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Article

Simulation-Based Educational Practices and Their Relationship with Emotional Intelligence and Stress Coping Skills: An Exploratory Case Study in First Aid Training for Physical Activity and Sports Sciences Students

by
Néstor Montoro-Pérez
1,
Raimunda Montejano-Lozoya
2,
Carmen Rocamora-Rodríguez
1,* and
Juana Perpiñá-Galvañ
1
1
Department of Nursing, Faculty of Health Sciences, University of Alicante, 03690 San Vicente del Raspeig, Spain
2
GREIACC Research Group, La Fe Health Research Institute, University School of Nursing “La Fe”, Center Attached to the University of Valencia, 46026 Valencia, Spain
*
Author to whom correspondence should be addressed.
Trends High. Educ. 2025, 4(3), 50; https://doi.org/10.3390/higheredu4030050
Submission received: 20 May 2025 / Revised: 30 August 2025 / Accepted: 2 September 2025 / Published: 9 September 2025
Versions Notes

Abstract

This study explores the integration of simulated environments into first aid training programmes within the field of Physical Activity and Sports Sciences. Grounded in the framework of student-centred teaching methodologies and competency-based education models, the research investigates the impact of simulated environments on students’ Emotional Intelligence (EI). The study hypothesizes that positive stress coping styles and good educational practices developed in simulated environments are correlated with higher levels of EI. Methodologically, a descriptive study was conducted, involving participants pursuing a Bachelor’s Degree in Physical Education and Sport Sciences. Measures included the Trait-Mood Scale 24 (TMMS-24) for EI assessment, the Stress Coping Questionnaire (SCQ) for stress evaluation, and the Educational Practices Questionnaire (EPQ) for assessing educational practices. Results revealed significant associations between active learning and higher levels of EI, problem-solving coping styles, and emotional clarity, as well as positive reappraisal coping styles and mood recovery. The study emphasizes the potential of integrating simulated environments into first aid training programmes, offering immersive learning experiences that enhance students’ practical skills and emotional development.

1. Introduction

Within the framework of the European Higher Education Area and in accordance with its regulations, universities have implemented new models of teaching and assessment that position the student as the central focus and subject rather than an object of education. This has been made possible through the integration of competency-based educational models and the adoption of new teaching methodologies in which the acquisition of not only knowledge but also skills, capabilities, and attitudes is pursued [1].
The acquisition of competencies in universities requires the integration of innovative teaching methods [1]. These techniques should aim to integrate knowledge that students will use in their future professional practice [2,3]. Among these techniques, simulated environments stand out as an effective tool for teaching and learning [4,5]. Simulation involves creating realistic environments through various methodologies such as simulation mannequins, role-playing with real people or actors, using different situations that students may face in the future [6]. In this context, by applying Kolb’s Experiential Learning Cycle in simulated environments, university students can engage in practical activities, reflect on their experiences, conceptualize abstract ideas, and actively experiment with the knowledge acquired, enabling students to effectively integrate theory with practice [7].
Other benefits of simulated environments are that they heighten students’ interest and enhance decision-making within a safe setting, thereby contributing to an enriching learning experience [8]. Moreover, the use of simulated environments fosters the development of Emotional Intelligence (EI) [9]. EI pertains to individuals’ perceptions of their own emotional abilities, such as their capacity to recognize and reflect upon their emotions, as well as to comprehend and regulate their own emotional states [10,11]. In this sense, simulated environments favour the development of various components of EI, such as self-control and motivation [12,13,14], which in turn appear to be linked to higher academic performance and the acquisition of appropriate coping styles in stressful situations [4,15,16]. In this regard, the development of EI leads to better management of emotions that arise during critical life situations students may encounter in their future professional practice [12,17,18]. Therefore, the interdependence and influence between the presence of good educational practices, such as simulated environments, the development of positive coping mechanisms to stress, and the development of EI, are recognized [19].
Numerous higher education institutions have implemented simulated environments as learning tools in diverse fields such as technology, engineering, mathematics, teaching, and health sciences [20,21,22]. In health sciences, there is extensive evidence supporting the effectiveness of simulation-based learning for acquiring both technical and non-technical skills [23,24,25], applicable in hospital settings and pre-hospital emergencies [26,27,28], benefiting both students and qualified professionals [29,30,31]. However, there is no scientific evidence that simulated environments are integrated into the first aid training curriculum for students of Physical Activity and Sports Sciences. These students are future professionals who will work in training centres, schools, and sports facilities where they may encounter critical situations of urgency and emergency involving the individuals they work with. One example is Sudden Cardiac Arrest (SCA), a situation that, if not addressed quickly and effectively, can lead to the death of the affected individual [32,33]. SCA accounts for 75% of all deaths during exercise and is the leading cause of death in athletes and sports participants [33]. Another example could be emergency childbirth as professionals in this field often engage in maintenance gymnastics and childbirth preparation [34]. In this context, adequate first aid training and preparation could significantly improve survival rates and reduce the incidence of complications [32,33].
In this context, the present study specifically focused on evaluating the possible relationship between the implementation of good educational practices in simulated environments, stress coping skills, and EI in third-year students pursuing a Bachelor’s Degree in Physical Education and Sport Sciences who are enrolled in the subject “First Aid and Pathophysiology of Physical Activity and Sport”. To assess the training plan, the following hypotheses were formulated: (1) positive stress coping strategies developed within simulated environments are expected to be positively associated with higher levels of EI, and (2) good educational practices implemented in simulated environments are expected to be positively associated with higher levels of EI. Therefore, this study adopts an exploratory approach to identify significant associations among variables relevant to emotional health and training in sports education.

