医学新知2024,Vol.34Issue(11) :1210-1219.DOI:10.12173/j.issn.1004-5511.202407085

脑力劳动者视疲劳影响因素分析与预测模型构建

Analysis of influencing factors and prediction model construction for asthenopia in mental laborers

王慧 马晓露 张芸 张玲玲 刘慧 张臻华 孙静 谷君
医学新知2024,Vol.34Issue(11) :1210-1219.DOI:10.12173/j.issn.1004-5511.202407085

脑力劳动者视疲劳影响因素分析与预测模型构建

Analysis of influencing factors and prediction model construction for asthenopia in mental laborers

王慧 1马晓露 1张芸 1张玲玲 1刘慧 1张臻华 1孙静 1谷君1
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作者信息

  • 1. 上海交通大学医学院附属第九人民医院眼科(上海 200011);上海市眼眶病眼肿瘤重点实验室(上海 200011)
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摘要

目的 了解脑力劳动者视疲劳的影响因素并构建预测模型.方法 采用横断面调查方法纳入脑力劳动者作为研究对象.通过问卷星平台收集参与者的基本信息、生活习惯和眼健康状况等资料.应用眼表疾病指数(OSDI)、过敏性结膜炎量表(AC-12)和视疲劳量表(ASQ-17)评估参与者的眼部健康状况.使用单因素和多因素Logistic回归分析确定视疲劳的影响因素并构建预测模型.通过受试者工作特征(ROC)曲线及其曲线下面积(AUC)、校准曲线、决策曲线以及Bootstrap自助抽样法评价模型性能.结果 共纳入221名脑力劳动者,其中102名(46.15%)存在视疲劳.多因素Logistic回归分析显示干眼[OR=1.16,95%CI(1.10,1.21)]和过敏性结膜炎[OR=1.17,95%CI(1.06,1.28)]为视疲劳的危险因素,每晚8~<11h的睡眠时间[OR=0.14,95%CI(0.02,0.98)]和每天饮茶的习惯[(OR=0.40,95%CI(0.16,0.99)]与视疲劳风险降低有关(P<0.05)o构建的视疲劳预测模型展现了较好的预测性能,AUC为0.913[95%CI(0.875,0.950)];模型的预测概率与实际观测结果高度一致,具有较好的校准度;内部验证结果显示准确率为80.6%,Kappa值为0.609;决策曲线表明模型的应用净效益显著优于"无干预"和"全面干预"策略.结论 应采取措施改善干眼、过敏性结膜炎和屈光状态异常症状,推广良好的睡眠习惯和饮茶习惯,有助于缓解脑力劳动者的视疲劳问题,提高工作效率和生活质量.

Abstract

Objective To analyze influencing factors of asthenopia among mental laborers,and construct a predictive model.Methods This cross-sectional study included mental laborers.Basic information,lifestyle habits,and ocular health were collected.Ocular health was assessed using the Ocular Surface Disease Index(OSDI),the Allergic Conjunctivitis 12-item(AC-12),and the Asthenopia Survey Questionnaire 17-Item(ASQ-17).Univariate and multivariate Logistic regression analyses were conducted to identify factors associated with asthenopia and to construct a predictive model.The performance of the predictive model was comprehensively evaluated and validated using the receiver operating characteristic(ROC)curve and area under curve(AUC),calibration curve,decision curve analysis,and Bootstrap resampling method.Results 221 mental laborers were included,with 102(46.15%)having asthenopia.Multivariate Logistic regression analysis showed that dry eye[OR=1.16,95%CI(1.10,1.21)]and allergic conjunctivitis[OR=1.17,95%CI(1.06,1.28)]were risk factors for asthenopia,while appropriate sleep duration with 8~<11 hours per night[OR=0.14,95%CI(0.02,0.98)]and daily tea drinking habits[OR=0.40,95%CI(0.16,0.99)]were associated with a reduced risk of asthenopia(all P<0.05).The constructed asthenopia predictive model demonstrated good predictive performance,with AUC of 0.913[95%CI(0.875,0.950)].The models'predicted probabilities were highly consistent with actual observations,indicating good calibration.Internal validation results showed an accuracy rate of 80.6%and a Kappa value of 0.609.Decision curve analysis indicated that the model's application net benefit was significantly superior to"no intervention"and"full intervention"strategies.Conclusion We recommended to strengthen the management of dry eye,allergic conjunctivitis,and abnormal refractive status,and to promote good sleep and tea-drinking habits,which can help alleviate the problem of asthenopia in mental laborers,and improve work efficiency and quality of life.

关键词

视疲劳/脑力劳动者/影响因素/预测模型/饮茶/睡眠时间/干眼/过敏性结膜炎

Key words

Asthenopia/Mental laborers/Influencing factor/Predictive model/Tea drinking/Sleep duration/Dry eye/Allergic conjunctivitis

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出版年

2024
医学新知
武汉大学中南医院,中国农工民主党湖北省委医药卫生工作委员会

医学新知

CSTPCD
影响因子:0.243
ISSN:1004-5511
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