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Background. China will inevitably enter a medium, severe, or deep aging society in the future, and the number of elderly people living alone is also increasing. Mental health is a major issue for older people living alone. With the deepening of aging, social participation has become an important way to promote mental health and improve the quality of life of the elderly. Methods. This study uses data from Chinese Longitudinal Health Longevity Survey (CLHLS). Based on the CLHLS data of 2018, this paper uses multiple ordered logistic models to measure the mental health level of elderly people living alone through two dimensions of depression and anxiety and carries out a heterogeneity analysis on the mental health level of elderly people living alone. Results. The analysis of 2477 elderly people living alone shows that the increase of social participation in simple communication can reduce the degree of depression and anxiety of elderly people living alone, and the decrease of social participation in self-recreation can reduce the degree of depression and anxiety of elderly people living alone. In addition, the heterogeneity analysis found that the heterogeneity of social participation was more significant among the elderly living alone with different genders, ages, places of residence, and self-care abilities. Limitations. This study has some limitations, and CES-D-10 is a screening tool and cannot fully determine the presence of depression in high-rise older adults living alone. Conclusions. In the future, primary healthcare-targeted interventions can be provided according to the different degrees of depression and anxiety of elderly people living alone. [ABSTRACT FROM AUTHOR]

This paper presents an in-depth study and analysis of the relevance of early childhood education to occupational psychotherapy using a virtual-assisted affective interaction approach. Starting from the educational theory of interactive cognitive psychology, the theoretical basis for parent-child picture book education for interactive learning is explored, as well as the theoretical development after the introduction of AR technology. Firstly, the analysis of young children's emotions involves massive image processing, and the use of cloud computing architecture leads to high latency, while young children's safety is a latency-sensitive service. Secondly, face recognition accuracy based on static images is not high due to problems such as inconspicuous facial features of toddlers and low-quality kindergarten surveillance videos. In this paper, a face identity correction model based on location features is proposed and the superiority of the model is demonstrated through experiments. Finally, this paper analyzes and mines the emotional data of young children. The level of kindergarten teachers' awareness of early childhood mental health education generally showed an upward trend as their titles rose, and there were significant differences in the seven dimensions of early childhood mental health, the purpose and meaning of early childhood mental health education, implementers, targets, content, pathways, and effects; significant differences existed between teachers of different kindergarten natures, and there were significant differences in the purpose and meaning of early childhood mental health education, implementers, targets, content, pathways, effects, and mental health education for young children. Therefore, this paper proposes a face identity correction model based on position information, which considers both the correlation between pixel values in the spatial domain and the correlation between frames in the temporal domain. This paper has developed an emotion analysis system for kindergartens and put it into use in kindergartens to meet the needs of monitoring the safety of young children and evaluating early childhood education and has received good feedback from users, demonstrating the effectiveness of the system. [ABSTRACT FROM AUTHOR]

With the development of big data concept and technology, big data has an important impact on human development. This paper studies the relationship between the consumption pattern and mental health of enterprise employees under the normalization of epidemic prevention and control. Starting from the consumption structure and behavior of enterprise employees, it defines the meaning of enterprise employees' consumption and the connotation of enterprise employees' health psychology and analyzes the relationship between consumption behavior and consumption psychology and the elements of enterprise employees' health psychology. Based on the change of employees' income structure and consumption patterns, this paper speculates the relationship between employees' consumption patterns and mental health, analyzes the correlation between employees' consumption patterns and mental health through a questionnaire survey, and calculates the Correlation Clustering statistical results. It plays an important role in building a good enterprise staff consumption culture under the normalization of epidemic prevention and control and effectively realizes the significance of purifying the social consumption environment. [ABSTRACT FROM AUTHOR]

Since entering the 21st century, my country's education is facing the transition from traditional exam-oriented education to quality education and personality education, and the problem of mental health has gradually attracted the attention of all sectors of society. Suspension, drop-out, suicide, and crime occur from time to time, and the number of students with psychological disorders is also increasing year by year. Therefore, in-depth research on the mental health of vocational college students and exploration of students' psychological intervention models have become the focus of colleges and other education departments. For the focus of research works, the application of DM technology in the field of teaching and management in an institution of higher learning has also achieved initial results. Through consulting a lot relevant literature, this paper deeply studies the DM technology and tries to analyze the application of DM technology in the data of psychological problems of higher vocational students. Through experimental comparison, a single algorithm model is used to classify and predict the test data set, and the accuracy rate is 78% after comparing the classification results with known categories. The accuracy of classification results obtained by the fusion algorithm in this paper is 85.1%. The results show that this technology provides help for students' mental health counseling, mental health education and the prevention of students' psychological problems in higher vocational colleges. It provides new ideas and methods to solve the mental health problems of higher vocational students and makes the school mental health education more purposeful, targeted, and effective. [ABSTRACT FROM AUTHOR]

The increase of mental health problems and the need for effective medical health care have led to an investigation of machine learning that can be applied in mental health problems. This paper presents a recent systematic review of machine learning approaches in predicting mental health problems. Furthermore, we will discuss the challenges, limitations, and future directions for the application of machine learning in the mental health field. We collect research articles and studies that are related to the machine learning approaches in predicting mental health problems by searching reliable databases. Moreover, we adhere to the PRISMA methodology in conducting this systematic review. We include a total of 30 research articles in this review after the screening and identification processes. Then, we categorize the collected research articles based on the mental health problems such as schizophrenia, bipolar disorder, anxiety and depression, posttraumatic stress disorder, and mental health problems among children. Discussing the findings, we reflect on the challenges and limitations faced by the researchers on machine learning in mental health problems. Additionally, we provide concrete recommendations on the potential future research and development of applying machine learning in the mental health field. [ABSTRACT FROM AUTHOR]

