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

A bibliometric analysis of anxiety and depression among primary school students

Background

Rising anxiety and depression in primary school students adversely affect their development and academics, burdening families and schools. This trend necessitates urgent, focused research within this young demographic. This alarming trend calls for a systematic bibliometric analysis to develop effective preventative and remedial strategies.

Objectives

This study aims to identify and analyze the prevailing research hotspots and emerging trends concerning anxiety and depression in primary school students, thereby furnishing a foundational reference for future academic endeavors in this area.

Methods

This study uses the Web of Science (WOS) Core Collection database as the data source, focusing on literature published between 2013 and 2023 concerning anxiety and depression in primary school students. An initial search identified 1852 articles, which were then manually screened to exclude duplicates, conferences, announcements, and unrelated literature, resulting in 1791 relevant articles. The analysis, executed on December 31, 2023, employed CiteSpace and Vosviewer tools to assess various bibliometric indicators including authorship, country, institutional affiliations, publication trends, keyword frequency, and citation analysis.

Results

The analysis revealed a corpus of 1,791 English-language articles, with a discernible upward trend in publications over the decade. The USA and China were the leading countries in this field, with 482and 272 papers, respectively. The research predominantly addresses the etiological factors of anxiety and depression, various intervention strategies, and the comorbidities associated with these conditions in the target population. Key research focuses have been identified in areas such as suicidal thoughts, bullying in schools, the impact of COVID-19, mindfulness interventions, and anxiety related to mathematics. Future research is projected to increasingly focus on the effects of mathematics anxiety on the psychological and behavioral outcomes in students.

Conclusion

This study provides a critical visual and analytical overview of the key research areas and trends in the field of anxiety and depression among primary school students. It underscores the necessity of concentrating on the underlying causes and potential interventions. Such focused research is imperative for mitigating the mental health challenges faced by young students and enhancing their educational and developmental outcomes.

Facilitation or hindrance? The impact of downward social comparison on adversarial growth

Introduction

While adversity can bring great challenges to individuals' life and work, many people also find ways to make positive changes and adapt to these difficult circumstances. Individuals tend to make social comparisons more frequently and intensely when faced with adversity or high stress. The study attempts to examine the influence mechanism of downward social comparison on individual adversarial growth.

Methods

By collecting data from 353 Chinese who have experienced adversities in the past 3 years, the study validates the dual mediating model of gratitude and self-acceptance and explores the moderating effect of interpersonal sensitivity.

Results

The findings indicate that: downward social comparison can increase the occurrence of adversarial growth by enhancing individuals' self-acceptance and gratitude. Compared to individuals with low interpersonal sensitivity, individuals with high interpersonal sensitivity are more likely to facilitate the occurrence of adversarial growth through self-acceptance and gratitude due to downward social comparison.

Discussion

In the face of adversity, individuals can regain self-confidence and respond positively by comparing themselves to people in worse situations than themselves. In particular, individuals with higher interpersonal sensitivity are more likely to benefit from downward social comparisons and grow from adversity.

Primary care physicians' perceptions of artificial intelligence systems in the care of adolescents' mental health

BACKGROUND

Given that mental health problems in adolescence may have lifelong impacts, the role of primary care physicians (PCPs) in identifying and managing these issues is important. Artificial Intelligence (AI) may offer solutions to the current challenges involved in mental health care. We therefore explored PCPs' challenges in addressing adolescents' mental health, along with their attitudes towards using AI to assist them in their tasks.

METHODS

We used purposeful sampling to recruit PCPs for a virtual Focus Group (FG). The virtual FG lasted 75 minutes and was moderated by two facilitators. A life transcription was produced by an online meeting software. Transcribed data was cleaned, followed by a priori and inductive coding and thematic analysis.

RESULTS

We reached out to 35 potential participants via email. Seven agreed to participate, and ultimately four took part in the FG. PCPs perceived that AI systems have the potential to be cost-effective, credible, and useful in collecting large amounts of patients' data, and relatively credible. They envisioned AI assisting with tasks such as diagnoses and establishing treatment plans. However, they feared that reliance on AI might result in a loss of clinical competency. PCPs wanted AI systems to be user-friendly, and they were willing to assist in achieving this goal if it was within their scope of practice and they were compensated for their contribution. They stressed a need for regulatory bodies to deal with medicolegal and ethical aspects of AI and clear guidelines to reduce or eliminate the potential of patient harm.

