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Article(id=1240972418781606407, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240972413354176744, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202311191, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1699977600000, receivedDateStr=2023-11-15, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773800480790, onlineDateStr=2026-03-18, pubDate=1715270400000, pubDateStr=2024-05-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773800480790, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773800480790, creator=13701087609, updateTime=1773800480790, updator=13701087609, issue=Issue{id=1240972413354176744, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='9', pageStart='1537', pageEnd='1728', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773800479495, creator=13701087609, updateTime=1773800596829, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240972905568334240, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240972413354176744, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240972905568334241, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240972413354176744, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1637, endPage=1642, ext={EN=ArticleExt(id=1240972419150705201, articleId=1240972418781606407, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Comprehensive evaluation of service effect of health education institutions in China in 2022, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To evaluate the service effect of health education institutions in China, identify the existing problems, and put forward feasible solutions.

Methods

The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Rank-sum ratio (RSR) were used to evaluate the service effect of health education institutions in 31 provinces (autonomous regions and municipalities directly under the central government).

Results

In total 14 indicators for evaluating the service effectiveness of health education institutions were selected in the study. Among them, the top two index with the largest weight were the number of people covered by short messages and the number of audio and video products, while the last two were the number of host websites and the number of programs by co-operating with TV stations. The evaluation of entropy weight TOPSIS method showed that the Ci value of each region was between 0.022 and 0.665. The evaluation results of RSR method showed that the number of areas where the service effect of health education institutions was poor, average, good, and excellent were 2,13, 13, and 3, respectively. The general trend of the two results was basically consistent with that of the fuzzy joint model.

Conclusion

The fuzzy combination of entropy weight TOPSIS method and RSR method can better evaluate the service effect of health education institutions in China. There is an imbalance between the content and the region in the service of health education institutions. We should increase the total investment in health education publicity and human resources, and put forward measures according to the differences of different regions, so as to improve the service effect of health education institutions and enhance residents’ well-being and satisfaction.

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目的

评价我国健康教育机构服务效果，找出存在的问题，并给出切实可行的解决方案。

方法

采用熵权优劣解距离法（technique for order preference by similarity to an ideal solution, TOPSIS）与秩和比法（rank-sum ratio, RSR）模糊联合的方法对我国31个省（自治区、直辖市）的健康教育机构服务效果进行综合评价。

结果

研究选取14项健康教育机构服务效果评价指标。其中指标权重排名前两位为手机短信覆盖人次数、音像制品数量，后两名为主办网站数、与电视台合办栏目数。经过熵权TOPSIS法评价显示，各地区Ci值在0.022～0.665之间；RSR法评价结果显示，健康教育机构服务效果处在较差、一般、良好、优秀的地区数分别为2、13、13和3个。两者结果与模糊联合模型结果总体趋势基本一致。

结论

熵权TOPSIS法和RSR法模糊联合可以较好的评价我国健康教育机构服务效果。我国健康教育机构服务存在内容和地区不平衡的现象，应增大健康教育宣传和人力资源的总投入，针对各地区的差异提出因地制宜的措施，以提升健康教育机构服务效果，增强居民幸福感和满足感。

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张馨予，E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=XvbBNWhbQQCNlHeW2B331w==, magXml=a9x/AceXW1mf5ftXyJwwHw==, pdfUrl=null, pdf=ilnN3hp5kfZOjWjAwjZCUQ==, pdfFileSize=677385, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=zm04Doy9yLL/b0YdMvqo4Q==, mapNumber=null, authorCompany=null, fund=null, authors=

蔡文璐（2002—），女，本科在读，研究方向：预防医学

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蔡文璐（2002—），女，本科在读，研究方向：预防医学

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Evaluation index system of service effect of health education professional institutions

, figureFileSmall=null, figureFileBig=null, tableContent=
维度指标编号指标说明
健康教育服务情况技术与政策建议次数（次）X1高优指标
开展公众健康教育活动次数（次）X2高优指标
业务培训人次数（万人次）X3高优指标
媒体合作情况主办网站数（个）X4高优指标
与电视台合办栏目数（个）X5高优指标
与广播电台合办栏目数（个）X6高优指标
与报刊合办栏目数（个）X7高优指标
媒体沟通与培训次数（次）X8高优指标
宣传情况传单/折页数量（万份）X9高优指标
小册子/书籍数量（万份）X10高优指标
宣传画数量（万份）X11高优指标
音像制品数量（万份）X12高优指标
实物数量（万个）X13高优指标
手机短信覆盖人次数（万人次）X14高优指标
), ArticleFig(id=1240986274601947521, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240972418781606407, language=CN, label=表1, caption=

