Application Effects and Optimization Strategies of Multi-Scenario Simulation Teaching in Practical Instruction of Infectious Diseases

Summary

This randomized controlled trial evaluated multi-scenario simulation teaching in infectious disease education among 121 medical and nursing students. Compared with traditional teaching, simulation improved OSCE performance, compliance with critical actions, clinical reasoning, teamwork, and procedural safety. The approach effectively bridged theory and practice under biosafety constraints and enhanced training outcomes.

Abstract

This prospective randomized controlled trial evaluated the effectiveness of multi-scenario simulation teaching in improving practical competence among medical and nursing students during infectious disease training. A total of 121 students were randomly assigned to a simulation group (n = 60) or a traditional teaching group (n = 61). The simulation curriculum covered key clinical workflows, including triage, isolation, specimen collection, infection prevention, antimicrobial stewardship, and occupational exposure management. Primary outcomes were post-intervention Objective Structured Clinical Examination (OSCE) scores and critical action compliance rates. Secondary outcomes included clinical reasoning, teamwork and communication skills, learner satisfaction, self-efficacy, engagement, and cognitive load. Compared with the control group, the simulation group achieved significantly higher OSCE scores (mean difference 8.1; 95% CI, 5.4–10.9; Cohen's d = 1.14; P < 0.001) and critical action compliance rates (10.5% higher; 95% CI, 7.3–13.6; Cohen's d = 1.23; P < 0.001). The simulation group also demonstrated improved teamwork, greater satisfaction and self-efficacy, and lower cognitive load. These findings indicate that multi-scenario simulation teaching enhances practical competence, safety-critical performance, and learning experiences in infectious disease education.

Introduction

As a specialized branch of clinical medicine, the teaching process for infectious diseases has long been restricted by two factors: public health safety and medical quality^1,2. In current clinical teaching practice, the high pathogenicity of infectious diseases and strict biosafety regulations have naturally formed an obstacle that limits medical students' in-depth hands-on practice in front-line isolation wards to a large extent. With the continuous improvement of global infection control standards, the traditional bedside teaching model has become increasingly difficult to meet the requirements for observing students' clinical practice in respiratory infectious diseases or highly virulent infectious diseases safely; it is often impossible to complete a full observation process³. Moreover, the distribution of infectious disease cases shows clear seasonality, regional differences, and sudden outbreaks, making it difficult for students to encounter a wide range of infectious diseases during their short clinical internship. This shortage of case-exposure opportunities creates a significant gap between theoretical knowledge and practical clinical application for medical students, especially when dealing with new and sudden infectious diseases. The lack of necessary clinical exposure experience has become a bottleneck restricting the cultivation of public health professionals^4,5.

Traditional infectious disease education primarily uses theoretical lectures or single teaching aids, and the model lacks connections when training medical students to handle complex clinical situations. Firstly, there is a deficiency in training for process chains. Management of real infectious diseases covers the entire closed-loop process, including triage, isolation, specimen collection, epidemic reporting, precise treatment, and post-disease follow-up. However, traditional teaching has long centered on etiological diagnosis and failed to pay attention to the reporting procedures prescribed by laws and regulations or the operational details of infection control^6,7. Given the persistent clinical challenges surrounding hand hygiene, proper PPE usage, and safety-critical compliance, robust training that actively measures and reinforces these standard precautions is paramount for novice practitioners⁸. According to relevant assessment data, the procedural error rate of beginners who have not received systematic simulation training and the risk of occupational exposure in clinical operations under high-level protective measures are significantly higher. Secondly, there is a superficiality in the development of teamwork abilities. Treatment for infectious diseases is based on the cooperation of multiple medical disciplines, including doctors and nurses involved in clinical work, technical staff, and specialists from the department of infectious diseases at a hospital⁹. Under the conventional medical model, there is usually only a community doctor position, and interdisciplinary consultation relationships have not yet been formed. There is no unified curriculum across training stages, nor is there systematic instruction in emergency infectious disease management. During an actual epidemic, trainees often exhibit a low degree of adaptability and a lack of awareness regarding infection prevention^10,11.

In response to deficiencies in traditional clinical teaching, multi-scenario simulation has emerged as a high-fidelity, low-risk educational approach and is now an essential direction for medical education reform. This approach constructs a tiered curriculum system for the key links of initial outpatient screening, ICU isolation, and emergency management of occupational exposure, thereby enhancing medical students' comprehensive clinical problem-solving abilities¹¹. In addition to assessing memory of the basic theories, several other aspects to be considered in this evaluation criterion include enhanced clinical critical thinking skills, adherence to standardized infection prevention and control requirements, and mental adjustment capacity under high-intensity working conditions. Indeed, prior evidence confirms that high-fidelity simulation fundamentally elevates higher-order practical competencies, notably enhancing clinical judgment and complex decision-making far beyond mere knowledge recall^12,13. Research shows that, through multi-scenario coupled teaching design, students' decision-making time in the face of atypical cases has been effectively shortened, and their operating accuracy in a complex environment has also been significantly improved. Through such repeated, immersive training in the simulation environment, from an objective standpoint, it transforms the abstract sense of protection into muscle memory and forms a protective habit that has become instinctive, thereby compensating for shortfalls in practical experience caused by insufficient real clinical work. Furthermore, immersive simulation has been consistently shown to foster greater learner satisfaction, self-efficacy, and active engagement, effectively mitigating the stress associated with high-risk clinical scenarios^14,15,16.

