Comparison of high-fidelity simulation combined with moulage and model-based visual teaching methods on the development of nursing students’ oral assessment skills
- Open Access
- 11.02.2026
- Research
Erschienen in:
Abstract
Introduction
Oral diseases are among the most prevalent non-communicable diseases on a global scale [1]. Poor oral health has been demonstrated to be a risk factor for systemic diseases, with a statistically significant effect on morbidity and mortality [2, 3]. Many studies have documented a correlation between poor oral health and numerous chronic conditions, including but not limited to diabetes, heart disease, stroke, kidney disease and chronic obstructive pulmonary disease [4‐6]. Consequently, it is imperative to provide oral care to patients to maintain oral health and prevent oral diseases or oral health-related conditions [7‐9].
Maintaining oral hygiene is a fundamental aspect of maintaining good health, with a proven efficacy in reducing the incidence of infections and the complications that can arise from them [10]. In cases where individuals experience a deviation from optimal health, their ability to meet oral care needs may be influenced by their level of dependence. In such instances, the responsibility for oral care typically falls upon nurses. This underscores the critical importance of nurses in safeguarding the integrity of the oral mucous membrane and maintaining oral health. Nurses must implement effective and appropriate oral care practices, which necessitate a comprehensive evaluation of patients’ conditions and a consideration of the risk factors associated with poor oral health.
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The provision of oral care is a complex and multifaceted process. Firstly, as Winning et al. [11] note, the evaluation of the oral mucosa and oral structures is of paramount importance. The employment of protocols and evidence-based practices, which have been developed for the purpose of oral care, in conjunction with the knowledge and experience of nurses in this field, has been demonstrated to increase the effectiveness of oral care [12, 13].
Basic knowledge and skills for oral care are taught to students in nursing education. In the first year of nursing education at our institution, students commence the acquisition of competencies essential for the preservation and maintenance of oral health. The development of students’ oral care competences is facilitated by the integration of theoretical knowledge acquired in course modules with practical skills in laboratory and clinical settings. The onus falls on nurse educators to establish an optimal learning environment and to employ efficacious learning methodologies to furnish students with the requisite knowledge and skills. Simulation is one such effective teaching method, and its application in nursing education is increasing in our country. In recent years, virtual fidelity applications have become an innovative extension of simulation-based learning. These applications are computer-based, interactive environments that replicate clinical scenarios with varying levels of realism, allowing learners to engage in clinical decision-making and problem-solving without direct patient contact [14, 15].
Simulation fidelity refers to the degree to which a simulation replicates real-life clinical scenarios along a continuum from low to high. Low-fidelity simulations typically involve basic task trainers or static models, while high-fidelity simulation involves advanced, interactive simulators that offer realistic physiological responses and immersive environments tailored to specific learning objectives [14, 15]. High-fidelity simulation is theorized to be effective because it more closely approximates real clinical practice, thereby enhancing contextual learning, decision-making, and the application of knowledge in complex situations [16].
Simulation-based education is grounded in experiential learning theory, which posits that learners acquire knowledge and skills most effectively through active engagement, reflection, and application in realistic contexts [17]. In this context, fidelity refers to the degree to which a simulation replicates real-life clinical scenarios. High-fidelity simulation involves advanced, interactive simulators that provide realistic physiological responses and immersive environments, while low-fidelity simulation refers to simpler models or task trainers that allow repetitive skill practice without extensive realism [18]. Moulage, as a component of high-fidelity simulation, enhances realism by visually and sometimes tactically replicating clinical conditions, thereby fostering student engagement and improving cognitive and psychomotor outcomes [14, 19]. Realism in simulation is critical, as it influences learner immersion, motivation, and the transfer of skills to real patient care [20].
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In nursing education, ensuring the effective integration of theoretical knowledge and clinical skills remains a persistent challenge. As healthcare environments become increasingly complex, it is essential to employ educational strategies that enhance students’ competence and confidence before they engage in real patient care. The fidelity continuum describes the range from low- to high-fidelity simulations, highlighting how different levels of realism support specific learning objectives and skill acquisition [21]. By aligning simulation fidelity with educational goals, educators can optimize learning experiences and outcomes.
The World Health Organisation (WHO), the National League for Nursing (NLN) and the National Council of State Boards of Nursing (NCSBN) have all recommended the use of simulation in the education and skill learning of student nurses [22, 23]. Simulation-based education enables students to practice safely, develop decision-making abilities, and integrate theoretical knowledge with practical skills in a controlled, reflective learning environment.