健康教育专业机构服务效果评价指标体系

, figureFileSmall=null, figureFileBig=null, tableContent=
维度指标编号指标说明
健康教育服务情况技术与政策建议次数（次）X1高优指标
开展公众健康教育活动次数（次）X2高优指标
业务培训人次数（万人次）X3高优指标
媒体合作情况主办网站数（个）X4高优指标
与电视台合办栏目数（个）X5高优指标
与广播电台合办栏目数（个）X6高优指标
与报刊合办栏目数（个）X7高优指标
媒体沟通与培训次数（次）X8高优指标
宣传情况传单/折页数量（万份）X9高优指标
小册子/书籍数量（万份）X10高优指标
宣传画数量（万份）X11高优指标
音像制品数量（万份）X12高优指标
实物数量（万个）X13高优指标
手机短信覆盖人次数（万人次）X14高优指标
), ArticleFig(id=1240986274824245639, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240972418781606407, language=EN, label=Table 2, caption=

Entropy method for calculating weights

, figureFileSmall=null, figureFileBig=null, tableContent=
指标信息熵值e信息效用值d权重系数w（%）
X10.779 70.220 311.90
X20.852 50.147 57.97
X30.899 90.100 15.41
X40.918 70.081 34.39
X50.921 40.078 64.24
X60.903 00.097 05.24
X70.887 80.112 26.06
X80.909 10.090 94.91
X90.881 10.118 96.42
X100.892 60.107 45.80
X110.894 40.105 65.70
X120.775 50.224 512.13
X130.881 30.118 76.41
X140.751 80.248 213.41
), ArticleFig(id=1240986274912326028, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240972418781606407, language=CN, label=表2, caption=

熵值法计算权重结果

, figureFileSmall=null, figureFileBig=null, tableContent=
指标信息熵值e信息效用值d权重系数w（%）
X10.779 70.220 311.90
X20.852 50.147 57.97
X30.899 90.100 15.41
X40.918 70.081 34.39
X50.921 40.078 64.24
X60.903 00.097 05.24
X70.887 80.112 26.06
X80.909 10.090 94.91
X90.881 10.118 96.42
X100.892 60.107 45.80
X110.894 40.105 65.70
X120.775 50.224 512.13
X130.881 30.118 76.41
X140.751 80.248 213.41
), ArticleFig(id=1240986275008795024, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240972418781606407, language=EN, label=Table 3, caption=

Calculation results of entropy weight TOPSIS evaluation

, figureFileSmall=null, figureFileBig=null, tableContent=
项正理想解距离D+负理想解距离D-相对接近度C排序结果
广东0.1080.2140.6651
四川0.1690.1830.5202
山东0.1820.1740.4903
河南0.1700.1480.4654
新疆0.2000.1640.4515
河北0.2080.1450.4116
湖北0.2160.1410.3957
湖南0.2080.1120.3508
山西0.2230.1130.3369
陕西0.2300.0990.30010
江苏0.2400.0910.27511
云南0.2550.0850.25012
内蒙古0.2390.0700.22613
江西0.2450.0710.22414
安徽0.2400.0650.21415
浙江0.2560.0610.19316
吉林0.2750.0610.18217
甘肃0.2520.0520.17218
重庆0.2570.0490.16119
贵州0.2570.0480.15720
上海0.2740.0460.14421
黑龙江0.2580.0390.13222
宁夏0.2640.0360.12023
福建0.2710.0250.08624
辽宁0.2710.0250.08525
广西0.2700.0240.08026
青海0.2750.0230.07727
西藏0.2790.0180.06028
天津0.2800.0120.04229
海南0.2850.0060.02230
北京0.2850.0060.02231
), ArticleFig(id=1240986275159789971, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240972418781606407, language=CN, label=表3, caption=

