Nurses' and Nursing students' perceptions of their knowledge and satisfaction in managing wound infections: A cross-sectional study

Objective: To analyze the perception and satisfaction of nurses and nursing students regarding their knowledge of the clinical management of infected wounds in Spain. Methods: A cross-sectional descriptive study was conducted using an ad hoc questionnaire with 18 questions on knowledge of infected wounds, divided into three sections, and was distributed electronically to nurses and nursing students over a two-month period. The questionnaire was piloted with a group of nurses and students, and data were collected anonymously and voluntarily. Results: A total of 520 completed questionnaires were collected, including 158 from professionals and 362 from students. Professionals demonstrated a significantly higher average knowledge score than students (4.7 +/- 0.13 vs 3.8 +/- 0.09; P < .001). Students performed worse in questions related to biofilm and assessment of subtle and manifest signs of infection in wounds. Specifically, only 45% of students correctly identified the role of bacterial biofilm in wound infections. Significant differences were observed in various items (P < .05) favoring non-clinical professionals over clinical professionals, particularly regarding biofilm and the use of topical antiseptics. Overall, professionals expressed significant satisfaction with their knowledge compared to students (P < .05). Conclusion: Nursing professionals, especially those with teaching, research, and/or managerial roles, demonstrate a greater perception of knowledge in specific areas. However, both professionals and students exhibit gaps in perceived knowledge regarding the management of wound infections, highlighting the importance of continuous education and the review of teaching strategies to address these deficiencies. Implementing a specific mandatory subject is suggested to ensure the quality of nursing education in this area from undergraduate level. (c) 2024 Elsevier Espana, S.L.U. All rights are reserved, including those for text and data mining, AI training, and similar technologies.