2. Materials and Methods

2.1. Design and Participants

A cross-sectional descriptive study was conducted to evaluate the benefits of implementing a training plan based on simulation in first aid. Participants were selected through non-probabilistic convenience sampling from students enrolled in the “First Aid and Pathophysiology of Physical Activity and Sport” subject who are pursuing a Bachelor’s Degree in Physical Education and Sport Sciences. Selection took place during the academic years of 2022–2023 and 2023–2024, with the following inclusion criterion applied: full attendance at the simulated environment sessions.

2.2. Sample Size

The sample size was determined based on similar previous studies [12] and enrolment and attendance records for the simulated first aid training sessions. Out of 103 students enrolled over the 2022–2024 academic years, 84 completed all practical sessions. With a 95% confidence level and a 5% margin of error, we required a minimum sample size of 70 participants.

2.3. Measures

2.3.1. Outcome Variable

EI was assessed using the Trait Meta-Mood Scale 24 (TMMS-24), developed by Salovey et al. [35] and adapted into Spanish by Espinoza-Venegas et al. [36]. The instrument comprises 24 items and three factors: attention to emotions, clarity of feelings, and mood repair. Responses are provided using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The instrument shows good internal consistency across all factors, with Cronbach’s alpha values of 0.86 for attention to emotions, 0.87 for clarity of feelings, and 0.82 for mood repair. The higher the score, the higher the level of EI.

2.3.2. Sociodemographic Variables

The following sociodemographic variables were examined: sex (male/female), age (as a continuous variable in years), previous experience in first aid (yes/no), and previous experience in simulation (yes/no).

2.3.3. Psychological Variables

Stress was assessed using the Stress Coping Questionnaire (SCQ), developed by Sandin and Chorot [37]. The instrument consists of 42 items and seven factors: social support seeking (identifies people and support networks to provide appropriate management of the stressful situation), open emotional expression (vents bad humour on others; expresses insults; is hostile and irritable; and pours out their feelings), religion (relies on religious beliefs in order to face the situation due to a feeling of losing control), focused on solving the problem (the person analyses the causes and plans and implements solutions to face the situation), evitation (concentrates on other things and prefers not to think of the problem), negative self-focus (the person self-blames and has feelings of helplessness and inability, resignation, dependence, loss of control, and pessimism), and positive re-evaluation (recognizes the stressful event but is centred on the positive aspects of the situation). Responses are provided using a four-point Likert-type scale ranging from 0 (never) to 4 (almost always). The instrument shows good internal consistency across all factors, with Cronbach’s alpha values of 0.92 for social support seeking, 0.74 for open emotional expression, 0.86 for religion, 0.85 for focused on solving the problem, 0.76 for evitation, 0.64 for negative self-focus, and 0.71 for positive re-evaluation.