熵权TOPSIS评价计算结果

, figureFileSmall=null, figureFileBig=null, tableContent=
项正理想解距离D+负理想解距离D-相对接近度C排序结果
广东0.1080.2140.6651
四川0.1690.1830.5202
山东0.1820.1740.4903
河南0.1700.1480.4654
新疆0.2000.1640.4515
河北0.2080.1450.4116
湖北0.2160.1410.3957
湖南0.2080.1120.3508
山西0.2230.1130.3369
陕西0.2300.0990.30010
江苏0.2400.0910.27511
云南0.2550.0850.25012
内蒙古0.2390.0700.22613
江西0.2450.0710.22414
安徽0.2400.0650.21415
浙江0.2560.0610.19316
吉林0.2750.0610.18217
甘肃0.2520.0520.17218
重庆0.2570.0490.16119
贵州0.2570.0480.15720
上海0.2740.0460.14421
黑龙江0.2580.0390.13222
宁夏0.2640.0360.12023
福建0.2710.0250.08624
辽宁0.2710.0250.08525
广西0.2700.0240.08026
青海0.2750.0230.07727
西藏0.2790.0180.06028
天津0.2800.0120.04229
海南0.2850.0060.02230
北京0.2850.0060.02231
), ArticleFig(id=1240986275348533655, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240972418781606407, language=EN, label=Table 4, caption=

RSR distribution results

, figureFileSmall=null, figureFileBig=null, tableContent=
RSR分布值频数f 累积频数Σ f 平均秩次平均秩次/n*100%Probit值
0.119 81113.23.151
0.121 01226.53.482
0.163 61339.73.700
0.174 014412.93.869
0.210 815516.14.011
0.270 716619.44.135
0.286 917722.64.247
0.315 718825.84.351
0.329 519929.04.448
0.343 31101032.34.540
0.350 21111135.54.628
0.399 81121238.74.713
0.471 21131341.94.796
0.483 91141445.24.878
0.520 71151548.44.960
0.539 21161651.65.040
0.564 51171754.85.122
0.615 21181858.15.204
0.629 01191961.35.287
0.630 222120.566.15.416
0.665 91222271.05.552
0.676 31232374.25.649
0.682 01242477.45.753
0.729 31252580.65.865
0.732 71262683.95.989
0.824 91272787.16.131
0.834 11282890.36.300
0.891 71292993.56.518
0.892 91303096.86.849
0.900 91313199.2a7.406
), ArticleFig(id=1240986275516305817, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240972418781606407, language=CN, label=表4, caption=

RSR分布表格

, figureFileSmall=null, figureFileBig=null, tableContent=
RSR分布值频数f 累积频数Σ f 平均秩次平均秩次/n*100%Probit值
0.119 81113.23.151
0.121 01226.53.482
0.163 61339.73.700
0.174 014412.93.869
0.210 815516.14.011
0.270 716619.44.135
0.286 917722.64.247
0.315 718825.84.351
0.329 519929.04.448
0.343 31101032.34.540
0.350 21111135.54.628
0.399 81121238.74.713
0.471 21131341.94.796
0.483 91141445.24.878
0.520 71151548.44.960
0.539 21161651.65.040
0.564 51171754.85.122
0.615 21181858.15.204
0.629 01191961.35.287
0.630 222120.566.15.416
0.665 91222271.05.552
0.676 31232374.25.649
0.682 01242477.45.753
0.729 31252580.65.865
0.732 71262683.95.989
0.824 91272787.16.131
0.834 11282890.36.300
0.891 71292993.56.518
0.892 91303096.86.849
0.900 91313199.2a7.406
), ArticleFig(id=1240986275700855196, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240972418781606407, language=EN, label=Table 5, caption=

Binning sorting cut-offs and binning results

, figureFileSmall=null, figureFileBig=null, tableContent=
档次百分位数临界值Probit临界值RSR临界值（拟合值）分档结果
优秀>93.319>6.5>0.851河南、广东、四川
良好50.000 ～93.3195 ～6.50.497 ～0.851河北、山西、内蒙古、江苏、浙江、安徽、江西、山东、湖北、湖南、山西、甘肃、新疆
一般6.681 ～50.0003.5 ～50.142 ～0.497天津、辽宁、吉林、黑龙江、上海、福建、广西、重庆、贵州、云南、西藏、青海、宁夏
较差<6.681<3.5<0.142北京、海南
), ArticleFig(id=1240986275923153313, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240972418781606407, language=CN, label=表5, caption=

