Nursing students’ diagnostic accuracy using a computer-based clinical scenario simulation
journal contributionposted on 29.11.2018, 00:00 by Vanessa E. C. Sousa Freire, Marcos V. O. Lopes, Gail M. Keenan, Karen Dunn Lopez
Background: Being able to make accurate clinical decisions about actual or potential health problems is crucial to provide a safe and effective care. However, nursing students generally have difficulties identifying nursing diagnoses accurately. Objective: To compare the diagnostic accuracy within and across the NANDA-I diagnoses domains of junior, senior, and graduate-entry students. Design: Descriptive study. Participants and Setting: The sample comprised one hundred thirty nursing students from a Midwestern American university. Methods: The participants were divided in three groups (juniors, seniors and graduate-entry) and invited to engage in a series of diagnostic exercises presented in a software. Students were presented with 13 scenarios and asked to identify the applicable defining characteristics, related factors, and nursing diagnoses from the NANDA-I taxonomy. The number of correct answers per scenario was used to compute diagnostic accuracy. Age, gender, previous exposure to the NANDA-I taxonomy, and student level were covariates in the analysis. Results: The average percent correct answers across all groups was 64.4% and no statistical differences between the groups were found. The scenarios belonging to the Health Promotion, Self-Perception, and Growth/Development Domains were those in which students had a higher number of incorrect answers. Students also had more difficulty recognizing the correct nursing diagnoses compared with related factors and defining characteristics. Conclusions: This study found no associations between demographic variables, exposure to the NANDA-I taxonomy, or academic program level and diagnostic accuracy. Some areas in which students had a poor performance indicate need for improvement in diagnostic reasoning skills.