The efficacy of patient-in-classroom instruction compared to traditional lectures: a quasi-experimental study in nursing education

Abstract

Background

Traditional, lecture-based nursing education often fails to prepare students for real-world patient care. This study evaluates experiential learning through direct patient engagement to bridge this theory-practice gap.

Methods

This quasi-experimental study employed a two-group, post-test-only design. A sample of 700 nursing students was determined through a priori power analysis. Participants were non-randomly assigned (quasi-experimental allocation due to intact classroom groups) to intervention (n = 350, patient-in-classroom teaching) or control (n = 350, traditional lectures) over 14 weeks. Teaching quality was measured using a validated 13-item questionnaire assessing four domains. Primary analyses used Mann-Whitney U tests with Cohen’s d for effect size (α = 0.05).

Results

The intervention group demonstrated statistically significant superiority across all teaching quality domains (P < 0.001). The mean total teaching quality score was 11.07 points higher in the intervention group (58.13 ± 4.44) compared to the control (47.06 ± 6.73), with a large effect size (Cohen’s d = 1.94). Domain-specific analyses revealed large effect sizes: conceptual learning (d = 1.91), instructional organization (d = 2.01), pedagogical methods (d = 2.15), and student engagement (d = 1.97). However, the large effect sizes should be interpreted cautiously given the potential for Hawthorne effects and social desirability bias inherent in self-reported perceptions.

Conclusion

The patient-in-classroom method was associated with significantly higher perceived teaching quality compared to traditional lectures. These findings suggest that this experiential approach may be a valuable addition to nursing curricula; however, further research using objective outcome measures is needed to establish effects on clinical competence and long-term learning outcomes.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12909-026-09586-w.

Background

Nursing education requires methods that effectively prepare students for clinical realities [1]. While most institutions rely on traditional, theory-based instruction and simulation, an emerging approach involves integrating real patients directly into the classroom [2]. This patient-in-classroom method offers a more realistic learning environment, allowing students to directly engage with patient needs and challenges.

Traditional teaching methods possess significant limitations in replicating real-life experiences, potentially leaving students inadequately prepared for actual patient care [3]. This can lead to diminished learning quality, increased student anxiety in clinical situations, and a subsequent reduction in the quality of nursing care. Studies on bedside teaching demonstrate that involving real patients enhances students’ clinical readiness, confidence, and ability to apply skills in practice [4], highlighting a clear pathway to address this theory-practice divide. Dickinson et al. demonstrated that involving real patients in case-based learning activities significantly increased student engagement and enhanced understanding of disease processes among medical students [5].

Despite evidence supporting innovative methods like simulation, interactive lectures, and blended learning in healthcare education, comprehensive research on the specific integration of real patients into nursing education remains limited [6].

Miller et al. compared engaging lectures with traditional didactic formats among dental students, finding that interactive lectures led to 8.6% higher exam scores and 22.9% better long-term retention on comprehensive finals [7]. The integration of technology with traditional teaching methods has also gained attention in healthcare education. Sadeghi et al. investigated blended learning approaches combining traditional and e-learning methods, finding that while knowledge acquisition was comparable between lecture-only and blended learning groups, student satisfaction was significantly higher with the blended approach [8]. This suggests the potential of hybrid methodologies as complements to traditional teaching methods.

While studies have demonstrated the benefits of real patient involvement in medical education and the effectiveness of simulation-based training in nursing programs, there is a need for comprehensive investigation into how real patient integration specifically impacts nursing student learning, skill development, and clinical preparedness [9]. Students who engage with real patients during their education demonstrate improved clinical skills, increased confidence, and enhanced empathy [10]. Therefore, investigating the impact of real patient integration in nursing education is essential for advancing teaching methodologies and improving student outcomes.

This study aimed to compare the quality of teaching between the traditional method and the patient-in-classroom approach in the Home Nursing Care course for nursing students, examining how the incorporation of real patients affects student learning outcomes and overall preparedness for professional practice.

Methods

Study design and setting

This quasi-experimental study employed a two-group, post-test-only design conducted from September 2022 to June 2025 at the Faculty of Nursing and Midwifery, Islamic Azad University, Babol Branch, Iran. Participants were assigned using a quasi-randomized approach (block assignment) but, reflecting real-world educational constraints, instruction was delivered in intact classroom groups, which renders the design quasi-experimental. The study adhered to the TREND (Transparent Reporting of Evaluations with Nonrandomized Designs) statement for reporting.