Moulage, as a component of high-fidelity simulation, plays a distinctive role in nursing education by enhancing the realism of clinical scenarios and fostering multisensory engagement among students. By providing visual, tactile, and sometimes olfactory cues, moulage increases learner motivation, active participation, and immersion in the simulated clinical environment [18, 24]. In nursing education, the integration of moulage with high-fidelity simulations has been shown to improve cognitive, psychomotor, and affective learning outcomes, while also enhancing students’ confidence and preparedness for real patient care [14, 17, 19]. Consequently, incorporating moulage into simulation-based learning provides a more authentic, effective, and engaging educational experience that bridges the gap between theory and practice.
The use of simulation methodologies enables nursing students to cultivate competencies in the domains of care, decision-making, evaluation, skill development, and management to practice safely without risk to patients [15]. A substantial body of research has indicated that the incorporation of high-fidelity simulations within nursing education has a favourable impact on the development of students’ knowledge, skills, and attitudes []. It is therefore hypothesized that integrating high-fidelity simulation, including virtual fidelity applications and multisensory elements like moulage, will enhance nursing students’ knowledge, skills, engagement, and confidence more effectively than traditional low-fidelity approaches [14‐16]. High-fidelity simulators are technologically advanced simulation tools designed to replicate realistic clinical scenarios and patient responses [27]. Among these high-fidelity simulation techniques, moulage plays a distinctive role by enhancing the realism of learning environments through the visual replication of clinical conditions such as wounds or lesions [25]. By creating lifelike scenarios, moulage promotes active engagement, strengthens clinical judgment, and contributes to the retention and transfer of psychomotor and cognitive skills [25, 27]. This realistic and immersive experience bridges the gap between theory and practice, fostering experiential learning and improving students’ preparedness for real clinical situations [26]. A growing body of research is focusing on the effectiveness of simulation applications in the acquisition of clinical skills, with evidence showing that high-fidelity simulation significantly increases knowledge acquisition, self-confidence, and skills performance in nursing education [26]. However, a paucity of research has been found that evaluates the effectiveness of high-fidelity simulation applications for oral assessment skills. It is hypothesised that the integration of simulation methodologies within oral care education can enhance students’ knowledge, skills, and attitudes regarding oral health, while concomitantly increasing their motivation to learn, akin to the acquisition of other skills. This study therefore fills an important gap by directly comparing the use of moulage and visual support in simulation-based learning for oral assessment. To our knowledge, no previous research has examined these two modalities within this specific educational context. The findings are expected to provide practical guidance for educators in selecting effective simulation tools to enhance psychomotor and observational skills in nursing students.
Patients have the right to receive the highest quality of care, and nurses have an obligation to provide competent and safe care to the individuals for whom they are responsible. Consequently, nurse educators must ensure that they are adequately prepared to impart the principles of nursing care to students in an optimal manner [28]. The education of students in the practice of oral care is an integral component of this educational mandate. It is evident that the competence in the knowledge and skills of nurses responsible for the provision of correct and effective oral care can be achieved by gaining competence in their knowledge and skills from the time they are students in vocational education [29, 30].
Oral care is a fundamental component of nursing practice and falls directly within the professional responsibilities of nurses. As the prevalence of conditions affecting oral health continues to increase in society—particularly among older adults, critically ill patients, and individuals with chronic diseases—nurses play a pivotal role in the early assessment and ongoing management of oral health problems [30, 31). Today’s nursing students, as the nurses of the future, will be at the forefront of delivering safe, effective, and evidence-based oral care in diverse clinical settings [31]. Therefore, ensuring that students acquire strong oral assessment knowledge and skills during their education is essential for improving patient outcomes and quality of care [30, 31].
The objective of this study was to compare the effects of high fidelity simulation combined with moulage and low fidelity simulation supported by visuals on nursing students’ oral assessment knowledge, skill levels, satisfaction and self-confidence.
Hypotheses
H1
There is a statistically significant difference in post-training knowledge scores between students who received oral assessment training using a low-fidelity simulator and students who received training using a high-fidelity simulation combined with moulage.
H2
There is a statistically significant difference in the skill scores of students who received oral assessment training using a low-fidelity simulator and students who received training using a high-fidelity simulation combined with moulage.
H3
There is a statistically significant difference Students’ Satisfaction and Self-Confidence Scale scores between students who received oral assessment training using a low-fidelity simulator and students who received training using a high-fidelity simulation combined with moulage.
H4
There is a statistically significant difference in Simulation Design Scale scores between students who received oral assessment training using a low-fidelity simulator and students who received training using a high-fidelity simulation combined with moulage.