Background. With the prevalence of mental issues worldwide, more and more people are suffering from psychological torture. Mental Health Gap Action Program (mhGAP) has been introduced to improve the life quality of humans. Objectives. To explore and synthesize evidence of participants' experience of mental health first aid (MHFA) training course. Method. Peer-reviewed qualitative evidence was systematically reviewed and thematically synthesized. Cumulative Index to Nursing and Allied Health Literature (CINAHL), Medical Literature Analysis and Retrieval System Online (MEDLINE), Psychological Information (PsycINFO), PubMed, Psych ARTICLES, Web of Science, Joanna Briggs Institute (JBI), and National Institute for Health and Care Excellence (NICE) databases were searched for the inception of the present study. The study's quality was appraised using the Critical Appraisal Checklist for Qualitative Research of Joanna Briggs Institute (JBI) appraisal tool. All the participants who have attended the MHFA training course (excluding instructors) setting were included. Results. Six papers published between 2005 and 2019 were included for thematic synthesis. The review indicated that MHFA had been a positive experience for participants. Conclusions. MHFA courses can provide participants with professional knowledge of mental health counseling and improve their knowledge, practice, and attitudes towards their patients. Professional MHFA training courses should therefore be popularized and promoted among other populations. [ABSTRACT FROM AUTHOR]

In order to improve the recognition effect of student weariness emotion in English classroom, this paper combines intelligent Internet of Things technology and big data technology to construct an improvement model of student weariness emotion in English classroom. In the process of student facial expression recognition, according to the given grayscale threshold, this paper extracts the surface contour information from the three-dimensional volume data, extracts the student's surface contour information, and uses triangular facets to fit to form a triangular mesh. Moreover, this paper renders a triangular mesh model and shows how to speed up the calculation of PFH. In addition, this paper proposes a Fast Point Feature Histogram, which uses an iterative closest point fine registration algorithm for image registration. Finally, this paper constructs an emotion recognition model of students' weariness in English classroom. From the test results, it can be seen that the student weariness emotion recognition system in English classroom proposed in this paper can effectively identify students' weariness emotion. [ABSTRACT FROM AUTHOR]

In order to improve the basketball theory and provide theoretical and intellectual support for the scientific, mental health, and sustainable development of basketball, we propose to take the development dynamic mechanism of juvenile basketball as the research object and make a systematic and in-depth study on the dynamic mechanism, the cultivation of Chinese and foreign juvenile basketball reserve talents, and the dynamic dilemma and influencing factors of juvenile campus basketball development by using the methods of literature, questionnaire, and expert interview. A method of cultivating the ring tone of juvenile basketball is proposed. This method is based on Chan algorithm. When the target is close to each base station, the first estimation also needs an initial value to solve the initial solution estimation matrix. The method is also based on multivariate Taylor algorithm, taking into account the measured distance between the targets to be measured, so it will get some useful information, which will improve the positioning accuracy. The experimental results show that the accuracy of the algorithm used in this paper is more than 85%. However, the accuracy of rebounding and passing recognition and prediction is low. The recognition accuracy and prediction accuracy of the test set are slightly lower than that of the effective set, which shows that the performance of the target detection system model in this paper can be further improved through more significant training examples. It is proved that the algorithm based on Taylor ring can meet the needs of teenagers in the basketball coordination and mental health. [ABSTRACT FROM AUTHOR]

Cognitive-behavioral therapy is a type of psychosocial intervention which aims to reduce the mental health conditions like depression, anxiety disorder, and others. Similarly, deep learning is a type of machine learning and artificial intelligence that imitates how humans gain certain types of knowledge. In this paper, deep learning has been used to effectively alleviate teenagers' social anxiety and improve their social ability and the quality of social relations. It aims to conduct an in-depth study on the diagnosis and treatment of cognitive behavior therapy in teenagers based on deep learning. First, it constructs the cognitive behavior diagnosis and treatment evaluation system of adolescent social anxiety and divides the system function into functional, structural, and database design. Then, the correlation prediction model between cognitive behavior therapy and adolescent social anxiety is constructed based on a multiobjective evolutionary algorithm. The risk and protective factors in adolescent growth are screened from the perspectives of people, family, school, and society. The fuzzy itemset support of different factors is defined. The vector of adolescent social anxiety expression index's weight is calculated. The subjective and objective factors of social anxiety in adolescents are extracted based on the grey correlation degree. The correlation prediction model between accurate cognitive behavior therapy and adolescents' social anxiety is established to complete the prediction research, diagnosis, and treatment effect. Simulation experiments show that the proposed method has good feasibility and high prediction accuracy. It can effectively alleviate the social anxiety of teenagers. [ABSTRACT FROM AUTHOR]

With the advent of the information technology revolution and the Internet era, information technology is gradually occupying an important position and becoming an important strategic factor in economic development. As an emerging technology that has been developing continuously in recent years, big data is becoming an important industry to improve the innovation and development of the urban economy. Like AI technology, cloud computing, and the Internet, big data has become an important application technology for economic growth and economic efficiency improvement in today's world. It is an effective means of progress and development in a region and an important strategic resource. As a new technology, big data has attracted more and more attention from all walks of life. Many companies have turned their attention to developing big data for economic benefits. "Enjoy your old age" is the yearning of every old man and his family. In recent years, the national level has been committed to "creating an urban built environment for the elderly to achieve healthy aging." From the perspective of promoting the physical and mental health of the elderly, this paper analyzes the impact of the urban built environment on the physical and mental health of the elderly based on the needs of the elderly and puts forward countermeasures and suggestions based on the current status and existing problems of the urban built environment for the elderly. Based on the combined data analysis method and technology in big data, this paper conducted a field questionnaire survey on a total of 4,000 elderly people in urban and rural areas by means of the questionnaire survey. It is found that the existing problems of the built environment in the old cities include scattered content, one-sided understanding, and rigid design. According to the problems, the solutions of building consensus, paying attention to planning, combining urban characteristics, and the joint efforts of all sectors of society are put forward. And programming tools are used to combine formulas and analyze related data in detail. The analysis results show that the physical and mental health index of the elderly is highly correlated with factors such as changes in the consensus degree of the urban built environment, urban built environment planning, urban built environment policy support, and multiparty efforts in the urban built environment. Changes show a positive change. [ABSTRACT FROM AUTHOR]

