Temidayo Oluwatosin Omotehinwa

Work place: Department of Mathematics and Computer Science, Federal University of Health Sciences, P.M.B. 145, Otukpo, Nigeria

E-mail: temidayo.omotehinwa@fuhso.edu.ng

Website:

Research Interests:

Biography

Temidayo O. Omotehinwa, Ph.D., received his B.Sc., M.Sc., and Ph.D. in Computer Science from the University of Ilorin, Nigeria, in 2007, 2011, and 2017 respectively. He currently holds the position of Senior Lecturer and acting head of the Department of Mathematics and Computer Science at the Federal University of Health Sciences, Otukpo, Nigeria. Dr. Omotehinwa specializes in machine learning, knowledge extraction, and data analytics, with notable contributions to the field through his published work in prestigious journals and conferences. In 2023, he was awarded an all-expense paid grant by Luxembourg Aid & Development via INSTITUT PASTEUR de DAKAR. This grant allowed him to bring his expertise to the first International Course on Genomic Algebra Theory, Tools, and Applications (GATTA) in Dakar, Senegal.

Author Articles
Assessment of Knowledge and Utilization of Computers Among Healthcare Workers in Benue South, Nigeria

By Temidayo Oluwatosin Omotehinwa Augustine Ovie Edegbene Oga Ode

DOI: https://doi.org/10.5815/ijitcs.2025.01.03, Pub. Date: 8 Feb. 2025

Literature confirms that the low success rate of eHealth systems is closely linked to inadequate computer knowledge. Therefore, this study aimed to assess knowledge and utilization of computers among healthcare workers in Benue South. An institution-based quantitative cross-sectional study design was conducted in 120 health facilities, including primary healthcare centres, and private clinics. This study involved 430 healthcare workers. Using Python programming, descriptive and multivariable logistic regression analyses were conducted to assess the level of computer knowledge and utilization among participants, as well as to identify factors influencing their computer knowledge and utilization. Of the 430 participants, 233 (54.19%) of healthcare workers passed the computer knowledge test, 216 (50.23%) of health workers have access to computers, and 221 (51.40%) of them had undergone formal computer training. The findings revealed that 263 (61.16%) of healthcare workers exhibit good computer utilization, while 167 (38.84%) demonstrated poor utilization. Access to a computer (adjusted odds ratio [AOR]=2.83, 95% CI 0.48-1.60), and prior computer training (AOR=3.34, 95% CI 0.65-1.76) were found to be significantly associated with computer knowledge, while Access to a computer (AOR=2.98, 95% CI 0.48-1.70), Sex (AOR=2.23, 95% CI 0.28-1.32), Department (AOR=1.06, 95% CI 0.00-0.11), and prior computer training (AOR=5.53, 95% CI 1.10-2.32) were found to be significantly associated with computer utilization. These findings imply that improved access to computers and comprehensive computer training for healthcare professionals is vital for improved service delivery.

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