天津市微信虚拟社区居民癌症防治知识知晓现状及影响因素的分类树分析
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摘要
目的了解天津市微信虚拟社区居民癌症防治核心知识知晓情况及影响因素,为今后肿瘤防治提供科学依据。方法于2017年11月17日18:00至2017年11月22日24:00,通过天津市疾病预防控制中心开发的"普及健康生活"公众号,发布匿名网络电子问卷对天津市18岁及以上常住居民进行调查,问卷内容包括一般人口学特征(性别、年龄、户口所在地、民族、文化程度和职业等)及《中国癌症防治三年行动计划(2015-2017年)》提出的癌症防治核心知识知晓率问卷中的核心知识问题。采用SPSS 22.0软件进行X~2检验、趋势X~2检验、非条件logistic回归和分类树模型,采用通过受试者工作特征(ROC)曲线下面积对logistic回归模型和分类树模型进行预测概率的效果评价。结果本研究共回收微信虚拟社区天津市居民的有效问卷8 290份,癌症防治核心知识知晓率为59.42%,不同性别、年龄、城乡、文化程度和职业调查对象的癌症防治核心知识知晓比例差异均有统计学意义(P<0.05)。多因素logistic回归模型结果显示,调整了其他因素后,女性、低年龄组、户口属于市区、文化程度高和职业为机关、事业单位是癌症防治知识知晓的有利因素,均有统计学意义(P<0.05)。分类树模型知晓分类正确百分比为90.9%,筛选出文化程度(重要性为0.043,标准化重要性为100%)、职业(重要性为0.020,标准化重要性为48.7%)、城乡(重要性为0.011,标准化重要性为24.7%)和年龄(重要性为0.001,标准化重要性为3.2%)为癌症防治知识知晓的重要影响因素,并存在交互作用。多因素非条件logistic回归模型预测概率的ROC曲线下面积为0.738,小于分类树模型预测概率的ROC曲线下面积(0.748),差异有统计学意义(P<0.05)。结论天津市微信虚拟社区居民癌症防治知识的知晓情况不平衡,文化程度、职业、城乡和年龄等因素独立或交互影响人群对癌症防治知识的知晓情况,应积极利用网络新媒体开展有效的公众健康教育以提高人群癌症防治知识的知晓率。
Objective To understand the current status of awareness of cancer prevention knowledge and risk factors in WeChat virtual community in Tianjin,and to provide the scientific basis for preventing and treating cancers. Methods From 18:00 of17 th in November of 2017 to 24:00 of 22 th in November of 2017,the online questionnaire investigation for adult residents(≥18 years old) was established in WeChat virtual community based on WeChat official platform. The questionnaire included the general demographic information(gender,age,registered permanent address,nationality,education level and occupation) and the core knowledge of cancer prevention and control proposed by 《Three-Year Action Plan for Cancer Prevention and Control in China(2015-2017)》. The used software was SPSS 22.0. X~2 test,non-conditional logistic regression and classification tree models were used to analyze the data. The prediction of probability of logistic regression model and classification tree model were evaluated by the area under receiver operating characteristic curve(ROC). Results The awareness rate of cancer prevention knowledge was59.42%. The awareness proportions in different gender,age,urban-rural areas,education level and occupation were significantly different(P <0.05). Multivariate logistic regression analysis showed that after adjusting other factors,female,lower age group,urban registration,the higher education level,occupation(government organization and institution) may be protective factors for the awareness of cancer prevention knowledge,P<0.05. The correct percentage of classification tree model awareness classification was 90.9%,the education level(importance:0.043,standardized importance:100%),occupation(importance:0.020,standardized importance:48.7%),urban-rural areas(importance:0.011,standardized importance:24.7%) and age(importance:0.001,standardized importance:3.2%) were important influencing factors of knowledge of cancer prevention and treatment with interaction effect. The areas under the ROC curve of the prediction of probability of logistic regression model were 0.738,which was significantly lower than that(0.748) of the dassification tree model(P<0.05). Conclusion There was an imbalance of the awareness of cancer prevention knowledge in WeChat virtual community,the education level,occupation,urban-rural areas and age had the independence and interaction effects on knowledge of cancer prevention and treatment,the knowledge rate of cancer prevention and treatment should be improved by health education on WeChat virtual community.
