Peer tutoring in clinical simulation for health sciences education: a systematic review

Abstract

Background

Simulation-Based Education and peer tutoring have become relevant pedagogical strategies in health sciences education, as they promote active, safe, and collaborative learning. However, studies demonstrating their combined benefits have not yet been sufficiently systematized. This systematic review analyzes the evidence on the implementation of peer tutoring and simulation-based teaching for the development of technical and non-technical skills among health sciences students, based on experimental and quasi-experimental interventions.

Methods

A search was conducted in the Web of Science, Scopus, and PubMed databases, including experimental and quasi-experimental studies published between 2020 and 2025. Eleven studies met the inclusion criteria, with a total sample of 860 students and 107 peer tutors.

Results

The results show that most interventions were implemented in low- to medium-complexity simulation settings and primarily reached Level 2 of Kirkpatrick’s evaluation model, assessing knowledge, skills, and attitudes. Peer tutoring demonstrated significant benefits in technical skills (e.g., specific clinical procedures) and in non-technical skills such as self-confidence, self-efficacy, communication, motivation, and reflection. Additionally, high levels of student satisfaction, reduced anxiety, and the creation of psychologically safe learning environments were reported.

The role of the peer tutor is characterized by cognitive and social proximity to students, acting as a learning facilitator, provider of feedback, and promoter of a climate of trust. However, the studies also revealed methodological limitations, including small sample sizes, non-randomized designs, and the absence of longitudinal follow-up.

Conclusions

In conclusion, the combination of Simulation-Based Education and peer tutoring represents a cost-effective and pedagogically sound strategy for health professions education. Future research should incorporate more rigorous designs, larger samples, and long-term evaluations, as well as formal training programs for peer tutors under faculty supervision.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12909-026-09582-0.

Introduction

The Simulation-Based Education (SBE) [1] and peer tutoring has made substantial contributions to health sciences [2]. Therefore, it is important to understand how these methodologies can complement each other, as both share a common goal of enhancing teaching and learning processes. SBE accomplishes this by providing a safe environment for clinical practice [3], while peer tutoring promotes collaborative and symmetrical learning [4].

Peer tutoring is primarily grounded in sociocultural learning theory [5], which conceptualizes learning as an active process in which social interaction is essential for knowledge acquisition.

Similarly, Bandura’s social learning theory [6], posits that a significant portion of human learning occurs through modeling—that is, by observing others’ behaviors. From this perspective, students acquire behaviors, attitudes, and skills through observation, imitation, and subsequent reproduction of a model’s actions—in this case, the peer tutor. This process is further supported by the social and cognitive congruence that peer tutors share with students [7, 8], which fosters greater social integration [9].

Within this theoretical framework, peer tutors act as mediators of the learning process, facilitating the development of new competencies. Peer tutors are competent students who assist their classmates in learning new content under the supervision of expert academic staff [10]. This educational role supports learning and skill development among higher education students [4], including those in health sciences [11], and is reinforced by the social and cognitive congruence that peer tutors share with learners [7, 8, 12].

Among the positive aspects of peer tutoring, the literature highlights improvements in academic performance—particularly during clinical stages and in the acquisition of practical skills—along with increased satisfaction, engagement, and acceptance of learning activities, reduced stress levels, and enhanced self-confidence, self-efficacy, and communication, collaboration, and leadership skills [2, 13–16]. However, aspects requiring improvement include the quality and consistency of teaching, the lack of pedagogical training among peer tutors, and insufficient preparation for more complex or specialized activities [2, 17].

In addition to the benefits observed in students, peer tutoring programs also generate positive effects on the tutors themselves, including improved academic performance and strengthened teaching and communication skills [18]. These advantages could be effectively transferred to clinical simulation, as this context requires communication, leadership, feedback, and teamwork competencies, while also promoting the consolidation of clinical reasoning and self-confidence in safe and collaborative environments.

SBE serves as a pedagogical bridge between the classroom and the clinical practice environment, allowing for both individual and team self-reflection. It offers opportunities to uncover personal and shared mental models through conversational techniques such as debriefing [19]. Across different levels of complexity and realism (SimZones), it may include self-instructional activities (software and automatic feedback – Zone 0), skills practice (Zone 1), participation in clinical scenarios (role-playing – Zone 2), native team training (Zone 3), and reflection on real clinical practices (Zone 4) [20].

Although peer tutoring contributes to the development of skills, it remains unclear whether its effectiveness is equivalent to that of expert faculty instruction [21] in skills and simulation laboratories. Previous studies have focused primarily on areas such as student self-efficacy [22], teamwork and communication in interprofessional simulation [23], peer feedback [24], and intelligent tutoring systems in general learning contexts [25].

The implementation of SBE and peer tutoring requires systematic evaluation. In this regard, Kirkpatrick’s evaluation model is a useful framework [26], as it enables the assessment of educational interventions across four levels: participants’ reactions, learning gained, behavioral changes, and results achieved in clinical practice.

In this context, the general aim of this review is to analyze the evidence on the implementation of peer tutoring and simulation-based teaching for the development of technical and non-technical skills among health sciences students, based on experimental and quasi-experimental interventions. The specific objectives are: (1) To describe the core components of peer tutoring, including its definition, the role and functions of the tutor, the required profile, and the theoretical framework supporting the approach; (2) To examine the characteristics of the interventions, considering the simulation zones described by Roussin [20] and Díaz-Guío [27], the level achieved according to Kirkpatrick [26], the technical and non-technical skills addressed, and the characteristics of peer tutoring; (3) To synthesize the main findings, conclusions, limitations, and suggested directions for future research on the implementation of peer tutoring within clinical simulation contexts.