Despite the growing adoption of simulation in medical education, there remains a critical evidence gap regarding its quantitative impact on safety-critical procedural compliance and cognitive load in complex infectious disease management. The novelty of this study lies in its multi-scenario, workflow-coupled simulation design that integrates real-time biosafety feedback to specifically target cross-infection risks. Accordingly, the primary hypothesis is that multi-scenario simulation training will significantly outperform traditional didactic teaching in enhancing students' practical competencies, specifically yielding higher OSCE scores and greater compliance with critical safety standards. Furthermore, this study aims to build a dynamic closed-loop evaluation system. A combination analysis of objective structured clinical examination data and behavioral logs from simulated operations can accurately identify cognitive load bottlenecks and operational defects arising from changes across various clinical situations among medical students. This study is not only intended to show the advantages of multi-scenario simulation teaching but also to put forward differentiated teaching pathway optimization strategies for infectious diseases with different transmission routes based on quantitative empirical data analysis¹⁷

Protocol

All procedures involving human participants were conducted in accordance with the ethical standards of the Institutional Review Board of the Affiliated Hospital of North Sichuan Medical College and the principles of the Declaration of Helsinki. The study protocol was approved by the Institutional Review Board of the Affiliated Hospital of North Sichuan Medical College (Approval No. 2025ER538-1). Written informed consent was obtained from all participants prior to enrollment.

1. Participant recruitment and screening

1. Obtain the official clinical rotation rosters from the Affiliated Hospital of North Sichuan Medical College during the spring academic semester. Screen and recruit eligible participants during the two weeks preceding the infectious disease training module.
2. Restrict eligibility to fourth- or fifth-year undergraduate clinical medicine and nursing students and first-year clinical residents. Review the academic transcripts and clinical rotation schedules of all candidates using two independent teaching coordinators to verify compliance with the inclusion criteria.
3. Conduct qualification reviews for all potential candidates in accordance with standardized inclusion and exclusion criteria.
4. Verify that participants have completed or are currently conducting theoretical courses related to infectious diseases.
5. Administer a foundational pre-simulation clearance checklist to objectively verify that all candidates possess the physical stamina and cognitive availability required to endure high-intensity scenario training. Utilize this standardized checklist to confirm their capacity to complete the rigorous Objective Structured Clinical Examination without any underlying medical restrictions or scheduling conflicts.
6. Obtain an agreement from the participants regarding the recording of the teaching process and data collection, including questionnaire completion and standard scoring.
7. Evaluate baseline communication and teamwork capacities using the standardized Mini-Clinical Evaluation Exercise communication sub-scale during their initial clinical rotation. Exclude candidates who score below the established threshold of 4 out of 9 to ensure adequate interactive skills for completing simulated role tasks.
8. Exclude participants who are not in the specified training phase or lack basic knowledge in infectious disease theory.
9. Exclude individuals who have received prior systematic multi-scenario simulation training that highly overlaps with the study intervention to avoid intervention contamination.
10. Exclude those with objective limitations, such as rotation/duty schedules preventing the completion of required class hours, or a high risk of serious absenteeism.
11. Collect baseline demographic and learning background data, including age, gender, training stage, course experience of infectious diseases, and simulation training experience.
12. Utilize this baseline data for subsequent descriptive analysis and necessary statistical adjustments¹⁸.

2. Study design and allocation

1. Adopt a prospective, randomized, parallel-controlled educational intervention design to evaluate the application effects of multi-scenario simulation teaching.
2. Follow the predefined study workflow for participant enrollment, group allocation, intervention delivery, and outcome assessment. See Figure 1 for an overview of the study pathway.
3. Perform individual-level randomization to allocate the 121 screened subjects into the intervention group comprising 60 students and the control group comprising 61 students. Generate the random allocation sequence using a computer-based random number generator with a 1-to-1 ratio. Conceal this sequence in opaque, sequentially numbered, and sealed envelopes administered by a designated research assistant who is entirely independent of the teaching and assessment processes.
4. Carry out the research for both groups within a standardized teaching environment.
5. Complete the corresponding teaching arrangements for both groups within the exact same instructional cycle.
6. Maintain the comparability of teaching content and class-hour arrangements between the intervention and control conditions to minimize interference caused by teaching dosage differences¹⁹.

