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

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.

Cultural moderation in sports impact: exploring sports-induced effects on educational progress, cognitive focus, and social development in Chinese higher education

BACKGROUND

This research examines the nuanced challenges confronting Chinese university students within the dynamic milieu of Chinese education. The study comprehensively investigates factors encompassing educational progress, social development, cognitive focus, and Psychological Well-being (PWB), specifically emphasizing the role of sports participation.

METHODS

To scrutinize the moderation-mediation nexus between cultural context and social development, a distribution of 500 questionnaires was administered to Chinese university students, yielding 413 responses, corresponding to an 82.6% response rate. Methodologically, this study employed moderation and mediation analyses, incorporating statistical techniques such as a principal component matrix, factor analysis, and hierarchical regression.

FINDINGS

Prominent findings underscore the significant impact of age on educational progress, shaping the trajectory of academic advancement. Cumulative Grade Point Average (CGPA) emerges as a promising metric, establishing a link between academic performance and educational progress. Active involvement in sports and physical activities (PSPA) positively affects academic performance and study habits. Participation in sports teams and clubs (ISTC) enriches social development by nurturing interpersonal relationships, teamwork, and leadership skills. Sports activities (ESA) correlate with enhanced cognitive focus and improved psychological well-being. Significantly, the findings unveil a nuanced association between Perceived Social Development Through Sports (PSDTS) and educational progress.

CONCLUSIONS

Cultural Context (CC) moderates PSDTS, Sport-induced Cognitive Focus (SICF), and PWB, influencing educational progress. This study emphasizes the need for enhanced support systems-academic guidance, awareness, sports programs, and cultural competence training-to advance student well-being and academic achievement in China, fostering an empowering educational environment for societal progress.

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.

The relationship of smartphone addiction with depression, anxiety, and stress among medical students

Introduction

An increasing amount of research has shown a link between psychopathological behaviors such as smartphone addiction, depression, anxiety, and stress. The aim of this study was to assess the association of smartphone addiction with depression, anxiety, and stress.

Methods

A cross-sectional study was conducted between 26th January and 3rd March 2021. The sample was chosen using a convenient sampling technique and Raosoft tool. The survey assessed smartphone addiction using abbreviated versions of the Addiction Scale Short Version, a self-administered questionnaire that has been validated in the English and Arabic languages. Also, Depression and Anxiety Stress Scale was used to measure the level of depression, anxiety, and stress among the university students.

Results

A total of 367 university students from the Medical and Health Sciences College participated. Our findings showed that smartphone addiction exhibited positive correlations with depression (r = 0.375, p < 0.01), anxiety (r = 0.253, p < 0.01), and stress (r = 0.328, p < 0.05). In addition, there was a strong positive correlation between depression and both anxiety and stress (r = 0.731, p < 0.01) (r = 0.778, p < 0.01), respectively. Finally, stress and anxiety showed a positive correlation (r = 0.708, p < 0.01).

Conclusion

When combined, our data offer strong support for a bidirectional hybrid theory that takes into account the link between smartphone addiction and depression, anxiety, and stress. The current study's findings might assist national health authorities in strengthening their efforts to prevent depression, anxiety, and stress associated with the use of modern technology.

Statistical analysis of mental influencing factors for anxiety and depression of rural and urban freshmen

The freshmen stage is a high incidence period for psychological issues. With the increasing gap between urban and rural areas in China, the mental problems of rural freshmen are more prominent in recent years due to the huge contrast of campus life with their growth environment and other reasons. The concern for the mental well-being of both rural and urban freshman students prompted our comprehensive five-year study (2018-2022) on psychological issues in a group of 12,564 first-year students from dozens of public universities in Shandong province. The investigation employed PPS (probability proportional to size) sampling and was conducted near the the end of the first semester. Using the data gathered, we analyzed and compared the indicators of psychological problems in rural and urban freshmen by Duncan's Multiple Range Test. We also conducted a canonical correlation analysis and pathway analysis to examine the psychological factors that contribute to anxiety and depression in both rural and urban freshmen. According to the findings, rural freshmen exhibit significantly higher levels of anxiety and depression than their urban counterparts. Inferiority, obsession, and internet addiction were identified as the primary influencing factors of anxiety and depression in both rural and urban freshmen. Social phobia was found to be a significant influencing factor for anxiety in rural freshmen, while bigotry was identified as a specific influencing factor for urban freshmen. Furthermore, the results of the path analysis suggest that anxiety plays a crucial role as a mediating factor between the main influencing factors and depression. These results substantially extend former research in this area and have important implications for the development of effective intervention strategies to address anxiety and depression. According to these results, policymakers should assess and intervene of anxiety and depression as a whole, and provide mental health education according to main effect factors of freshmen from rural and urban areas. Detailed policy recommendations are in discussion and conclusion.

