Community participation in community-based surveillance of infectious diseases: A structural equation modeling approach based on the theory of reasoned action
Background and Aim: Community-based surveillance (CBS) is a critical mechanism for early detection of infectious diseases. Understanding the behavioral drivers of CBS participation is essential to strengthening community engagement. This study employed structural equation modeling (SEM) based on the...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Veterinary World
2025-06-01
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| Series: | International Journal of One Health |
| Subjects: | |
| Online Access: | https://www.onehealthjournal.org/Vol.11/No.1/17.pdf |
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| Summary: | Background and Aim: Community-based surveillance (CBS) is a critical mechanism for early detection of infectious diseases. Understanding the behavioral drivers of CBS participation is essential to strengthening community engagement. This study employed structural equation modeling (SEM) based on the theory of reasoned action (TRA) to investigate the impact of knowledge, subjective norms (SN), and attitudes on the intention and behavioral likelihood (BL) of participating in CBS activities.
Materials and Methods: A cross-sectional survey was conducted among 470 schoolteachers selected through a multi-stage mixed sampling strategy across Kelantan, Malaysia. A structured questionnaire assessing sociodemographic factors, knowledge, attitudes, and perceptions toward CBS was developed and validated. Confirmatory factor analysis and SEM were employed with model parameters estimated using the robust maximum likelihood (MLR) approach. Model fit was assessed using comparative fit index (CFI), Tucker-Lewis index (TLI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR) indices.
Results: The final model demonstrated good fit (CFI = 0.923; TLI = 0.913; RMSEA = 0.045; SRMR = 0.070). Knowledge (β = 0.335) and SN (β = 0.296) positively influenced intention to participate in CBS, whereas negative attitudes (β = −0.313) showed a significant negative association. Intention significantly predicted BL (β = 0.633). The model explained 40% of the variance in intention and 43% in BL. Intention mediated the effects of knowledge, norms, and attitudes on behavioral engagement.
Conclusion: Knowledge, positive SN, and reduced negative attitudes are pivotal in fostering community participation in CBS initiatives. Intention emerged as a critical mediator linking cognitive and normative beliefs to actual behavioral engagement. These findings provide actionable insights for designing targeted interventions that enhance CBS participation and strengthen infectious disease surveillance at the community level. |
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| ISSN: | 2455-5673 2455-8931 |