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

• Published in: BMC public health Vol. 24; no. 1; pp. 2193 - 12
• Main Authors: Zhao, Jiajia, Nie, Limei, Pan, Lutong, Pang, Mingli, Wang, Jieru, Zhou, Yue, Chen, Rui, Liu, Hui, Xu, Xixing, Zhou, Chengchao, Li, Shixue, Kong, Fanlei
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 13-08-2024; BioMed Central; BMC
• Subjects: Adolescent; Adult; Analysis; Anxiety; Chi-square test; China; College students; Colleges & universities; Correlation; Data analysis; Data collection; Demographics; Digital health literacy; Evaluation; Family income; Female; Females; Health aspects; Health education; Health literacy; Health Literacy - statistics & numerical data; Humans; Impact analysis; Literacy; Male; Mean; Mental depression; Mental disorders; Mental Health; Multilevel Analysis; Online health care information services; Participation; Psychological aspects; Questionnaires; Social aspects; Social Capital; Social capital (Sociology); Social support; Statistical analysis; Stress; Students; Students - psychology; Students - statistics & numerical data; Students, Medical - psychology; Students, Medical - statistics & numerical data; Surveys and Questionnaires; Telemedicine; Universities; University students; Validity; Variance analysis; Young Adult; China; Digital health literacy; University students; Social capital; Mental health
• ISSN: 1471-2458; 1471-2458
• DOI: 10.1186/s12889-024-19672-7

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.
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.
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).
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.