Climate change,ambient air pollution,and students'mental health

The impact of global climate change and air pollution on mental health has become a crucial public health issue.Increased public awareness of health,advancements in medical diagnosis and treatment,the way media outlets report environmental changes and the variation in social resources affect psychological responses and adaptation methods to climate change and air pollution.In the context of climate change,extreme weather events seriously disrupt people's living environments,and unstable educational environments lead to an increase in mental health issues for students.Air pollution affects students'mental health by increasing the incidence of diseases while decreasing contact with nature,leading to problems such as anxiety,depression,and decreased cognitive function.We call for joint efforts to reduce pollutant emissions at the source,improve energy structures,strengthen environmental monitoring and governance,increase attention to the mental health issues of students,and help student groups build resilience;by establishing public policies,enhancing social support and adjusting lifestyles and habits,we can help students cope with the constantly changing environment and maintain a good level of mental health.Through these comprehensive measures,we can more effectively address the challenges of global climate change and air pollution and promote the achievement of the United Nations Sustainable Development Goals.

Unlocking the power of physical activity in easing psychological distress

The severity of the current global mental health situation and the importance of maintaining psychological well-being call for more powerful,convenient,and efficient solutions for addressing psychological issues and relieving mental stress.Physical activity not only effectively improves physical fitness and reduces negative emotions such as anxiety and depression but also increases the improvement of psychological health and sense of well-being.At the same time,physical activity interventions for mental health have unique advantages,including reducing the side effects of psychological interventions and increasing necessity,convenience,and cost-effectiveness,as well as flexible adaptability across multiple methods,groups,and age ranges,providing stronger support for relieving psychological stress and addressing psychological issues.Although physical activity is an important intervention measure in relieving psychological stress,its value and role in mental health care seem to have not yet received sufficient attention,and its potential remains to be further revealed.Given the significant advantages and effectiveness of physical activity in mental health intervention practices,it is necessary to stimulate its potential in relieving psychological stress through various means in future studies to better safeguard the public’s physical and mental health.Developing guidelines for physical activity for improved mental health,enhancing organic integration with other intervention measures,and providing necessary respect,encouragement,and support are important directions to consider.

Potential use of large language models for mitigating students’problematic social media use:ChatGPT as an example

The problematic use of social media has numerous negative impacts on individuals'daily lives,interpersonal relationships,physical and mental health,and more.Currently,there are few methods and tools to alleviate problematic social media,and their potential is yet to be fully realized.Emerging large language models(LLMs)are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life.In mitigating problematic social media use,LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users,providing personalized information and resources,monitoring and intervening in problematic social media use,and more.In this process,we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT,leveraging their advantages to better address problematic social media use,while also acknowledging the limitations and potential pitfalls of ChatGPT technology,such as errors,limitations in issue resolution,privacy and security concerns,and potential overreliance.When we leverage the advantages of LLMs to address issues in social media usage,we must adopt a cautious and ethical approach,being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.

Using ChatGPT to promote college students’participation in physical activities and its effect on mental health

As one of the most famous large language models,ChatGPT has great potential for application in physical education.It can provide personalized exercise plans,a variety of exercise options,and interactive support.The integration of ChatGPT into the teaching process can promote college students’participation in physical activities and improve their mental health while expanding the traditional teaching environment and promoting the reform of traditional teaching methods.However,the application of ChatGPT faces challenges and obstacles in physical education.To make full use of ChatGPT in physical education,it can be combined with wearable devices and sports equipment to enhance the efficiency of interactions with users.Relevant policies are urgently needed to avoid the improper use of users’data.

Risk factors and digital interventions for anxiety disorders in college students:Stakeholder perspectives

The worldwide prevalence of anxiety disorders among college students is high,which negatively affects countries,schools,families,and individual students to varying degrees.This paper reviews the relevant literature regarding risk factors and digital interventions for anxiety disorders among college students from the perspectives of different stakeholders.Risk factors at the national and societal levels include class differences and the coronavirus disease 2019 pandemic.College-level risk factors include the indoor environment design of the college environment,peer relationships,student satisfaction with college culture,and school functional levels.Family-level risk factors include parenting style,family relationship,and parental level of education.Individual-level risk factors include biological factors,lifestyle,and personality.Among the intervention options for college students'anxiety disorders,in addition to traditional cognitive behavioral therapy,mindfulness-based interventions,psychological counseling,and group counseling,digital mental health interventions are increasingly popular due to their low cost,positive effect,and convenient diagnostics and treatment.To better apply digital intervention to the prevention and treatment of college students'anxiety,this paper suggests that the different stakeholders form a synergy among themselves.The nation and society should provide necessary policy guarantees,financial support,and moral and ethical supervision for the prevention and treatment of college students'anxiety disorders.Colleges should actively participate in the screening and intervention of college students'anxiety disorders.Families should increase their awareness of college students'anxiety disorders and take the initiative to study and understand various digital intervention methods.College students with anxiety disorders should actively seek psychological assistance and actively accept and participate in digital intervention projects and services.We believe that in the future,the application of methods such as big data and artificial intelligence to improve digital interventions and provide individualized treatment plans will become the primary means of preventing and treating anxiety disorders among college students.