Participants and sampling

The study population consisted of all nursing students enrolled in the “Home Nursing Care” practical course during semesters 5–8. From a total pool of 850 eligible students across the study period, participants were selected through systematic random sampling. Inclusion criteria were: enrollment in the Home Nursing Care course during semesters 5–8, active student status, willingness to participate for the full 14-week period, and provision of informed consent.

Exclusion criteria were: withdrawal from the course during the study period, absence from more than three sessions (> 21% absenteeism), submission of incomplete questionnaire responses, and prior formal exposure to patient-in-classroom teaching methods.

A priori power analysis was conducted using G*Power version 3.1.9.7. Based on previous studies with an expected medium effect size (Cohen’s d = 0.5), α = 0.05 (two-tailed), and power = 0.95, the minimum required sample size was 210 per group. To account for potential clustering effects (estimated ICC = 0.10) and attrition, we applied a design effect multiplier of 1.3, resulting in a target of 350 per group (total N = 700).

Assignment and blinding

Participants were assigned to intervention (patient-in-classroom teaching) or control (traditional lecture-based teaching) using block assignment with varying block sizes (4 and 6), stratified by academic year and previous semester GPA. Due to the use of intact classroom groups, this represents a quasi-experimental rather than truly randomized design. Allocation was concealed using sequentially numbered opaque envelopes opened after baseline data collection. Due to the nature of the educational intervention, blinding of participants was not feasible. However, research assistants administering outcome measures were blinded to group allocation, and data analysts were blinded until primary analyses were complete.

Intervention protocol and fidelity monitoring

Patient-in-classroom group (intervention)

The intervention group received instruction through the patient-in-classroom method following a structured protocol. Patients with stable chronic conditions relevant to home nursing care (diabetes mellitus: 33%, hypertension: 25%, heart failure: 17%, other chronic conditions: 25%) were recruited from university-affiliated outpatient clinics. Patients were screened for medical stability, communication ability, and willingness to participate. Each patient received a 2-hour orientation session outlining educational objectives, session structure, and boundaries.

Each 90-minute session included a 15-minute structured patient narrative about living with their condition, a 30-minute moderated Q&A session facilitated by the instructor, a 30-minute small group discussion applying theoretical concepts to the patient case, and a 15-minute debriefing and synthesis. A total of 12 different patients participated across the 14-week course, with each patient attending 2–3 sessions. Patients received compensation of approximately $20 per session.

Traditional lecture group (control)

The control group received traditional lecture-based instruction covering identical curriculum content, learning objectives, and materials. Lectures were delivered by the same instructors using PowerPoint presentations, with identical time allocated for questions and answers.

Standardization and fidelity

Both groups received identical contact time (21 h). To control for potential instructor effects, the same five faculty members taught in both groups across different semesters using a partial crossover design. All instructors received standardized training: 4 h on traditional lecture techniques and 8 h on facilitating patient-in-classroom sessions. Fidelity was monitored through monthly observation of 20% of randomly selected sessions using a 10-item fidelity checklist, yielding a mean fidelity score of 92.4% (range: 85–100%).

Ethical considerations

This study was conducted in accordance with the Declaration of Helsinki and received approval from the Institutional Review Board of Islamic Azad University, Babol Branch (IR.IAU.BABOL.REC.1403.061). Written informed consent was obtained from all participating students and patient-instructors. Ethical protections for patients included comprehensive informed consent, confidentiality agreements, emotional safety protocols with on-site counseling, and the right to withdraw at any time.

Primary outcome

Teaching quality was assessed using the Teaching Quality Evaluation Questionnaire, a validated 13-item instrument [11] measuring four domains: Concept Transfer and Learning (3 items), Teaching Organization and Planning (3 items), Teaching Methods and Tools (4 items), and Student Engagement and Participation (3 items). Each item was rated on a 5-point Likert scale (1 = Very Low to 5 = Very High), with total scores ranging from 13 to 65. Higher scores indicated superior perceived teaching quality.

In the current sample, the instrument demonstrated strong psychometric properties: total scale Cronbach’s α = 0.89; domain α values ranged from 0.78 to 0.84. Confirmatory factor analysis supported the four-factor structure (CFI = 0.92, TLI = 0.90, RMSEA = 0.07). Test-retest reliability over 2 weeks (n = 50) was r = 0.84 (P < 0.001).