Methods
Design and participants
This study was conducted as a quasi-experimental study between February 2023 and June 2024. The simulation-based experiences were designed according to the Healthcare Simulation Standards of Best Practice [32]. Scenarios were created using the simulation design template, and content validity was established through consultation with simulation experts in the field of nursing education. The study population comprised first-year nursing students in a nursing faculty in Turkey. The study population comprised students enrolled in the Fundamentals of Nursing course during the spring 2023–2024 academic year. The sample size was determined using G*Power software, with an effect size of 0.25, α = 0.05, and a power (1 − β) of 0.95, indicating a required total sample size of 104 participants. Participants who met the inclusion criteria were enrolled and assigned to the intervention and control groups. Participant retention and attrition were monitored throughout the study period. Participants were randomly assigned to either the intervention or control group using a computer-generated simple randomisation sequence created in Randomizer.org. Allocation concealment was ensured by using sealed opaque envelopes. Volunteer students were included in the study, while students who had previously received any training related to simulation, or those repeating their courses (repeating the class) and students who transferred vertically were excluded from the study.
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In this study, the first author delivered the theoretical training sessions. The second author conducted the oral assessment of patients in the clinical setting without knowing the participants’ group allocations, thereby maintaining assessor blinding. The third author was responsible for organising the simulation (moulage) sessions together with the first author, but did not participate in the teaching or assessment phases. These role separations were intentionally designed to minimize potential bias and ensure the objectivity of both the educational process and the outcome evaluations.
Instruments
Data collection form of students
This form was developed by the researchers to include five items capturing students’ demographic and educational characteristics, such as gender, place of residence, type of high school attended, voluntary choice of the nursing program, and age (see Table 1). In Turkey, high schools are classified into different categories based on their educational focus. Accordingly, an analysis was conducted to examine whether the type of high school attended had an impact on students’ skill acquisition. This evaluation aimed to identify potential differences in baseline competencies that could influence learning outcomes in the simulation-based training.
A knowledge test on oral assessment
The oral assessment knowledge test was developed by researchers based on the extant literature [7, 33]. We developed the content of the knowledge test by reviewing studies in the literature focusing on oral care practices in patients on mechanical ventilation support and the prevention of ventilator-associated pneumonia. We also utilized current international guidelines on this subject. The oral assessment knowledge test consists of 16 multiple-choice questions divided into three sections: seven questions on the etiology of oral mucosa, four questions on oral assessment, and five questions on oral care methods. (Supplementary File, Appendix A). Scores within this system range from 0 to 100, with 100 representing the highest level of knowledge. Although it is generally recommended that content validity assessments involve five or more experts, previous methodological studies have reported that evaluations conducted with a minimum of three experts may also be acceptable [19, 34]. In line with these recommendations, the expert panel in the present study consisted of four experts. The evaluation of the test was conducted by four experts in this field. Two of the participants were intensive care nurses, and the remaining two were faculty members. In evaluating the knowledge test, experts were selected based on predefined criteria, including a minimum of five years of combined clinical and academic experience in intensive care nursing and demonstrated competence in the assessment of intensive care patients. Two of the experts were certified nurses actively working in intensive care units, while the remaining two were academics with relevant publications and teaching experience in intensive care nursing. All experts were independent of the research team and were not involved in the study design, data collection, or data analysis. They were informed about the overall purpose of the study but were blinded to group allocation and study outcomes to ensure an objective and independent evaluation. The suitability and content validity of the written materials, including the oral care practice guide, were evaluated using the DISCERN (Quality Criteria for Consumer Health Information) instrument with input from four experts [35]. The experts were invited to rate the suitability of the items on a scale of 1 to 5. The lowest and highest scores allocated by the experts for the items, the item score mean, and the standard deviations were calculated. In order to evaluate the agreement among expert opinions for the items of the DISCERN scale, the data obtained from the four experts was analysed using the intraclass correlation coefficient method. The intraclass correlation coefficient (ICC) of the scale was found to be 0.88 (p: 0.000).
Performance checklist (for the researcher)
The researchers prepared this form by referring to the extant literature [7, 36]. The evaluation of the form was conducted by the same experts. The form consists of the stages of the oral assessment scale and contains eight items. The student’s performance was scored as follows: ‘correctly applied’ (3 points), ‘incorrectly applied’ (1 point), ‘not applied’ (0 points), and ‘incorrectly applied’ (0 points). The scale’s minimum and maximum scores are 0 and 24 points, respectively. “Skill points” refer to scores obtained from the performance checklist used to assess students’ oral assessment skills (Supplementary File, Appendix B).