CONCLUSION

This study provides the groundwork for assessing PCPs' perceptions of AI systems' features and characteristics, potential applications, possible negative aspects, and requirements for using them. A future study of adolescents' perspectives on integrating AI into mental healthcare might contribute a fuller understanding of the potential of AI for this population.

The relationship between mobile phone dependence and academic burnout in Chinese college students: a moderated mediator model

Objective

The aim of this study was to examine the correlation between the level of mobile phone dependence among college students and their experience of academic burnout. Additionally, the study sought to explore the potential mediating effect of study engagement and the moderating role of love.

Methods

During October and December 2023, a cross-sectional study measuring mobile phone dependence, academic burnout, and study engagement among Chinese college students, using the UtrechtWork Engagement Scale-student (UWES-S), College Student Mobile Phone Dependence Questionnaire (CSMPDQ), and Academic Burnout Questionnaire (ABQ). To examine the hypothesis of mediating and moderating effect, SPSS PROCESS was utilized.

Results

The predictive effect of mobile phone dependence on academic burnout was significant (β = 0.410, t = 14.236, p < 0.001), and the predictive effect of mobile phone dependence on academic burnout remained significant when the mediating variable study engagement was introduced (β = 0.308, t = 10.288, p < 0.001), mobile phone dependence had a significant predictive effect on study engagement (β = -0.292, t = -11.639, p < 0.001), and study engagement had a significant positive predictive effect on academic burnout (β = -0.270, t = -9.028, p < 0.001). Love significantly negatively predicted study engagement (β = -0.564, t = -9.641, p < 0.001); and the interaction term for mobile phone dependence and love was significant (β = -0.211, t = -3.688, p < 0.001), indicating a significant moderating effect of love between mobile phone dependence and study engagement.

Conclusion

Mobile phones among college students has been found to have a direct correlation with academic burnout. It can also indirectly contribute to academic burnout by diminishing levels of academic engagement. This indirect relationship is further influenced by love. These findings can help researchers and educators better understand the underlying mechanisms between smartphone dependence and learning burnout in undergraduates.

Adolescent suicide risk factors and the integration of social-emotional 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, self-awareness, 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 social-emotional 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.

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.

The Relationship Between Resilience, Interactive Distance, and College Students' Online Mathematics Learning Engagement: A Longitudinal Study

Introduction

Resilience, a pivotal construct in positive psychology, remains incompletely understood in its facilitation of learners' online engagement. This study aims to investigate the relationship between resilience, transactional distance, and Online Mathematics Learning Engagement (OMLE) among first-year university students.

Methods

Utilizing a cross-lagged path analysis approach, the study surveyed 612 first-year students. Multiple models were constructed and compared to explore the mutual predictive relationships between resilience, transactional distance, and OMLE.

Results

Among the compared models, Model 4 demonstrated the best fit. The model revealed that: (1) resilience at Time 1 and Time 2 positively predicted transactional distance at Time 2 and Time 3; (2) transactional distance at Time 1 and Time 2 positively predicted OMLE at Time 2 and Time 3; (3) resilience at Time 1 significantly predicted OMLE at Time 3; and (4) transactional distance at Time 2 fully mediated the relationship between resilience at Time 1 and OMLE at Time 3. Furthermore, mediational model analysis confirmed that transactional distance played a mediating role in the longitudinal relationship between resilience and OMLE. Using a cross-lagged mediational model with 5000 bootstrap samples, the indirect effect of transactional distance on the relationship between resilience at Time 1 and OMLE at Time 3 was significant and remained stable over time.

Discussion

The findings suggest that resilience, as a positive psychological resource, stimulates students to seek and utilize protective resources in online environments, leading to more active participation in interpersonal communication and classroom interactions. Additionally, resilience helps students overcome emotional and practical difficulties encountered in online learning, thereby enhancing their OMLE. These insights offer valuable implications for educators, highlighting the potential to improve students' online learning engagement by fostering their psychological resilience.

Longitudinal Examination of the Relationship Between Virtual Companionship and Social Anxiety: Emotional Expression as a Mediator and Mindfulness as a Moderator

Purpose

As the interweaving of human interaction and Artificial Intelligence (AI) intensifies, understanding the psychological impact, especially regarding social anxiety, of engaging with AI-driven virtual companionship becomes crucial. While a substantial body of research on social anxiety has concentrated on interactions between individuals, both online and offline, there is a noticeable deficit in explorations concerning how human-computer interactions influence social anxiety. This study offers a comprehensive, longitudinal examination of this underinvestigated relationship, intricately dissecting the roles of emotional expression and mindfulness within the context of AI-based interactions.