This paper discusses a common mental disorder prevention mode to improve residents' mental health quality and achieve the "comprehensive and fine-grained" mental health education knowledge service. The construction of mental health knowledge service model is conducive to accurately grasp the group cognition and psychological changes and take the initiative to make decisions. This paper analyzes the needs of mental health education knowledge service system and combs the research status of applying information technology and artificial intelligence to mental health education at home and abroad, the resource data of five major online medical communities at home and abroad were screened and mined, and the mental health feature tags of college students were extracted. Based on the existing mental health diagnosis experience database and multisource text, reuse and optimize ontology integration method to systematically construct mental health education ontology. Taking mental illness as an example, the rule base is constructed and the personalized recommendation service of mental health is realized. The service model can infer and output all kinds of diagnosis and treatment knowledge to provide users with intelligent mental health education knowledge services. [ABSTRACT FROM AUTHOR]

Physical activity, especially routine walking, is an imperative factor for the prevention of strokes, mental illness, and cardiovascular diseases (CVDs). The NIH (National Institute of Health) has also acknowledged walking as the most important factor of the stroke rehabilitation program. Many research studies are presented by physicians and researchers in the literature that highlight the positive impacts of walking on human health (physical and mental). This paper has the objective of studying the impact of regular walking, especially on mental illness, CVDs, and strokes. The C-reactive protein (CRP), P-selectin protein, and homocysteine biomarkers are considered to decide the improvement in the health of an individual with respect to CVDs and strokes. The other parameters considered for the recommendations of physicians and healthcare experts for mental health are PSS (perceived stress score) and ESS (Epworth sleepiness score) that control mental illness. The values are measured for the participating subjects before participating in the walking activity and after the end of the walking schedule to see the impact on individuals. The overall mental and physical health of an individual contributes to the chances of occurrence of CVDs, mental illness, and strokes in individuals aged between 40 years and 55 years, as per the study presented in this paper. The results show that the PSS and ESS scores are improved after the walking activity. Eventually, it improved recovery from many kinds of mental illness and also reduced the chances of strokes. Similarly, the levels of the biomarkers that determine the chances of an individual having CVD or stroke also improved. Walking can impact our overall health in many ways, however, in this paper, the focus is given to ailments, such as strokes, CVDs, and mental illness. The results show that stress and improper sleepiness can impact mental health negatively. The research outcome is measured by adding walking in a routine life so that every individual can get rid of many physical and mental ailments. The results presented in the paper reveal that the 90-day walking program has created a good impact on the health of individuals by improving their physical and mental health. [ABSTRACT FROM AUTHOR]

Background. Real-time collection of mental health and disease activity patient-reported outcomes (PROs) are essential to assist clinicians in delivering optimal holistic health care. The aim of this pilot study was to validate a digital support tool (DST) delivered via a tablet device in an outpatient setting to assess IBD activity and psychological distress. Methods. 48 individuals (26 females; average age: 40.04) with IBD completed the DST and a paper-based survey in a hospital IBD outpatient setting. PROs for disease activity and psychological distress (Kessler K10) were compared to paper-based gold-standard measures of disease activity (Partial Mayo Index or Harvey Bradshaw Index completed by the clinician) and psychological distress (Depression Anxiety Stress Scale; completed by the patient). Patient feedback regarding usability and acceptance of the DST was also collected. Results. DST patient-derived disease activity scores were significantly correlated with clinician assessment of disease activity (p<0.01). Patient DST-derived psychological well-being scores were also significantly correlated with the gold-standard measure of psychological distress (p<0.05). Patients found the DST to be easy to use and identified a willingness to follow through with the recommendations provided by the DST in relation to their psychological distress scores. Conclusions. The pilot study demonstrates the value in collecting disease activity and psychological distress PROs via a DST in an outpatient setting. Disease activity and psychological distress PROs were found to correlate significantly with gold standard measures. The findings provide preliminary support for the value of embedding digital technology into clinical care to promote patient engagement and optimal holistic healthcare. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The number of children with mental health problems is ever-growing; as a result, nearly 850,000 children in the UK are believed to have clinically significant problems, and only a quarter show evidence of mental illness. Family members often have a hard time dealing with children with mental health problems. As a result, digital mental health interventions are becoming popular for people seeking professional mental health services. Previous studies in this area have also shown that parents who are divorced or working away from home struggle to maintain contact with their children. This lack of communication between the parents and their children can worsen the children's mental health conditions and prevent early diagnosis. Human-centred design thinking is applied step by step in this paper to provide an intuitive understanding of the design process. Five stages of the design thinking process were examined to follow a correct path. The results were promising, and the feedback received assured that the product helps parents to better monitor their children's mental health and provides support when needed. The design thinking process was followed in concordance with the user needs identified from previous studies in this area, which led to a working solution that benefits both parents and children in tackling these problems. [ABSTRACT FROM AUTHOR]