Students’ Satisfaction and Self-Confidence Scale (SSSC)
The scale was originally developed by Jeffries and Rizzolo [37] and comprised 13 items. It was subsequently adapted into Turkish by Ünver et al. [38]., resulting in a version comprising 12 items. The scale in question is designed to assess the students’ self-confidence and satisfaction with their learning experience in a simulated environment. The total scale Cronbach alpha value was found to be 0.89 [38]. The scale is comprised of two sub-dimensions: ‘Satisfaction with current learning’ and ‘Self-confidence’. The ‘Satisfaction with current learning’ sub-scale consists of five items, while the ‘Self-confidence sub-scale consists of seven items. As the total score on the scale increases, it is hypothesised that students’ satisfaction with learning and self-confidence will increase [38]. In our study, the Cronbach alpha value for the total scale was 0.90.
Simulation design scale (SD)
The SD scale was developed by Jeffries and Rizzolo [37] and adapted into Turkish by Ünver et al. [38]. The scale comprises 20 items and five sub-dimensions: ‘goals and knowledge’, ‘support’, ‘problem solving’, ‘guided reflection or feedback’ and ‘loyalty’. The Cronbach alpha value for the total scale was found to be 0.90 [38]. The initial part of the scale, which is administered in two sections, comprises statements pertaining to the students’ perceptions regarding the application of optimal simulation design elements in the simulation. An increase in the total score obtained from the first part of the scale is indicative of the application of the best simulation design elements in the simulation [38]. In our study, the Cronbach alpha value for the total scale was 0.93.
Procedures
This study was conducted in two stages to compare the effects of high-fidelity simulation and low-fidelity simulation supported by moulage and visuals on nursing students’ oral assessment knowledge, skill levels, satisfaction, and self-confidence.
Preparation phase
The creation of materials to be utilised in the research process:
This encompasses the creation of data collection forms by the researcher, the development of course content for students, the formulation of scenarios, the preparation of moulage application and laboratory work plans.
During the creation of the theoretical course content on oral assessment, the targeted learning outcomes were first determined. These included explaining the pathophysiology of mouth sores, listing the factors involved in their etiology, understanding the scales used in risk assessment by defining oral injury risk assessment, and being able to record the evaluation of mouth sores. The course content was then developed in alignment with these learning outcomes, utilising the extant literature to inform the theoretical training titled ‘oral assessment’.
1. The creation of a scenario for use in a simulation for the intervention group
The scenarios to be used in the laboratory practice and evaluation of the intervention and control groups were created by the researchers in line with the literature. The scenario used in the simulation involved a 66-year-old male patient who had been hospitalised in the chest diseases clinic for two days due to shortness of breath and persistent coughing. The patient’s oral intake had decreased, and he was experiencing dryness and discomfort in the mouth. Within this scenario, participants were expected to perform a systematic oral assessment by applying the Oral Assessment Scale. They identified changes in the oral mucosa, such as dryness, redness, or ulceration, and recorded their findings on the assessment form. The scenario aimed to enable students to recognise the importance of oral assessment in clinical care and to develop their skills in identifying oral health problems in hospitalised patients. Prior to the implementation of laboratory applications for oral assessment, preliminary applications of simulation-based training and scenarios were conducted. Both simulation sessions were developed using the same scenario template, learning objectives, and assessment criteria to minimise potential confusion regarding simulation design. The moulage materials, environment, duration, and instructions were standardized across all groups. The facilitators followed a structured guideline to ensure consistent delivery of the simulation. Furthermore, the assessment checklist was validated and applied uniformly by the evaluators. These measures were taken to ensure that any differences in student performance reflected learning outcomes rather than variations in simulation design.
2. The creation of visuals for oral assessment
In the simulation applications created for the laboratory application and evaluation stages of the control group, photographs with oral ulcers were used for oral evaluation on models. Colour printouts of these images were obtained and adhered to the lips, palate, tongue, teeth and gums of the models using appropriate adhesives during the laboratory application and evaluation stages. The visuals consisted of photographs showing actual pathologies found in the literature, such as dryness, redness or ulceration of the oral mucosa.
3. Moulage application
In the planning stage, the moulage materials to be used in simulation applications were determined. In the subsequent preparation phase, a series of moulage applications were executed to accrue experience for the moulage application to be employed during the training sessions. The moulage application on the model for the intervention group was carried out by the researcher. For the laboratory application of the intervention group students, the moulage materials were applied to the lips, palate, tongue, teeth and gums of the models. In the subsequent evaluation phase, the application was repeated on the lips, palate, tongue, teeth and gums of the model. The created moulage can be palpated, irrigated and wound dressing applications can be made on it. All three researchers obtained certificates by participating in numerous simulation courses and received moulage training. The moulage application in the study was performed by the third researcher, who holds a doctoral degree in nursing. The researcher who performed the moulage application served as a visiting faculty member at the Simulation-Based Learning Center of the Faculty of Health Sciences at McMaster University in 2019. She received one year of specialized training in simulation and moulage at a simulation center in Canada. She has also participated in national and international simulation training projects to develop moulage scenarios and facilitate simulation sessions in undergraduate nursing education. In addition, she has published papers on simulation and moulage in peer-reviewed journals and contributed to book chapters on these topics.