Methods

We use social support theory and emotion regulation theory as our theoretical foundation. Data were collected from 618 undergraduate students in Eastern China over two intervals (May 15, 2023 and September 15, 2023). We utilized SPSS 26.0 to conduct descriptive statistics, while AMOS 25.0 facilitated multi-group confirmatory factor analysis (CFA) and the cross-lagged panel modeling.

Results

Our findings indicate that as the frequency of virtual companionship use increases, there's a decline in online social anxiety but a rise in offline social anxiety. Emotional expression emerges as a significant mediator, with heightened emotional expression leading to reduced social anxiety in both contexts. Mindfulness serves as a potent moderator, suggesting its protective role against the potential pitfalls of frequent virtual interactions.

Conclusion

This research not only deepens our theoretical understanding of the dynamics between virtual interactions and social anxiety but also serves as a cornerstone for future endeavors aimed at optimizing AI and devising therapeutic interventions tailored for the digital generation.

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 gover-nance, 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.

Bidirectional reduction effects of perceived stress and general self-efficacy among college students: a cross-lagged study

Perceived stress and general self-efficacy are important issues closely related to the mental health and academic performance of college students. Previous studies have explored the correlation between perceived stress and general self-efficacy, but the understanding of the reciprocal effects of these two factors is still limited. Based on two-wave longitudinal data, this study investigated the bidirectional relationship between perceived stress and general self-efficacy in a sample of Chinese college students. The correlation results showed that perceived stress was significantly negatively correlated with general self-efficacy. Furthermore, by cross-lagged analysis, it was found that perceived stress can significantly negatively predict subsequent general self-efficacy and that general self-efficacy can significantly negatively predict subsequent perceived stress. Bidirectional reduction effects between perceived stress and general self-efficacy are observed among Chinese college students. The results emphasize the necessity of timely stress intervention for college students and the establishment of measures to enhance general self-efficacy.

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 inter-vention measures, and providing necessary respect, encouragement, and support are important directions to consider.

Subjective well-being among PhD students in mainland China: the roles of psychological capital and academic engagement

The mental well-being of PhD students is a major concern in higher education. However, very few studies have investigated the influencing factors of PhD students' subjective well-being (SWB) - an important indicator of mental well-being. Even no study on the influencing factors of PhD students' SWB has been undertaken in mainland China. Based on job demands-resources theory, the present study pioneers the investigation of the relationship between PhD students' psychological capital (PsyCap; comprising self-efficacy, hope, resilience, and optimism) and SWB (comprising positive affect, negative affect, and life satisfaction) in mainland China. It further examined the mediating role of academic engagement (comprising vigor, dedication, and absorption) in this relationship. PhD students (n = 376) from two comprehensive universities in Jiangsu province responded to an online survey. The results showed that (1) self-efficacy was positively associated with life satisfaction, hope was positively associated with positive affect, optimism was significantly associated with all three dimensions of SWB, but resilience was not significantly associated with any of the three SWB dimensions; and (2) dedication mediated the relationship between hope and life satisfaction and that between optimism and negative affect and life satisfaction, but vigor and absorption did not mediate any of the PsyCap-SWB relationships. Limitations and practical implications of this study are discussed.

Perceived discrimination, anxiety and mood disorders among university students during the COVID-19 era: evidence from a cross-sectional survey in a Ghanaian public university

Introduction

Before 2020 and the advent of the COVID-19 pandemic, mental disorders, including anxiety and mood disorders, were considered the leading causes of the global disease burden. There is evidence from multiple countries and social contexts that suggest the high risk of anxiety and mood disorders among students. Yet, there is a knowledge gap concerning understanding the association between the experience of discrimination and the risk of anxiety and mood disorders. We examined the association between the experience of discrimination and the risk of anxiety and mood disorders among university students.

Methods

This study is a cross-sectional survey among university students in Ghana. A quota sampling technique was used to recruit 1,601 students. Data were collected using structured questionnaires. All data were analyzed using Stata. Binary logistic regression model was used to examine the significant association between the outcome variable and the explanatory variables.

Results

The prevalence of anxiety disorder among the respondents was 67 per cent. Students who had experienced discrimination or had any member of their family experienced discrimination had higher odds (OR = 4.59, Cl = 2.64, 7.96) of anxiety and mood disorder compared to those who had not experienced any form of discrimination. Respondents aged 20-24 years had higher odds (OR = 1.47, Cl = 1.16, 1.85) of anxiety and mood disorder than those aged 15-19. Students with a high perceived risk of contracting COVID-19 had a higher odd (OR = 1.52, CI = 1.10, 2.10) compared to those with a low perceived risk.