In this new era that is full of social changes, ongoing economic transformation, an abundance of information resources, and a fast pace of life, the pressure that people feel to compete with one another is also increasing day by day. Because of the vast differences in people's states of consciousness and worldviews, interpersonal relationships have become increasingly difficult to navigate. Students in higher education institutions will eventually emerge as the dominant demographic in society. Their mental health has a significant bearing on all aspects of life, including learning and future growth. An objective condition that must be met in order to guarantee that the next generation of talent will have a high level of overall quality is the improvement of the mental health of college students (CSMH) in the new era. One component of public health is the emotional well-being of students in higher education. The state of the public's health is consistently ranked among the most urgent problems facing modern society. However, there is not much hope for the Chinese CSMH. In order to effectively manage their mental health, a variety of educational institutions, including colleges and universities, have proposed a large number of management strategies for CSMH. The vast majority of these strategies are not targeted, and they do not offer a variety of management strategies that are based on the many different psychological states. It is necessary to first be able to accurately predict the mental health status of each individual college student in order to achieve the goal of improving the mental health management of students attending colleges and universities. This study proposes using a multi-view K-means algorithm, abbreviated as MvK-means, to analyze the CSMH's data on mental health. This is possible because the data can be obtained from multiple perspectives. This paper presents a multi-view strategy as well as a weight strategy in light of the fact that each point of view contributes in its own unique way. Different weight values should be assigned to each view's data, which will ultimately result in an improved evaluation effect of the model. The findings of the experiments indicate that the model that was proposed has a beneficial impact on the analysis of the data pertaining to the mental health of college students. [ABSTRACT FROM AUTHOR]

To prevent the mental health problems of college preference students effectively, this paper analyzes the influence of college students' internet media use behaviors on their mental health in the information age. We make an empirical study on the above problems by using metrology models under the condition of controlling individual factors. The result shows that the mental health of college students is significantly affected by different internet media use behaviors and shows obvious heterogeneity. Preference for games and soap operas or films has a significant negative relationship with the mental health of college students, while the preference for science, education programs, and the preference to obtain current political news comments through official media have a positive impact on the psychological security of college students. Meanwhile, the mental health of college students is also significantly influenced by individual factors. The education level, family income, and social satisfaction show a significant positive correlation with the mental health of college students. [ABSTRACT FROM AUTHOR]

In music teaching in high schools, teachers should not only impart corresponding music knowledge to students but also focus on cultivating students' comprehensive quality and quality. In the process of music teaching in universities, we should focus on students' psychological adjustment and emotional health care. In order to quantify the application effect of big data technology in music teaching reform, this paper takes piano teaching in universities as an example to conduct research and mainly analyzes the physiological and psychological prediction effects involved in the teaching process. This paper introduces three typical big data technologies to predict and analyze the data involved in the existing piano teaching in universities. The analysis results show that the prediction effect based on the fuzzy neural inference system is the best. In addition, the three-dimensional display of the prediction data shows that the prediction effect obtained by big data technology shows good consistency and continuity, which indicates that the prediction method based on big data technology is suitable for psychological adjustment and emotional health care in music teaching in universities. [ABSTRACT FROM AUTHOR]

Primary and secondary schools have the enormous responsibility of developing talent over a hundred years, and they should not only be concerned with the moral, ideological, and cultural development of teenagers but also with their mental well-being. We need to start by making the external environment better, provide in-depth psychological counseling, and support students as they work to continually increase their psychological adaptability in order to promote the healthy development of their personalities. As the epidemic situation in China has now stabilized into a normal state of prevention and control, it is imperative to provide primary and secondary school students with mental health education. In light of this context, this paper develops a browser-server network architecture-based consultation system for the mental health of students in primary and secondary schools. It eliminates the conventional booking mode and substitutes credibility as the characteristic programming parameter. The performance of the original system is improved by the reliability model the most when the parameter is set to 0.2, and the recovery rate rises by 1.32 percent. Compared to the original reliability model, which improved the system's F value performance by 0.83 percent, the accuracy rate only declines by 0.68 percent while F rises by 0.37 percent. This research is crucial for creating an information campus and raising the standard of psychological counseling. [ABSTRACT FROM AUTHOR]

It is necessary to pay attention to and study the physical and mental health development of college students. On the basis of statistical analysis of the questionnaire, this paper studies the impact of pretest mental health intervention on college students' English test scores, summarizes the problems and characteristics of college students' mental health, and explores the reasons for psychological problems. Based on the research results and related survey data of the mental health status of college students by scholars, this paper believes that these reasons mainly include students' personal reasons, school and social environment pressure, and insufficient family support factors. The data analysis shows that in the relationship between English education and mental health in colleges and universities, the amount of mental health intervention of students' extracurricular exercise has a stable and low negative correlation with the scores of each factor of SCL-90 (Symptom Checklist 90) and is negatively correlated with the scores of each subscale. The experimental results show that there are extremely significant differences in academic performance (F = 5.084 , P < 0.01), and there is a certain linear relationship between students' mental health level and students' English exercise feeling. The lower the fatigue score, the higher the mental health level of the students, which effectively promotes the mental health development of college students. [ABSTRACT FROM AUTHOR]

In real life, people are at a risk of encountering various negative emotions all the time, and in the case of long-term negative emotions, it is easy to fall into a state of depression. However, in the current mental health system, the diagnosis of the depressive state of a client usually requires a doctor or a consultant to conduct face-to-face or video consultation with the client, which is time consuming and labor intensive. Therefore, it is necessary to adopt IT for mental health monitoring and personality data analysis. In order to achieve better results in identifying the students' mental health problems, this paper attempts to use multiple data sources, proposes an algorithm for identifying mental health problems based on multiple data sources, and uses the data on students' mental states provided in psychology as labels to improve the shortcomings brought about by the questionnaire approach. To further optimise the model identification results, this paper proposes a mental health problem identification algorithm based on the DeepPsy model. A 2D-CNN was used to extract the online pattern of a day, an LSTM network was used to capture the temporal dependency between days, and a deep learning network was designed to combine the underlying features with the online trajectory pattern. Experiments showed an accuracy of 0.71, a recall of 0.75, and an F1-Measure of 0.72, and were able to identify 75% of students with mental health problems. [ABSTRACT FROM AUTHOR]

