Digital literacy as correlate of use of electronic resources by nurses in Northwest,Nigeria

Abstract

This study examines digital literacy as a correlate of electronic resource use among practising nurses in Northwest, Nigeria, with the objective of assessing their digital competencies, e-resource utilization patterns, and associated challenges. The research contributes to bridging the knowledge gap on digital adoption in Nigerian healthcare by providing empirical evidence on how digital literacy influences clinical practice and suggesting policy interventions for improved e-health integration. A descriptive survey design was employed, with data collected from 350 nurses across seven states in Northwest Nigeria using a structured questionnaire. Frequency counts, percentages, and mean scores were used for analysis, with a benchmark mean of 2.50 for decision-making. Pearson’s correlation (r) was applied to determine the relationship between digital literacy and e-resource use. Findings revealed low e-resource utilization, with an aggregate mean of 1.63, indicating infrequent use of online databases (x̄ = 1.63), e-journals (x̄ = 1.46), and clinical decision tools (x̄ = 1.57). Digital literacy levels were also suboptimal (x̄ = 1.96), with nurses struggling in computer proficiency (x̄ = 2.05), software use (x̄ = 1.87), and internet navigation (x̄ = 1.99). A moderate positive correlation (r = 0.498, p < 0.05) was found between digital literacy and e-resource use, explaining 24.8% of variance. Key challenges included poor internet connectivity (x̄ = 3.74), power outages (x̄ = 3.56), and lack of institutional support (x̄ = 3.48). The study underscores the critical role of digital literacy in enhancing e-resource adoption among nurses. Implications include the need for mandatory digital training, improved ICT infrastructure, and policy reforms to foster technology-driven healthcare delivery. Recommendations advocate for workplace upskilling programs, reliable power and internet access, and user-friendly e-health platforms to optimize clinical decision-making and patient care outcomes.