分档排序临界值及分档结果

, figureFileSmall=null, figureFileBig=null, tableContent=
档次百分位数临界值Probit临界值RSR临界值（拟合值）分档结果
优秀>93.319>6.5>0.851河南、广东、四川
良好50.000 ～93.3195 ～6.50.497 ～0.851河北、山西、内蒙古、江苏、浙江、安徽、江西、山东、湖北、湖南、山西、甘肃、新疆
一般6.681 ～50.0003.5 ～50.142 ～0.497天津、辽宁、吉林、黑龙江、上海、福建、广西、重庆、贵州、云南、西藏、青海、宁夏
较差<6.681<3.5<0.142北京、海南
), ArticleFig(id=1240986276371943844, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240972418781606407, language=EN, label=Table 6, caption=

Fuzzy joint ranking of entropy-weighted TOPSIS method and RSR method

, figureFileSmall=null, figureFileBig=null, tableContent=
地区Ci排序RSR排序0.1Ci+0.9RSR排序0.5Ci+0.5RSR排序0.9Ci+0.1RSR排序
广东0.66510.90110.87710.78310.6891
四川0.52020.89230.85520.70620.5572
山东0.49030.82550.79240.65840.5243
河南0.46540.89320.85030.67930.5084
新疆0.45150.72970.70160.59060.4795
河北0.41160.67690.65080.54470.4386
湖北0.39570.630110.607110.51390.4197
湖南0.35080.83440.78650.59250.3988
山西0.33690.68280.64790.509100.3719
陕西0.300100.73360.69070.51780.34310
江苏0.275110.666100.627100.471110.31411
云南0.250120.484180.461180.367160.27312
内蒙古0.226130.629130.589130.428120.26613
江西0.224140.630110.589120.427130.26514
安徽0.214150.615140.575140.415140.25415
浙江0.193160.539160.504160.366170.22816
吉林0.182170.164290.166280.173270.18020
甘肃0.172180.565150.526150.369150.21117
重庆0.161190.400200.376200.281200.18519
贵州0.157200.521170.485170.339180.19318
上海0.144210.271260.258260.208230.15722
黑龙江0.132220.471190.437190.302190.16621
宁夏0.120230.343220.321220.232210.14223
福建0.086240.329230.305230.208230.11024
辽宁0.085250.316240.293240.201250.10825
广西0.080260.35210.323210.215220.10726
青海0.077270.287250.266250.182260.09827
西藏0.060280.211270.196270.136280.07528
天津0.042290.174280.161290.108290.05529
海南0.022300.120310.110310.071310.03231
北京0.022310.121300.111300.072300.03230
), ArticleFig(id=1240986276715876774, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240972418781606407, language=CN, label=表6, caption=

熵权TOPSIS法和RSR法模糊联合排序

, figureFileSmall=null, figureFileBig=null, tableContent=
地区Ci排序RSR排序0.1Ci+0.9RSR排序0.5Ci+0.5RSR排序0.9Ci+0.1RSR排序
广东0.66510.90110.87710.78310.6891
四川0.52020.89230.85520.70620.5572
山东0.49030.82550.79240.65840.5243
河南0.46540.89320.85030.67930.5084
新疆0.45150.72970.70160.59060.4795
河北0.41160.67690.65080.54470.4386
湖北0.39570.630110.607110.51390.4197
湖南0.35080.83440.78650.59250.3988
山西0.33690.68280.64790.509100.3719
陕西0.300100.73360.69070.51780.34310
江苏0.275110.666100.627100.471110.31411
云南0.250120.484180.461180.367160.27312
内蒙古0.226130.629130.589130.428120.26613
江西0.224140.630110.589120.427130.26514
安徽0.214150.615140.575140.415140.25415
浙江0.193160.539160.504160.366170.22816
吉林0.182170.164290.166280.173270.18020
甘肃0.172180.565150.526150.369150.21117
重庆0.161190.400200.376200.281200.18519
贵州0.157200.521170.485170.339180.19318
上海0.144210.271260.258260.208230.15722
黑龙江0.132220.471190.437190.302190.16621
宁夏0.120230.343220.321220.232210.14223
福建0.086240.329230.305230.208230.11024
辽宁0.085250.316240.293240.201250.10825
广西0.080260.35210.323210.215220.10726
青海0.077270.287250.266250.182260.09827
西藏0.060280.211270.196270.136280.07528
天津0.042290.174280.161290.108290.05529
海南0.022300.120310.110310.071310.03231
北京0.022310.121300.111300.072300.03230
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2022年我国健康教育机构服务效果综合评价
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蔡文璐 1 , 郭鑫 1 , 李俊然 1 , 张瑶 2 , 张馨予 1
现代预防医学 | 卫生政策与管理 2024,51(9): 1637-1642
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现代预防医学 | 卫生政策与管理 2024, 51(9): 1637-1642
2022年我国健康教育机构服务效果综合评价
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蔡文璐1, 郭鑫1, 李俊然1, 张瑶2, 张馨予1
作者信息
  • 1.天津医科大学公共卫生学院，天津 300070
  • 2.四川省疾控中心