Surviving the shift: College student satisfaction with emergency online learning during COVID-19 pandemic

BACKGROUND

The coronavirus disease 2019 (COVID-19) epidemic disrupted education systems by forcing systems to shift to emergency online leaning. Online learning satisfaction affects academic achievement. Many factors affect online learning satisfaction. However there is little study focused on personal characteristics, mental status, and coping style when college students participated in emergency online courses.

AIM

To assess factors related to satisfaction with emergency online learning among college students in Hebei province during the COVID-19 pandemic.

METHODS

We conducted a cross-sectional survey of 1600 college students. The collected information included demographics, psychological aspects of emergent public health events, and coping style. Single factor, correlation, and multiple linear regression analyses were performed to identify factors that affected online learning satisfaction.

RESULTS

Descriptive findings indicated that 62.9% (994/1580) of students were satisfied with online learning. Factors that had significant positive effects on online learning satisfaction were online learning at scheduled times, strong exercise intensity, good health, regular schedule, focusing on the epidemic less than one hour a day, and maintaining emotional stability. Positive coping styles were protective factors of online learning satisfaction. Risk factors for poor satisfaction were depression, neurasthenia, and negative coping style.

CONCLUSION

College students with different personal characteristics, mental status, and coping style exhibited different degrees of online learning satisfaction. Our findings provide reference for educators, psychologists, and school administrators to conduct health education intervention of college students during emergency online learning.

Positive affect and resilience in tertiary education students

Mental illnesses are the greatest health problems faced by younger people. As a group, tertiary education students demonstrate higher levels of distress than their age matched peers who are not tertiary students, making them an at-risk group for the development of psychopathology. Therefore, this study investigates existing theories of resilience in order to determine how it may be promoted in tertiary education students. Data relating to affect, depression, anxiety, distress, and resilience were collected from 1072 tertiary education students during the COVID-19 pandemic. The results of this study found that positive affect was responsible for approximately 25% of the variance in depressive symptoms but less than 10% of the variance in symptoms of anxiety in tertiary students. The results further showed that positive affect was responsible for 21% of variance in overall distress and the 15% of variance in resilience. The findings of this study suggest that positive affect is more closely associated with symptoms of depression than with symptoms of anxiety in tertiary students. The results further suggest that positive affect may be a useful tool for relieving symptoms of depression and overall distress, and improving levels of resilience in this population.

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.

Depression Among University Students in Jordan After the COVID-19 Pandemic: A Cross-Sectional Study

Background

University students encounter stressors that make them more susceptible to depression than the general population. Depression negatively impacts mental and physical health. Our study assessed the prevalence of depression among university students in Jordan and its associated predictors after the COVID-19 pandemic.

Methods

We conducted this cross-sectional online survey study in the first quarter of 2022 by sending an online questionnaire to university students aged 18 years and older. This study assessed the symptoms of depression using the Patient Health Questionnaire-9 (PHQ-9). Binary logistic regression analysis was used to identify associated predictors of depression.

Results

A total of 535 university students participated in this study. The mean depression score for the study participants was 13.9 (SD: 7.1) out of 27, representing a moderate level of depression. Among the participants, 26.2% had moderate, 19.3% had moderately severe, and 25.8% had severe depression. Students who drink three or more cups of coffee per day, have had an evaluation of their psychological state by specialists before, and have been diagnosed with any mental illness were more likely to have a higher depression score compared to others (p<0.05). On the other hand, students who were aged 24 years and older and those who practiced regular exercise were less likely to have a higher depression score compared to others (p<0.05).

Conclusion

We found a high prevalence of depression among university students in Jordan. This result is vital for decision-makers to implement a plan to prevent and manage this mental health issue.

