The construction and evaluation of new educational software for nursing diagnoses: a randomized controlled trial

Student nurses often have difficulties with diagnostic inferences. To achieve high accuracy nursing diagnoses, effective learning strategies are required.

To describe the construction and evaluation of new educational software called Wise Nurse, which was developed to increase the capacity of student nurses to identify nursing diagnoses (NDx) and to establish relationships between NDx, defining characteristics (DC), and related factors (RF).

Randomized controlled trial.

Participants were 2nd to 4th year student nurses from an undergraduate program at a university in Brazil. Of the 47 recruited students, 37 completed the survey.

Students were randomly assigned to test the software (experimental group) and to solve printed clinical cases (comparison group). A pretest and post-test were applied before and after the experiment. Statistical analyses of the students' performance in the tests were conducted. The primary outcome was the students' progress in solving questions and clinical cases regarding NDx. The System Usability Scale was used to measure the software's ease of use.

No significant difference was found between the experimental and comparison groups before and after the experiment. The average students' performance in identifying RF and NDx was higher than in identifying DC. The post-test score was higher than the pretest score in both groups (P=0.022). The usability score was good (average score 83.75, N=20).

The use of Wise Nurse supported an improvement in student diagnostic reasoning equivalent to that of the traditional NDx training, but the software stands out as an innovative teaching tool.