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Modelling the Psychological Impact of COVID-19 in Saudi Arabia Using Machine Learning

Computers, Materials & Continua 2021年第5期67卷 2029-2047页

作者： Mohammed A.Aleid kh.led a.z.alyamani Mohieddine Rahmouni Theyazn H.H.Aldhyani Nizar Alsharif Mohammed Y.Alzahrani College of Education King Faisal UniversityAl-Ahsa31982Saudi Arabia Community College in Abqaiq King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Economics and Quantitative Methods ESSECTUniversity of TunisTunisTunisia Department of Computer Engineering and Science Al-Baha UniversityAl-BahahSaudi Arabia

This article aims to assess health habits,safety behaviors,and anxiety factors in the community during the novel coronavirus disease(COVID-19)pandemic in Saudi Arabia based on primary data collected through a questionnaire with 320 *** other words,this paper aims to provide empirical insights into the correlation and the correspondence between sociodemographic factors(gender,nationality,age,citizenship factors,income,and education),and psycho-behavioral effects on individuals in response to the emergence of this new *** focus on the interaction between these variables and their effects,we suggest different methods of analysis,comprising regression trees and support vector machine regression(SVMR)*** to the regression tree results,the age variable plays a predominant role in health habits,safety behaviors,and *** health habit index,which focuses on the extent of behavioral change toward the commitment to use the health and protection methods,is highly affected by gender and age *** average monthly income is also a relevant factor but has contrasting effects during the COVID-19 pandemic *** results of the SVMR model reveal a strong positive effect of income,with R^(2) values of 99.59%,99.93%and 99.88%corresponding to health habits,safety behaviors,and anxiety.

关键词： COVID-19 health habits safety behaviors anxiety support vector machine regression regression trees

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