Delivering substance use prevention interventions for adolescents in educational settings:A scoping review

Currently,a proportion of adolescents use alcohol,tobacco,and illicit drugs,which inevitably harms their health and academic progress.Adolescence is a peak period for substance use initiation and a critical time for preventing substance use problems.Various entities,such as families,schools,and communities,have implemented a variety of interventions to alleviate adolescent substance use problems,and schools play a unique role.To explore the types,characteristics,and effectiveness of substance use interventions in educational settings for adolescents,we conducted a scoping review and identified 32 studies after screening.We divided the 32 studies according to intervention type,including curriculum interventions focusing on cognitive-behavioral skill enhancement,exercise interventions,peer interventions and family-school cooperation,and electronic interventions.Except for the mixed results on electronic interventions,the results showed that the other interventions were beneficial to different extents in alleviating adolescent substance use problems.In addition,we analyzed and summarized the advantages and challenges of intervening in adolescent substance use in educational settings.Schools can use equipment and human resources to provide adolescents with various types of intervention measures,but they also face challenges such as stigmatization,ineffective coordination among multiple resources,and poor implementation effects.In the future,school-based intervention measures can fully utilize big data and artificial intelligence technology and collaborate with families and communities to intervene appropriately while paying attention to the comorbidity risks of substance use disorders and psychological health issues.

Digital interventions empowering mental health reconstruction among students after the COVID-19 pandemic

With the gradual end of the coronavirus disease 2019(COVID-19)pandemic,the reconstruction of students’mental health is urgently necessary.Digital interventions offer advantages such as high accessibility,anonymity,and accurate identification,which can promote the reconstruction of students’mental health through the provision of psychological support platforms,psychological assessment tools,and online mental health activities.However,we recognize that digital interventions must undergo many adjustments,and corresponding ethical norms require further clarification.It is crucial for different stakeholders to collaborate and work toward maximizing the effectiveness of digital interventions for the reconstruction of mental health after the COVID-19 pandemic.

Potential and limitations of ChatGPT and generative artificial intelligence in medical safety education

The primary objectives of medical safety education are to provide the public with essential knowledge about medications and to foster a scientific approach to drug usage.The era of using artificial intelligence to revolutionize medical safety education has already dawned,and ChatGPT and other generative artificial intelligence models have immense potential in this domain.Notably,they offer a wealth of knowledge,anonymity,continuous availability,and personalized services.However,the practical implementation of generative artificial intelligence models such as ChatGPT in medical safety education still faces several challenges,including concerns about the accuracy of information,legal responsibilities,and ethical obligations.Moving forward,it is crucial to intelligently upgrade ChatGPT by leveraging the strengths of existing medical practices.This task involves further integrating the model with real-life scenarios and proactively addressing ethical and security issues with the ultimate goal of providing the public with comprehensive,convenient,efficient,and personalized medical services.

Relationship between depression,smartphone addiction,and sleep among Chinese engineering students during the COVID-19 pandemic

BACKGROUND Existing research has demonstrated that depression is positively related to smartphone addiction, but the role of sleep has not been discussed thoroughly, especially among engineering undergraduates affected by the coronavirus disease 2019 pandemic.AIM To evaluate sleep as a mediator of the association between smartphone addiction and depression among engineering undergraduates.METHODS Using a multistage stratified random sampling method, a cross-sectional survey was conducted among 692 engineering undergraduates from a top engineering university in China, and data were collected by self-reported electronic questionnaires. The data included demographic characteristics, such as age, gender, the Smartphone Addiction Scale-Short Version(SAS-SV), the 9-item Patient Health Questionnaire, and the Pittsburgh Sleep Quality Index. Pearson correlation and multiple linear regression analyses were used to examine the association between smartphone addiction and depression, while structural equation models were established to evaluate the possible mediating role of sleep.RESULTS Based on the cutoffs of the SAS-SV, the rate of smartphone addiction was 63.58 percent, with 56.21 percent for women and 65.68 percent for men, among 692 engineering students. The prevalence of depression among students was 14.16 percent, with 17.65 percent for women, and 13.18 percent for men. Smartphone addiction was positively correlated with depression, and sleep played a significant mediating effect between the two, accounting for 42.22 percent of the total effect. In addition, sleep latency, sleep disturbances, and daytime dysfunction significantly mediated the relationship between depression and smartphone addiction. The mediating effect of sleep latency was 0.014 [P < 0.01;95% confidence interval(CI): 0.006-0.027], the mediating effect of sleep disturbances was 0.022(P < 0.01;95%CI: 0.011-0.040), and the mediating effect of daytime dysfunction was 0.040(P < 0.01;95%CI: 0.024-0.059). The influence of sleep latency, sleep disturbances, and daytime dysfunction accounted for 18.42%, 28.95%, and 52.63% of the total mediating effect, respectively.CONCLUSION The results of the study suggest that reducing excessive smartphone use and improving sleep quality can help alleviate depression.

