ArticleJournal of public health research2025
Modeling the determinants of community engagement in community-based surveillance of infectious diseases: Applying the Health Belief Model.
Article in Journal of public health research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of health belief model (HBM) in health sciences and medical researches: systematic review on African and Asian countries.BMC public health · 2026Pooled it
- Modeling social and behavioral factors associated with community participation in community-based surveillance of communicable diseases: a cross-sectional study in Kelantan, Malaysia.Osong public health and research perspectives · 2026Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Community-Based Surveillance (CBS) refers to involving community members in the detection and reporting of diseases within their communities for timely and effective response. Hence, it is necessary to study the factors that influence community participation in CBS. Objective: This study aims to utilize the Health Belief Model (HBM) to identify predictors of community engagement in CBS activities in Kelantan state, Malaysia. Design and methods: Perceived Benefit (BEN), Perceived Barriers (BARR), Perceived Susceptibility (SUS), and Behavioral Likelihood (BL) were assessed using a validated questionnaire (KAP-CBS-ID). A Covariance-based Structural Equation Modeling (SEM) approach was used to understand the relationships between the study variables. Results: The model demonstrated a good fit (RMSEA = 0.048, 90% CI [0.042, 0.054]; CFI = 0.935; TLI = 0.925; SRMR = 0.078) and explained 40.5% of the variance in the behavioral likelihood of engaging in CBS. Self-efficacy (SE) emerged as a strong direct predictor of participation. SUS showed both direct and indirect (mediated) effects on behavioral likelihood to participate in CBS, with the indirect effect occurring through SE. Similarly, BEN influenced BL indirectly through SE. The perceived barriers, on the other hand, had a significant negative direct effect on participation (BL). The effects of SE, BARR, and SUS on participation in CBS were substantial. Conclusion: Public health interventions should focus on improving community self-efficacy to participate in CBS initiatives, as well as raising awareness of disease susceptibility, highlighting the benefits of CBS, and addressing participation barriers to increase community engagement in surveillance systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.