Association between social capital, mental health, and digital health literacy among the university students in China: a multigroup analysis based on major difference.

BACKGROUND: This study aimed to clarify medical-nonmedical difference on the relationship between social capital, mental health and digital health literacy of university students in China, and furtherly provide evidence-based suggestions on the improvement of the digital health literacy for the university students. METHODS: The snowball sampling method was used to collect data from the university students (including medical students and nonmedical students) through online questionnaires, and finally 1472 university students were included for the data analysis, of whom, 665 (45.18%) were medical students, 807 (54.82%) were nonmedical students; 462 (31.39%) were male, 1010 (68.61%) were female. Mean value of the age was 21.34 ± 2.33 for medical students vs. 20.96 ± 2.16 for nonmedical students. Descriptive analysis, chi-square test analysis, one-way Analysis of Variance (conducted by SPSS) and structural equation modeling (conducted by AMOS) were employed to explore the difference on the relationship between social capital, mental health and digital health literacy between the medical students and nonmedical students. RESULTS: The mean value of the digital health literacy was 36.27 (37.33 for medical students vs. 35.39 for nonmedical students). The SEM analysis showed that there was a statistically positive correlation between social capital and digital health literacy (stronger among the nonmedical students (0.317) than medical students (0.184)). Mental health had a statistically positive impact on the digital health literacy among medical students (0.242), but statistically significant correlation was not observed in nonmedical students (0.017). Social capital was negatively correlated with the mental health for both medical students and NMS (stronger among the nonmedical students (0.366) than medical students (0.255)). And the fitness indices of SEM were same between medical students and nonmedical students (GFI = 0.911, AGFI = 0.859, CFI = 0.922, RMSEA = 0.074). CONCLUSION: The digital health literacy of the university student was relatively high. Both social capital and mental health could exert a positive effect on digital health literacy, while social capital was found to be positively associated with mental health. Statistical difference was found between medical students and nonmedical students on the above correlations. Implications were given on the improvement of the digital health literacy among university students in China.

The Migrant-Local Difference in the Relationship Between Social Support, Sleep Disturbance, and Loneliness Among Older Adults in China: Cross-Sectional Study.

BACKGROUND: Driven by the accelerated aging of the population of China, the number of older adults has increased rapidly in the country. Meanwhile, following children, migrant older adults (MOA) have emerged as a vulnerable group in the process of fast urbanization. Existed studies have illustrated the association between social support and loneliness and the relationship between sleep disturbance and loneliness; however, the underlying mechanisms and the migrant-local difference in the association between social support, sleep disturbance, and loneliness have not been identified. OBJECTIVE: This study aimed to clarify the migrant-local difference in the relationship between social support, sleep disturbance, and loneliness in older adults in China. METHODS: Multistage cluster random sampling was used to select participants: 1205 older adults (n=613, 50.9%, MOA and n=592, 49.1%, local older adults [LOA]) were selected in Weifang City, China, in August 2021. Loneliness was assessed with the 6-item short-form University of California, Los Angeles Loneliness Scale, social support was evaluated with the Social Support Rating Scale, and sleep disturbance was measured with the Pittsburgh Sleep Quality Index. The chi-square test, t test, and structural equation modeling (SEM) were adopted to explore the migrant-local difference between social support, sleep disturbance, and loneliness among the MOA and LOA. RESULTS: The mean score of loneliness was 8.58 (SD 3.03) for the MOA and 8.00 (SD 2.79) for the LOA. SEM analysis showed that social support exerts a direct negative effect on both sleep disturbance (standardized coefficient=-0.24 in the MOA and -0.20 in the LOA) and loneliness (standardized coefficient=-0.44 in the MOA and -0.40 in the LOA), while sleep disturbance generates a direct positive effect on loneliness (standardized coefficient=0.13 in the MOA and 0.22 in the LOA). CONCLUSIONS: Both MOA and LOA have a low level of loneliness, but the MOA show higher loneliness than the LOA. There is a negative correlation between social support and loneliness as well as between social support and sleep disturbance among the MOA and LOA (MOA>LOA), while loneliness is positively associated with sleep disturbance in both populations (MOA

Erratum: Addendum: Validation of the digital health literacy assessment among the university students in China.

[This corrects the article DOI: 10.3389/fpubh.2023.1294183.].

A comparative study of bibliometric analysis on old adults' cognitive impairment based on Web of Science and CNKI via CiteSpace.