    • 蔡文璐（2002—），女，本科在读，研究方向：预防医学

通讯作者:

张馨予，E-mail:
Comprehensive evaluation of service effect of health education institutions in China in 2022
Wen-lu CAI1, Xin GUO1, Jun-ran LI1, Yao ZHANG2, Xin-yu ZHANG1
Affiliations
  • School of Public Health, Tianjin Medical University, Tianjin 300070, China
出版时间: 2024-05-10 doi: 10.20043/j.cnki.MPM.202311191
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摘要
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目的

评价我国健康教育机构服务效果，找出存在的问题，并给出切实可行的解决方案。

方法

采用熵权优劣解距离法（technique for order preference by similarity to an ideal solution, TOPSIS）与秩和比法（rank-sum ratio, RSR）模糊联合的方法对我国31个省（自治区、直辖市）的健康教育机构服务效果进行综合评价。

结果

研究选取14项健康教育机构服务效果评价指标。其中指标权重排名前两位为手机短信覆盖人次数、音像制品数量，后两名为主办网站数、与电视台合办栏目数。经过熵权TOPSIS法评价显示，各地区Ci值在0.022～0.665之间；RSR法评价结果显示，健康教育机构服务效果处在较差、一般、良好、优秀的地区数分别为2、13、13和3个。两者结果与模糊联合模型结果总体趋势基本一致。

结论

熵权TOPSIS法和RSR法模糊联合可以较好的评价我国健康教育机构服务效果。我国健康教育机构服务存在内容和地区不平衡的现象，应增大健康教育宣传和人力资源的总投入，针对各地区的差异提出因地制宜的措施，以提升健康教育机构服务效果，增强居民幸福感和满足感。

健康教育  /  优劣距离法  /  秩和比法  /  服务效果评价
Objective

To evaluate the service effect of health education institutions in China, identify the existing problems, and put forward feasible solutions.

Methods

The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Rank-sum ratio (RSR) were used to evaluate the service effect of health education institutions in 31 provinces (autonomous regions and municipalities directly under the central government).

Results

In total 14 indicators for evaluating the service effectiveness of health education institutions were selected in the study. Among them, the top two index with the largest weight were the number of people covered by short messages and the number of audio and video products, while the last two were the number of host websites and the number of programs by co-operating with TV stations. The evaluation of entropy weight TOPSIS method showed that the Ci value of each region was between 0.022 and 0.665. The evaluation results of RSR method showed that the number of areas where the service effect of health education institutions was poor, average, good, and excellent were 2,13, 13, and 3, respectively. The general trend of the two results was basically consistent with that of the fuzzy joint model.

Conclusion

The fuzzy combination of entropy weight TOPSIS method and RSR method can better evaluate the service effect of health education institutions in China. There is an imbalance between the content and the region in the service of health education institutions. We should increase the total investment in health education publicity and human resources, and put forward measures according to the differences of different regions, so as to improve the service effect of health education institutions and enhance residents’ well-being and satisfaction.

