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Research On Data Mining And Early Warning Mechanism Of The Influencing Factors Of Junior High School Students’ Mental Health

Posted on:2022-04-01Degree:MasterType:Thesis
Country:ChinaCandidate:L Z MaFull Text:PDF
GTID:2507306350952529Subject:Applied Statistics
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At present,the mental health of adolescents has become an increasingly prominent social problem,and the national education department has frequently emphasized the importance of strengthening mental health education for middle school students in its policies.There is an inseparable relationship between mental health and physical health,which plays a vital role in the growth and development of students.At the same time,due to the psychological closure of junior high school students,there are many difficulties in the observation of psychological problems.Therefore,it is of theoretical and practical significance to explore the specific influencing factors and early warning mechanism of junior high school students’ mental health.This study is a non-mechanical and non-interventional exploratory research based on the data from the China Education Panel Survey.Firstly,Apriori algorithm is used to dig out the inner connections between 5 common psychological problems of junior high school students,and 3 important psychological problems are found.Then,Classification And Regression Tree(CART)and Random Forest are used to screen the important influence characteristics of important psychological problems and explore the influence rules,based on which the mental health indicators of junior high school students are constructed.Then we try to identify students with abnormal mental health level by using Robust Mahalanobis Distance and Isolation Forest anomaly detection algorithm under different input variables,and finally choose Isolation Forest anomaly detection algorithm based on junior high school students’ mental health indicators for mental health pre-warning.Finally,the standard scores are used to attribute the abnormal characteristics of junior high school students with abnormally low mental health indicators.Based on the above process,the mental health early warning mechanism of junior high school students is designed.The results of the study show that academic performance,frequency of parent-child communication,physical health,good friend behavior,personality,self-confidence,sleep time,parent-child relationship,living environment,classmate relationship,and parental expectations have an important impact on the mental health of junior high school students.On this basis,this article puts forward suggestions from three aspects:family,school and individual.At the same time,the junior high school students’mental health early warning mechanism has an accuracy rate of 76.5%in identifying students with abnormal mental health,indicating that the early warning mechanism has certain practical reference value.
Keywords/Search Tags:Mental health, Apriori algorithm, Classification And Regression Tree, Random Forest, Isolation Forest
PDF Full Text Request
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