Efficacy of clinical simulation in line with the conceptual map on the diagnostic reasoning ability of nursing students
Nursing; Nursing Education; Nursing Diagnoses; Educational technology; Simulation.
The diagnostic inference in nursing, because it is something complex, can lead to difficulties for students. Thus, there is a need to develop educational technologies aimed at improving this reasoning. Thus, the objective is: to evaluate the effectiveness of clinical simulation in line with the conceptual map in the diagnostic reasoning ability of nursing students. The research was developed in three stages, the first two being subsidized by a methodological study and the third by a controlled and randomized clinical trial. The first includes the construction of two clinical cases for the pre-test and post-test instruments, two clinical simulation scenarios on diagnostic reasoning in nursing and the elaboration of the students' leveling assessment. The second stage corresponded to content analysis of clinical cases, simulation scenarios and assessment of students' placement by judges. The evaluation of the scenarios had 45 judges in diagnostic reasoning and/or clinical simulation, who analyzed each item using a likert scale. To assess the degree of diagnostic accuracy, the Nursing Diagnosis Accuracy Scale was used. Clinical cases and leveling questions had their content evaluated by 8 judges in a focus group. The third stage included the application of clinical simulation in line with conceptual maps to improve the ability of diagnostic reasoning for undergraduate nursing students. Students were randomized into intervention and control groups. The intervention group was submitted to the use of educational technology and the control group to the traditional class. The following inclusion criteria were adopted: age 18 years or older; being a student of the nursing course at a Federal University of Rio Grande do Norte and having attended or being studying the curricular component referring to the Nursing Process content, specifically, Nursing diagnosis. The following were used as exclusion criteria: students who had any cognitive or behavioral difficulties, which made communication unfeasible and also those who had a grade higher than 7 in the leveling assessment. As discontinuation criteria, the following were considered: withdrawal from participating in the research after the beginning of data collection and/or the appearance of flu-like symptoms during this period. Data were analyzed by descriptive and inferential statistics. For the simulation scenarios, an agreement of 85% of the judges was considered. For the Nursing Diagnosis Accuracy Scale, the S coefficient was calculated for all diagnoses. The students' performance was analyzed using inferential statistics in the pre-test, post-test and Diagnostic Reasoning Inventory instruments, adopting a significance level of 5% (p≤0.05). The research project was approved by the responsible Ethics Committee, under number 3,084,032. It was registered in the Brazilian Clinical Trials Registry database, receiving the number: RBR-7qjpn6. The results show that the scenarios were judged with acceptable agreement by the experts, the proposed diagnoses showed a high degree of accuracy. The clinical cases used in the pre-test and post-test had an average content validity index of 93.7%. In the last stage, the intervention group stands out in the inference of the diagnostic label, which presented a statistically significant difference when comparing the pre- and post-test moments (p = 0.001). The same happened in the correct answers regarding related factors (p=0.004) and defining characteristics (p=0.004). Thus, it is concluded that the educational strategy clinical simulation in line with the conceptual map was effective in improving the diagnostic reasoning of nursing students. Furthermore, the study provides visibility for two active teaching methodologies, clinical simulation and the conceptual map, which represents an advance in the role of students as active subjects in the teaching-learning process.