Signal detection for pediatric patient deterioration with nursing students: An explanatory sequential design mixed-methods study

Failure to rescue occurs when nurses fail to detect signals of clinically significant changes in the early stages of disease complication or patient deterioration. Pediatric patient deterioration detection poses a different challenge because pediatric patients physiologically respond differently from adults. Nursing students are especially challenged in detecting pediatric patient deterioration because adult illness is the primary focus of nursing education. The study aims to identify vital signs that nursing students categorize as signals of pediatric deterioration, determine influences on their response to signals, and how these influences affect their performance in signal detection trials.

To assess and understand nursing students' pediatric deterioration detection performance, an explanatory sequential mixed-method design was conducted with second-semester senior baccalaureate nursing students. Students participated in signal detection trials, and then a subset was interviewed about their performance and thought processing. The quantitative data were analyzed for descriptive statistics, mean rate, sensitivity, and response bias. The qualitative data were analyzed with thematic analysis. The quantitative and qualitative results were compared to examine how performance and influences on response are related.

Participants (n=21) had a low sensitivity d' = 1.19 (SD 0.85) to signals of pediatric deterioration and an increased tendency c = -0.03 (SD 0.66) to misclassify non-critical stimuli as indicators of deterioration. Respiratory rate changes were the most accurately identified among all signal types. Vital sign type did not significantly affect detection. Four major themes were identified as factors influencing student responses in the trials. Differences in detection performance corresponded with differences in influencing factors.

Students demonstrated low sensitivity in detecting early signs of patient deterioration. These findings highlight the need to enhance student knowledge and preparedness to detect signals of pediatric deterioration early and reduce failure to rescue. This study demonstrates the innovative use of signal detection to assess nursing students' ability to recognize patient deterioration cues. By quantifying the sensitivity index and response bias, educators can identify knowledge gaps and tailor remediation to individual needs. Signal detection testing provides a unique framework to evaluate decision-making under uncertainty, advancing nursing education to better prepare students for clinical practice.