Effect of Digital Intervention on Nurses’ Knowledge About Diabetic Foot Ulcer: A Quasi-Experimental Study

Abstract

Educational strategies based on technological models that integrate the dimensions of prevention, screening, and treatment of diabetic foot ulcers are emerging as promising methods to improve nurses’ knowledge, skills, and clinical competencies in primary care. In this investigation, we evaluated the effectiveness of a digital education program, mediated by a virtual learning environment, in enhancing nurses’ clinical knowledge about diabetic foot ulcers. This quasi-experimental intervention study was conducted with 114 nurses, selected for convenience, from the five health districts that make up primary care in the municipality of Teresina, Brazil. Two stages, separated by the educational intervention, allowed us to measure their knowledge levels before and after the implementation of the digital technology. A characterization form and the Nurse Knowledge Assessment Questionnaire on Diabetic Foot were used to evaluate the outcomes. The McNemar test compared the pre- and post-intervention knowledge levels, while accuracy rate-based parameters allowed for the classification of results into performance categories. The intervention effect size was estimated using Cohen’s d test. Results showed substantial improvements in knowledge, particularly in domains related to definition (p = 0.002), risk factors (p < 0.001), associated complications (p < 0.001), signs and symptoms of neuropathies (p < 0.001), application of tests to assess protective sensation (p < 0.001) and foot biomechanics (p < 0.001), risk classification (p < 0.001), and prevention strategies (p < 0.001), with performance ratings predominantly “good” or “excellent” after the intervention. The effect size for paired samples was large (Cohen’s dz = 1.82), based on the total knowledge scores. Findings support the effectiveness signal of the virtual learning environment for knowledge improvement; however, without a control group, we cannot rule out testing effects. Controlled or stepped-wedge trials should confirm causality.