The present study was conducted with students enrolled in the Nursing Principles course during the spring semester of the 2023–2024 academic year. In this context, all students in the intervention and control groups were administered a 2-hour theoretical course in the form of an oral presentation, question and answer session, and slide show. Subsequent to this, a demonstration application was performed, which lasted for a duration of one hour and was attended by all students.
Following a week, simulation applications were conducted in the simulation laboratory with three researchers. Prior to participating in the simulation application, students were required to complete two forms: the student identifying characteristics form, which was to be completed in the classroom, and the ‘Oral Assessment Scale’ form, which was to be used during the simulation application.
The simulation was initiated with a preliminary briefing, and each simulation application lasted between 10 and 15 minutes. The oral assessment of the students in the simulation applications was recorded on video. The students were divided into pairs and escorted to the simulation practice area. Immediately following each simulation, a debriefing session was conducted. The plus/delta approach was utilised for the debriefing session, as evidenced in the works of Lavoie et al. [39] and Fanning & Gaba [40]. This learning-centred approach provided students with the opportunity for self-assessment. The facilitator posed the following questions to the students: ‘What worked in the simulation?’ (plus) and ‘What could have been done better?’ (delta) [41, 42]. The debriefing sessions lasted for an average duration of 20–30 minutes. Following this, the students were asked to complete the ‘SSSC scale’ and ‘SD scale’.
The students in the intervention group performed an oral assessment of a hospitalized patient in a single scenario using a high-fidelity simulation and moulage application. Subsequent to the simulation, a debriefing session was conducted with the students, wherein the evaluations they had provided on the evaluation form were discussed, and feedback was provided. Following this, the Student Satisfaction and Self-confidence Scale and the Simulation Design Scale were administered. Two to four weeks after the simulation application, students were expected to perform an oral assessment in clinical practice with a real patient. The researcher then evaluated the oral assessment using an oral assessment skill checklist.
The students in the control group performed the simulation with a low-fidelity simulator and visuals for oral assessment. Subsequent to the simulation, a debriefing session was conducted with the students, wherein the evaluations they had provided on the evaluation form were discussed, and feedback was provided. Subsequently, the Student Satisfaction and Self-confidence Scale and the Simulation Design Scale were administered. Following the simulation, students were expected to perform oral assessments in clinical practice with actual patients within a 2–4 week period. The oral assessment was then evaluated by the researcher using an oral assessment skill checklist.
Following the conclusion of the clinical practice, an oral assessment knowledge test was administered to all students in both the intervention and control groups.
Ethical considerations
Ethics committee approval was obtained from the İzmir Bakırçay University Non-Interventional Clinical Research Ethics Committee (registration number 1440/1420, January 2024). Prior to the initiation of the study, approval was obtained from the nursing faculty where the study was conducted. The purpose and method of the study were explained to the students, and those who voluntarily agreed to participate were included. Written informed consent was obtained from all participants. During the study, the students were informed that pressure injury assessment practices in laboratory and clinical settings would not affect their ability to pass the course and that these scores would only be used as data. They were also informed that they could withdraw from the study at any time.
Data analysis
The analysis of the data was conducted utilising the Statistical Package for Social Sciences 25.00 software program (SPSS Inc., Chicago, IL). The significance level was set at 0.05 for all tests. Descriptive statistics were presented using arithmetic mean, standard deviation, minimum-maximum, frequency and percentage values. The results obtained were then compared using Mann-Whitney U test and Independent Sample-t test.
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Results
During the study, four students were excluded due to absenteeism. The final sample consisted of 100 students, with 48 in the intervention group and 52 in the control group.
The following flow chart illustrates the implementation of the research (Fig. 1).