Health education  /  Superior and inferior distance method  /  Rank sum ratio method  /  Service effect evaluation
蔡文璐, 郭鑫, 李俊然, 张瑶, 张馨予. 2022年我国健康教育机构服务效果综合评价. 现代预防医学, 2024 , 51 (9) : 1637 -1642 . DOI: 10.20043/j.cnki.MPM.202311191
Wen-lu CAI, Xin GUO, Jun-ran LI, Yao ZHANG, Xin-yu ZHANG. Comprehensive evaluation of service effect of health education institutions in China in 2022[J]. Modern Preventive Medicine, 2024 , 51 (9) : 1637 -1642 . DOI: 10.20043/j.cnki.MPM.202311191
正文
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随着社会的发展，人民对健康的需求日益增加，健康教育事业的发展受到广泛重视[1]。健康教育工作在预防疾病、促进健康、提高生活质量等方面发挥着至关重要的作用。为推进健康中国政策的落实，提高全民健康素养水平，2016年10月，中共中央、国务院印发的《“健康中国2030”规划纲要》（简称“纲要”）将“普及健康生活”列为了五大重点内容的首项[2]，健康教育与健康促进被提到了一个空前未有的新层次，而健康教育的建设只有落实到各个健康教育机构的建设，才能实现“健康中国”的最终目标。通过对我国健康教育机构服务效果综合评价，将31个省份进行整体比较和排序，试分析出我国地区间健康教育机构服务效果不平衡不充分之处，提出对策与建议，创造新时代健康教育模式。
1　资料与方法
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1.1　资料来源
数据资料来源于《中国卫生健康统计年鉴（2022）》，其中，健康教育专业机构指省级、市（州）和县（区、县级市）级健康教育专业机构，包括独立健康教育所、隶属于疾控中心或卫生健康委等的健康教育所（科）。本文选取健康教育服务情况、媒体合作情况、宣传情况三个维度的14项指标进行评价，所选指标均为国家卫健委对我国健康教育专业机构服务情况的评价指标体系。均为高优指标，见表1。
1.2　研究方法
1.2.1　熵权TOPSIS法
（1）权重计算[3]
首先，将健康教育机构效果评价指标的原始数据进行无量纲化处理及归一化处理，并构建相应的决策矩阵。公式为。应用熵值法确定处理后数据的指标权重可使其更具有客观性、可比较性。
其次，根据所构建的决策矩阵计算信息熵及信息效用值。评价指标的信息熵值越低，表明变异度越大，第k项指标等的信息熵值公式为，其中，fij为第i个评价对象的第j个指标值占该指标总值的比重，rij为评价对象i在第j项指标的值，k与样本量的大小有关，常取k=1/ln n。第j项指标的信息效用值为dj=1-ej。
最后，根据信息效用值计算对应的指标权重，信息效用值越大，则表明该指标越重要。第j项指标的权重为。
（2）计算加权欧氏距离　根据权重规格化值确定正负理想解，将决策矩阵中指标的最大值与最小值记作最优解Z+和最劣解Z-。通过正负理想解计算加权欧氏距离。公式如下：
（3）计算相对接近度　相对接近度得分越高，表明该对象越接近理想值，评价结果越好，反之则评价效果越差。公式如下：
1.2.2　秩和比法
秩和比法（rank-sum radio，RSR法）常见于卫生资源配置评价，于1988年被我国著名统计学家田凤调[4]教授提出。其核心思想是将n个对象、m个指标构建成一个n×m的矩阵，将各指标的秩次作为一个无量纲的统计量，即为RSR。其次，通过最小二乘法拟合回归方程，判断其拟合程度及是否具有统计学意义，若拟合程度较好并具有统计学意义，即可对秩和比值排序和分档，并对不同档次间的差异性进行分析。
1.2.3　熵权TOPSIS和和RSR法的模糊联合
基于模糊联合（FUZZY SET）理论[5]与熵权TOPSIS法、RSR法相结合的方法对上述两种方法进行验证，设置Ci与RSR的权重比为W1∶W2，即求W1Ci∶W2RSR，根据W1、W2比值分为3档，即将Ci∶RSR分别设为0.1∶0.9、0.5∶0.5、0.9∶0.1，分别计算出其值并排序，以此保证其结果的科学性[5]。
2　结果
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2.1　熵值法计算权重