3. Implementation of the control condition (routine practice teaching)

1. Deliver routine infectious disease practice teaching to the control group to reflect the common teaching mode in the current education system.
2. Standardize the educational exposure by providing exactly 16 total contact hours distributed evenly over a four-week cycle for both conditions. Maintain a consistent faculty-to-student ratio of 1:10 across all sessions to equalize instructor interaction and prevent instructional dosage bias.
3. Conduct traditional case discussions and deliver clinical guideline explanations within a standard forty-seat lecture hall. Perform all theoretical instruction and situational demonstrations using a strict teacher-centered approach, allocating exactly four hours per weekly session to ensure temporal equivalence with the intervention group.
4. Provide routine demonstrations of specimen collection, basic hospital infection control procedures, and isolation techniques utilizing static, low-fidelity anatomical models. Limit learner engagement during these routine demonstrations strictly to passive observation and basic physical return demonstrations without any immersive contextual stressors.
5. Restrict the practical components of the control curriculum to paper-based theoretical case discussions and isolated single-skill practice on low-fidelity benchtop models. Verify that these learners do not participate in any integrated multi-scenario simulations or immersive clinical problem-solving environments.
6. Prevent cross-group contamination operationally by scheduling the intervention and control group training sessions on entirely different days and utilizing physically separate campus facilities.
7. Monitor compliance strictly by requiring all enrolled participants to sign a formal confidentiality agreement prohibiting the sharing of instructional materials or scenario details prior to the final assessment.

4. Implementation of the intervention (multi-scenario simulation teaching)

1. Base the overall simulation course design on actual clinical work processes.
2. Standardize high-frequency and high-risk practical tasks into specific training and quantity evaluation teaching units.
3. Organize the simulation curriculum sequentially around key infectious disease workflows, including triage and risk assessment, isolation decision-making, specimen collection, infection prevention and control, antimicrobial stewardship, and occupational exposure management.
4. Deliver the simulation modules according to the predefined curriculum framework and competency objectives. See Figure 2 for an overview of the curriculum structure.
5. Utilize a matrix-based construction method to align the scenario themes directly with the practical workflows of infectious diseases.
6. Assign a target competency and predefined observable behavioral criteria to each simulation scenario to guide instruction and assessment.
7. Implement the scenario-competency framework throughout the training program. See Figure 3 for the mapping between simulation scenarios and target competencies.
8. Implement the simulation scenarios according to the parameters specified in Table 1. Use high-fidelity patient manikins with programmable vital signs and standard clinical equipment to create a realistic clinical training environment.
9. Conduct the training in small cohorts of five learners to guarantee optimal hands-on engagement. Schedule four distinct simulation sessions per cohort, allocating precisely four hours per session to achieve a total of 16 contact hours per learner.
10. Ensure that all simulations are facilitated by senior attending physicians who hold formal simulation instructor certification and possess over five years of clinical experience in infectious disease management.
11. Conduct each simulation according to a standardized script containing patient information, risk factors, decision points, critical actions, and reporting requirements. Follow the predefined workflow from triage assessment through isolation, specimen collection, and handoff communication. See Figure 4 for an example of the scenario script.
12. Perform a continuous clinical scenario involving triage risk stratification, isolation decision-making, and specimen testing handover. Limit the scenario duration to 15–25 min without interruption to replicate time-sensitive clinical decision-making.
13. Apply an invisible fluorescent tracer lotion to selected surfaces or equipment within the simulation environment. Inspect participants and environmental contact points using a 395 nm ultraviolet light system immediately after high-risk procedures, such as specimen handling or personal protective equipment (PPE) doffing.
14. Use the inspection results to identify contamination pathways, missed hand hygiene steps, and high-risk contact areas. Provide immediate visual feedback to participants based on the observed contamination patterns (see Figure 5).
15. Assign a trained simulation instructor to monitor participant performance throughout each scenario using a predefined critical-error rubric. Identify safety-critical errors, including improper hand hygiene, incorrect PPE use, and unprotected exposure events.
16. Provide immediate corrective feedback for serious safety breaches using standardized instructor scripts. Limit interventions to errors that compromise participant safety or interfere with achieving the learning objectives.
17. Conduct a structured debriefing immediately after each simulation session. Use the Gather, Analyze, and Summarize (GAS) framework to facilitate reflection on clinical decision-making, teamwork, communication, and infection control practices.

