Emotional Skills and Nursing Training: A Study on Italian Students and a TRI-COM-Based Educational Model
Bibliographic record
Abstract
Background/Objectives: Emotional competence is a crucial skill in nursing education, yet it remains underdeveloped in academic curricula. This study aims to (1) propose and preliminarily apply the TRI-COM model as a conceptual and educational framework to operationalize the definition of emotions within nursing contexts, and (2) explore the multidimensional structure of emotional competence among nursing students. Methods: A cross-sectional study was conducted with 233 nursing students (M_age = 23.79, SD = 5.19) from various Italian universities, with 82.8% identifying as female. The participants completed an online questionnaire including the Toronto Alexithymia Scale (TAS-20) and the Jefferson Scale of Empathy—Health Profession Student (JSE-HPS) version. Descriptive statistics, t-test, ANOVA, and Pearson’s correlation analyses were performed. Results: The overall mean TAS-20 score was 60.36 (SD = 11.22), which is close to the clinical threshold (cut-off = 61). The EOT subscale showed the highest mean (M = 26.48, SD = 3.16), suggesting a tendency toward externally oriented thinking. The mean JSE-HPS total score was 87.05 (SD = 7.88), with higher scores for Perspective Taking (M = 60.95, SD = 7.42) than Compassionate Care (M = 18.92, SD = 6.40). A significant gender difference was found in Perspective Taking (female: M = 61.54, male: M = 58.10; p = 0.007). The ANOVA results showed no significant differences in empathy across academic years, but the DIF subscale of TAS-20 showed a trend near significance (p = 0.053). Significant negative correlations were observed between age and TAS-20 scores (e.g., age–TAS-20 total: r = −0.23, p < 0.001). Conclusions: The findings suggest a general tendency toward rationalization and emotional detachment among students, possibly as a coping strategy in emotionally demanding contexts. The TRI-COM model—an original pedagogical framework inspired by tripartite theories of emotion—was used as a conceptual lens, providing a preliminary framework to interpret emotional competence in nursing education. Further research is needed to validate its educational relevance and explore practical applications within curricula.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".