Brain optimization with additional study time: potential brain differences between high- and low-performance college students

This study investigates potential differences in brain function among high-, average-, and low-performance college students using electroencephalography (EEG). We hypothesize that the increased academic engagement of high-performance students will lead to discernible EEG variations due to the brain's structural plasticity. 61 third-year college students from identical majors were divided into high-performance (n = 20), average-performance (n = 21), and low-performance (n = 20) groups based on their academic achievements. We conducted three EEG experiments: resting state, Sternberg working memory task, and Raven progressive matrix task. Comprehensive analyses of the EEG data from the three experiments focused on power spectral density (PSD) and functional connectivity, with coherence (COH) employed as our primary metric for the latter. The results showed that in all experiments, there were no differences in working memory ability and IQ scores among the groups, and there were no significant differences in the power spectral densities of the delta, theta, alpha1, alpha2, beta, and gamma bands among the groups. Notably, on the Raven test, compared to their high-performing peers, low-performing students showed enhanced functional connectivity in the alpha 1 (8-9 Hz) band that connects the frontal and occipital lobes. We explored three potential explanations for this phenomenon: fatigue, anxiety, and greater cognitive effort required for problem-solving due to inefficient self-regulation and increased susceptibility to distraction. In essence, these insights not only deepen our understanding of the neural basis that anchors academic ability, but also hold promise in guiding interventions that address students' diverse academic needs.

Career Education Skills and Career Adaptability among College Students in China: The Mediating Role of Career Decision-Making Self-Efficacy

In the past, the shift in career patterns and the unprecedented disruptions caused by events such as COVID-19 have posed notable challenges for job seekers. This holds particularly true for college students who are preparing to enter the workforce. In this context, enhancing career adaptability plays a vital role in shaping their career development. The primary objective of this research was to investigate the relationship between career education skills and career adaptability among 273 undergraduate students in China. Additionally, the study aimed to explore the mediating effect of career decision-making self-efficacy in shaping this relationship. The findings of the correlation analysis indicate a significant positive correlation between career education skills and career adaptability. Moreover, the results of the mediation model revealed that career education skills significantly contribute to improving career adaptability along with the mediating effect of college students' self-efficacy in making career decisions. This study suggests that universities should prioritize the development and expansion of career education initiatives. They should not only help establish clear career goals for college students but also cultivate a positive and flexible career outlook to assist them in better adapting to various changes that may arise throughout their career journeys.

How does change in leisure-time physical activity influence the growth trajectory of depressive symptoms in college students?

Objectives: This longitudinal study was designed to examine the growth trajectory of depressive symptoms among early-stage college students and how the development of vigorous, moderate, and light leisure-time physical activity (LTPA) was related to the growth trajectory. Participants: Four hundred and eighty-eight first- and second-year undergraduate students completed measures of depressive symptoms and LTPA at the beginning, middle, and end of a semester. Methods: Latent growth mixture modeling (LGMM) was conducted. Results: On average, students reported mild levels of depressive symptoms with significant variability at the semester start, but the symptoms elevated over time. LGMM identified two trajectories: low/gradual (75.8%) and high/increasing (24.2%). For both groups, neither vigorous nor moderate LTPA development predicted the growth trajectory of depressive symptoms. However, the change of light LTPA was negatively and significantly associated with the growth trajectory. Even when controlling for covariances, increased light LTPA still had a unique effect on buffering depressive symptoms. Conclusion: There is great potential in targeting comprehensive LTPA strategies to improve college students' mental health and promote an active lifestyle.

Employers Feedback on Psychosocial Counselling Graduates' Performance in Selected Healthcare Facilities in Malawi

Purpose

Psychosocial counselling is vital for addressing mental health challenges in Malawi, a low-income country in sub-Saharan Africa. However, there is a shortage of qualified mental health professionals, including Psychosocial counsellors. The Saint John of God College of Health Sciences aims to produce competent graduates in psychosocial counselling, but there is a lack of information on the quality of graduates and their ability to meet employer expectations. This qualitative study aimed to explore employers' feedback on psychosocial counselling graduates' performance in selected healthcare facilities in Malawi.

Methods

This qualitative approach employed an explorative research design. Eighteen participants were selected purposefully from ten healthcare facilities across three regions of Malawi. They were interviewed independently using a semi-structured interview guide. The data were analysed thematically using content analysis approach.