2.3.4. Educational Variables

Good educational practices in simulated environments were assessed using the Educational Practices Questionnaire (EPQ), translated into Spanish by Farrés-Tarafa et al. [38]. The instrument consists of 16 items and four dimensions: active learning, collaboration, diverse ways of learning, and high expectations. Responses are provided using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Higher scores on the scale indicate greater recognition of best practices in curriculum studies. The instrument shows good internal consistency across all factors, with Cronbach’s alpha values ranging from 0.89 to 0.86 for active learning, from 0.86 to 0.76 for collaboration, from 0.83 to 0.77 for learning diversity, and from 0.84 to 0.76 for high expectations.

2.4. Scenario Development and Procedure

The activity took place during the academic years of 2022–2023 and 2023–2024 at the experiential laboratory of the Faculty of Health Sciences in Alicante, Spain. It was conducted in subgroups of three to five students. Initially, a pre-briefing phase was held, where the clinical case to be developed in the simulated scenario was presented. Each group then participated in three scenarios: (1) a person with airway obstruction due to a foreign body; (2) a pregnant woman with imminent childbirth; (3) a person with altered consciousness; and (4) a person with PCR (Table 1). The scenarios each lasted between 10 and 15 min, followed by a final debriefing phase that lasted about 15 min. Depending on the scenario, either actors or high-fidelity manikins from brands such as CAE AresAR Medical Simulator, Resusci Family QCPR Laerdal, and PROMPT Flex Laerdal were used. Students were informed that the activity was not for assessment purposes but rather for knowledge integration and skill development to enhance learning. The development of each simulated clinical case was projected in video and audio into a nearby room where the simulated scenarios were conducted, allowing for discussion by the instructors, the participating students, and the rest of the students who were not involved at that time. The debriefing approach used was known as “debriefing with good judgment”, a method where personal opinions are openly shared, assuming the best contributions from students through a “brainstorming” process and understanding that mistakes are a source of learning [39]. After the students completed all the scenarios, they were invited to fill out a questionnaire using Google Forms. The questionnaire was administered via a link sent by email. To achieve a better response rate, a reminder was sent to participants who met the inclusion criteria at the first and second weeks.

2.5. Statistical Analysis

Statistical analysis of the data was performed using SPSS version 29.0.2.0 for Macintosh [40]. A descriptive analysis was conducted on the entire sample and by sex for all variables and instruments included. Continuous variables were presented as the mean (standard deviation), while categorical variables were described using frequencies and percentages. To explore sex differences, t-tests were conducted comparing male and female participants on the key variables included in this study. For those variables where significant differences were observed, effect sizes were calculated using Cohen’s d, providing an estimate of the magnitude of the differences between groups. Cohen’s d was interpreted according to conventional thresholds, with values of 0.2, 0.5, and 0.8 representing small, medium, and large effects, respectively [41]. A hierarchical regression was conducted to identify which group of variables was more strongly associated with the TMMS-24 subscale scores. Basic statistical assumptions were evaluated to ensure the validity of the hierarchical regression analysis. Residual normality was assessed using Q-Q plots and the Shapiro–Wilk test. Multicollinearity among predictors was examined by calculating the variance inflation factor (VIF), where values below 10 indicate absence of serious collinearity issues. Linearity and homoscedasticity were evaluated through scatterplots of standardized residuals versus predicted values, revealing no violations. The independence of the residuals was assessed using the Durbin–Watson statistic, considering an acceptable range of 1.5 to 2.5 [42]. Separate models were developed for each factor of the TMMS-24. Variables were entered into the regression equation in two blocks, ensuring the simultaneous inclusion of all variables within each block. The variables included were (1) factors from the SCQ and (2) factors from the EPQ. The level of statistical significance was set at p < 0.05.

2.6. Ethical Considerations

All participants in the study consented to participate voluntarily. The study received approval from the research ethics committee of the centre (registration number: UA-2023-02-21_1). Regarding data confidentiality, privacy and confidentiality were ensured in accordance with Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 [43].

