Frontiers in public health · 2026
Digital health literacy, social support, and online health information-seeking behavior profiles among nursing students: a latent profile and structural equation modeling analysis.
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Yang Lijie, Liang Liujiang, Hu Huihui, Pan Kaili, Ding Qingqing, Meng Xiaohong
Аннотация
BACKGROUND: Online health information-seeking behavior (OHISB) is important for nursing students, yet its heterogeneity and associations with digital health literacy and social support remain unclear.
OBJECTIVE: To identify OHISB profiles among nursing students and examine the hypothesized indirect association between digital health literacy and profile membership through perceived social support.
METHODS: This cross-sectional study included 772 nursing students. Data were collected using a sociodemographic questionnaire, the eHealth Literacy Scale, the Online Health Information-Seeking Behavior Scale, and the Perceived Social Support Scale. Latent profile analysis identified OHISB profiles. Multinomial logistic regression examined predictors of profile membership, with three-step analyses accounting for classification uncertainty. Structural equation modeling assessed indirect associations through perceived social support using bootstrap confidence intervals.
RESULTS: Among the nursing students, latent profile analysis identified three distinct online health information-seeking behavior profiles: high (n = 286, 37%), moderate (n = 328, 42.5%), and low (n = 158, 20.5%) OHISB profiles. Place of origin, family structure, household income, education level, grade, and social support were associated with profile membership (p < 0.05). In adjusted three-step analyses, higher perceived social support was associated with lower odds of high- (OR = 0.956) and moderate-OHISB (OR = 0.959) membership relative to low-OHISB membership. Digital health literacy was positively associated with perceived social support (B = 0.293, p < 0.001). Perceived social support was negatively associated with high- (B = -0.311, OR = 0.733, p < 0.001) and moderate-OHISB membership (B = -0.215, OR = 0.807, p < 0.001) relative to low-OHISB membership. Direct effects of digital health literacy were not significant (p = 0.637 and 0.511). Significant indirect effects were observed for high versus low (a × b = -0.091, 95% bootstrap CI: -0.136 to -0.060) and moderate versus low (a × b = -0.063, 95% bootstrap CI: -0.102 to -0.036) contrasts.
CONCLUSION: Online health information-seeking behavior among nursing students was heterogeneous and characterized by three profiles. Perceived social support showed significant indirect associations between digital health literacy and OHISB profile membership. These findings highlight the potential importance of social support, while the cross-sectional design precludes causal inference.
OBJECTIVE: To identify OHISB profiles among nursing students and examine the hypothesized indirect association between digital health literacy and profile membership through perceived social support.
METHODS: This cross-sectional study included 772 nursing students. Data were collected using a sociodemographic questionnaire, the eHealth Literacy Scale, the Online Health Information-Seeking Behavior Scale, and the Perceived Social Support Scale. Latent profile analysis identified OHISB profiles. Multinomial logistic regression examined predictors of profile membership, with three-step analyses accounting for classification uncertainty. Structural equation modeling assessed indirect associations through perceived social support using bootstrap confidence intervals.
RESULTS: Among the nursing students, latent profile analysis identified three distinct online health information-seeking behavior profiles: high (n = 286, 37%), moderate (n = 328, 42.5%), and low (n = 158, 20.5%) OHISB profiles. Place of origin, family structure, household income, education level, grade, and social support were associated with profile membership (p < 0.05). In adjusted three-step analyses, higher perceived social support was associated with lower odds of high- (OR = 0.956) and moderate-OHISB (OR = 0.959) membership relative to low-OHISB membership. Digital health literacy was positively associated with perceived social support (B = 0.293, p < 0.001). Perceived social support was negatively associated with high- (B = -0.311, OR = 0.733, p < 0.001) and moderate-OHISB membership (B = -0.215, OR = 0.807, p < 0.001) relative to low-OHISB membership. Direct effects of digital health literacy were not significant (p = 0.637 and 0.511). Significant indirect effects were observed for high versus low (a × b = -0.091, 95% bootstrap CI: -0.136 to -0.060) and moderate versus low (a × b = -0.063, 95% bootstrap CI: -0.102 to -0.036) contrasts.
CONCLUSION: Online health information-seeking behavior among nursing students was heterogeneous and characterized by three profiles. Perceived social support showed significant indirect associations between digital health literacy and OHISB profile membership. These findings highlight the potential importance of social support, while the cross-sectional design precludes causal inference.