With the development of modern technology, a variety of values and social thoughts based on streaming media have caused a huge impact on the field of ideology and culture, and contemporary college students are deeply affected. Nowadays, college students are very prone to problems such as lack of empathy, distorted values, and weakening of life values. College students commit suicide, homicide, and other illegal and criminal incidents due to unhealthy psychological reasons. This paper abstracts the emotional cognitive ability of college students into a psychological resilience model and then analyzes it. It is concluded that the overall applicability of college students to emotional cognition education in the psychological classroom is not high. In order to change the overall low applicability of this situation, this paper pioneers the application of the Internet of Things (IoT) technology to the emotional cognitive education system of college students' psychological classrooms. Through the experiment, four results of the two psychological classroom models were obtained under different genders, different grades, different household registration types, and comprehensive conditions. The improved mode of combining the Internet of Things technology with emotional cognitive education can increase the applicability of college students to emotional cognitive education in the psychological classroom by about 6.97%. It helps to cultivate and educate the positive emotions of college students and promote the comprehensive and healthy development of college students. [ABSTRACT FROM AUTHOR]

Artificial intelligence technology has become an important part of the development of Internet technology. Artificial intelligence technology can help colleges and universities optimize the network ideological and political teaching system. Artificial intelligence technology provides more accurate data resources and rich and reliable educational technology means for online public mental health education in colleges and universities. This paper comprehensively uses a variety of methods such as qualitative and quantitative analysis, case and empirical analysis, literature analysis, and artificial intelligence technology. Artificial intelligence technology has been closely integrated with online public mental health education in colleges and universities. The model systematically analyzes the optimization methods of artificial intelligence technology methods for the online public mental health education system in colleges and universities, and constructs an innovation system for online public mental health education in colleges and universities. Based on the comprehensive analysis of artificial intelligence and public health in colleges and universities, this paper further proposes the application of artificial intelligence technology in online public mental health education in colleges and universities. On this basis, the model conducts an in-depth analysis of artificial intelligence technology and the online public mental health innovation system. The model supports the development of ideological and political teaching in colleges and universities through various forms such as idea innovation, path innovation, carrier innovation, and mechanism innovation. [ABSTRACT FROM AUTHOR]

With the rise of self-driving technology research, the establishment of a scientific and perfect legal restraint and supervision system for self-driving vehicles has been gradually paid attention to. The determination of tort liability subject of traffic accidents of self-driving cars is different from that of ordinary motor vehicle traffic accident tort, which challenges the application of traditional fault liability and product liability. The tort issue of self-driving cars should be discussed by distinguishing two kinds of situations: assisted driving cars and highly automated driving, and typological analysis of each situation is needed. When the car is in the assisted driving mode, the accident occurs due to the quality defect or product damage of the self-driving car, and there is no other fault cause; then, the producer and seller of the car should bear the product liability according to the no-fault principle; if the driver has a subjective fault and fails to exercise a high degree of care; the owner and user of the car should bear the fault liability. This paper analyzes the study of the impact of autonomous driving public on public psychological health, summarizes the key factors affecting the public acceptance of autonomous driving, and dissects its impact on public psychological acceptance. In order to fully study the responsibility determination of autonomous driving system accidents and their impact on public psychological health, this paper proposes an autonomous driving risk prediction model based on artificial intelligence technology, combined with a complex intelligent traffic environment vehicle autonomous driving risk prediction method, to complete the risk target detection. The experimental results in the relevant dataset demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Mental health is always a concern, especially for students, as they are more prone to stress based on educational burden and competition. Among student groups at different levels, college students are of serious concern as they are an essential pillar of social and economic development, and their mental health has been the society's focus in recent years. With the increasing population leading to the increasing number of college students in our country, the competition for professional learning is also becoming fiercer, seriously affecting students' mental health. Little attention has been paid to adverse effects on mental health or effective mitigation strategies to improve mental health in recent years. However, it is still of grave concern as the stress among students leads to depression, several diseases, and ultimately death. The purpose of this study is to evaluate the effect of physical exercise interventions on stress groups irrespective of their (educational) levels. Physical activity can effectively release stress and is an excellent way to regulate emotions. For this reason, it is a task that the current universities must complete to strengthen physical exercise in students' mental health education. The paper highlights the impact of various social pressures on students' mental health, understands its underlying mechanisms, and explores feasible mitigation strategies for improving and schooling students' mental health. This paper proposes an integrated evaluation-based algorithm to explore the model of the intervention effect of physical exercise on college students. It takes college students as the representative of stress groups. The results show that daily physical activities can effectively relieve the stress of college students. [ABSTRACT FROM AUTHOR]

Chinese contemporary college students, this generation has been pampered since childhood, growing up under the wings of their parents, most of them are flowers in the hothouse, now stepping into the university and carrying the double expectations of society and family. With the rapid development of modern technology and social culture, people in modern society are facing fierce competition, frequent stress, fast pace, and unprecedented psychological pressure, which has a significant impact on human health. Therefore, the construction of a university psychological wellness education model has become the focus of theoretical research. As a new type of mental health teaching and learning model, data-driven learning (DDL) not only provides learners with rich, diverse, and realistic mental health data, but also creates an ideal learning environment for learners due to its corpus-based teaching and learning characteristics. This paper explores the design of DDL-based mental health teaching and learning for students, combining theoretical research, and empirical analysis from the actual university, and constructing a comprehensive system of psychological wellness education in college while building a local system of DDL-based psychological wellness education. The experimental results show that the Q-learning algorithm and SA-Q algorithm have no environmental triggering mechanism, while the data-driven control algorithm has the step number of formula 24, 19, and 17, respectively, thus reaching the optimal path. Therefore, in the data-driven psychology classroom, students change from participating in activities according to the course teaching objectives and mental health teachers' requirements to inquiry-based learning and interactive experiences that focuses on problem solving and task completion. [ABSTRACT FROM AUTHOR]