3. Results

3.1. Overview of the Variables Included in the Study

The sociodemographic characteristics of the total sample and by sex are presented in Table 2. The study involved 77 participants, of whom 55.84% were male. The average age for the entire sample was 21.61 years (SD = 2.75). A total of 46.8% of participants had prior experience in first aid, while no participants had previous experience in simulated environments.
Table 3 presents the results for the TMMS-24, SCQ, and EPQ by total sample and sex. Regarding the TMMS-24 outcome variable, the mean scores for the total sample were 27.23 (SD = 5.56) for attention to emotions, 27.57 (SD = 5.23) for clarity of feeling, and 29.15 (SD = 4.36) for mood recovery. For the different stress-coping strategies assessed using the SCQ, the average scores were 14.12 (SD = 5.53) for social support seeking, 7.32 (SD = 3.83) for open emotional expression, 1.88 (SD = 4.12) for religion, 14.68 (SD = 4.00) for problem-solving focus, 14.77 (SD = 4.05) for avoidance, 7.24 (SD = 3.72) for negative self-focus, and 17.00 (SD = 3.97) for positive re-evaluation. Regarding the educational practices in simulation measured by the EPQ, the average scores for the total sample were 39.46 (SD = 7.21) for active learning, 9.16 (SD = 1.32) for collaboration, 8.64 (SD = 1.56) for diverse ways of learning, and 8.32 (SD = 1.64) for high expectations. The only statistically significant differences between males and females were found for attention to emotions (TMMS-24) and evitation (SCQ), with effect sizes of 0.49 and 0.31, respectively.

3.2. Hierarchical Regression Model of Factors from the TMMS-24

3.2.1. Attention to Emotions

Q-Q plots and the Shapiro–Wilk test confirmed a normal distribution. Multicollinearity diagnostics indicated that all predictors had VIF values ranging from 1.66 to 3.02. Linearity and homoscedasticity were examined through scatterplots of standardized residuals against predicted values, revealing no violations. The Durbin–Watson statistic was 2.02. The best hierarchical regression model that significantly explained the attention to emotions factor from the TMMS-24 was model 2, [F(2.47), ΔR2 = 0.11, p = 0.05]. This model accounted for 28% of the variance. The variable that significantly contributed to attention to emotions was active learning. The positive association with the active learning factor of the EPQ suggests that greater active learning was linked to higher EI (β = 0.47, p = 0.01).

3.2.2. Clarity of Feeling

Q-Q plots and the Shapiro–Wilk test confirmed a normal distribution. Multicollinearity diagnostics indicated that all predictors had VIF values ranging from 1.45 to 3.02, indicating no severe multicollinearity issues. Linearity and homoscedasticity were examined through scatterplots of standardized residuals against predicted values, revealing no violations. The Durbin–Watson statistic was 1.48. The best hierarchical regression model that significantly explained the clarity of feeling factor from the TMMS-24 was model 1, [F(6.78), p < 0.01]. This model accounted for 40% of the variance. The variable that significantly contributed to clarity of feeling was focused on solving the problem. The positive association with the problem-solving focus factor of the SCQ suggests that a problem-solving style of coping with stress was linked to higher EI (β = 0.39, p < 0.01).

3.2.3. Recovery of Mood

Q-Q plots and the Shapiro–Wilk test confirmed a normal distribution. Multicollinearity diagnostics indicated that all predictors had VIF values ranging from 1.39 to 3.16. Linearity and homoscedasticity were examined through scatterplots of standardized residuals against predicted values, revealing no violations. The Durbin–Watson statistic was 1.60. The best hierarchical regression model that significantly explained the recovery of mood factor from the TMMS-24 was model 1, [F(6.29), p < 0.01]. This model accounted for 39% of the variance. The variable that significantly contributed to the recovery of mood was positive re-evaluation. The positive association with the positive re-evaluation factor of the SCQ suggests that a positive appraisal of stressful situations was linked to higher EI (β = 0.54, p < 0.01) (Table 4).