Conclusion

The findings underscore a need for university authorities to lay out clear initiatives that will reinforce and meet the mental health needs of university students during and after periods of crisis, such as returning from COVID-19 lockdown. There must be a conscious effort to advocate and raise students' awareness of anxiety disorders. Also, it is imperative to create support groups within the university set up to address the mental health needs of all students. Younger students should be the primary focus of these interventions.

Developmental trajectories of depression, anxiety, and stress among college students: a piecewise growth mixture model analysis

Mental health issues are becoming increasingly common among college students, but not all students follow the same developmental trends of mental health. This study aims to identify the developmental trajectories of depression, anxiety, and stress among college students and the related factors for different trajectory classes. The data were collected from a longitudinal survey of college students over four consecutive years, and 2473 students were included in the analysis. The study used a piecewise growth mixture model to determine the subtrajectories, and a multinomial logistic regression model was constructed to investigate the related factors affecting students in subtrajectories. The results revealed that subtrajectories include the low and stable class, increasing class, decreasing then stable class, increasing then decreasing class, and decreasing and high class. The decreasing and high class only presents in the trajectories of anxiety and stress. Regarding related factors, high BMI and high sleep hours were identified as related factors for the increasing class of depression; gender and high sleep hours were associated with the increasing class of anxiety; and hometown location was related to the increasing class of stress. Extroversion personality, relationship with classmates, siblings, and father’s education level are related factors for other subtrajectories. Considering that college students experience multiple trajectories of depression, anxiety, and stress, mental health education and psychological intervention should be carried out for students in each class.

Does Subjective Well-Being Improve Self-Rated Health from Undergraduate Studies to Three Years after Graduation in China?

The health status of emerging adults is at risk. Although subjective well-being is one of the factors closely associated with health, their longitudinal relationship is not clear among emerging adults. The study aimed to investigate the prospective relationship between self-rated health and subjective well-being in emerging adults. The study collected longitudinal data from a total of 1021 Chinese college students (537 males and 484 females) for five years, including two years in college and three years after graduation. In the baseline survey, the average age of the sample was 21.57 years old. Descriptive statistics indicated that both self-rated health and subjective well-being significantly decreased from the senior year of college to the year after graduation. Correlation analysis revealed that self-rated health and subjective well-being had a significant positive relationship. In the five-wave random intercept cross-lagged panel model, subjective well-being unidirectionally predicted self-rated health. In other words, the subjective well-being in the previous year could positively predict self-rated health in the following year, but the previous self-rated health could not predict subsequent subjective well-being. Given the significance of emerging adulthood to individual development, more attention and care should be dedicated to improving subjective well-being so as to maintain good health and engagement in work.

ChatGPT in action: Harnessing artificial intelligence potential and addressing ethical challenges in medicine, education, and scientific research

Artificial intelligence (AI) tools, like OpenAI's Chat Generative Pre-trained Transformer (ChatGPT), hold considerable potential in healthcare, academia, and diverse industries. Evidence demonstrates its capability at a medical student level in standardized tests, suggesting utility in medical education, radiology reporting, genetics research, data optimization, and drafting repetitive texts such as discharge summaries. Nevertheless, these tools should augment, not supplant, human expertise. Despite promising applications, ChatGPT confronts limitations, including critical thinking tasks and generating false references, necessitating stringent cross-verification. Ensuing concerns, such as potential misuse, bias, blind trust, and privacy, underscore the need for transparency, accountability, and clear policies. Evaluations of AI-generated content and preservation of academic integrity are critical. With responsible use, AI can significantly improve healthcare, academia, and industry without compromising integrity and research quality. For effective and ethical AI deployment, collaboration amongst AI developers, researchers, educators, and policymakers is vital. The development of domain-specific tools, guidelines, regulations, and the facilitation of public dialogue must underpin these endeavors to responsibly harness AI's potential.

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 adole-scents, 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 appro-priately 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.

