Understanding University Students' Experiences, Perceptions, and Attitudes Toward Peers Displaying Mental Health-Related Problems on Social Networking Sites: Online Survey and Interview Study

Psychometric properties of the chinese version of the value-based stigma inventory (VASI): a translation and validation study

OBJECTIVE

This study aimed to develop a culturally adapted Chinese version of the Value-based Stigma Inventory (VASI) and to evaluate its psychometric properties, including reliability and validity, among the general Chinese population.

METHODS

This study is a cross-sectional study. Convenience sampling was used to recruit 708 general citizens from Shenyang City, Liaoning Province, China. The VASI's internal consistency, split-half reliability, and test-retest reliability were tested to assess the translated scale's reliability. Several validity tests were performed, including expert consultation, exploratory factor analysis, and confirmatory factor analysis. Data were analyzed using SPSS 25.0 (IBM Corp., Armonk, NY, United States) and AMOS 23.0 (IBM Corp., Armonk, NY, United States).

RESULTS

The Chinese version of the VASI showed good reliability, with a Cronbach's α value of 0.808, and the dimensions ranged from 0.812 to 0.850. Test-retest reliability showed good temporal stability with a value of 0.855, and the split-half reliability value was 0.845, indicating a high degree of consistency. The scale also demonstrated good content validity with a content validity index of 0.952. After conducting exploratory factor analysis, a five-factor structure was identified, including factors of self-realization, personal enrichment, reputation, meritocratic values, and security. In the confirmatory factor analysis, all recommended fit indicators were found to be within the acceptable range, including χ2/DF = 1.338, GFI = 0.960, AGFI = 0.940, RMSEA = 0.031, TLI = 0.985, CFI = 0.989, IFI = 0.989, PGFI = 0.640, and PNFI = 0.729.

CONCLUSION

The Chinese version of the VASI is valid and reliable among the Chinese general public. The five-factor structured scale effectively assessed public stigma against mental illness, including the value orientations associated with personal stigma. Given the harsh and widespread public stigma against mental illness, the findings from the questionnaire may inform the development of future public health education programs. Public health education is needed to reduce the stigma of mental illness, increase public awareness of mental health issues, and mitigate the continued stigmatization of mental illness.

Chinese university students' help-seeking behaviors when faced with mental health challenges

BACKGROUND

Mental illnesses and mental health challenges have become increasingly pervasive among Chinese university students. However, the utilization rate of mental health services is low among students.

AIMS

We aimed to explore Chinese university students' help-seeking behaviors to understand how they deal with mental health challenges and use the results to inform the development of effective mental health promotion initiatives.

METHODS

In this study, we conducted 13 focus group interviews with students in six universities in Jinan, China, including 91 (62%) female students and 56 (38%) male students. We drew on the Theory of Planned Behaviors to guide our thematic analysis to gain a contextual understanding of participants' accounts on help-seeking.

RESULTS

Our results have depicted the help-seeking patterns of Chinese university students and show that there are four major behaviors which are self-reliance, seeking support from peers and families, seeking professional support, and accessing virtual mental health care.

CONCLUSION

Results from this study can be used to inform the development of mental health literacy programming for students in universities that share similar contexts, and the study has also opened up a new space for using qualitative approaches to study mental health needs and access to care in diverse populations.

Understanding University Students' Perspectives towards Digital Tools for Mental Health Support: A Cross-country Study

Background

Organisational and individual barriers often prevent university students from seeking mental health support. Digital technologies are recognised as effective in managing psychological distress and as a source of health-related information, thus representing useful options to address mental health needs in terms of accessibility and cost-effectiveness. However, university students' experiences and perspectives towards such interventions are little known.

Objectives

We thus aimed to expand the existing base of scientific knowledge, focusing on this special population.

Methods

Data were from the qualitative component of "the CAMPUS study", longitudinally assessing the mental health of students at the University of Milano-Bicocca (Italy) and the University of Surrey (UK). We conducted in-depth interviews and thematically analysed the transcripts using the framework approach.

Results

An explanatory model was derived from five themes identified across 33 interviews (15 for Italy, 18 for the UK). Students perceived that social media, apps, and podcasts could deliver relevant mental health content, ranging from primary to tertiary prevention. Wide availability and anonymity were perceived as advantages that make tools suitable for preventive interventions, to reduce mental health stigma, and as an extension of standard treatment. These goals can be hindered by disadvantages, namely lower efficacy compared to face-to-face contact, lack of personalisation, and problematic engagement. Individual and cultural specificities might influence awareness and perspectives on the use of digital technologies for mental health support.

Conclusion

Although considering some specific features, digital tools could be a useful instrument to support the mental health needs of students. Since personal contact remains crucial, digital tools should be integrated with face-to-face interventions through a multi-modal approach.

Exposure to blue space surroundings and depressive symptoms in young Chinese adults: The mediating role of sleep

OBJECTIVE

Existing evidence suggests that the natural environment can influence mental health. However, limited research has focused on the relationship between blue space and depressive symptoms in young adults. To investigate the association between blue space surroundings and depressive symptoms in young adults in China and explore the underlying mechanisms.