5. Outcome measurement and data collection

1. Conduct a unified outcome assessment for all participants within 1 week after completion of the teaching intervention.
2. Blind all OSCE assessors to participant group allocation throughout the assessment process.
3. Schedule participants from the intervention and control groups in a mixed order during the assessment sessions to minimize allocation disclosure.
4. Assess participant performance using a six-station Objective Structured Clinical Examination (OSCE).
5. Allocate 10 min for completion of each OSCE station.
6. Assign two independent examiners to each station and evaluate performance using standardized 100-point scoring sheets.
7. Calculate the intraclass correlation coefficient after the examination to assess inter-rater reliability.
8. Evaluate compliance with predefined critical actions using standardized OSCE checklists.
9. Score triage risk stratification according to the accuracy of risk classification completed within 3 min.
10. Score isolation decision-making according to the timely initiation of the appropriate notification and reporting procedures.
11. Score specimen collection according to correct labeling, packaging, and double-bagging procedures.
12. Score personal protective equipment (PPE) removal according to adherence to the prescribed doffing sequence.
13. Score occupational exposure management according to the timeliness and completeness of decontamination procedures.
14. Measure compliance with safety-critical behaviors throughout the OSCE assessment.
15. Evaluate hand hygiene according to the timing and completeness of hand hygiene actions.
16. Evaluate PPE use according to the correct sequence of donning and doffing procedures.
17. Evaluate specimen management according to compliance with specimen packaging and transport requirements.
18. Evaluate exposure-response according to compliance with predefined response time limits and management procedures.
19. Administer scenario-based reasoning and decision-making evaluations as secondary outcome indicators to prevent relying solely on knowledge-memory-based questions.
20. Observe and score team communication and collaboration behaviors during the scenarios.
21. Evaluate observable communication items, focusing on the completeness of information conveyed, the structure of SBAR (Situation, Background, Assessment, Recommendation) expression, closed-loop communication, and cross-role task assignments.
22. Administer a comprehensive set of previously validated psychometric questionnaires to capture learner-reported outcomes, specifically targeting satisfaction, self-efficacy, active engagement, and perceived cognitive load.
23. Ensure these established instruments have undergone rigorous cultural adaptation and preliminary pilot testing within the local instructional context prior to formal deployment. Refer to Table 2 for reliability and validity evidence, acquisition methods, and evaluation criteria for all performance assessment tools.
24. Train all assessors during a standardized 4 h calibration session. Require each assessor to achieve a Cohen's kappa value >0.80 before formal scoring.
25. Utilize partial video recordings during the sample checks to verify examiner consistency and scoring accuracy.
26. Designate specific research personnel to completely anonymize all collected data by replacing personal identifiers with randomized alphanumeric codes. Store this de-identified data securely on an encrypted institutional cloud server with password-protected access restricted solely to the core research team, and maintain these records for a mandatory retention duration of five years to ensure traceability and compliance.

6. Statistical analysis preparation

1. Calculate the means and standard deviations (or medians and quartiles) for continuous variables, and present categorical variables as frequencies and percentages.
2. Test all continuous outcome variables for normality using the Shapiro-Wilk test prior to executing any covariance analysis or generalized linear modeling. Subsequently, assess the homogeneity of variances via Levene's test to guarantee that all foundational statistical assumptions are strictly satisfied.
3. Control for baseline levels and key background variables (e.g., age, gender, training stage, prior infectious disease experience) within the linear models to improve estimation robustness.
4. Analyze dichotomous outcomes, such as key step compliance, using generalized linear models for between-group comparisons.
5. Report the corresponding effect sizes, odds ratios, and confidence intervals for all primary outcomes.
6. Impute missing follow-up data using multiple imputation with fully conditional specification. Compare imputed and complete-case datasets in sensitivity analyses.
7. Set the significance level at 0.05 for all two-tailed statistical tests.

Results

Baseline characteristics
A total of 121 participants were included in the study, comprising 60 students in the multi-scenario simulation group and 61 in the control group. Baseline demographic characteristics and learning experiences were comparable between the two groups. Age distribution, gender composition, training type, training stage, and specialty distribution were similar across groups. The proportions of senior undergraduate students and junior residents were also comparable. No significant ...

Discussion

Through a prospective randomized controlled trial, this study demonstrated that multi-scenario simulation teaching is significantly more effective than traditional teaching for the practice education of infectious diseases^20,21. The intervention group achieved considerable gains in OSCE total scores, compliance with essential steps, triage risk stratification, isolation decision-making, specimen collection, hand hygiene, and protective equipment donning and doffi...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
High-fidelity Simulation System	Simulation Center, Affiliated Hospital of North Sichuan Medical College	Model-specific	Multi-scenario infectious disease simulation training
OSCE Checklist & Scoring Forms	Research Team	Standardized protocol	Objective assessment of clinical skills and critical actions
Questionnaire Survey Forms	Research Team	Validated scales	Evaluation of learner satisfaction, self-efficacy and cognitive load
Statistical Software (SPSS)	IBM Corp.	Version 26.0	Statistical analysis of outcome data