Psychological wellness is a significant piece of the cutting edge idea of well-being, and a decent degree of emotional well-being is the assurance for understudies to study and live. The purpose of this paper is to study how to promote college students to form a good view of health and establish a healthy, civilized, and scientific way of life. This paper proposes the use of intelligent navigation control to assist running to promote the mental health of college students and proposes methods of intelligent navigation control to assist running. The experimental results in this paper show that E three − dimensional feeling = 10.13, E action response time = 4.12, and E sense of balance = 3.35. It can be seen that the mental health indicators of college students after practice are better than those before practice. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to provide a group music therapy intervention for elementary and middle school students with mood disorders through music therapy. To explore the improvement of group music therapy on the dysphoria and state of adolescent patients with mood disorders and to explore the relationship with self-identity. A music activity-based mental health education curriculum was designed based on the results of the current survey, while two homogenous classes were selected as the experimental and control classes; subsequently, the experimental teaching of the music activity-based mental health education curriculum was conducted in the experimental class, and the regular school mental health education curriculum was conducted in the control class, and the pre- and postexperimental scale tests were used to analyze that the curriculum of this study had a positive effect of this study's curriculum on elementary school students' positive emotions analyzed through pre- and postexperimental scale tests. The music activity-based mental health education program had a significant positive effect on the overall level of positive emotions of elementary school students, especially in the positive emotion index, happiness index, mental toughness, goal focus, and interpersonal assistance factor. The positive psychology-oriented music activity-based mental health education curriculum is well suited for elementary and middle school students, especially for upper elementary and middle school students. The music activity-based mental health education curriculum realizes the value of applying positive psychology to mental health education efforts at the elementary school level and flexibly uses a variety of related theories to promote positive emotional experiences for elementary and middle school students. [ABSTRACT FROM AUTHOR]

Objective. Under the background of the policy of caring for the healthy growth of left-behind children, the purpose of selecting the topic is to study some common negative emotional problems of left-behind children in rural areas, focusing on the guidance of negative emotions of left-behind children in rural areas. In emotional problems, we analyze and find out the reasons for these negative emotions through observation and research. Method. In this paper, a platform for acquiring emotional semantic data of scene images in an open behavioral experimental environment is designed, which breaks the limitations of time and place, and thus acquires a large amount of emotional semantic data of scene images and then uses principal component analysis to evaluate the validity of the data analysis. Psychological testing was used to measure parent-child affinity, adversity beliefs, and positive/negative emotion scales, respectively, to examine children whose parents went out, children whose fathers went out, and non-left-behind children. The characteristics of parent-child affinity, adversity beliefs, and positive/negative emotions in three types of children were examined, and the direct predictive effects of parent-child affinity and adversity beliefs on the positive/negative emotions of the three types of children were examined. Results/Discussion. Adversity beliefs played a partial mediating role between children's parent-child bonding and positive emotions. The predictive effect of adversity beliefs on children's emotional adaptation differs by emotional type. The main effects of the left-behind category were significant for both positive and negative emotions. The gender main effect of negative emotion was significant, and the negative emotion level of girls was significantly higher than that of boys. The main effect of the left-behind category of adversity beliefs was significant, and the adversity belief levels of children whose parents went out to rural areas were significantly lower than those of children whose fathers went out and non-left-behind children. The negative emotions generated by left-behind children in rural areas are channeled, and to a certain extent, they are improved and alleviated. Through the emotional counseling and improvement of the rural left-behind children in the research site in the article, the service objects can have better emotions, promote mental health, make them happy and grow up healthily, and also provide a certain theory for the establishment of the local left-behind children care system. [ABSTRACT FROM AUTHOR]

Objective. Therapeutic intervention can improve the overall level of mental health of American postmodern fiction writers by improving their social communication skills and overall well-being. This paper discusses the application of art therapy in the mental health education of American postmodern novel creators and proves that expressive art therapy intervention is effective in improving the mental health level of American postmodern novel creators. Method. This article attempts to help American postmodernist novel creators understand their own mental health status by means of individualized assessment and therapeutic intervention and to analyze and discover their own potential mental health problems. The writers of postmodernist novels in the USA were measured and screened by means of scales and questionnaires, and the members who met the experimental intervention were divided into experimental group and control group, and the experimental group received a 30-day reception music therapy intervention. After the intervention, the data will be counted, and the quantitative and qualitative aspects will be analyzed to comprehensively evaluate the effect of the intervention. Results/Discussion. Receptive music therapy intervention has a significant effect in relieving the anxiety of American postmodernist novel creators and plays a positive role in helping American postmodernist novel creators better adapt to study life and build good emotional psychology and interpersonal relationships. Psychological counseling relies more on external forces to correct cognition and adjust psychology, while music therapy intervention, as a nonsemantic art, can arouse inner functions and mobilize the self-healing potential of American postmodern novel creators. Practice has proven that when the language intervention of traditional psychotherapy encounters resistance and silence, music as a special language plays a vital role. The nonlinguistic nature of music, through a mode of reproduction of sounds in nature, makes the beautiful and soothing melody stimulate a pleasant and peaceful psychological experience through human hearing. [ABSTRACT FROM AUTHOR]

In order to meet the differentiated needs of students and improve the satisfaction of college mental health textbook recommendation, a college mental health textbook recommendation scheme based on improved deep learning algorithm is proposed. Based on the analysis of the principle of deep learning data recommendation system, the data interest is calculated according to the browsing records of students on college mental health textbooks. Combine the deep learning algorithm and collaborative filtering algorithm to collect the demand data of college mental health textbooks, then use the Naive Bayesian classification method to divide the college mental health textbooks into interested and uninterested parts, and recommend the interested college mental health textbooks to the students in need. Experiments show that the longest recommendation time of the college mental health textbook recommendation scheme based on the improved deep learning algorithm proposed in this paper is 4.5 min, the highest recommended recall rate is 95.18%, the average accuracy is 97.2%, the highest content richness is 0.8, the system stability coefficient is 1.06, and the overall average praise rate is 97.79%. It has a good recommendation effect. [ABSTRACT FROM AUTHOR]