4. Discussion

The primary objective of this study was to examine the potential relationship between the implementation of good educational practices in simulated environments, stress coping skills, and EI among students enrolled in the course “First Aid and Pathophysiology of Physical Activity and Sport” in the third year of a Bachelor’s Degree in Physical Education and Sport Sciences. The hypotheses propose that positive stress coping styles and good educational practices in these environments would be positively associated with higher levels of EI. While numerous higher education institutions in fields such as technology, mathematics, and engineering [20]; health sciences [22]; and education [21] have implemented training programmes based on simulated environments, this is the first study to examine the relationship between EI, stress coping skills, and good educational practices within the context of a newly developed programme based on simulated environments for undergraduate students in Physical Activity and Sports Sciences.
Firstly, our findings indicate that the only statistically significant sex differences occurred in attention to emotions and evitation, with moderate effect sizes. This aligns with previous research reporting nuanced gender differences in EI and stress coping. Females generally score higher on emotional awareness and attentiveness to feelings, reflecting greater emotional expressiveness and sensitivity. Regarding coping strategies, the findings are mixed—some studies show that women are more likely to engage in avoidance or emotion-focused coping, while men tend to use more problem-focused coping. These sex differences are influenced by a complex interplay of biological, social, and cultural factors that shape emotional development and regulation [44,45,46,47].
Secondly, our findings indicate that active learning is positively associated with higher levels of EI. Our results are consistent with those found in other contexts, particularly within the realm of health sciences [48,49]. There are studies suggesting that it is feasible to enhance EI through educational interventions in students, especially concerning the understanding and management of emotions, which are considered strategic elements of EI according to Mayer et al. [11]. In this regard, through educational interventions based on simulated environments, students can actively learn by participating both in the execution of scenarios and in subsequent debriefing sessions, where emotions and observed performances are discussed [50]. On the one hand, according to Russell’s circumplex model of emotions [51], emotional involvement in simulated scenarios allows students to focus more on their own emotions and those of others, thus facilitating the development of EI. On the other hand, it is suggested that improving the emotional attention component of EI not only prepares students to face and resolve future critical situations but also directly influences graduates’ employability, particularly due to its association with potential future leadership roles [52,53]. In this sense, there is scientific evidence suggesting that fostering the emotional attention component is strongly related to academic performance as it appears to be the essential element linking emotional intelligence to problem-focused coping skills, which in turn are associated with higher academic achievement and success [54], greater life satisfaction [55], and consequently better job performance [53,55].
Thirdly, our findings indicate that a positive stress coping style, focused on problem-solving where individuals analyze the causes and plan solutions to address the situation in simulated learning environments, is positively associated with higher levels of emotional clarity. These results are akin to those found in other studies conducted with primary education students [56]; undergraduates in fields such as arts, business, and law, albeit not specifically in simulated environments [57,58]; and nursing students in simulated palliative care scenarios [12]. In this regard, simulated environments can enhance students’ positive coping strategies towards various stressful situations by providing a safe and controlled environment to address such scenarios, thereby acquiring the ability to resolve them [59]. Repeated exposure to stressful situations in these environments allows students, during debriefing sessions, to analyze the causes of stress, plan solutions, and effectively regulate their emotions through feedback and reflection [7,39]. This contributes to the development of resilience [60], strengthening the ability to manage stress in real-life situations [57,60,61].
Fourthly, our findings indicate that the positive reappraisal coping style, where the individual acknowledges the stressful event but focuses on its positive aspects, is positively associated with higher levels of EI in simulated environments. This finding aligns with previous research, such as that of Khorasani et al. [62], although their focus is not specifically on simulated environments. In this regard, on the one hand, a positive reappraisal coping style is associated with less distress after negative events [63], potentially influencing students in various ways, leading them to believe that adversity has provided them with opportunities to gain knowledge, wisdom, and patience [64], as well as to acquire valuable life skills [65], appreciate the value of life, find a new sense of purpose, and strengthen social relationships [66]. On the other hand, the literature also suggests that positive reappraisal-based coping strategies are positively related to academic success among nursing students [67].
Fifthly, among the eleven correlations examined, only three reached statistical significance. Although these partial findings provide valuable insights into the ways in which simulation-based environments may influence EI and stress coping strategies, it is important to emphasize that most of the hypothesized associations were not confirmed. This outcome suggests that the impact of simulation on EI and coping may be more nuanced and context-dependent than initially assumed, consistent with the broader literature highlighting the complexity of these interrelationships. Several factors may explain the non-significant results, including sample size limitations, the sensitivity of measurement instruments, or uncontrolled individual differences—such as intrinsic motivation, self-efficacy, or prior exposure to similar educational contexts. Recent studies also emphasize that while simulation can indeed foster EI, outcomes largely depend on the quality of instructional design, the clarity and depth of feedback provided, and the active engagement of learners [68].

