Determinants of preventive Chinese herbal medicine use: an extended health belief model analysis and its nursing...

The COVID-19 pandemic catalyzed global interest in traditional health practices. In Taiwan, Chinese herbal medicine (CHM) emerged as a key component of preventive care; yet, its psychological adoption mechanisms remain insufficiently understood. This study evaluated an extended Health Belief Model (HBM) to elucidate these cognitive associations.

To examine factors associated with preventive CHM adoption among Taiwanese adults during the COVID-19 Omicron wave and evaluate the mediating role of cues to action within the HBM framework.

A cross-sectional survey was conducted (January-December 2022) with 499 Taiwanese adults. Multivariable linear regression and Hayes' PROCESS Macro (Model 4) path mediation analysis were executed, adjusting for five socio-demographic covariates (age, gender, education, healthcare professional status, and Hualien residence).

Preventive CHM behavior correlated significantly with cues to action ( $r=0.588,p<0.001$ ) and perceived benefits ( $r=0.519,p<0.001$ ). Covariate-adjusted regression identified cues to action ( $B=0.369,p<0.001$ ) and perceived barriers ( $B=-0.095,p=0.008$ ) as independent predictors, accounting for $34.4\%$ of total variance ( $R^2=0.344$ ). Crucially, cues to action fully mediated the statistical relationship between perceived benefits and behavior (indirect effect $=0.351,95\%\text{Bootstrap}\mathrm{CI}[0.236,0.478]$ ; direct path $p=0.726$ ). Significant subgroup variations emerged among healthcare professionals, individuals with chronic conditions ( $24.4\%$ ), and Hualien residents.

Health beliefs-specifically perceived benefits catalyzed via cues to action-are pivotally associated with CHM adoption. Nursing administrators should leverage these insights to design culturally tailored health communication, empower nurses as institutional triggers, and establish structured safety screening for chronic disease cohorts regarding potential herb-drug interactions.