Time Use and Cognitive Achievement among Adolescents in China: Depression Symptoms as Mediators

Everyone's time is limited, and there is competition between different aspects of time use; this requires comprehensive consideration of the effects of different aspects of time use on cognitive achievement in adolescents. This study uses a dataset of 11,717 students from a nationally representative large-scale survey project conducted in 2013 to 2014 to clarify the relationship between time use (including working on homework, playing sports, surfing the Internet, watching TV, and sleeping) and cognitive achievement among Chinese adolescents, and explores the mediating role of depression symptoms in the relationship between time use and cognitive achievement. The results of the correlation analysis show that the average daily time spent on homework, playing sports, and sleeping is significantly positively correlated with cognitive achievement (p < 0.01), while time spent surfing the Internet and watching TV are significantly negatively correlated with cognitive achievement (p < 0.01). The results of the mediating effect model show that depression symptoms play a mediating role in the relationship between time use and cognitive achievement among Chinese adolescents. Specifically, time spent playing sports (indirect effect = 0.008, p < 0.001) and sleeping (indirect effect = 0.015, p < 0.001) have a positive effect on cognitive achievement when using depression symptoms as mediators; time spent on homework (indirect effect = -0.004, p < 0.001), surfing the Internet (indirect effect = -0.002, p = 0.046), and watching TV (indirect effect = -0.005, p < 0.001) have a negative effect on cognitive achievement when using depression symptoms as mediators. This study contributes to the understanding of the relationship between time use and cognitive achievement among Chinese adolescents.

The Chatbots Are Invading Us: A Map Point on the Evolution, Applications, Opportunities, and Emerging Problems in the Health Domain

The inclusion of chatbots is potentially disruptive in society, introducing opportunities, but also important implications that need to be addressed on different domains. The aim of this study is to examine chatbots in-depth, by mapping out their technological evolution, current usage, and potential applications, opportunities, and emerging problems within the health domain. The study examined three points of view. The first point of view traces the technological evolution of chatbots. The second point of view reports the fields of application of the chatbots, giving space to the expectations of use and the expected benefits from a cross-domain point of view, also affecting the health domain. The third and main point of view is that of the analysis of the state of use of chatbots in the health domain based on the scientific literature represented by systematic reviews. The overview identified the topics of greatest interest with the opportunities. The analysis revealed the need for initiatives that simultaneously evaluate multiple domains all together in a synergistic way. Concerted efforts to achieve this are recommended. It is also believed to monitor both the process of osmosis between other sectors and the health domain, as well as the chatbots that can create psychological and behavioural problems with an impact on the health domain.

Trajectories of college students' general self-efficacy, the related predictors, and depression: A piecewise growth mixture modeling approach

General self-efficacy plays a critical role in the development of college students, and mastering the development of students' general self-efficacy is helpful to explain students' behavior and psychological performance. Based on the data from the same cohort of college students for four consecutive years, this study used the piecewise growth mixture model to identify the developmental trajectories of general self-efficacy, built a multinomial logistic regression model to analyze the related predictors on different trajectories, and further compared the differences in depression symptoms in general self-efficacy trajectories. Three trajectories of college students' general self-efficacy were identified: stable-rising (8.7%), stable-decreasing (2.4%), and moderate and stable (88.9%). With the moderate and stable class as the reference, gender and extraversion are the predictors of students in the stable-increasing class; gender, extraversion, mother's education level, and university tier significantly predict students who fall into the stable-decreasing class. With the stable-increasing class as the reference, gender also has a significant predictive effect on students who belong to the stable-decreasing class. However, age, ethnicity, siblings, hometown location, father's education level, BMI, sleep, and major were not related predictors. Furthermore, mean differences in depression between latent classes of general self-efficacy trajectories were significant, and the depression scores of the stable-decreasing class were beyond the normal range in the third and fourth years. To promote college students' mental health, we suggest that colleges provide more specific psychological interventions to students based on the classification.

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.

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.

Do college entrance examination admission characteristics influence students' college satisfaction? Evidence from China

Students' college satisfaction is an important part of measuring the quality of college teaching. The admission of college entrance exam is the first step for college students to enter colleges and corresponding majors. Whether they affect students' college satisfaction after enrollment is related to the formulation and adjustment of college admission strategies and training methods. This paper is based on data from students in colleges in Beijing enrolled in the fall of 2006 and 2008 and adopts propensity score matching to analyze the influence of the admitted characteristics of college entrance exams, such as whether they were accepted by their first choice. We also further explored the heterogeneity. The empirical results show that whether the student was admitted to the first-choice college has a significant positive impact on overall satisfaction and academic and nonacademic satisfaction, while whether the student was admitted to the first-choice major has no significant impact on nonacademic satisfaction. In addition, making an independent major choice has a positive effect on the improvement of overall satisfaction and academic satisfaction, and the impact on overall satisfaction is even greater than that of being admitted to the first-choice major. The impact of the admission characteristics of college entrance examinations on the satisfaction of students in liberal arts and science and students of different types of colleges and universities presents different characteristics.