INTRODUCTION: The purpose of this study was to analyze the current status, the research hot spots and frontiers of cognitive impairment (CI) on old adults from 2012 to 2022 based on Web of Science (WoS) and China National Knowledge Infrastructure (CNKI) via CiteSpace, and provide new in-sights for researchers. METHODS: The articles regarding the old adults' CI in the WoS and CNKI were retrieved from 2012 to 2022. CiteSpaceV.6.1.R4 was used to generate network maps. RESULTS: Four thousand seven hundred thirteen publications and 304 publications from CNKI were retrieved. Overall, from 2012 to 2022, the trend of articles published in WoS and CNKI were increasing. Data from WoS showed that USA, University of California, Petersen RC were the most influential country, institution and author respectively; Folstein MF, Neurology and a diagnosis guideline of mild CI were the most cited author, journal and reference separately; while the keywords of CI could be summarized in 3 aspects: related disease and symptom, risk factors, manifestations. Data from CNKI illustrated that Peking Union Medical College, Dan Liu were the most influential institution and scholar respectively, while the keywords of CI could be summarized in 3 aspects: related disease and symptoms, risk factors, intervention. CONCLUSION: Articles published on old adults' CI were drawing an increasing amount of attention from 2012 to 2022 both in WoS and CNKI. Keywords of CI in WoS and CNKI both focused on risk factors, related disease and symptom, yet WoS contributed more to the mechanism and CNKI contributed more to the intervention.

The relationships of preventive behaviors and psychological resilience with depression, anxiety, and stress among university students during the COVID-19 pandemic: A two-wave longitudinal study in Shandong Province, China.

Introduction: Studies have shown that the psychological impact of the COVID-19 pandemic may lead to long-term health problems; therefore, more attention should be paid to the mental health of university students. This study aimed to explore the longitudinal effects of preventive behaviors and psychological resilience on the mental health of Chinese college students during COVID-19. Methods: We recruited 2,948 university students from five universities in Shandong Province. We used a generalized estimating equation (GEE) model to estimate the impact of preventive behaviors and psychological resilience on mental health. Results: In the follow-up survey, the prevalence of anxiety (44.8% at T1 vs 41.2% at T2) and stress (23.0% at T1 vs 19.6% at T2) decreased over time, whereas the prevalence of depression (35.2% at T1 vs 36.9% at T2) increased significantly (P < 0.001). Senior students were more likely to report depression (OR = 1.710, P < 0.001), anxiety (OR = 0.815, P = 0.019), and stress (OR = 1.385, P = 0.011). Among all majors, medical students were most likely to report depression (OR = 1.373, P = 0.021), anxiety (OR = 1.310, P = 0.040), and stress (OR = 1.775, P < 0.001). Students who wore a mask outside were less likely to report depression (OR = 0.761, P = 0.027) and anxiety (OR = 0.686, P = 0.002) compared to those who did not wear masks. Students who complied with the standard hand-washing technique were less likely to report depression (OR = 0.628, P < 0.001), anxiety (OR = 0.701, P < 0.001), and stress (OR = 0.638, P < 0.001). Students who maintained a distance of one meter in queues were less likely to report depression (OR = 0.668, P < 0.001), anxiety (OR = 0.634, P < 0.001), and stress (OR = 0.638, P < 0.001). Psychological resilience was a protective factor against depression (OR = 0.973, P < 0.001), anxiety (OR = 0.980, P < 0.001), and stress (OR = 0.976, P < 0.001). Discussion: The prevalence of depression among university students increased at follow-up, while the prevalence of anxiety and stress decreased. Senior students and medical students are vulnerable groups. University students should continue to follow relevant preventive behaviors to protect their mental health. Improving psychological resilience may help maintain and promote university students' mental health.

Validation of the digital health literacy assessment among the university students in China.

Purpose: With the development of the internet, digital health literacy (DHL) has become increasingly important for managing health. Consequently, various digital health literacy scales have been created for different groups. The purpose of this study was to verify the reliability and validity of the simplified Chinese version of the Digital Health Literacy Assessment (DHLA) scale among university students in China. Method: Snowball sampling was used to recruit the participants via an online platform (Wenjuan.com), and finally 304 university students were included in the survey. Demographic information and the status of DHL were collected through the online questionnaire. Cronbach's alpha and split-half reliability were used to test the internal consistency of the scale, while the structural validity was verified by exploratory factor analysis and confirmatory factor analysis. Additionally, the convergence of the scale was tested by composite reliability (CR) and average variance extracted (AVE). Result: Two dimensions were generated from 10 entries in the scale, named Self-rated Digital Health Literacy and Trust Degree of Online Health Information, respectively. The Cronbach's alpha and split-half reliability of the total scale were 0.912 and 0.828, while the Cronbach's alpha of the two dimensions were 0.913 and 0.830, respectively. The structural validity-related indexes of the scale met the standards (RMSEA = 0.079, GFI = 0.943, AGFI = 0.902, CFI = 0.971). In each dimension, the CR and AVE also reached critical values (CR > 0.7 and AVE > 0.5). Conclusion: The scale had high reliability and validity, indicating the simplified Chinese DHLA scale could be used to evaluate the DHL of university students in China.