Building Community Resilience to COVID-19: An Interprofessional Collaborative Model

Abstract

Introduction: Coronavirus Disease 2019 (COVID-19) is a significant global health issue, requiring vigilance and adherence to health protocols to prevent transmission. This study aimed to develop an interprofessional collaborative model based on community sectoral coordination. Methods: A mixed-methods explanatory research design was employed, involving 934 respondents selected through convenience sampling. The research instrument was a modified version of a validated and reliable questionnaire covering interprofessional collaboration, community health nursing, alertness, compliance, and resilience. The data was analyzed using Partial Least Squares (PLS) to test the model's fit and predictive relevance. Results: The coefficient of determination (R²) was 0.772, indicating that 77.2% of the variance in interprofessional collaborative community sectoral coordination could be explained by individual, team, task, and work structure characteristics, as well as community leaders and cross-sectoral factors. The remaining 22.8% was attributed to other variables not included in this study. The Predictive Relevance (Q²) value was greater than 0, suggesting that the model was adequately predictive. Significance testing showed that the exogenous variables had a significant impact on endogenous variables with a total T-statistics value of 1.96 or P value <0.05. Conclusion: The developed interprofessional collaborative model based on community sectoral coordination significantly enhances community alertness, compliance, and resilience, contributing to the achievement of COVID-19 herd immunity.