Fig. 1
Research flow chart
Sociodemographic characteristics
Table 1
The following Table 1 details the distribution of personal characteristics of the control and intervention groups (n = 100)
Identifying Features | Control (n = 52) | Intervention (n = 48) | |||
|---|---|---|---|---|---|
n | % | n | % | ||
Gender | Female | 40 | 76,9 | 41 | 85,4 |
Male | 12 | 23,1 | 7 | 14,6 | |
Place of Residence | Metropolitan | 26 | 50,0 | 23 | 47,9 |
Province | 10 | 19,2 | 8 | 16,7 | |
District | 12 | 23,1 | 13 | 27,1 | |
Village | 4 | 7,7 | 4 | 8,3 | |
Graduated High School | Plain High School | 3 | 5,8 | 0 | 0 |
Anatolian High School | 38 | 73,1 | 36 | 75,0 | |
Health Vocational High School | 1 | 1,9 | 1 | 2,1 | |
Other | 10 | 19,2 | 11 | 22,9 | |
Voluntary choice of school | Yes | 29 | 55,8 | 29 | 60,4 |
No | 23 | 44,2 | 19 | 39,6 | |
Age | X ± SD (Min-Max) | 19,88 ± 1,52 (18,00–26,00) | 19,16 ± 1,11 (18,00–23,00) | ||
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The demographic composition of the two groups is significantly different, with 76.9% of the control group and 85.4% of the intervention group comprising females, while 23.1% and 14.6% of the respective groups were male. Furthermore, 50.0% of the participants in the control group and 47.9% of the participants in the intervention group reside in metropolises. Furthermore, a significant proportion of the participants in both groups graduated from Anatolian high school: 73.1% in the control group and 75.0% in the intervention group. Additionally, a higher percentage of the participants in the intervention group (60.4%) chose their school willingly compared to the control group (55.8%). The average age of the participants in the control group was 19.88 years (SD 1.52), and the average age of the participants in the intervention group was 19.16 years (SD 1.11).
Table 2
The following Table 2 presents a comparison of the mean values obtained in the post-intervention skill and knowledge tests, categorised according to the control and intervention groups
Control Group (n = 52) | Intervention Group (n = 48) | ||||
|---|---|---|---|---|---|
Mean ± SD | Median | Mean ± SD | Median | Test; p | |
Skill Scores | 12.40 ± 4.42 | 12.00 | 17.31 ± 3.54 | 17.00 | **6.094;0.001*** |
Knowledge test Score | 68.99 ± 13.78 | 68.75 | 81.90 ± 7.21 | 81.25 | *510.000;0.001*** |
A subsequent comparison of the post-intervention skill scores of the control and intervention groups revealed that the arithmetic mean of the former was 12.40 ± 4.42, with a median of 12.00, while the arithmetic mean of the latter was 17.31 ± 3.54, with a median of 17.00. The post-intervention skill scores of the intervention group were found to be significantly higher than those of the control group (p < 0.05).
A similar pattern was observed when the post-intervention knowledge test scores of the control and intervention groups were compared. In this case, the arithmetic mean of the control group was 68.99 ± 13.78, Median 68.75; the arithmetic mean of the intervention group was 81.90 ± 7.21, Median 81.25. The post-intervention test scores of the intervention group were found to be significantly higher than those of the control group (p < 0.05).
Table 3
Below compares the satisfaction and self-confidence scale scores and simulation design scale scores of students in the control and intervention groups (n = 100)
Control (n = 52) | Intervention (n = 48) | ||||||
|---|---|---|---|---|---|---|---|
Min.-Max. | Mean ± SD | Median | Min.-Max. | Mean ± SD | Median | MW-U; p | |
Student’ satisfaction and self-confidence scale | 1.67-5.00 | 3.82 ± 0.66 | 3.88 | 2.50-5.00 | 4.27 ± 0.51 | 4.42 | 692.500;0.000* |
Student satisfaction in learning | 1.20-5.00 | 3.85 ± 0.85 | 3.90 | 2.00–5.00 | 4.38 ± 0.56 | 4.50 | 744.000;0.000* |
Self-confidence in learning | 1.86-5.00 | 3.80 ± 0.66 | 3.86 | 2.86-5.00 | 4.20 ± 0.57 | 4.29 | 791.500;0.002* |
Simulation desing scale | 1.00-4.95 | 3.55 ± 0.95 | 3.71 | 2.39-5.00 | 4.18 ± 0.53 | 4.31 | 736.000;0.000* |
Objectives and information | 1.00–5.00 | 3.47 ± 1.06 | 3.40 | 2.80-5.00 | 4.18 ± 0.61 | 4.20 | 749.500;0.001* |
Support | 1.00–5.00 | 3.51 ± 1.03 | 3.75 | 1.75-5.00 | 3.91 ± 0.76 | 4.13 | 979.000;0.061 |
Problem solving | 1.00–5.00 | 3.55 ± 1.10 | 3.60 | 1.40-5.00 | 4.27 ± 0.72 | 4.40 | 741.500;0.000* |
Feedback/guided reflection | 1.00–5.00 | 3.48 ± 1.09 | 3.75 | 1.00–5.00 | 4.13 ± 0.71 | 4.25 | 792.500;0.002* |
Fidelity | 1.00–5.00 | 3.74 ± 1.15 | 4.00 | 3.00–5.00 | 4.42 ± 0.68 | 4.50 | 821.000;0.002* |
The mean scores of the intervention group on the Satisfaction and Self-Confidence Scale and its subscales were higher than the control group (p < 0.05). Furthermore, the mean scores of the intervention group on the Simulation Design Scale, as well as the subscales of Objectives and Information, Problem Solving, Feedback/guided reflection, and Fidelity, were higher than the control group (p < 0.05). However, a statistically insignificant difference was observed between the mean scores of the Support Subscale of the intervention and control groups (p > 0.05).
