大学生生活方式的潜在剖面分析及其与学习投入的关系  

Latent profile analysis on the college students’lifestyles and the association with learning engagement

作　　者：张配嘉 吴宏阳[2] 刘慧瀛[3] 何雯倩 要子慧 吴柯 王盼盼[1] 王众楷 吴田田 胡博[1] 王昱 孙长青[1,4] ZHANG Pei-jia;WU Hong-yang;LIU Hui-ying;HE Wen-qian;YAO Zi-hui;WU Ke;WANG Pan-pan;WANG Zhong-kai;WU Tian-tian;HU Bo;WANG Yu;SUN Chang-qing(School of Nursing and Health,Zhengzhou University,Zhengzhou,Henan 450001,China;不详)

机构地区：[1]郑州大学护理与健康学院社区护理教研室,河南郑州450001 [2]郑州大学校党委 [3]郑州大学心理健康中心 [4]郑州大学公共卫生学院社会医学与卫生事业管理教研室

出　　处：《现代预防医学》2023年第4期692-697,共6页Modern Preventive Medicine

基　　金：国家社会科学基金项目(20BRK041);河南省科技攻关项目(212102310767);河南省教育科学规划一般项目(2022YB0008)。

摘　　要：目的考察大学生生活方式的潜在类别,分析不同类别的影响因素,并探究不同生活方式与学习投入的关系。方法整群抽取某高校4830名大学生,采用健康促进生活方式和学习投入等量表进行调查,对大学生生活方式的特征进行潜在剖面分析,采用logistic回归探讨社会适应类型的相关人口学因素,并采用多元线性回归分析不同生活方式类型对学习投入的影响。结果潜在剖面分析将生活方式显示分为4个类别效果最佳,分别定义为“不良生活方式组”(27.9%)、“次健康-稳定组”(25.1%)、“次健康-低责任少运动组”(36.7%)和“健康生活方式组”(10.3%)。回归分析显示年龄(OR=1.080,95%CI:1.044~1.120)、家庭居住地为农村(OR=1.964,95%CI:1.562~2.470)、高年级(OR=1.388,95%CI:1.076~1.791)和就读专业非医科(OR=1.513,95%CI:1.193~1.918)是不良生活方式组的危险因素;女性(OR=0.638,95%CI:0.496~0.822)是次健康-稳定组的保护因素;年龄(OR=1.037,95%CI:1.001~1.074),家庭居住地为农村(OR=1.419,95%CI:1.128~1.785),高年级(OR=1.536,95%CI:1.200~1.966)是次健康-低责任少运动组的危险因素。在年龄、性别等校正混杂因素后,与健康生活方式组相比,不良生活方式组,次健康-稳定组,次健康-低责任少运动组均能负向预测学习投入(β分别为-30.078,-11.582,-18.513,P值均<0.001);还对学习投入的三个维度:动机(β分别为-11.149,-4.788,-6.024)、精力(β分别为-10.388,-3.544,-6.920)、专注(β分别为-8.540,-3.251,-5.569)具有负向预测作用(P值均<0.001)。结论大学生生活方式存在4种不同潜在类别,其影响因素包括年龄、性别、家庭居住地、年级和专业;大学生生活方式越健康,其学习投入水平越高。Objective To investigate the potential classes of college students’lifestyles,to analyze the influencing factors of different categories,and to explore the relationship between different lifestyles and learning engagement.Methods The cluster sampling method was used to select 4830 students from a university,and the health promotion lifestyle and learning engagement scales were used to test the characteristics of their lifestyles for latent profile analysis.The multinomial logistic regression was used to explore the demographic factors related to the type of social adaptation.Multiple linear regression was used to analyze the impact of different classes of lifestyles on learning engagement.Results The latent profile analysis showed that the effect was best in four classes,which were defined as"poor lifestyle group"(27.9%),"sub-healthy and stable group"(25.1%),"sub-healthy low responsibility and less exercise group"(36.7%)and"healthy lifestyle group"(10.3%).The multinomial logistic regression showed that higher age(OR=1.080,95%CI:1.044-1.120),rural family residence(OR=1.964,95%CI:1.562-2.470),upper grade(OR=1.388,95%CI:1.076-1.791)and non-medical students(OR=1.513,95%CI:1.193-1.918)were risk factors in the poor lifestyle group.Female(OR=0.638,95%CI:0.496-0.822)was a protective factor in the sub-healthy and stable group.Higher age(OR=1.037,95%CI:1.001-1.074),rural family residence(OR=1.419,95%CI:1.128-1.785)and upper grade(OR=1.536,95%CI:1.200-1.966)were risk factors in the sub-healthy low responsibility and less exercise group.After adjusting confounders,compared with the healthy lifestyle group,poor lifestyle group,sub-healthy and stable group,and sub-healthy low responsibility and less exercise group could all negatively predict learning engagement(β=-30.078,-11.582,-18.513,P<0.001).They could also negatively predict dedication(β=-11.149,-4.788,-6.024,P<0.001),vigor(β=-10.388,-3.544,-6.920,P<0.001)and absorption(β=-8.540,-3.251,-5.569,P<0.001).Conclusion There are four latent classes of college students’l

关 键 词：大学生 生活方式 学习投入 影响因素 潜在剖面分析 

分 类 号：R163[医药卫生—公共卫生与预防医学]