将指标进行同趋化和归一化处理，通过熵值法进行TOPSIS权重值计算，结果见表2。权重系数从大到小依次为X14手机短信覆盖人次数、X12音像制品数量、X1技术与政策建议次数、X2开展公众健康教育活动次数、X9传单/折页数量、X13实物数量、X7与报刊合办栏目数、X10小册子/书籍数量、X11宣传画数量、X3业务培训人次数、X6与广播电台合办栏目数、X8媒体沟通与培训次数、X4主办网站数、X5与电视台合办栏目数，分别为13.41%、12.13%、11.90%、7.97%、6.42%、6.41%、6.06%、5.80%、5.70%、5.41%、5.24%、4.91%、4.39%、4.24%。
2.2　熵权TOPSIS分析
对14个指标、31个对象的加权后的数据进行TOPSIS分析。通过计算出正负理想解值及其距离值Di+和Di-。根据Di+和Di-值，最终得出各评价对象与最优方案的接近程度Ci，该值越大说明该省的健康教育机构服务效果越接近最优标准。对Ci的值进行排序得到的结果显示，广东省的健康教育机构服务效果最接近最优标准，北京市的健康教育机构服务效果离最优标准最远。见表3。
2.3　RSR分析
通过计算RSR值，将RSR值从小到大进行排序，根据组别频数，得到各组的秩次R，同时计算平均秩次以及向下累计频率。通过《百分数与概率单位对照表》查找与向下累计频率P对应的概率单位Probit。见表4。
以Probit为自变量，RSR分布值为因变量，计算直线回归方程。结果为RSR=-0.685+0.236*Probit（F=643.396，P<0.001），说明拟合方程的差异有统计学意义。结合此回归模型公式得到31个省份RSR值的拟合值，最终的分档排序结果见表5。我国31个省份被分为四个档次，其中河南、广东、四川为优秀水平，占所有被统计省份的9.677%；河北、山西、内蒙古等13个地区为良好水平，占总数的41.935%；天津、辽宁、吉林等13个地区为一般水平，占总数的41.935%；北京、海南地区为较差水平，占总数的6.452%。
2.4　熵权TOPSIS法和RSR法模糊联合
根据模糊联合理论，将Ci与RSR的权重分别设为W1、W2,求W1Ci∶W2RSR,并将比值分为3档，即Ci∶RSR分别为0.1∶0.9、0.5∶0.5、0.9∶0.1,计算结果均处在（0,1）之间，数字越接近1越好，排序结果见表6。
使用0.1Ci+0.9RSR模糊联合，计算出排名前五的地区为广东、四川、河南、山东、湖南，排名后五的地区为西藏、吉林、天津、北京、海南。使用0.5Ci+0.5RSR模糊联合，计算得出排名前五的地区为广东、四川、河南、山东、湖南，排名后五的地区为吉林、西藏、天津、北京、海南。使用0.9Ci+0.1RSR模糊联合，计算得出排名前五的地区为广东、四川、山东、河南、新疆，排名后五的地区为青海、西藏、天津、北京、海南。
将模糊联合的排序结果与熵权TOPSIS法和RSR法得到的排序结果相对比，所求得的数值不同，且排序存在差异，但总体趋势相同。结果显示，广东、四川、河南等排名均较高，健康教育机构服务效果较好；北京、天津、海南等排名均靠后，健康教育机构服务效果较差。
个别地区存在特殊现象。在不同权重比例下，上海、云南等地区，三种比例分布排序差异较大。例如，上海在三种比例下的计算结果分别为0.258、0.208、0.157，而排名分别为第26名、第23名、第22名。Ci值占比越大时排名越靠前，说明上海地区部分指标偏低，与其他地区差距较大，健康教育机构服务内容不平衡，存在极端值。
3　讨论
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3.1　熵权TOPSIS法和RSR法模糊联合的应用价值
熵权TOPSIS法通过引入信息熵的概念，对各指标权重进行客观、合理的分配，规避了主观赋予权重值的不确定性，全面利用各指标原始数据的信息对评价对象进行优劣排序，但该方法无法实现分档功能[6-7]；RSR法是一种利用秩次的排序方法，它考虑了指标的变异程度，但无法解决指标本身存在的问题，例如样本分布不均、极端值等情况。
将熵权TOPSIS法和RSR法模糊联合，可以充分利用两种方法的优势，既还原了真实数据，又实现了分档功能，使评价结果更综合、客观、全面。该种多方法联合的模型已成熟应用于卫生服务效果评价，并取得了较为丰富的研究成果。如王芊芊等[8]学者对我国31个省份的社区卫生服务中心医疗服务质量进行综合评价，并得出我国地区间社区卫生服务中心医疗服务质量发展不均衡的结论；朱艳等[9]学者运用这种方法，结合国家护理质量数据平台中的15项护理指标，对安徽省2016—2019年护理质量进行评价并得到验证；李贞等[10]学者采用该方法对广西各地市妇幼保健服务质量进行评价，得出降低孕产妇死亡率是广西妇幼卫生保健工作的难点与重点的结论。
3.2　健康教育机构服务的内容不平衡