Objective To understand the current status of awareness of cancer prevention knowledge and risk factors in WeChat virtual community in Tianjin,and to provide the scientific basis for preventing and treating cancers. Methods From 18:00 of17 th in November of 2017 to 24:00 of 22 th in November of 2017,the online questionnaire investigation for adult residents(≥18 years old) was established in WeChat virtual community based on WeChat official platform. The questionnaire included the general demographic information(gender,age,registered permanent address,nationality,education level and occupation) and the core knowledge of cancer prevention and control proposed by 《Three-Year Action Plan for Cancer Prevention and Control in China(2015-2017)》. The used software was SPSS 22.0. X~2 test,non-conditional logistic regression and classification tree models were used to analyze the data. The prediction of probability of logistic regression model and classification tree model were evaluated by the area under receiver operating characteristic curve(ROC). Results The awareness rate of cancer prevention knowledge was59.42%. The awareness proportions in different gender,age,urban-rural areas,education level and occupation were significantly different(P <0.05). Multivariate logistic regression analysis showed that after adjusting other factors,female,lower age group,urban registration,the higher education level,occupation(government organization and institution) may be protective factors for the awareness of cancer prevention knowledge,P<0.05. The correct percentage of classification tree model awareness classification was 90.9%,the education level(importance:0.043,standardized importance:100%),occupation(importance:0.020,standardized importance:48.7%),urban-rural areas(importance:0.011,standardized importance:24.7%) and age(importance:0.001,standardized importance:3.2%) were important influencing factors of knowledge of cancer prevention and treatment with interaction effect. The areas under the ROC curve of the prediction of probability of logistic regression model were 0.738,which was significantly lower than that(0.748) of the dassification tree model(P<0.05). Conclusion There was an imbalance of the awareness of cancer prevention knowledge in WeChat virtual community,the education level,occupation,urban-rural areas and age had the independence and interaction effects on knowledge of cancer prevention and treatment,the knowledge rate of cancer prevention and treatment should be improved by health education on WeChat virtual community.
引文
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[16]董秀珍,李枫,阿力木江·阿布都热合曼,等.上海市长宁区江苏街道居民肿瘤相关知识、态度、行为调查[J].中国健康教育,2007,23(8):589-592.
[17]乔芬芬,高晶蓉,刘丽,等.上海市部分社区居民肿瘤防治知识调查[J].中国健康教育,2010,26(6):463-466.
[18]李星华,季明芳,吴标华,等.中山市小榄镇1453名居民癌症综合防治知识问卷调查分析[J].中国肿瘤,2011,20(1):30-33.
[19]刘双喜,许可葵,王静,等.湖南省慈利县3609名妇女癌症综合防治知识问卷调查分析[J].中国肿瘤,2008,17(2):98-100.
[20]王德征,张辉,徐忠良,等.天津市1999-2015年慢性非传染性疾病过早死亡趋势分析[J].中华流行病学杂志,2017,38(12):1672-1676.
[21] Khan TM,Leong JP,Ming LC,et al. Association of knowledge and cultural perceptions of Malaysian women with delay in diagnosis and treatment of breast cancer:a systematic review[J]. Asian Pac J Cancer Prev,2015,16(13):5349-5357.
[22]秦瑞,梁明斌,俞敏,等.浙江省非医学科技工作者癌症预防知识信念行为调查[J].中国预防医学杂志. 2015,16(2):100-104.
[23] Allam MF,Abd EK. Evaluation of the level of knowledge of Egyptian women of breast cancer and its risk factors. A cross sectional study[J]. J Prev Med Hyg,2012,53(4):195-198.
[24]孟舒娴,沈冲.南京某高校大学生电子健康素养及行为现状调查[J].中国健康教育,2018,34(3):254-257.
[25]梁栋,黄丹丹,郑慧楠,等.仙游县较发达地区居民肿瘤知晓度及健康干预研究[J].安徽医科大学学报,2015,50(11):1615-1620.
[26] Barber SR,Davies MJ,Kamlesh K,et al. Risk assessment tools for detecting those with pre-diabetes:a systematic review[J]. Diabetes Res Clin Pract,2014,105(1):1-13.
[2] Rolls K,Hansen M,Jackson D,et al. How health care professionals use social media to create virtual communities:an integrative review[J]. J Med Internet Res,2016,18(6):e166. DOI:10.2196/jmir.5312.
[3]方婧,陆伟.微信公众号信息传播热度的影响因素实证研究[J].情报杂志,2016,35(2):157-162.