We selected a general teaching quality scale rather than a therapeutic interaction-specific instrument because the primary objective was to evaluate the pedagogical effectiveness of the teaching method itself, rather than to measure students’ clinical interaction competencies. Future research should employ specialized instruments such as the Nurse-Patient Therapeutic Interaction Scale (NuPTIS) to capture the latter.

Additional measures

Demographic data (age, gender, academic year, previous GPA), prior clinical experience, and attendance records were collected.

Data collection

Data collection occurred at two time points: Week 1 (demographic data and covariates) and Week 15 post-intervention (Teaching Quality Evaluation Questionnaire). All measures were administered electronically using secure survey software. Students were assured that responses would not affect course grades and would remain confidential.

Statistical analysis

Due to violations of normality and homogeneity of variance assumptions for teaching quality scores, primary between-group comparisons were conducted using the Mann-Whitney U test. For transparency, Welch’s t-test results are also reported. Sensitivity analyses using the Brunner-Munzel test confirmed the robustness of findings.

To address potential clustering by instructor, section, and semester, we conducted mixed-effects modeling (3-level model: students nested within classes nested within semesters) and calculated cluster-robust standard errors. These results are presented in the Supplementary Appendix.

Cohen’s d was calculated using pooled standard deviation adjusted for unequal group sizes. For non-parametric tests, rank-based effect sizes (r) were calculated as r = Z / √N. Intention-to-treat analysis using multiple imputation (20 imputations) was conducted as a sensitivity analysis.

All analyses were conducted using IBM SPSS Statistics Version 27 and R version 4.2.1, with α = 0.05 (two-tailed).

Results

Participant flow and baseline characteristics

Of the 850 students assessed for eligibility, 724 met inclusion criteria and were invited to participate. Twenty-four students declined, resulting in 700 enrolled participants. After exclusions for absenteeism (n = 18) and incomplete responses (n = 9), 682 participants were included in the final analysis (intervention: n = 341, control: n = 341). Attendance rates were comparable between groups (intervention: 94.2%, control: 93.8%) (Fig. 1).

Fig. 1.

Study design and methodology flowchart for patient-in-classroom versus traditionalteaching methods comparison. CONSORT flow diagram of participant enrollment, allocation, and analysis in the quasi-experimental study. The diagram details the number of nursing students assessed for eligibility, randomly assigned to the patient-in-classroom (intervention) or traditional lecture (control) groups, and included in the final analysis

The groups were well-matched at baseline with no statistically significant differences in demographic or academic variables (Table 1). Mean age was 21.4 ± 0.87 years, and 64.2% of participants were female.

Table 1.

Demographic characteristics and baseline data of study participants (N = 682)

Variable	Total (N = 682)	Intervention Group (n = 341)	Control Group (n = 341)	P-value
Age (years)	21.4 ± 0.87	21.4 ± 0.86	21.4 ± 0.88	0.921
Range	18.0–26.0	18.1–25.8	18.0–26.0	-
Gender, n (%)				0.935
Male	244 (35.8%)	122 (35.8%)	122 (35.8%)
Female	438 (64.2%)	219 (64.2%)	219 (64.2%)
Academic Year, n (%)				0.942
Year 3	341 (50.0%)	171 (50.1%)	170 (49.9%)
Year 4	341 (50.0%)	170 (49.9%)	171 (50.1%)
Semester, n (%)				0.876
Semester 5	170 (24.9%)	85 (24.9%)	85 (24.9%)
Semester 6	171 (25.1%)	86 (25.2%)	85 (24.9%)
Semester 7	171 (25.1%)	85 (24.9%)	86 (25.2%)
Semester 8	170 (24.9%)	85 (24.9%)	85 (24.9%)
Previous GPA	17.05 ± 1.24	17.0 ± 1.23	17.1 ± 1.25	0.892
Range	10.0–20.0	10.2–20.0	10.0-19.8	-

*Note: Data presented as mean ± SD unless otherwise indicated *

Primary outcomes

The intervention group demonstrated significantly higher teaching quality scores across all domains (Table 2). The mean total teaching quality score was 11.07 points higher in the intervention group (58.13 ± 4.44) compared to the control group (47.06 ± 6.73), with a large effect size (Cohen’s d = 1.94; Mann-Whitney U: P < 0.001).

Table 2.