4.1. Implications for Practice

The integration of simulated environments into first aid training programmes within first aid courses represents a transformative educational approach within the field of Physical Activity and Sports Sciences, with significant implications for educational practice. By incorporating programmes that focus on developing problem-solving skills related to critical health situations in simulated environments into the curriculum, educational institutions can create immersive learning experiences that equip students with practical skills while fostering their emotional and cognitive development. This paradigm shift in educational practices represents an innovative approach to curriculum enhancement, aligning educational methods with those proposed in the Bologna Declaration [1]. The findings of this study highlight the role of simulated environments as a teaching and learning tool capable of developing EI among students. EI is crucial for professionals working in environments where quick decision-making and effective stress management are essential [69]. Teachers and educators can leverage simulated scenarios to encourage students to adopt constructive approaches to stressful situations, thereby enhancing their ability to handle adversity in real-world contexts.

4.2. Limitations and Future Directions

In this study, some limitations need to be noted. A significant limitation of this study lies in the sample size and its representativeness. The use of a relatively small sample may restrict the generalization of findings to broader populations. Specifically, in this study, 11 predictors were examined with a sample of 77 participants, resulting in a ratio of approximately 7 participants per predictor. This falls short of the commonly recommended minimum of 10 to 15 participants per predictor, which may lead to unstable estimates, increased risk of overfitting, and limited generalizability of the results [70]. Moreover, the results were obtained based on self-report tools, which may lead to possible social desirability bias in the results. Furthermore, causal relationships could not be identified because this was a relational study. Also, factors not considered in the study may have an impact on the findings. Future studies should aim to include larger samples with a higher participant-to-predictor ratio to improve the stability and generalizability of estimates and incorporate longitudinal or experimental designs to better explore causal mechanisms.

5. Conclusions

The results partially confirm our hypotheses that positive stress coping strategies and good educational practices developed within simulated environments are positively associated with higher levels of EI. Specifically, adaptive coping strategies related to reflection and positive problem-solving, assessed through the SCQ, showed positive links to EI components such as clarity of feeling and mood recovery. Additionally, the active learning dimension from the EPQ was positively associated with attention to emotions, underscoring the importance of good educational practices in enhancing EI. These findings highlight the potential of simulation-based training to advance educational methods and foster emotional skills development in the field of sports sciences.

Author Contributions

N.M.-P. made substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data; N.M.-P., C.R.-R. and J.P.-G. involved in drafting the manuscript or revising it critically for important intellectual content; N.M.-P., R.M.-L., C.R.-R. and J.P.-G. given final approval of the version to be published. Each author should have participated sufficiently in the work to take public responsibility for appropriate portions of the content; N.M.-P., R.M.-L., C.R.-R. and J.P.-G. agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors have read and agreed to the published version of the manuscript.