Artificial intelligence ecosystem for computational psychiatry:Ideas to practice

Computational psychiatry is an emerging field that not only explores the biological basis of mental illness but also considers the diagnoses and identifies the underlying mechanisms.One of the key strengths of computational psychiatry is that it may identify patterns in large datasets that are not easily identifiable.This may help researchers develop more effective treatments and interventions for mental health problems.This paper is a narrative review that reviews the literature and produces an artificial intelligence ecosystem for computational psychiatry.The artificial intelligence ecosystem for computational psychiatry includes data acquisition,preparation,modeling,application,and evaluation.This approach allows researchers to integrate data from a variety of sources,such as brain imaging,genetics,and behavioral experiments,to obtain a more complete understanding of mental health conditions.Through the process of data preprocessing,training,and testing,the data that are required for model building can be prepared.By using machine learning,neural networks,artificial intelligence,and other methods,researchers have been able to develop diagnostic tools that can accurately identify mental health conditions based on a patient’s symptoms and other factors.Despite the continuous development and breakthrough of computational psychiatry,it has not yet influenced routine clinical practice and still faces many challenges,such as data availability and quality,biological risks,equity,and data protection.As we move progress in this field,it is vital to ensure that computational psychiatry remains accessible and inclusive so that all researchers may contribute to this significant and exciting field.

Influencing factors,prediction and prevention of depression in college students:A literature review

The high prevalence of depression among college students has a strong negative impact on individual physical and mental health,academic development,and interpersonal communication.This paper reviewed the extant literature by identifying nonpathological factors related to college students'depression,investigating the methods of predicting depression,and exploring nonpharmaceutical interventions for college students'depression.The influencing factors of college students'depression mainly fell into four categories:biological factors,personality and psychological state,college experience,and lifestyle.The outbreak of coronavirus disease 2019 has exacerbated the severity of depression among college students worldwide and poses grave challenges to the prevention and treatment of depression,given that the coronavirus has spread quickly with high infection rates,and the pandemic has changed the daily routines of college life.To predict and measure mental health,more advanced methods,such as machine algorithms and artificial intelligence,have emerged in recent years apart from the traditional commonly used psychological scales.Regarding nonpharmaceutical prevention measures,both general measures and professional measures for the prevention and treatment of college students'depression were examined in this study.Students who experience depressive disorders need family support and personalized interventions at college,which should also be supplemented by professional interventions such as cognitive behavioral therapy and online therapy.Through this literature review,we insist that the technology of identification,prediction,and prevention of depression among college students based on big data platforms will be extensively used in the future.Higher education institutions should understand the potential risk factors related to college students'depression and make more accurate screening and prevention available with the help of advanced technologies.

Artificial intelligence-assisted psychosis risk screening in adolescents:Practices and challenges

Artificial intelligence-based technologies are gradually being applied to psychiatric research and practice.This paper reviews the primary literature concerning artificial intelligence-assisted psychosis risk screening in adolescents.In terms of the practice of psychosis risk screening,the application of two artificial intelligence-assisted screening methods,chatbot and large-scale social media data analysis,is summarized in detail.Regarding the challenges of psychiatric risk screening,ethical issues constitute the first challenge of psychiatric risk screening through artificial intelligence,which must comply with the four biomedical ethical principles of respect for autonomy,nonmaleficence,beneficence and impartiality such that the development of artificial intelligence can meet the moral and ethical requirements of human beings.By reviewing the pertinent literature concerning current artificial intelligence-assisted adolescent psychosis risk screens,we propose that assuming they meet ethical requirements,there are three directions worth considering in the future development of artificial intelligenceassisted psychosis risk screening in adolescents as follows:nonperceptual realtime artificial intelligence-assisted screening,further reducing the cost of artificial intelligence-assisted screening,and improving the ease of use of artificial intelligence-assisted screening techniques and tools.

Adolescent suicide risk factors and the integration of socialemotional skills in school-based prevention programs

Adolescents are considered one of the most vulnerable groups affected by suicide.Rapid changes in adolescents’physical and mental states,as well as in their lives,significantly and undeniably increase the risk of suicide.Psychological,social,family,individual,and environmental factors are important risk factors for suicidal behavior among teenagers and may contribute to suicide risk through various direct,indirect,or combined pathways.Social-emotional learning is considered a powerful intervention measure for addressing the crisis of adolescent suicide.When deliberately cultivated,fostered,and enhanced,selfawareness,self-management,social awareness,interpersonal skills,and responsible decision-making,as the five core competencies of social-emotional learning,can be used to effectively target various risk factors for adolescent suicide and provide necessary mental and interpersonal support.Among numerous suicide intervention methods,school-based interventions based on social-emotional competence have shown great potential in preventing and addressing suicide risk factors in adolescents.The characteristics of school-based interventions based on social-emotional competence,including their appropriateness,necessity,cost-effectiveness,comprehensiveness,and effectiveness,make these interventions an important means of addressing the crisis of adolescent suicide.To further determine the potential of school-based interventions based on social-emotional competence and better address the issue of adolescent suicide,additional financial support should be provided,the combination of socialemotional learning and other suicide prevention programs within schools should be fully leveraged,and cooperation between schools and families,society,and other environments should be maximized.These efforts should be considered future research directions.