ABSTRACT
Introduction Standard precautions are part of the infection control basis to protect radiology technologists from COVID-19 and other infections to prevent transmission from patient to patient and from healthcare workers to healthcare workers. This study ascertains the relationship between the standard practices and attitudes of radiologic technologists in handling COVID-19 patients. Methodology A quantitative-correlational design as used to specifically determine the standard precaution practices and attitudes of 46 radiologic technologists in the affiliated hospitals of the university, and the relationship of the two variables. Google form was used to gather data using the WHO Standard Precautions Protocol, which underwent pilot testing and a Cronbach alpha value of .804. Data analysis included descriptive statistics, Analysis of Variance (ANOVA) and Pearson-r correlation. Results The study revealed that radiologic technologists’ have high level of practices (μ=2.97 ±.0694) and attitude (μ=2.97 ±.824) in standard precaution. No significant difference was revealed in the standard precaution practices of radiologic technologists when grouped according to gender, years of service, age, and hospital type, Furthermore, no significant difference was revealed in the attitudes of radiologic technologist when grouped according to years of service, age, and hospital type, however, a significant difference was observed when the radiologic technologists were grouped according to gender (t (46) =2.04, p=.048) with female radiologic technologists having higher attitude (x̄=2.99, SD=.0253) on standard precautions than male radiologic technologists (x̄=2.94, SD=.0118). Overall, a high-positive correlation (r= .855, p=0.001) was revealed between the standard precaution practices and attitudes of radiologic technologists in handling COVID-19 patients. Conclusion There exist a good practice and good attitude in standard precaution of Radiologic technologists in handling COVID-19 patients and a very high-positive relationship between the two variables.