Funding

The authors declare the funding of the following research by the REDES-XARXES INNOVAESTIC programme, University of Alicante.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Scenarios and interventions in simulated environments.
Table 1. Scenarios and interventions in simulated environments.
Scenario 1: Obstruction of the Airway by a Foreign BodyScenario 2: Emergency ChildbirthScenario 3: Consciousness AlterationsScenario 4: Cardiorespiratory Pulmonary Arrest (CPA)
-
Problem detection.
-
PAR protocol.
-
Encourage coughing in case of incomplete obstruction.
-
Heimlich maneuver in case of complete obstruction.
-
CPR in case of Heimlich failure.
-
Problem detection.
-
PAR protocol.
-
Calming the mother.
-
Correct extraction of the fetus.
-
First care of the newborn.
-
Newborn resuscitation if needed.
-
Problem detection.
-
PAR protocol.
-
Neurological assessment.
-
First responder intervention appropriate to the problem.
-
CPR in case of cardiac arrest.
-
Problem detection.
-
PAR protocol.
-
Correct X-ABCD evaluation.
-
Assessment of breathing effectiveness, compressions, and use of semi-automatic defibrillator.
Notes. PAR: Protect, Alert, and Rescue protocol; CPR: Cardio-Pulmonary Reanimation.
Table 2. Sociodemographic data of the sample.
Table 2. Sociodemographic data of the sample.
VariablesTotal
(n = 77)		Male
(n = 43)		Female
(n = 34)
Age in years M ± SD21.61 ± 2.75 *21.51 ± 1.75 *21.73 ± 3.68 *
Previous first aid experience n (%)Yes36 (46.8)23 (53.5)13 (38.2)
No41 (53.2)20 (46.5)21 (61.8)
Prior experience in high-fidelity simulation n (%)Yes0 (0)0 (0)0 (0)
No77 (100)43 (100)34 (100)
Note. (*) Mean ± Standard Deviation.
Table 3. Results obtained using the TMMS-24, CAE, and EPQ.
Table 3. Results obtained using the TMMS-24, CAE, and EPQ.
VariablesTotal
(n = 77)
M ± SD		Males
(n = 43)
M ± SD		Females
(n = 34)
M ± SD		Contrasting Statistics Between Males and Females
TMMS-24Attention to emotions27.23 ± 5.5626.06 ± 5.2428.70 ± 5.68t = −2.11, p = 0.02
Clarity of feeling27.57 ± 5.2328.13 ± 4.9126.85 ± 5.60t = −1.07, p = 0.15
Recovery of mood29.15 ± 4.3629.34 ± 4.5028.91 ± 4.23t = 0.43, p = 0.33
SCQSocial support seeking14.12 ± 5.5313.79 ± 5.0614.55 ± 6.12t = −1.02, p = 0.15
Open emotional expression7.32 ± 3.836.65 ± 4.138.17 ± 3.28t = −1.07, p = 0.16
Religion1.88 ± 4.121.72 ± 3.692.08 ± 4.66t = −1.17, p = 0.12
Focused on solving the problem14.68 ± 4.0015.46 ± 3.6213.70 ± 4.30t = −0.76, p = 0.22
Evitation14.77 ± 4.0513.91 ± 4.2115.88 ± 3.59t = −1.82, p = 0.04
Negative self-focus7.24 ± 3.726.72 ± 3.817.91 ± 3.55t = −0.59, p = 0.27
Positive re-evaluation17.00 ± 3.9716.79 ± 4.0217.26 ± 3.94t = −0.15, p = 0.44
EPQActive learning 39.46 ± 7.2138.90 ± 6.8640.17 ± 7.67t = −0.76, p = 0.22
Collaboration 9.16 ± 1.329.02 ± 1.359.35 ± 1.25t = −1.09, p = 0.13
Different ways of learning 8.64 ± 1.568.46 ± 1.488.88 ± 1.64t = −1.16, p = 0.12
Expectation 8.32 ± 1.678.32 ± 1.648.32 ± 1.73t = −0.01, p = 0.50
Notes. EPQ: Educational Practices Questionnaire; p: p-value; SCQ: Coping with Stress Questionnaire; t: Student’s t-test; TMMS-24: Trait-Mood Scale 24.
Table 4. Hierarchical regression model of TMMS-24 factors.
Table 4. Hierarchical regression model of TMMS-24 factors.
BlockVariableSt βtp95% CIΔR2FpR2
1Attention to emotions factor TMSS-24-1.950.750.16
Social support seeking−0.08−0.660.51−0.33 to 0.17
Open emotional expression0.191.580.12−0.07 to 0.63
Religion−0.18−1.510.13−0.56 to 0.08
Focused on solving the problem0.090.680.50−0.23 to 0.50
Evitation0.040.350.73−0.28 to 0.40
Negative self-focus0.120.930.36−0.20 to 0.55
Positive re-evaluation0.282.210.030.04 to 0.75
2 0.112.470.050.28
Social support seeking−0.11−0.860.40−0.36 to 0.14
Open emotional expression0.171.450.15−0.09 to 0.60
Religion−0.16−1.330.19−0.54 to 0.11
Focused on solving the problem0.030.230.82−0.31 to 0.39
Evitation0.080.670.51−0.22 to 0.45
Negative self-focus0.080.660.52−0.24 to 0.48
Positive re-evaluation0.161.210.23−0.14 to 0.58
Active learning0.472.560.010.08 to 0.64
Collaboration−0.20−1.140.26−2.30 to 0.63
Different ways of learning0.100.540.59−0.96 to 1.67
Expectation−0.11−0.640.52−1.55 to 0.80
1Clarity of feeling factor TMSS-24-6.780.000.40
Social support seeking0.181.170.09−0.03 to 0.37
Open emotional expression0.111.080.28−0.13 to 0.43
Religion−0.14−1.400.16−0.43 to 0.08
Focused on solving the problem0.393.710.000.24 to 0.80
Evitation−0.22−2.050.05−0.55 to −0.01
Negative self-focus−0.11−1.010.32−0.45 to 0.15
Positive re-evaluation0.111.010.32−0.14 to 0.42
2 0.051.370.250.36
Social support seeking0.201.880.06−0.01 to 0.40
Open emotional expression0.070.720.48−0.18 to 0.38
Religion−0.14−1.320.19−0.44 to 0.09
Focused on solving the problem0.363.260.000.18 to 0.75
Evitation−0.17−1.610.11−0.50 to 0.05
Negative self-focus−0.13−1.210.23−0.46 to 0.12
Positive re-evaluation0.070.590.55−0.21 to 0.38
Active learning0.372.320.020.04 to 0.50
Collaboration−0.05−0.360.72−1.41 to 0.97
Different ways of learning−0.16−0.990.32−1.61 to 0.54
Expectation−0.13−0.820.41−1.35 to 0.56
1Recovery of mood factor TMSS-24-6.290.000.39
Social support seeking0.100.950.35−0.88 to 0.25
Open emotional expression0.141.360.18−0.07 to 0.39
Religion−0.17−1.640.11−0.39 to 0.04
Focused on solving the problem−0.070.600.55−0.31 to 0.16
Evitation0.070.660.52−0.15 to 0.31
Negative self-focus0.000.000.99−0.25 to 0.25
Positive re-evaluation0.544.980.000.35 to 0.83
2 0.010.140.960.40
Social support seeking0.110.990.32−0.09 to 0.27
Open emotional expression0.141.270.21−0.09 to 0.40
Religion−0.19−1.730.09−0.43 to 0.03
Focused on solving the problem−0.050.440.66−0.31 to 0.20
Evitation0.080.680.50−0.16 to 0.32
Negative self-focus0.000.020.98−0.26 to 0.26
Positive re-evaluation0.564.760.000.36 to 0.88
Active learning−0.05−0.310.76−0.23 to 0.17
Collaboration−0.04−0.230.82−1.16 to 0.93
Different ways of learning0.040.230.82−0.83 to 1.05
Expectation−0.04−0.250.80−0.95 to 0.74
Note. TMMS-24: Trait Mood Scale 24.
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Montoro-Pérez, N.; Montejano-Lozoya, R.; Rocamora-Rodríguez, C.; Perpiñá-Galvañ, J. Simulation-Based Educational Practices and Their Relationship with Emotional Intelligence and Stress Coping Skills: An Exploratory Case Study in First Aid Training for Physical Activity and Sports Sciences Students. Trends High. Educ. 2025, 4, 50. https://doi.org/10.3390/higheredu4030050