Results

The study reveals the assigned responsibilities of psychosocial counselling graduates, including providing HIV/AIDS therapeutic services, individual and group counselling, crisis intervention, and coordinating referrals. Employers recognize the graduates' competence in communication skills, empathy, theoretical knowledge, and professionalism. However, some weaknesses were identified, such as difficulties in maintaining boundaries, limited knowledge of health-related terms, and a lack of proactivity. Suggestions for improvement include teaching professionalism, incorporating health-related terms in the curriculum, following up with graduates, continuing the practicum aspect, establishing partnerships, and expanding training in evidence-based practices.

Conclusion

The study explored employer feedback on psychosocial counselling graduates from Saint John of God College of Health Sciences in Malawi. The study to identified strengths, areas for improvement, and recommendations were made to improve the Psychosocial counselling academic programme. Implementing them can improve graduates quality and mental health outcomes in Malawi.

Prevalence and factors associated with depression and suicidal ideation among French students in 2016: A national study

Depression is one of the leading causes of morbidity worldwide and increases the risk of suicide. Students are known as a population at risk for depression. This study aimed to evaluate the prevalence of 12 months major depressive episode (MDE) and suicidal thoughts in French students and investigate associated factors. A questionnaire was sent by email to a representative sample of the French student population between April 28th and June 27th 2016. MDE was assessed using the Composite International Diagnostic Interview Short Form (CIDI-SF). The response rate was 18.7% (N= 18,875). Prevalence of 12 months MDE was 15.8%, and suicidal thoughts was 9%. Factors associated with MDE were being a woman, study field (law/eco, human/social sciences, and medical), having failed midterms exams or dropout, refusal or stop social scholarship, and subjective financial difficulties. Factors associated with suicidal thoughts were study field (human/social sciences), having failed midterms exams or dropout, and important subjective financial difficulties. The use of CIDI-SF allows comparison with the 2017 French national study, and showed more MDE in students than in the general population. This is the only national study on French students before COVID 19 pandemic.

Exploring the relationship between multiple dimensions of subjective socioeconomic status and self-reported physical and mental health: the mediating role of affect

Introduction

This study aimed to investigate the predictive effects of two types of subjective socioeconomic status on self-reported physical and mental health. Specifically, we examined the MacArthur Scale (MacArthur) which measures perceived socioeconomic rank in the society and a novel scale called ComSim, which assessed how participants compared themselves socioeconomically to others coming from a similar socioeconomic background. We also considered the influence of income, education, and personal relative deprivation (PRD) in these analyses. Additionally, we explored whether these effects were mediated through negative and positive affect.

Methods

The data were collected through a cross-sectional, two-wave survey of 294 women and 294 men, with a mean age 41.6 years. Participants were recruited via an online platform.

Results

The results from multivariate regression models revealed that socioeconomic status measured with both the MacArthur Scale and ComSim significantly predicted both self-reported health measures, whereas income and education did not predict any of these measures in the full multivariate models. PRD only predicted self-reported mental health. Mediation analyses showed that negative and positive affect mediated the relationships between socioeconomic status measured by ComSim and self-reported health measures.

Discussion

These findings are discussed in the context of the similarity hypothesis of social comparison theory. The results underscore the importance of considering multiple dimensions when examining socioeconomic health disparities.

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.

Meaning in life as a protective factor against depression

The main objective of this study was to analyze the mediating role that meaning in life has between emotion dysregulation and depressive symptomatology in Spanish university students. Five hundred and sixty-six Spanish university students participated in the study. All of them completed the Difficulties in Emotion Regulation Scale (DERS), the Patient Health Questionnaire (PHQ-9) and the Purpose in Life Test (PIL-10). A mediation model was performed to test the hypothesis that meaning in life mediates the effect of emotional dysregulation on depressive symptomatology in college students. The results show a positive, moderate, and statistically significant correlation between depression and emotional dysregulation. In addition, a negative, moderate, and statistically significant correlation was found between depression and meaning in life, and a negative, small, and statistically significant correlation between emotional dysregulation and meaning in life. Finally, the results of the mediation model evidence the role of meaning in life in different emotional dysregulation strategies and depressive symptomatology. These findings suggest the importance of incorporating the meaning in life variable in the development and implementation of prevention and treatment programs for psychological disorders.

