Major differences in the relationship between electronic health literacy, social capital and negative mental health states among the university students in China
Abstract
Background: The aim of this study was to examine the relationship between electronic health literacy (eHealth literacy), social capital and negative mental health statesamong Chinese university students, and further clarify its major disparities.
Methods: The data was gathered from Chinese university students via Wenjuan.com using the snowball sampling method. Data from 1472 participants were analyzed, with 665 (45.18%) medical students (MS) and 807 (54.82%) non-medical students (NMS). Depression Anxiety Stress Scale (DASS-21) was utilized to assess negative mental health states, eHealth Literacy Scale (eHEALS) to measure eHealth literacy, and Chinese Shortened Social Capital Scale (CSSCS) to evaluate social capital. To explore the relationships among eHealth literacy, social capital and negative mental health states, SPSS was used for descriptive analysis, chi-square tests and t-tests, and AMOS was used for structural equation modeling (SEM).
Results: Total scores of negative mental health states was 30.87 ± 26.72 (25.26 ± 24.86 for MS, 35.49 ± 27.33 for NMS). eHealth literacy was significantly positively associated with negative mental health states in MS but not significant among NMS. Social capital was negatively associated with negative mental health states among MS and NMS. eHealth literacy showed a significant positive association with social capital among MS and NMS.
Conclusion: NMS reported higher negative mental health states than MS. Higher eHealth literacy was significantly correlated with higher negative mental health states in MS but not significant in NMS. Higher social capital was linked to lower negative mental health states among the MS and NMS. eHealth literacy in both MS and NMS showed a significant positive correlation with social capital.
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BibTeX
@article{sun2026major,
title = {{Major differences in the relationship between electronic health literacy, social capital and negative mental health states among the university students in China}},
author = {Zhengna Sun and Rui Chen and Mao Cheng and Kaiyuan Feng and Qinling Li and Ziwei Qin and Shuyi Yan and Yunwei Huang and Jing Wang and Fanlei Kong},
journal = {BMC Public Health},
year = {2026},
month = oct,
doi = {10.1186/s12889-026-29817-5},
url = {https://link.springer.com/10.1186/s12889-026-29817-5},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Major differences in the relationship between electronic health literacy, social capital and negative mental health states among the university students in China
AU - Zhengna Sun
AU - Rui Chen
AU - Mao Cheng
AU - Kaiyuan Feng
AU - Qinling Li
AU - Ziwei Qin
AU - Shuyi Yan
AU - Yunwei Huang
AU - Jing Wang
AU - Fanlei Kong
PY - 2026
DA - 2026/10/13
JO - BMC Public Health
DO - 10.1186/s12889-026-29817-5
UR - https://link.springer.com/10.1186/s12889-026-29817-5
AB - Background: The aim of this study was to examine the relationship between electronic health literacy (eHealth literacy), social capital and negative mental health statesamong Chinese university students, and further clarify its major disparities. Methods: The data was gathered from Chinese university students via Wenjuan.com using the snowball sampling method. Data from 1472 participants were analyzed, with 665 (45.18%) medical students (MS) and 807 (54.82%) non-medical students (NMS). Depression Anxiety Stress Scale (DASS-21) was utilized to assess negative mental health states, eHealth Literacy Scale (eHEALS) to measure eHealth literacy, and Chinese Shortened Social Capital Scale (CSSCS) to evaluate social capital. To explore the relationships among eHealth literacy, social capital and negative mental health states, SPSS was used for descriptive analysis, chi-square tests and t-tests, and AMOS was used for structural equation modeling (SEM). Results: Total scores of negative mental health states was 30.87 ± 26.72 (25.26 ± 24.86 for MS, 35.49 ± 27.33 for NMS). eHealth literacy was significantly positively associated with negative mental health states in MS but not significant among NMS. Social capital was negatively associated with negative mental health states among MS and NMS. eHealth literacy showed a significant positive association with social capital among MS and NMS. Conclusion: NMS reported higher negative mental health states than MS. Higher eHealth literacy was significantly correlated with higher negative mental health states in MS but not significant in NMS. Higher social capital was linked to lower negative mental health states among the MS and NMS. eHealth literacy in both MS and NMS showed a significant positive correlation with social capital.
SN - 1471-2458
ER -