Predicting preventive behaviors on Dog-Borne Zoonoses using the Health Belief Model
Journal Title: Annals of Tropical Research - Year 2023, Vol 45, Issue 1
Abstract
Due to the risks posed by dog-borne zoonotic diseases, a cross-sectional survey was carried out on: (1) respondents’ socio-demographic characteristics and prior exposure to dog-borne risks; (2) respondents’ knowledge, risk perceptions and preventive behavior towards dog-borne zoonotic diseases; and (3) relationships between respondents’ information exposure, knowledge, risk perceptions, and preventive behavior towards dog-borne zoonotic diseases. Since health behavior is dependent on multiple factors within a social context, this study used the Health Belief Model to achieve the study objectives. A randomly selected sample of 147 residents of the City of Baybay (aged 20-77 years (mean=47.29, SD=13.27)) perceived dog-borne zoonoses to be highly severe types of diseases. Structural equation modelling based on the Health Belief Model showed that dog ownership, perceptions on severity and susceptibility, and perceptions on benefits and barriers directly predicted the likelihood of adopting dog-borne zoonotic disease preventive measures. In addition, there were significant indirect effects of knowledge on dog-borne zoonoses, demographic factors including prior exposure to dog-borne zoonoses, membership of community organizations, and barangay (village) residence zone. Information exposure to dog-borne zoonoses (cues to action) also had a significant indirect effect on behavior. All these denote that the health belief model (HBM) is effective in predicting preventive behaviors on dog-borne zoonotic diseases. However, to maintain these levels of prevention behavior, there is a need for sustained exposure to information on dog-borne zoonoses, and the institutionalization of a community-based dog-borne zoonotic disease prevention initiative.
Authors and Affiliations
Eula Dee A. Lañada, Nelfa M. Glova, Eugene B. Lañada
Keywords
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- EP ID EP755450
- DOI https://doi.org/10.32945/atr4517.2023
- Views 2
- Downloads 0
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