METHODS

The study was conducted between September and November 2019, including 2,743 young adults from China. We assessed the exposure to blue space around participants' living environments during June, July, and August 2019 using the Modified Normalized Difference Water Index (MNDWI). Blue indexes were calculated for 300 m, 1000 m, and 3000 m circular buffer zones near residential environments. Logistic regression models were employed to explore the associations between blue space exposures (quartiles) and depressive symptoms, exploring potential mechanisms through structural equation modeling (SEM), while accounting for potential confounders. Stratification analysis was used to identify sensitive populations.

RESULTS

Depressive symptoms were found in 148 (5.3%) of the 2,743 young adults in the study. We observed a negative correlation between depressive symptoms and average MNDWIs at participants' addresses (OR: 0.84; 95%CI: 0.72-0.98), within 300m (OR: 0.81; 95%CI: 0.70-0.95), 1000m (OR: 0.80; 95%CI: 0.69-0.93), and 3000m (OR:0.77; 95%CI: 0.66-0.89) buffer zones. Within the 1000m buffer zone, sleep was found to mediate 21% of the relationship between the presence of blue space and depressive symptoms. The stratified analysis revealed a stronger association between low MNDWI levels within the 1000m buffer zone and depressive symptoms in females (P < 0.05). Additionally, average MNDWI levels within the 3000m buffer zone were associated with depressive symptoms in both females and males.

CONCLUSIONS

Blue space could improve depressive symptoms, particularly in females, with sleep playing a mediating role. Incorporating blue spaces into environmental planning is important for improving mental health.

Mental Health Study from the Perspective of Behavior Preference under the Environment of Internet Media: Based on China's Data Analysis

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

Quantifying Changes in the Language Used Around Mental Health on Twitter Over 10 Years: Observational Study

BACKGROUND

Mental health challenges are thought to affect approximately 10% of the global population each year, with many of those affected going untreated because of the stigma and limited access to services. As social media lowers the barrier for joining difficult conversations and finding supportive groups, Twitter is an open source of language data describing the changing experience of a stigmatized group.

OBJECTIVE

By measuring changes in the conversation around mental health on Twitter, we aim to quantify the hypothesized increase in discussions and awareness of the topic as well as the corresponding reduction in stigma around mental health.

METHODS

We explored trends in words and phrases related to mental health through a collection of 1-, 2-, and 3-grams parsed from a data stream of approximately 10% of all English tweets from 2010 to 2021. We examined temporal dynamics of mental health language and measured levels of positivity of the messages. Finally, we used the ratio of original tweets to retweets to quantify the fraction of appearances of mental health language that was due to social amplification.

RESULTS

We found that the popularity of the phrase mental health increased by nearly two orders of magnitude between 2012 and 2018. We observed that mentions of mental health spiked annually and reliably because of mental health awareness campaigns as well as unpredictably in response to mass shootings, celebrities dying by suicide, and popular fictional television stories portraying suicide. We found that the level of positivity of messages containing mental health, while stable through the growth period, has declined recently. Finally, we observed that since 2015, mentions of mental health have become increasingly due to retweets, suggesting that the stigma associated with the discussion of mental health on Twitter has diminished with time.

CONCLUSIONS

These results provide useful texture regarding the growing conversation around mental health on Twitter and suggest that more awareness and acceptance has been brought to the topic compared with past years.

Exploration and Strategy Analysis of Mental Health Education for Students in Sports Majors in the Era of Artificial Intelligence

This study aims to explore new educational strategies suitable for the mental health education of college students. Big data and artificial intelligence (AI) are combined to evaluate the mental health education of college students in sports majors. First, the research status on the mental health education of college students is introduced. The internet of things (IoT) on mental health education, a structure based on big data and convolutional neural network (CNN), is constructed. Next, the survey design and questionnaire survey are carried out. Finally, the questionnaire data are analyzed and compared with the mental health status under traditional education. The results show that the CNN model has good accuracy and ability to distinguish symptoms, so it can be applied to the existing psychological work in colleges. In the symptom comparison survey, under the traditional education and big data network, the number of college students with mild mental health problems is found to be 158 (84.9%) and 170 (91.4%), respectively. It indicates that the number of college students with moderate mental health problems decreases significantly. In the comparative investigation of the severity of mental problems, the number of students with normal mental health, subhealth, and serious mental health problems under the background of traditional mental health education is 125 (67.2%), 56 (30.1%), and 5 (2.7%), respectively. The mental health status of college students under the influence of big data networks on mental health education is better than that of traditional mental health education. There are 140 students with normal mental health, a year-on-year increase of 16.7%. In the comparative survey of specific mental disorders, students with obsessive-compulsive symptoms under traditional mental health education account for 22.0% of the total sample, having the largest proportion. In the subhealth psychological group under the big data network on mental health education, the number of hostile students decreases by 7, which is the psychological factor with the most obvious improvement. Hence, the proposed path of mental health education is feasible.