[4]中华人民共和国中央人民政府.中国防治慢性病中长期规划(2017—2025年)[EB/OL].(2017-02-14).[2018-09-10]http://www.gov.cn/zhengce/content/2017-02/14/content_5167886.htm.
[5]中华人民共和国国家卫生和计划生育委员会.中国癌症防治三年行动计划(2015-2017年)[EB/OL].(2015-09-10).[2018-09-10].http://www.nhfpc.gov.cn/jkj/s5878/201509/656437bc5c7e4cd0af b581de85be998a.shtml.
[6]路平,徐翠林,杨薇,等.社区居民肿瘤防治知识知晓状况调查分析[J].中国肿瘤. 2010,19(12):789-792.
[7]林小婷,陈茹梅,符之武,等.海口市食管癌高危人群肿瘤防治知识知晓情况[J].中国老年学杂志,2015,2(35):1066-1067.
[8]俞文敏,王杰,黄美红,等.虚拟社区健康教育需求分析[J].中华现代护理杂志,2009,15(8):739-740.
[9]向文杰.移动互联网发展的回顾与展望[J].电信技术,2009,1(1):66-69.
[10] Rodrigues RG,das Dores RM,Camilo-Junior CG,et al. SentiHealthCancer:a sentiment analysis tool to help detecting mood of patients in online social networks[J]. Int J Med Inform,2016,85(1):80-95.
[11] Lane TS,Armin J,Gordon JS. Online recruitment methods for webbased and mobile health studies:a review of the literature[J]. J Med Internet Res,2015,17(7):e183. DOI:10.2196/jmir.4359.
[12] Cavallo DN,Chou WY,McQueen A,et al. Cancer prevention and control interventions using social media:user-generated approaches[J].Cancer Epidemiol Biomarkers Prev,2014,23(9):1953-1956.
[13]钱碧云,王庆生,夏小明,等.天津市居民对肿瘤知识认知程度的调查分析[J].中国慢性病预防与控制,2002,10(6):244-246.
[14]浙江省癌症中心.浙江省癌症中心公布癌症防治核心知识调查结果[EB/OL].(2017-10-26).[2018-09-10].http://health.zjol.com.cn/jkxw/201710/t20171026_5459944.shtml.
[15]张一英,彭慧,顾文洁,等.上海市嘉定区居民肿瘤早发现知识和行为监测分析[J].上海预防医学,2016,28(2):90-94.
[16]董秀珍,李枫,阿力木江·阿布都热合曼,等.上海市长宁区江苏街道居民肿瘤相关知识、态度、行为调查[J].中国健康教育,2007,23(8):589-592.
[17]乔芬芬,高晶蓉,刘丽,等.上海市部分社区居民肿瘤防治知识调查[J].中国健康教育,2010,26(6):463-466.
[18]李星华,季明芳,吴标华,等.中山市小榄镇1453名居民癌症综合防治知识问卷调查分析[J].中国肿瘤,2011,20(1):30-33.
[19]刘双喜,许可葵,王静,等.湖南省慈利县3609名妇女癌症综合防治知识问卷调查分析[J].中国肿瘤,2008,17(2):98-100.
[20]王德征,张辉,徐忠良,等.天津市1999-2015年慢性非传染性疾病过早死亡趋势分析[J].中华流行病学杂志,2017,38(12):1672-1676.
[21] Khan TM,Leong JP,Ming LC,et al. Association of knowledge and cultural perceptions of Malaysian women with delay in diagnosis and treatment of breast cancer:a systematic review[J]. Asian Pac J Cancer Prev,2015,16(13):5349-5357.
[22]秦瑞,梁明斌,俞敏,等.浙江省非医学科技工作者癌症预防知识信念行为调查[J].中国预防医学杂志. 2015,16(2):100-104.
[23] Allam MF,Abd EK. Evaluation of the level of knowledge of Egyptian women of breast cancer and its risk factors. A cross sectional study[J]. J Prev Med Hyg,2012,53(4):195-198.
[24]孟舒娴,沈冲.南京某高校大学生电子健康素养及行为现状调查[J].中国健康教育,2018,34(3):254-257.
[25]梁栋,黄丹丹,郑慧楠,等.仙游县较发达地区居民肿瘤知晓度及健康干预研究[J].安徽医科大学学报,2015,50(11):1615-1620.
[26] Barber SR,Davies MJ,Kamlesh K,et al. Risk assessment tools for detecting those with pre-diabetes:a systematic review[J]. Diabetes Res Clin Pract,2014,105(1):1-13.