基于大数据的少数民族大学生网络心理健康分析与指导系统

Huan Wu, Chan Luo
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摘要

当前,少数民族大学生的心理健康问题已受到高校的广泛关注。虽然研究较多,但相应的解决方案和资源相对匮乏,社会关注度不高。为了更好地分析和解决少数民族大学生网络心理健康的相关问题,本文基于大数据构建了少数民族大学生网络心理健康分析与指导系统,选取我省955名少数民族大学生作为实验对象,其中男生543人,女生412人,城市学生310人,乡镇学生645人。本研究采用问卷和症状自评量表(SCL-90)对民族大学955名少数民族大学生进行调查,回收有效问卷928份,有效回收率为97.1%。问卷调查结束后,采用spss20.0统计软件对数据进行收集、录入和处理,将SCL-90评分分为5个等级进行评分。结果显示,SCL-90阳性检出率高达25.9%,大学生心理问题检出率为3.79% ~ 26.14%。因此,调查结果显示,样本的阳性检出率已经接近该范围的最大值,说明少数民族大学生的网络心理健康状况并不理想。由此可见,基于大数据的少数民族大学生网络心理健康分析与指导系统的研究与设计具有重要的价值。
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Network Mental Health Analysis and Guidance System for Minority College Students Based on Big Data
: At present, the mental health problems of ethnic minority college students have been widely concerned by colleges and universities. Although there are many studies, the corresponding solutions and resources are relatively scarce, and the social attention is not high. In order to better analyze and solve the related problems of the network mental health of ethnic minority college students, this paper constructs the network mental health analysis and guidance system of ethnic minority college students on the basis of big data, and selects 955 ethnic minority college students in our province as the experimental objects, including 543 boys, 412 girls, 310 urban students and 645 Township students. In this study, we used questionnaire and symptom Checklist-90 (SCL-90) to investigate 955 minority college students in Minzu University. 928 valid questionnaires were collected, and the effective recovery rate was 97.1%. After the questionnaire survey, the data were collected and input and processed by spss20.0 statistical software, and the SCL-90 scores were scored according to five levels. The results showed that the positive detection rate of SCL-90 was as high as 25.9%, while the detection rate of College Students' psychological problems was 3.79%-26.14%. Therefore, the survey results show that the positive detection rate of the sample has been close to the maximum value of this range, indicating that the network mental health status of minority college students is not ideal. It can be seen that the research and design of the network mental health analysis and guidance system for minority college students based on big data is of great value.
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