动模板”,带动更多居民形成稳定、主动的健康习惯,共同营造中医药健康素养提升的良好氛围。
本研究存在以下局限:首先,研究对象以城市居民为主,乡镇及农村人群相对不足。此外,横断面设计难以进行因果推断,也无法动态观测素养的长期变化趋势。未来可纳入城乡样本,通过多阶段分层抽样与纵向跟踪,揭示“知信行”转化机制,以增强结论的普适性。
  • 浙江省中医药科技计划项目(2024ZF105; 2024ZF114)
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2026年第53卷第8期
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doi: 10.20043/j.cnki.MPM.202511367
  • 接收时间:2025-11-23
  • 首发时间:2026-11-02
  • 出版时间:2026-04-25
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  • 收稿日期:2025-11-23
基金
浙江省中医药科技计划项目(2024ZF105; 2024ZF114)
作者信息
    1.西湖大学医学院附属杭州市第一人民医院,浙江 杭州 310006
    2.杭州师范大学公共卫生与护理学院
    3.杭州师范大学公共管理学院

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2种不同金属材料的力学参数
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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