In order to solve the problems of high misevaluation rate and low work efficiency in the process of mental health intelligent evaluation, a method of mental health intelligent evaluation system oriented to the decision tree algorithm is proposed. First, the current research status of mental health intelligent evaluation was analyzed and the framework of mental health intelligent evaluation system was constructed. Then, the mental health intelligent evaluation data were collected and the decision tree algorithm was used to analyze and classify the mental health intelligent evaluation data to obtain the mental health intelligent evaluation results. Finally, specific simulation experiments are used to analyze the feasibility and superiority of the mental health intelligent evaluation system. The experimental results show that the recall rate of each system increases with the increasing number of iterations, and the system has the highest recall rate. Also, it is stable after the number of iterations reaches 20, with good recall and adaptive scheduling performance. The recall rate of comparison system 1 and comparison system 2 fluctuates greatly, and the recall rate is lower than that of the system in this paper. It is proved that the method of the mental health intelligent evaluation system of the decision tree algorithm can effectively solve the problem and improve the accuracy of the mental health intelligent evaluation. The efficiency of mental health intelligent evaluation is improved, and the system stability is better, which can meet the actual requirements of current mental health intelligent evaluation.
Background In response to the COVID-19 pandemic, people in many countries have shown xenophobia toward China, where the pandemic began. Within China, xenophobia has also been observed toward the people of Wuhan, the city where the first cases were identified. The relationship between disease threat and xenophobia is well established, but the reasons for this relationship are unclear. This study investigated the mediation role of perceived protection efficacy and moderation role of support seeking in the relationship between perceived COVID-19 risk and xenophobia within China. Methods An online survey was administered to a nationally representative sample (N = 1103; 51.7% women; ages 18 to 88) of Chinese adults during the early stage of the COVID-19 pandemic. Participants completed questionnaires about their perceived COVID-19 risk, perceived protection efficacy in reducing risk, support seeking, and xenophobic attitudes toward people of the Wuhan area. Results Regression based analyses showed that the perceived COVID-19 risk positively predicted xenophobia. Low perceived protection efficacy partly mediated the relationship between perceived COVID-19 risk and xenophobic attitudes, and this indirect effect was moderated by support seeking. Specifically, the indirect effect was weaker among individuals who sought more social support. Conclusions Under disease threat, xenophobia can appear within a country that otherwise seems culturally homogeneous. This study extends the extant research by identifying a possible psychological mechanism by which individuals’ perception of disease threat elicits xenophobia, and by addressing the question of why this response is stronger among some people than others. Increasing the public’s perceived efficacy in protecting themselves from infection, and encouraging support seeking, could reduce xenophobic attitudes.
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