Criteria for detection of possible risk factors for mental health problems in undergraduate university students

Introduction

Developing approaches for early detection of possible risk clusters for mental health problems among undergraduate university students is warranted to reduce the duration of untreated illness (DUI). However, little is known about indicators of need for care by others. Herein, we aimed to clarify the specific value of study engagement and lifestyle habit variables in predicting potentially high-risk cluster of mental health problems among undergraduate university students.

Methods

This cross-sectional study used a web-based demographic questionnaire [the Utrecht Work Engagement Scale for Students (UWES-S-J)] as study engagement scale. Moreover, information regarding life habits such as sleep duration and meal frequency, along with mental health problems such as depression and fatigue were also collected. Students with both mental health problems were classified as high risk. Characteristics of students in the two groups were compared. Univariate logistic regression was performed to identify predictors of membership. Receiver Operating Characteristic (ROC) curve was used to clarify the specific values that differentiated the groups in terms of significant predictors in univariate logistic analysis. Cut-off point was calculated using Youden index. Statistical significance was set at p < 0.05.

Results

A total of 1,644 students were assessed, and 30.1% were classified as high-risk for mental health problems. Significant differences were found between the two groups in terms of sex, age, study engagement, weekday sleep duration, and meal frequency. In the ROC curve, students who had lower study engagement with UWES-S-J score < 37.5 points (sensitivity, 81.5%; specificity, 38.0%), <6 h sleep duration on weekdays (sensitivity, 82.0%; specificity, 24.0%), and < 2.5 times of meals per day (sensitivity, 73.3%; specificity, 35.8%), were more likely to be classified into the high-risk group for mental health problems.

Conclusion

Academic staff should detect students who meet these criteria at the earliest and provide mental health support to reduce DUI among undergraduate university students.

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.

Association between sleep quality and psychological symptoms: A cross-sectional survey of Chinese university students performed during the COVID-19 pandemic

Background

Since the start of the coronavirus 2019 pandemic, people have faced many challenges, including in relation to sleep quality and psychological health. This study aims to analyze the association between sleep quality and psychological symptoms among university students in China, and to provide reference data to facilitate the development of interventions to improve the physical and mental health of university students.

Methods

A stratified cluster sampling method was used to investigate the sleep quality and psychological symptoms of 6,363 university students in China. The Chi-square test was used to analyze differences in sleep quality among groups. Logistic regression analysis was used to analyze the association between sleep quality and psychological symptoms.

Results

The proportions of Chinese university students with good, medium, and poor sleep quality were 25.73, 10.99, and 63.28%, respectively. The overall rate of psychological symptoms was 16.5%. Logistic regression analysis showed that, in general, university students with poor sleep quality had a higher risk of psychological symptoms than those with good sleep quality (OR = 1.53, 95%CI: 1.28, 1.84, p < 0.01). Compared with university students with good sleep quality, those with poor sleep quality were more likely to experience emotional symptoms (OR = 1.62, 95%CI: 1.36, 1.94), behavioral symptoms (OR = 1.55, 95% CI: 1.3, 1.84), and difficulties with social adaptation (OR = 1.84, 95% CI: 1.51, 2.25) (all p < 0.01).

Conclusion

There was an association between sleep quality and psychological symptoms among Chinese university students. University students with poor sleep quality have a higher risk of psychological symptoms. Measures should be taken to improve the sleep quality of university students and reduce the incidence of psychological symptoms. This study provides reference data for government and education departments that could inform public health policies.

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.

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.

A bidirectional association between smartphone addiction and depression among college students: A cross-lagged panel model

Background

Smartphone addiction (SA) is associated with adverse consequences, especially for freshmen. Evidence indicates that SA is associated with depression, and it is necessary to conduct a longitudinal study to explore the association further.

Methods

SA (measured by the Smartphone Addiction Scale-Short Version) and depression (measured by the Zung's Self-Rating Depression Scale) among 1,186 freshmen were surveyed at baseline and a respective 12-month follow-up for each participant. The application of a cross-lagged panel model approach (CLPM) revealed an association between SA and depression after adjusting for demographic variables.

Results

The CLPM results showed a significant path from baseline SA to follow-up depression (β = 0.08, P < 0.001) and a significant path from baseline depression to follow-up SA (β = 0.08, P < 0.001). Compared with the overall cross-lagged model, the cross-lagged coefficient of the path from baseline SA to follow-up depression increased in the female group (β = 0.10, P = 0.015), and the cross-lagged coefficient of the path from baseline depression to follow-up SA also increased significantly (β = 0.15, P < 0.001). In contrast, the cross-lagged model in the male group showed no predictive effect between SA and depression (P > 0.05).