Comparison of teaching quality outcomes between groups

Variable	Intervention (n = 341)	Control (n = 341)	Mean Difference	Cohen’s d	P-value
Total Teaching Quality	58.13 ± 4.44	47.06 ± 6.73	11.07	1.94	< 0.001
Concept Transfer	12.55 ± 1.64	8.83 ± 2.20	3.71	1.91	< 0.001
Teaching Organization	12.57 ± 1.58	8.76 ± 2.17	3.81	2.01	< 0.001
Teaching Methods	16.59 ± 2.01	11.61 ± 2.59	4.97	2.15	< 0.001
Student Engagement	12.63 ± 1.48	8.91 ± 2.22	3.72	1.97	< 0.001

*Note: Data presented as mean ± SD. All P-values from Mann-Whitney U tests *

Domain-specific analyses revealed large effect sizes for all four dimensions: concept transfer (d = 1.91), teaching organization (d = 2.01), teaching methods (d = 2.15), and student engagement (d = 1.97). All differences were statistically significant (P < 0.001).

Individual item analysis

All 13 questionnaire items showed statistically significant improvements in the intervention group, with mean differences ranging from 1.15 to 1.35 points on the 5-point Likert scale and effect sizes consistently exceeding d = 1.0 (Table 3). Figure 2 provides a multi-panel visualization comparing performance on each of the 13 individual items between the two groups. The largest effect sizes were observed for classroom preparation (d = 1.250) and dynamic teaching techniques (d = 1.213).

Table 3.

Individual item comparisons (selected items)

Item	Domain	Mean Difference	Cohen’s d	P-value
Classroom preparation	Teaching Organization	1.35	1.250	< 0.001
Dynamic teaching techniques	Student Engagement	1.29	1.213	< 0.001
Problem-solving assignments	Concept Transfer	1.28	1.212	< 0.001
Appropriate teaching methods	Student Engagement	1.25	1.182	< 0.001
Transfer of learning through senses	Concept Transfer	1.15	1.051	< 0.001

*Note: Full item-level results are available in the Supplementary (Table S2). All P-values remained significant after Bonferroni correction (adjusted α = 0.0038) *

Fig. 2.

Teaching quality outcomes: patient-in-classroom vs. traditional method. Comparative bar graph (with error bars) illustrating the mean total score and domain-specific scores (Concept Transfer, Teaching Organization, Teaching Methods, Student Engagement) on the Teaching Quality Evaluation Questionnaire for the intervention and control groups. Asterisks denote statistically significant differences (P < 0.001). Figure 2 displays (A) overall teaching quality score comparison via boxplot, (B) mean scores with 95% confidence intervals for each teaching quality dimension, (C) Cohen's d effect sizes for all domains, and (D) score distribution densities for both groups. All comparisons demonstrate p <0.001 with large effect sizes

The consistent superiority of the Patient-in-Classroom method across all items is further illustrated in Fig. 3, a Heatmap showing effect size (Cohen’s d) for each questionnaire item, grouped by domain, where Warmer colors indicate larger improvement.

Fig. 3.

Detailed analysis of teaching quality questions across multiple statistical dimensions. A multi-panel visualization (e.g., a series of bar charts or a radar chart) depicting the performance on each of the 13 individual questionnaire items, comparing the patient-in-classroom and traditional lecture groups. This figure highlights the consistent superiority of the intervention across all measured aspects of teaching quality

Secondary and sensitivity analyses

After controlling for baseline GPA and prior clinical experience, ANCOVA confirmed significant group differences (F[1,679] = 418.6, P < 0.001, partial η² = 0.381). Intention-to-treat analysis using multiple imputation (n = 700) yielded consistent results (mean difference = 10.85, d = 1.91, P < 0.001). Mixed-effects modeling accounting for clustering by section and semester showed that the intervention effect remained significant (β = 10.89, SE = 0.56, P < 0.001). Full mixed-model results are presented in the Supplementary (Table S1).

Objective outcome pilot data

While the primary study focused on perceived teaching quality, a pilot assessment of communication skills in a subsample (n = 50) showed significant improvement in the intervention group (mean difference = 2.34 points, P < 0.05, d = 0.65). This finding is preliminary and requires replication with larger samples and validated instruments.

Discussion

This quasi-experimental study compared patient-in-classroom teaching to traditional lecture-based instruction among 682 nursing students. The patient-in-classroom method was associated with significantly higher perceived teaching quality across all measured domains, with large effect sizes (d = 1.94–2.15). These findings suggest that integrating real patients into the classroom may offer substantive pedagogical benefits.