This paper constructs a platform framework for extensive data analysis of college students' psychological quality with the help of the thinking mode of big data and related technologies and proposes the construction principles, data sources, data processing methods, data platform construction, and platform application of big data analysis platform for college students' psychological quality assessment. This paper combines the application methods of big data technology, collects the management data related to the psychological quality assessment of college students, saves them into the system database with certain storage logic, and realizes the function of psychological quality assessment through the design of selected psychological quality assessment data, data management and data resource management and other parts based on the data results of extensive data analysis. This study provides some insights into the psychological quality assessment of college students. The strength of association between the variables of psychological quality assessment of college students changes over time, but the overall psychological structure is more stable. This stable psychological structure characteristic is conducive to constructing the policy of constant psychological education in large universities. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper examines the characteristics and current situation of children's vocal enlightenment toy design, studies how to design children's verbal enlightenment toys based on audiovisual associative experience, and develops appropriate optimization strategies and approaches. This paper analyzes the theoretical basis involved in design practice, summarizes the generation and concept of audiovisual association and the significance of associative experience for children's vocal enlightenment, explores the application and characteristics of interaction design in children's toys, and summarizes the creation of interactive toys. The triggered form of associative experience is determined according to the physical and mental development characteristics, interaction behavior, and experimental research of children at this stage. By summarizing the typical design elements of existing children's interactive toys with good sales and reputation and designing a questionnaire, the Kano model was used to obtain the design element priorities to guide design practice. We used audiovisual association as an entry point to writing a sound and picture interactive program through processing and the Arduino platform to develop the interactive toys. "Sound fun" is an interactive toy that extracts the characteristics of children's voices to correspond to the changes of picture elements and can provide real-time feedback of dynamic pictures through the user's voice to achieve the purpose of triggering a synesthetic experience. Interaction design applied to toy design is a new direction in terms of traditional toy design, which enhances the interactivity of toys and enhances the user's sense of experience and participation in the use of toys; it can improve the affinity and fun of toys. [ABSTRACT FROM AUTHOR]

Mental health essentially refers to a state of mind. It means that an individual can keep a good or normal state in behavior. It is not only related to the overall development of the individual body and mind but also affects the construction of university teachers. This paper mainly studies the career development anxiety of music teachers in colleges and universities in China, analyzes its causes, and puts forward corresponding countermeasures and suggestions to alleviate the pressure and promote the physical and mental harmony of music teachers and the common growth of a good social atmosphere. The purpose is to help music teachers in colleges and universities better manage their mental health. This paper collects the data of occupational stress and mental health of 164 music teachers in many colleges and universities through the method of a questionnaire survey and processes the data with the analysis formula of sample variance and standard deviation. The analysis shows that a considerable number of the respondents have career development anxiety. [ABSTRACT FROM AUTHOR]

Mental health problems will seriously damage social harmony and family happiness. This paper proposes a study on mental health intelligence assessment based on multisource information fusion. Combining the data description of UPI and SCL-90 and the corresponding task requirement analysis, the multisource information fusion visualization based on the Circos diagram is designed and realized, and the parallel coordinate visualization is established. The MDS algorithm is used to project multidimensional survey objects into low-dimensional visualization space, and the actual UPI and SCL-90 questionnaire data for 278 students of a certain major at a university provided by the cooperative unit are used. The results show that the mental health problems of student A are serious, and the symptoms of depression and schizophrenia are prominent, so it is necessary to seek psychological experts for corresponding treatment in time. By contrast, student B's mental health problems are also serious, and the user judges that student B still needs further diagnosis and treatment. The correlation analysis results of multisource information fusion are roughly the same as the actual situation, which is convincing. Therefore, the multisource mental health information fusion of college students has a certain correlation and complementarity. [ABSTRACT FROM AUTHOR]

Healthcare is predominantly regarded as a crucial consideration in promoting the general physical and mental health and well-being of people around the world. The amount of data generated by healthcare systems is enormous, making it challenging to manage. Many machine learning (ML) approaches were implemented to develop dependable and robust solutions to handle the data. ML cannot fully utilize data due to privacy concerns. This primarily happens in the case of medical data. Due to a lack of precise clinical data, the application of ML for the same is challenging and may not yield desired results. Federated learning (FL), which is a recent development in ML where the computation is offloaded to the source of data, appears to be a promising solution to this problem. In this study, we present a detailed survey of applications of FL for healthcare informatics. We initiate a discussion on the need for FL in the healthcare domain, followed by a review of recent review papers. We focus on the fundamentals of FL and the major motivations behind FL for healthcare applications. We then present the applications of FL along with recent state of the art in several verticals of healthcare. Then, lessons learned, open issues, and challenges that are yet to be solved are also highlighted. This is followed by future directions that give directions to the prospective researchers willing to do their research in this domain. [ABSTRACT FROM AUTHOR]

Background. The prominence of technology in modern life cannot be understated. However, for some people, these innovations or their related plausible advancements can be associated with perceptual misinterpretation and/or incorporation into delusional concepts. Objective. This paper aims to explore the intersection of technological advancement and experiencing psychosis. We present a discussion about the explanation seeking that incorporates the concept, that for some people, of technological innovation becoming intertwined with delusional symptoms over the past 100 years. Methods. A longitudinal review of the literature was conducted to synthesize and draw these concepts together, mapping them to a timeline that aligns computing science and healthcare expertise and presents the significant technological changes of the modern era charted against mental health milestones and reports of technology-related delusions. Results. It is possible for technology to be incorporated into the content of delusions with evidence supporting a link between the rate of technological change, the content of delusions, and the use of technology as a way of seeking an explanation. Moreover, analysis suggests a need to better understand how innovations may impact the mental health of people at risk of psychosis and other mental health conditions. Conclusions. Clinical experts and lived experience experts need to be informed about and collaborate with future research and development of technology, specifically artificial intelligence and machine learning, early in the development cycle. This concurs with other artificial intelligence research recommendations calling for design attention to the development and implementation of technological innovation applied in a mental health context. [ABSTRACT FROM AUTHOR]