从熵权法计算得到的指标权重可以看出，在健康教育的实施过程中，往往存在一些方面得到较多的关注和资源投入，而其他方面则相对忽视或缺乏足够的支持。根据权重计算的结果来看，健康教育服务情况中，技术政策建议、开展公众健康教育活动及手机短信覆盖方面较为积极，而与媒体合办栏目、媒体沟通与培训、相关业务培训开展较差。究其原因可能是国家近年出台多项关于健康教育活动政策，如《关于服务乡村振兴促进家庭健康行动的实施意见》《中小学健康教育指导纲要》等，多方面、多层次、多阶段的落实健康教育活动开展，从而提升公众对健康教育的认识及接受程度，积极进行健康教育技术咨询及政策建议；另一方面，电视台、广播电台及报刊等旧媒介受时间、空间的限制，受众只能被动接受而无法进行及时有效的反馈，开展健康教育服务较为困难，而手机短信通过将健康教育信息碎片化，能较为便利对群众进行健康教育宣传。同时在传播材料制作方面，音像制品服务情况较好，但由于纸质媒体的传播模式相对单一，无法满足当今社会人们获取多元化信息的需求，难以吸引受众眼球，故而纸质传播材料所占比重均较小。综上，唯有传统媒介在传播内容、传播形式上与新媒体融合发展，才能突破困局，获得新机遇、新发展，让受众找到适合自己的媒介获取所需的健康教育信息与产品[11]，提升媒体宣传对健康教育服务效果的影响。
3.3　健康教育机构服务效果存在地域差异
在健康中国战略背景下，我国积极推动健康教育机构的建设及发展，并取得了积极地意义，但我国健康教育机构服务的整体兴起掩盖了我国部分地区的发展欠缺，基于熵权TOPSIS和RSR法模糊联合的评价结果验证了我国健康教育机构服务存在地区之间不平衡的问题。广东省健康教育机构服务效果位居首位，2023年4月20日，《中共广东省委广东省人民政府关于推进卫生健康高质量发展的意见》公布了有关健康教育的十个方面31个重大举措，以创建高质量发展示范省为牵引[12]，创造了健康教育事业发展的“广东经验”；自“西部大开发”以来，政府开始关注西部地区的经济发展，《国务院关于实施西部大开发若干政策措施的通知》《中共中央国务院关于新时代推进西部大开发形成新格局的指导意见》等一系列政策应运而生[13]，经济发展带动了西部地区居民健康素养的提升，健康教育机构的建设因此得以提升。除青海、西藏等由于人口密度较小而导致该地区在健康教育方面的投入低于西部地区平均水平，西部其余地区健康机构服务效果均位于良好水平；而部分医疗机构服务水平较高的地区，如北京、天津、上海等，健康教育机构服务效果并不与之相匹配，究其原因，可能与其生活节奏快、流动人口比重大相关。一方面，快节奏生活无形中加剧了竞争压力，使得人们没有过多精力关注健康教育宣传及活动；另一方面，流动人口获得公共卫生服务可能存在文化壁垒，方言一定程度的阻碍了流动人口获得健康教育服务[14]。由于流动人口较多且流动人口接触健康教育的途径比较单一，多为社区健康教育，而处于同一社区的户籍人口和流动人口健康教育项目的覆盖面存在显著差异，如职业病防治、性病/艾滋病防治、结核病防治、心理健康、慢性病防治等覆盖面都是户籍人口显著大于流动人口，仅有少数如生殖健康与避孕、妇幼保健/优生优育、控制吸烟和突发公共事件自救教育是流动人口略大于户籍人口[15]；且有数据显示，有26.91%的流动人口没参加过任何一项关于社区公共健康教育[16]。基于此，流动人口较多的地区加强社区公共健康教育具有非常重要的意义。应适当提高社区健康教育的可及性和可得性，广泛采用多途径、多手段对健康教育进行宣传，提高其健康知识普及率；设置社区健康教育宣传员及指导员，为人民提供健康教育服务。
基金
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  • 国家自然科学基金青年科学基金项目(71904142)
文献
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2024年第51卷第9期
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doi: 10.20043/j.cnki.MPM.202311191
  • 接收时间：2023-11-15
  • 首发时间：2026-03-18
  • 出版时间：2024-05-10
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  • 收稿日期：2023-11-15
基金
国家自然科学基金青年科学基金项目(71904142)
作者信息
    1.天津医科大学公共卫生学院，天津 300070
    2.四川省疾控中心

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张馨予，E-mail:
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2种不同金属材料的力学参数
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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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