AMA Style

Montoro-Pérez N, Montejano-Lozoya R, Rocamora-Rodríguez C, Perpiñá-Galvañ J. Simulation-Based Educational Practices and Their Relationship with Emotional Intelligence and Stress Coping Skills: An Exploratory Case Study in First Aid Training for Physical Activity and Sports Sciences Students. Trends in Higher Education. 2025; 4(3):50. https://doi.org/10.3390/higheredu4030050

Chicago/Turabian Style

Montoro-Pérez, Néstor, Raimunda Montejano-Lozoya, Carmen Rocamora-Rodríguez, and Juana Perpiñá-Galvañ. 2025. "Simulation-Based Educational Practices and Their Relationship with Emotional Intelligence and Stress Coping Skills: An Exploratory Case Study in First Aid Training for Physical Activity and Sports Sciences Students" Trends in Higher Education 4, no. 3: 50. https://doi.org/10.3390/higheredu4030050

APA Style

Montoro-Pérez, N., Montejano-Lozoya, R., Rocamora-Rodríguez, C., & Perpiñá-Galvañ, J. (2025). Simulation-Based Educational Practices and Their Relationship with Emotional Intelligence and Stress Coping Skills: An Exploratory Case Study in First Aid Training for Physical Activity and Sports Sciences Students. Trends in Higher Education, 4(3), 50. https://doi.org/10.3390/higheredu4030050

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