Interpretation of findings and potential biases

The effect sizes observed in this study are exceptionally large compared to typical educational interventions, where Cohen’s d > 0.8 is considered large [12]. Several factors may have contributed to these magnitudes. First, the Hawthorne effect—where students in the intervention group may have rated their experience more favorably due to awareness of receiving a novel, special treatment—likely inflated scores. Second, social desirability bias may have led students to please instructors who facilitated these innovative sessions. Third, the lack of baseline measures of student attitudes toward innovative teaching methods prevents adjustment for pre-existing differences in receptivity. The extreme separation in score distributions (Fig. 4) should be interpreted with these considerations in mind; while the differences are statistically robust, the magnitude may reflect a combination of genuine pedagogical effectiveness and these potential biases.

Fig. 4.

Individual question performance differences heatmap between patient-in-classroomand traditional teaching methods. Figure 4 displays the mean score differences for all 13questionnaire items organized by teaching quality domains (Concept Transfer: Q1-Q3, Teaching Organization: Q4-Q6, Teaching Methods: Q7-Q10, Student Engagement: Q11-Q13). The colorintensity represents the magnitude of improvement favoring the patient-in-classroom method,with darker red indicating larger mean differences. Values shown represent the mean difference between intervention and control groups on the 5-point Likert scale. Heatmap of teaching quality improvement magnitude across domains and individual items. A color-coded matrix visualizing the effect size (Cohen's d) for each questionnaire item, grouped within their respective domains (Concept Transfer, Teaching Organization, Teaching Methods, Student Engagement). Warmer colors indicate larger effect sizes, demonstrating the extent of improvement attributable to the patient-in-classroom method

Comparison with existing literature

These findings align with previous research demonstrating the value of patient involvement in education. Dickinson et al. found that incorporating real patients into preclinical curricula enhanced student engagement and provided authentic learning experiences [5]. Similarly, McLean’s review of case-based learning across health professions confirmed its effectiveness in bridging theoretical knowledge with clinical application [13]. Bokken et al. compared real patient contacts with simulated patients, noting that students perceived real patients as more authentic despite some limitations in feedback quality [14]. Our study extends this work by demonstrating measurable improvements across multiple teaching quality domains.

The effect sizes observed exceed those reported for simulation-based training [6, 15] or interactive lectures [7, 16], suggesting that the authenticity of real patient interactions may offer unique advantages. Cook and colleagues’ meta-analysis of technology-enhanced simulation similarly demonstrated moderate to large effects on knowledge and skills outcomes [17]. However, it is important to note important distinctions between these approaches. Standardized patient (SP) models, while offering less authenticity, provide controlled, repeatable scenarios that allow for standardized assessment of clinical competencies. In contrast, the real patient model used in this study trades controllability for authentic unpredictability. Recent evidence suggests that AI-assisted assessments in SP-based education can significantly enhance therapeutic communication skills while maintaining controllability [18]. Future research should directly compare these models to isolate the unique contribution of “authenticity” from the benefits of structured, repeatable experiential learning.

Practical implementation considerations

Successful integration of patient-in-classroom teaching requires substantial institutional support, including sustainable pipelines for recruiting and compensating patient-instructors, faculty development for facilitating sessions, and logistical coordination. These requirements may pose barriers to adoption in resource-constrained settings. Future implementation research should focus on developing cost-effective protocols and evaluating scalability across different contexts.

Mechanisms underlying effectiveness

The observed improvements can be understood through educational theory. Kolb’s experiential learning theory posits that learning occurs through concrete experience, reflective observation, abstract conceptualization, and active experimentation [19]. Yardley and colleagues further Elaborated on how experiential learning transforms theoretical knowledge into practical clinical competence [20]. The patient-in-classroom approach incorporates all these elements, allowing students to observe real clinical presentations, reflect on patient interactions, and conceptualize theoretical knowledge in practice.

Social learning theory [21] may explain improved engagement through observation and modeling. The qualities of effective teaching identified by Azer—including clarity, enthusiasm, and the ability to create authentic learning experiences—align with the patient-in-classroom approach [22]. The highest effect size observed for teaching methods (d = 2.15) suggests that authentic patient scenarios bridge the theory-practice gap that traditionally challenges nursing education [23].

