Construction of Rural Left-Behind Children’s Mental Health Mobile Information System Based on the Internet of Things

Author:

Liu Xiaoyan1ORCID

Affiliation:

1. Normal College of Special and Preschool Education, Weifang University, Weifang 261021, Shandong, China

Abstract

Left-behind children, as a special phenomenon group stationed in rural areas, lack parents’ education and care for a long time and shoulder the burden of life early. Moreover, in rural areas with relatively closed information, their communication with their parents only relies on short-term telephone contact. If things go on like this, it may lead to mental health problems in children. In recent years, the group of left-behind children began to get the attention of the society. The social people want to help the left-behind children mainly through the information provided by the school, which cannot actually understand the real situation of the left-behind children, and the help to the left-behind children is only a drop in the bucket. Therefore, it is necessary to use the internet as a convenient and fast platform to build a mobile information system for the mental health of rural left-behind children, input the mental health of left-behind children, and pay attention to and track the left-behind children. This paper mainly studies the construction of the rural left-behind children’s mental health mobile information system based on the Internet of Things. This paper expounds the related concepts of the Internet of Things, which has a good connection effect on the construction of the left-behind children’s mental health mobile information system. Then, it analyzes the functional requirements of the rural left-behind children’s mental health mobile information system, in terms of design, the C/S model is used, the database in the data server is designed to analyze the mental health information management needs of left-behind children, and the data model is established by defining the key domains in the system. This paper also collects and sorts out the left-behind children’s mental health data through data mining technology, studies the factors affecting the left-behind children’s mental health, and clarifies the necessity of constructing the rural left-behind children’s mental health mobile information system and focuses on the observation objects. The results show that the evaluation factors of left-behind children’s mental health are significantly higher than those of non-left-behind children, and their mental health needs attention because left-behind children lack the care of their parents for a long time. The mental health status of left-behind children aged 7–12 is the most worrying, which is significantly different from other age groups in obsessive-compulsive disorder, interpersonal sensitivity, anxiety, hostility, paranoia, and mental illness. It may be because left-behind children aged 7–12 are in the development stage, they are not as ignorant as left-behind children aged 1–6, and they are not as mature as left-behind children aged 13–17.

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Computer Science Applications

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