Assessing the Impact of Digital Deep Learning Tools on Knowledge, Attitude, Practice, and Behavioural Change in Food Safety Among Food Handler Workers in Al Qassim Hospitals

Main Article Content

Mohammad Salih Alguit
Syamimi Samah

Abstract

Food safety in hospital settings is critical due to the vulnerability of patients to foodborne illnesses. This study aimed to evaluate the effectiveness of a digital learning intervention in improving food safety knowledge, attitudes, practices (KAP), and behavioral change among hospital food handlers in public hospitals in Al Qassim, Saudi Arabia. A quasi-experimental pre–post design was employed involving 211 participants. Data were collected using structured questionnaires, behavioral assessments, and qualitative methods. The Wilcoxon signed-rank test revealed statistically significant improvements across all KAP dimensions and behavioral outcomes (p < .001), with large effect sizes (r = 0.87). Regression analysis indicated that practice improvement was the strongest predictor of behavioral change, followed by knowledge, perceived training effectiveness, and attitude. Qualitative findings highlighted the role of engagement, relevance, and organizational support in enhancing training outcomes. Despite these improvements, barriers such as workload and digital literacy challenges were identified. The study concludes that digital learning is an effective and scalable approach for improving food safety practices in hospital settings, particularly when supported by institutional reinforcement mechanisms.

Article Details

Section

Articles

How to Cite

Assessing the Impact of Digital Deep Learning Tools on Knowledge, Attitude, Practice, and Behavioural Change in Food Safety Among Food Handler Workers in Al Qassim Hospitals (M. S. Alguit & S. Samah, Trans.). (2026). International Journal of Aquatic Research and Environmental Studies, 6(S1), 658-664. https://doi.org/10.70102/g53tf143

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