Discussion
This study evaluated the effects of integrating a high-fidelity simulation with moulage on nursing students’ oral assessment knowledge, skills, learning satisfaction, self-confidence, and perceptions of simulation design. The findings demonstrated that this simulation-based learning approach is effective in developing both cognitive and psychomotor skills and increases students’ satisfaction and confidence in performing oral examinations. These results add to the evidence supporting the use of high-fidelity simulations integrated with moulage as a valuable learning method in nursing education.
The effects of the simulation method oral assessment knowledge
In this study, the post-intervention knowledge test scores of the students in the intervention group were significantly higher than the control group (p < 0.05) (Table 2). This finding indicates the efficacy of utilising a high-fidelity simulation in conjunction with mulaj in enhancing the oral assessment knowledge of first-year nursing students. Consistent with the findings of this study, a study conducted with nursing students revealed that the utilisation of a virtual fidelity application significantly augmented the knowledge level of the intervention group concerning oral health care for geriatric patients, in comparison to the control group [43]. The findings of studies conducted with different nursing skills in the literature also demonstrate the efficacy of the high fidelity simulation method in enhancing students’ knowledge levels [44‐50]. The present study’s findings align with those of other research in the relevant literature [14, 51]. In this study, it was hypothesised that the integration of a high-fidelity simulation with moulage application could enhance the level of knowledge by providing students with a more authentic learning experience [19]. From a simulation theory perspective, these findings may be also explained by the reduced cognitive load and enhanced psychological fidelity associated with high-fidelity simulation environments [51]. The use of moulage likely minimized extraneous cognitive load by providing realistic visual and sensory cues, allowing students to allocate more cognitive resources to task-relevant learning processes rather than to imagining or compensating for missing clinical details [19]. In addition, the increased realism may have reduced the need for suspension of disbelief, thereby facilitating greater immersion, engagement, and emotional investment in the learning experience [52]. The observed differences between the two simulation approaches may relate to the degree of learner engagement. The more interactive simulation allowed students to actively participate in clinical decision-making and skill performance, which aligns with Kolb’s Experiential Learning Theory, emphasizing learning through active experience and reflection [52, 53]. In contrast, the more passive approach may have limited opportunities for experiential engagement, resulting in lower performance outcomes.
The effects of the simulation method oral assessment skills
In this study, the post-intervention skill scores of the students in the intervention group were significantly higher than the control group (p < 0.05) (Table 2). This finding indicates the efficacy of the moulage technique employed in high-fidelity simulations in enhancing the oral assessment skills of first-year nursing students. The findings of studies evaluating different nursing skills in the literature demonstrate that the high fidelity simulation method is more effective in improving students’ psychomotor skills [45, 49, 54, 55]. The present study’s findings align with those of other research in this field. The present study demonstrates that the integration of high-fidelity simulation with mulaj fosters a clinically authentic learning environment, thereby facilitating a multifaceted, sensory-rich oral assessment experience that engages vision, hearing, and touch. This observation lends credence to the hypothesis that this approach may contribute to the enhancement of students’ oral assessment competencies.
Although high-fidelity simulation has been shown to improve nursing students’ knowledge and psychomotor skills, previous studies have largely focused on general nursing procedures and have not addressed oral assessment, which requires careful visual inspection and interpretation of subtle clinical findings [54‐56]. Moulage has been used to enhance realism in simulation-based education, but its contribution to oral assessment skill development has been not studied, with most research focusing on other clinical skills [45, 48, 50]. Additionally, few studies have simultaneously evaluated cognitive, psychomotor, and affective outcomes within a single intervention, particularly among first-year nursing students [57, 58]. By presenting realistic oral wounds, moulage enabled students to systematically observe, accurately identify findings, and follow appropriate assessment steps, supporting skill acquisition [19, 32, 56]. This immersive and experiential learning process, consistent with simulation and experiential learning theories, may explain the higher oral assessment skill scores observed in the intervention group.
The effects of the simulation method on satisfaction with learning and selfconfidence
Student satisfaction and self-confidence are considered key indicators of effective simulation-based learning, as they are closely associated with learner motivation, engagement, and the transfer of acquired knowledge and skills to clinical practice [22, 32]. The International Nursing Association for Clinical Simulation and Learning (INACSL) standards emphasize that well-designed simulation experiences should promote learner satisfaction, self-confidence, and psychological safety in order to support meaningful learning and achievement of intended learning outcomes [44]. Higher levels of self-confidence have also been shown to positively influence clinical performance, decision-making ability, and readiness for real patient care [59].
