Expression and Functional Use of Emotions as Predictors of Clinical Reasoning in Undergraduate Nursing Students: A Cross-Sectional Study

Background: Clinical reasoning (CR) involves intertwined cognitive and affective processes, yet the specific contribution of emotional competence (EC) sub-dimensions to CR remains underexplored in undergraduate nursing education. Identifying which EC components matter can inform targeted, low-cost educational routines to support decision quality and patient safety. Aim: To examine the association between EC and CR and to determine, among PEC dimensions (intrapersonal, interpersonal) and the ten PEC sub-dimensions, which independently predict CR in undergraduate nursing students. Methods: A cross-sectional study was conducted in Morocco (Tanger–Tétouan–Al Hoceïma region, March–May 2025). Students completed the Profile of Emotional Competence (PEC, 50 items) and the Nurses’ Clinical Reasoning Competence Scale (NCRCS). Analyses included descriptive statistics, Pearson/Spearman correlations, and multiple linear regressions. Results: Clinical reasoning (CR) was positively associated with both intrapersonal emotional competence (EC) (r = 0.23, p < 0.01) and interpersonal EC (r = 0.19, p < 0.01). In the two-dimensional model, the regression was significant (F(2, 308) = 11.27, p < 0.001, R² = 0.07), with independent contributions from intrapersonal EC (β = 0.19, p = 0.002) and interpersonal EC (β = 0.13, p = 0.027). In the ten-subdimension model, overall fit remained significant (F(10, 300) = 3.56, p < 0.001, R² = 0.106, adjusted R² = 0.076). Two intrapersonal subdimensions, emotional expression (β = 0.15, p = 0.013) and task-oriented use of emotions (β = 0.17, p = 0.005)—emerged as independent predictors of CR when modeled simultaneously. Conclusion: Two intrapersonal emotional micro-skills, expressing emotions and using them in a task-oriented way are priority targets to strengthen clinical reasoning. Embedding brief metacognitive prompts and structured debriefings (including simulation) may offer scalable, cost-effective ways to improve decision quality in undergraduate nursing.