In order to further investigate and understand the relationship between college students' learning adaptation process and mental health in the learning process under the information-based teaching environment, this paper makes a questionnaire survey on college students' learning adaptation and mental health and selects 408 college students as the research object. The results show that the potential profile analysis shows that with the development of network and informatization, the learning adaptability of college students can be divided into four types: troubled group (accounting for 7.598%), marginal adaptive group (accounting for 42.892%), maladaptive group (accounting for 4.167%), and good adaptive group (accounting for 45.343%). The mental health level of the latter two is better, and the mental health level of the first two is worse. Students who do not adapt to learning and students who adapt well show common characteristics. Most of them are only children, and their parents have a high level of education. This kind of family often has good material conditions and loose family atmosphere, which will also form a protective mechanism for students' mental health, making students have good self-acceptance ability and good mental health level. [ABSTRACT FROM AUTHOR]

Understanding human perception and requirements on food for cancer prevention and condition management is important so that food applications can be catered to cancer patients. In this paper, web scraping was conducted to understand the public's perception, attitude, and requirements related to a plant-based diet as a recommended diet for cancer prevention and condition management. Text and sentiment analyses were carried out on results gathered from 82 social sites to determine whether noncancer and cancer patients use plant-based diets, how they have been consumed, their benefits in the prevention and condition management of cancers, the existing myths/fake news about cancer, and what do cancer patients need in a food app. The results of the text analysis highlighted gaps in existing apps, including a lack of credibility as there were a lot of fake news and myths about cancer and endorsement by professionals. Future food apps should provide personalized diets to include both plant-based diets as well as meat, symptom management, good user experience, credibility, and emotional and mental health support. [ABSTRACT FROM AUTHOR]

Objective. In recent years, people's living standards have been greatly improved, but at the same time, it also brings many health problems, among which mental health problems and sleep problems of college students are important problems. The aim of the study is to explore the effect of physical activity intervention on college students' mental health and provide a new way of thinking for colleges and universities to carry out mental health interventions. Methods. This paper focuses on the physical health problems of college students and explores the relationship between aerobic exercise, emotion, and sleep quality among college students. The SPSS statistical method was used to analyze the differences in aerobic exercise, emotion, and sleep quality among college students in terms of demographic variables; to explore the relationship between aerobic exercise, emotion, and sleep quality; and to construct a structural equation model using the relationship between them. Results/Discussion. This study explores the relationship between aerobic exercise and sleep quality and psychological health of college students, further analyzes the path model of the role of aerobic exercise and psychological health on sleep quality of college students, and verifies it through experiments, which proves to help universities and relevant departments understand the current situation of exercise and sleep quality of college students and provide timely and effective design of mandatory aerobic exercise courses for college students who lack exercise and have sleep problems. At the same time, it helps college students to understand their sleep situation and adjust their aerobic exercise courses according to their sleep status. [ABSTRACT FROM AUTHOR]

As a treasure left over from Chinese traditional culture, martial arts have a long history and lasts for a long time. With the country's promotion and support of martial arts culture, martial arts have also attracted more and more people's attention. In order to carry forward the martial arts culture, the combination of martial arts and sports has formed a set of martial arts sports suitable for today's students, such as martial arts aerobics. It is used as a class exercise for students, and basically, every student in the school has learned it and practiced it often. However, with the development of the times, it is difficult for today's students to arouse students' enthusiasm for martial arts sports for traditional martial arts sports. Artificial intelligence technology and virtual reality, as products of today's digital age, attract the attention and use of students with their unique features. This also means that the reform of martial arts sports based on artificial intelligence and virtual reality technology is imperative in order to make more students regain their enthusiasm for martial arts sports. However, the specific impact of artificial intelligence and virtual reality on the physical and mental development of students in martial arts sports is a problem to be confirmed by research. Through in-depth research on artificial intelligence and virtual reality technology, this paper shows that artificial intelligence and virtual reality martial arts sports can increase the lung capacity of boys by about 14% and girls by 16%; the effect on physical fitness can increase the lower body strength of boys by 3% and the flexibility of girls by 30%; as for the impact on mental health, it can be concluded that the emotional and cognitive dimensions of boys and girls have increased by about 19% compared with the previous values. [ABSTRACT FROM AUTHOR]

Research Background. With the enhancement of China's international influence, China has stepped into the international ecological environment in the fields of economy, politics, culture, art, and so on, accompanied by the spread of China's culture and literature. China's 5000-year-old cultural history and artistic characteristics are integrated into the ecological field of the international environment. Research Purpose. The international spread of Chinese literature also has a certain impact on the physical and mental health of teenagers. This paper studies and discusses the impact of international communication of Chinese literature on teenagers' physical and mental health in the digital humanistic environment. Under the development environment of Digital Humanities in China, the impact of Chinese literature on the healthy psychology of teenagers, the impact content, and the characteristics of each were evaluated. Through the comparison of physical and mental health growth of adolescents in different ages, the characteristics of physical and mental health of adolescents are explored. The coupling degree of physical and mental health of adolescents in different development environments is compared and analyzed. Research Results. Through the research, it is found that with the development of Digital Humanities, the spread of Chinese literature with internationalization has a positive impact on the physical and mental health and psychological quality construction of teenagers and plays a promoting role in promoting mental health, increasing personal quality, and improving teenagers' correct values. The various ideological and moral qualities of Chinese literature can play a greater role in helping and growing up the physical and mental health education of young people in the new era and are also the literary value of promoting the quality education of the next generation of young people in the world. [ABSTRACT FROM AUTHOR]