In this study, students who practised oral assessment skills using a high-fidelity simulation combined with a moulage exhibited significantly higher levels of satisfaction and self-confidence compared to those who used a simulator with a low-fidelity mock-up supported by visuals (Table 3). These findings are consistent with those reported in the literature, where high levels of student satisfaction and self-confidence scale scores were observed in learning contexts [45, 49, 57, 58]. The incorporation of moulage in the learning process, by enhancing sensory realism through visual and olfactory cues, may have contributed to students’ heightened perceptions of realism during oral assessment practice, thereby increasing their satisfaction and self-confidence. In line with this interpretation, previous studies have demonstrated that high-fidelity simulation environments effectively enhance learning outcomes by fostering active participation, critical thinking, and clinical skill acquisition [14, 19]. The use of moulage may further strengthen these effects by increasing the perceived authenticity of the clinical scenario, which reduces the need for students to imagine missing clinical details. This increased realism supports immersion and reduces extraneous cognitive load, allowing learners to concentrate on performing the oral assessment task itself. As a result, students experience greater task mastery and perceived competence, which in turn may be contributes to higher levels of learning satisfaction and self-confidence.
Effects of simulation method on simulation design
In the present study, it was established that the mean simulation design scale scores of students who received training with moulage were higher than those of students who received training with oral wound visuals (Table 3). In studies comparing low- and high-fidelity simulations in terms of simulation design scale scores, high-fidelity scores were similarly found to be higher [48, 54, 60]. In a separate study, Wang et al. [58] utilised medium- and high-fidelity simulations and observed that students in the high-fidelity simulation group exhibited higher mean SD scale scores. These results are analogous to those of our own study. In the present study, the students who participated in the simulation performed with moulage demonstrated significantly higher simulation design scale scores, which were associated with the more realistic oral wounds. In light of these findings, simulation-based education in nursing should be designed to foster active learner engagement and support the integration of theoretical and practical knowledge. Simulations that enable students to actively perform oral assessment procedures and make clinical decisions appear to enhance knowledge acquisition more effectively than passive observation. Incorporating structured debriefing sessions encourages reflection on clinical reasoning and helps consolidate learning outcomes. Additionally, maintaining a realistic clinical environment increases the authenticity of the experience and facilitates the transfer of knowledge to real patient care. These design recommendations align with experiential learning theory, which emphasizes learning through active experience, reflection, and application in practice.
Limitations
This study has several limitations. First, it was conducted in a single center and included only first-year nursing students, which may limit the generalizability of the findings. In addition, students’ oral performance was evaluated only once in the laboratory setting and once during clinical practice with a real patient, and baseline measurements of oral assessment skills were not obtained, restricting the ability to determine the magnitude of improvement attributable to the intervention. Furthermore, the oral assessment and skill list forms were developed solely by the research team. Although these forms were based on standardized clinical guidelines, they were not subjected to a formal evaluation by an independent expert panel, and a Content Validity Index (CVI) was not calculated. This may have introduced potential bias regarding the content validity of the evaluation tools. Another limitation is the use of self-report scales to assess student satisfaction and self-confidence, which may be subject to response bias, including social desirability bias, as participants may have provided favorable responses based on perceived expectations rather than their actual experiences. Finally, despite efforts to standardize the simulation design and delivery, minor variations in facilitation, levels of student engagement, and prior exposure to simulation-based learning could not be fully controlled. Therefore, residual confounding related to simulation implementation may have influenced the study outcomes and should be considered when interpreting the results.
Conclusions
As a result of this study, it was determined that the high-fidelity simulation method combined with moulage was more effective than the low-fidelity simulation in developing nursing students’ oral assessment knowledge and skills. Students who received training with high-fidelity simulation had higher self-confidence and satisfaction levels and were more successful in the oral assessment they performed on a real patient for the first time. More studies are needed on the effects of different applications used in simulation-based training on the acquisition of different skills.
Acknowledgements
The author(s) would like to thank all nurse students who participated in this study.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. All participants were informed of the voluntary nature of their participation and the commitment to confidentiality and anonymity. Signed informed consent was obtained from all participants prior to the start of data collection; they were informed of the purpose of the study, the nature of their participation and their right to withdraw at any time. Approval was obtained from the İzmir Bakırçay University Non-Interventional Clinical Research Ethics Committee, Approval no: (1440/1420).
Informed consent
Written consent has been obtained from the participants.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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