Comparison with standardized and AI-assisted approaches

Our focus on real patient authenticity is valuable, but recent evidence suggests that structured, AI-assisted assessments in SP-based education can also significantly enhance therapeutic communication skills. Erkayıran (2025) demonstrated that AI-assisted assessment in standardized patient-based education provided more controllable metrics while maintaining educational effectiveness. This raises important questions about the trade-offs between authenticity and controllability in nursing education. Future research should directly compare real patient, standardized patient, and AI-assisted approaches to determine optimal strategies for different learning objectives. Frambach and colleagues noted that cultural factors significantly influence self-directed learning, suggesting that the generalizability of our findings to non-Iranian contexts requires empirical verification [24].

Implications for future research and measurement

While this study measured perceived teaching quality, future research should employ objective outcome measures such as standardized knowledge tests, Objective Structured Clinical Examinations (OSCEs), or direct observation of clinical skills. Additionally, specialized instruments like the Nurse-Patient Therapeutic Interaction Scale (NuPTIS) [25] should be used to capture the development of clinical interaction competencies specifically. Such instruments would provide a more accurate assessment of whether patient-in-classroom teaching translates into improved therapeutic communication skills.

Limitations

This study has several limitations that must be considered. First, the lack of baseline (pre-test) measures of teaching quality or student attitudes prevents adjustment for potential pre-existing differences and limits causal inference. Second, the exclusive reliance on student self-reported perceptions is susceptible to Hawthorne effects, social desirability bias, and novelty effects, which likely inflated effect sizes. The absence of objective learning outcomes means the impact on actual knowledge and clinical competency remains unmeasured. Third, potential clustering effects were not formally modeled in primary analyses, and the extremely large effect sizes may be partially influenced by unmodeled cluster effects. Fourth, patient-instructors varied not only by medical condition but also in storytelling ability, communication style, and capacity to engage students. These unmeasured characteristics may have influenced student perceptions of teaching quality independently of the pedagogical method itself. Future studies should systematically document patient-instructor characteristics or use standardized patient training protocols to reduce this source of variability. Fifth, the extended data collection period (2022–2025) introduces the possibility of secular trends. Finally, while described as randomized at the student level, the quasi-experimental nature of allocating intact groups and the lack of participant blinding are inherent limitations.

Conclusion

This study found that the patient-in-classroom teaching model was associated with significantly higher perceived teaching quality compared to traditional lecture-based instruction, with large effect sizes across all measured domains. However, the magnitude of these effects should be interpreted cautiously given the potential for Hawthorne effects and social desirability bias. The findings suggest that this experiential approach may be a valuable addition to nursing curricula, but successful integration requires addressing practical considerations such as sustainable patient recruitment, faculty development, and resource allocation.

Suggestions for future research

To build upon these findings, future studies should employ objective outcome measures (standardized knowledge tests, OSCEs, or direct observation of clinical skills) to validate self-reported data. Longitudinal studies are needed to assess the durability of learning and translation into clinical competence. Qualitative investigations should explore the experiences of students, faculty, and patient-instructors to understand mechanisms of effectiveness.

Cost-effectiveness analyses are required to evaluate resources relative to benefits. Importantly, future research should directly compare real patient, standardized patient, and AI-assisted approaches using validated instruments such as the Nurse-Patient Therapeutic Interaction Scale (NuPTIS) to determine optimal strategies for developing clinical competencies. Finally, replication in diverse cultural and institutional settings is needed to establish generalizability.

Authors’ contributions

F.M.N. and F.R. conceived the research idea and designed the study framework, with F.R. leading manuscript preparation and supervision. A.S. contributed to the theoretical foundation and educational methodology. L.J. provided nursing education expertise and validated outcome measures. A.K. conducted all statistical analyses and reporting. F.Z.S. coordinated participant recruitment and data collection. M.F. managed the implementation of teaching sessions. F.M.N. also drafted the introduction and literature review sections. All authors read and approved the final manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

The datasets generated and analyzed during the current study are not publicly available due to privacy and confidentiality considerations. However, anonymized data supporting the conclusions of this article are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

This study was conducted in accordance with the ethical standards of the Declaration of Helsinki. Approval was granted by the Institutional Review Board (IRB) of the Islamic Azad University, Babol Branch (IR.IAU.BABOL.REC.1403.061). Written informed consent was obtained from all participating students and patient-instructors.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.