Conclusions

The current study showed a significant bidirectional association between smartphone addiction and depression among freshmen, but only in the female population.

The link among academic stress, sleep disturbances, depressive symptoms, academic performance, and the moderating role of resourcefulness in health professions students during COVID-19 pandemic

Background

The rapid shift to virtual learning in response to the COVID-19 pandemic contributed to high academic stress among health profession students. High academic stress was associated with impaired psychosocial well-being and decreased academic performance.

Objectives

The purpose of this study was to assess the relationship between academic stress, anxiety, sleep disturbances, depressive symptoms, academic performance, and the moderating effect of resourcefulness among undergraduate health profession students.

Methods

This descriptive and cross-sectional study included undergraduate health profession students. The primary investigator distributed the study link to all students through the university's Central Messaging Centre, Twitter account, and WhatsApp. The study variables were measured using the Student Life Stress Inventory, the Generalized Anxiety Disorder-7 questionnaire, the Centre for Epidemiology Scale of Depression, the Pittsburgh Sleep Quality Index, and the Resourcefulness Skills Scale. Pearson R correlation and linear regression analysis were utilized for statistical analysis.

Results

Our sample included 94 undergraduate health profession students, 60 % of which were females with a mean age of 21, and the majority were nursing and medicine students. High academic stress, anxiety, sleep disturbances, depressive symptoms, and resourcefulness were reported among 50.6 %, 43 %, 79.6 %, 60.2 %, and 60 % of the participants, respectively. However, no effect of resourcefulness was found on any of the study variables. Instead, academic stress and sleep disturbances were the strongest predictors of depressive symptoms regardless of the level of resourcefulness.

Conclusion

Adequate academic support during virtual learning and tools to early detect subtle signs of high academic stress, anxiety, depression, and sleep disturbance should be routinely utilized by educational institutions. In addition, incorporating sleep hygiene and resourcefulness training in health professions education is highly indicated.

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.

The relationship between depression symptoms and academic performance among first-year undergraduate students at a South African university: a cross-sectional study

Background:

South African universities face a challenge of low throughput rates, with most students failing to complete their studies within the minimum regulatory time. Literature has begun to investigate the contribution of well-being, including mental health, with depression among students being one of the most common mental disorders explored. However, locally relevant research exploring associations between depression and academic performance has been limited. This research hypothesizes that the presence of depression symptoms, when controlling for key socio-demographic factors, has an adverse impact on student academic outcomes and contributes to the delay in the academic progression of students.

Methods:

The study used a cross-sectional design. Data were collected in 2019 from first-time, first-year undergraduate students using a self-administered online questionnaire. In total, 1,642 students completed the survey. The Patient Health Questionnaire-9 (PHQ-9) was used to screen for depression symptoms. Data on students’ academic performance were obtained from institutional records. Bivariate and multivariate regression analyses were used to examine associations between depression symptoms and academic performance.

Results:

Most participants (76%) successfully progressed (meeting the requirements to proceed to the second year of university study). Of the participants, 10% displayed symptoms of severe depression. The likelihood of progression delay (not meeting the academic requirements to proceed to the second year of university study) increased with the severity of depression symptoms. Moderate depression symptoms nearly doubled the adjusted odds of progression delay (aOR = 1.98, 95% CI: 1.30-3.00, p = 0.001). The likelihood of progression delay was nearly tripled by moderate severe depression symptoms (aOR = 2.70, 95% CI:1.70–4.36, p < 0.001) and severe depression symptoms (aOR = 2.59, 95% CI:1.54–4.36, p < 0.001). The model controlled for field of study, financial aid support as well as sex and race.

Conclusion:

Higher levels of depression symptoms among first-year university students are associated with a greater likelihood of progression delay and may contribute to the low throughput rates currently seen in South African universities. It is important for students, universities and government departments to recognize student mental wellness needs and how these can be met.

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

Artificial intelligence-based technologies are gradually being applied to psych-iatric 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 intelligence-assisted psychosis risk screening in adolescents as follows: nonperceptual real-time 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.