Methods

A systematic review of the literature was conducted using the Web of Science, Scopus, and PubMed databases. During the preliminary search, prior reviews related to the topic were identified and are reported in the introduction [21–25]. The search strategy (Table 1) was developed based on the keywords identified in the preliminary review and by incorporating descriptors from the MeSH, DeCS, ERIC, and UNESCO thesauri.

Table 1.

Search strategy

Level 1: simulation OR “Computer Simulation” OR “Computer-Based Simulation” OR “Patient Simulation” OR “Simulated patient” OR “High Fidelity Simulation Training” OR “Simulation Training” OR “simulation-based training” OR “Clinical simulation” OR “educational simulation” OR “simulation-based education” OR “Healthcare Simulation” OR “simulation in healthcare” OR “Simulation in Health” OR “Immersive Simulation” OR “Simulated-Based Learning Experience” OR “virtual reality simulation” OR “virtual simulation” OR “simulation-based learning”

AND

Level 2: “peer tutoring” OR “peer teach*” OR “peer educ*” OR “peer led” OR “peer mentor” OR “peer instruction” OR “peer tutor” OR “peer collaboration” OR “student run” OR “student-led” OR “peer- assisted teach*” OR “peer-assisted learn*” OR “peer group teach*” OR “near peer teach*” OR “near peer tutor*” OR “peer tutor*” OR “peer-to- peer tutor*” OR “peer-to-peer teach*” OR “peer assisted learning” OR “Peer Educators” OR “Peer relationship” OR “Tutoring” OR “peer feedback” OR “peer feedback quality”

The search filters applied were as follows: publication period between 2020 and 2025; document type restricted to journal articles; and search fields limited to title, abstract, and keywords in Scopus and Web of Science, while in PubMed the search was restricted to title and abstract fields

Ethical principles of transparency, methodological rigor, and academic integrity were upheld throughout the review process. Copyright and intellectual property rights of the included studies were respected through appropriate citation and referencing. The review was registered in PROSPERO under the identification number CRD42025642104.

A previous review covering the period 2010–2020 [28] identified that peer-assisted learning programs provide benefits in the learning environment, the development of support networks, and confidence in acquired knowledge. However, its findings also highlight the need to further examine the methodological characteristics that influence learning outcomes. In this context, the present study specifically focuses on clinical simulation and limits its analysis to the last five years in order to update the most recent evidence on peer tutoring in healthcare simulation.

The inclusion criteria were defined according to the PICO elements (Population, Intervention, Comparison, Outcome), which also guided the formulation of the research question: What is the evidence regarding the implementation of peer tutoring in clinical simulation for the development of technical and non-technical skills among health sciences students, based on experimental and quasi-experimental intervention studies? The components of the PICO framework are described in Table 2.

Table 2.

PICO elements

Elements	Description
Population (P)	Undergraduate students enrolled in health sciences programs who participate in clinical simulation activities.
Intervention (I)	Implementation of peer tutoring or Peer-Assisted Learning (PAL) programs in clinical simulation settings. Studies were included when peer tutoring involved advanced students supporting the development of technical and non-technical skills among junior students.
Comparison (C)	Other teaching methods without the participation of peer tutors, or different modalities of peer tutoring.
Outcome (O)	Changes in participants’ technical and non-technical skills.

The first phase of the systematic review was conducted following the PRISMA guidelines [29]. The final database search was performed on December 3, 2025. After applying filters for publication year and document type, 834 records remained. Following the removal of duplicates, 407 records were retained.

In the second phase (screening), titles and abstracts were reviewed, and studies that clearly did not meet the inclusion criteria were excluded. Eligible studies were those with experimental or quasi-experimental designs that explored peer tutoring experiences in clinical simulation, involved undergraduate students, and included the participation of at least one senior student acting as a peer tutor. As a result of this process, 21 articles were selected. Subsequently, full texts were reviewed, and only those that met all inclusion criteria were retained for the final analysis.

After full-text screening, 11 articles were included in the final analysis (Fig. 1). Data extraction was conducted independently by four researchers. Inter-rater agreement was assessed through a comparison of the data extracted by each reviewer, ensuring consistency in variable coding and in the interpretation of the inclusion criteria. When discrepancies were identified, they were discussed in consensus meetings until agreement was reached. This process ensured consistency, reliability, and methodological rigor in data extraction. In mixed-methods studies, only the quantitative component was included.

Fig. 1.

PRISMA flow diagram of the article selection process [29]

Given the heterogeneity in study designs, interventions, outcome measures, and reporting methods, a meta-analysis was not feasible. Therefore, a narrative synthesis of the results was conducted.

The synthesis followed a formal combined approach of framework synthesis and thematic analysis. The framework synthesis was based on the data extraction matrix and the theoretical models of Kirkpatrick and Simulation Zones, while the thematic analysis allowed for the identification of relevant themes rather than recurrent patterns, given that only 11 studies were included. However, to facilitate the analysis, findings that were consistently reported in at least three studies were considered patterns. Recurrences in the results were analyzed, specifically regarding technical and non-technical skills, as well as the characteristics of the interventions. No directly contradictory findings were identified among the included studies.

The synthesis was structured based on the categories defined in the data extraction table (Supplementary Material 1) to analyze the following information: country, author, year, title, participants, study design, interventions, measurements, definition of peer tutoring, tutor roles and responsibilities, required tutor profile, theoretical framework supporting the tutoring approach, definition of simulation, academic program, technical and non-technical skills addressed, academic year or semester in which the intervention was implemented, characteristics of peer tutoring, number and duration of sessions, results and main findings, conclusions, other relevant contributions, limitations, and implications for future research.

Additionally, the results were analyzed using the levels of Kirkpatrick’s model to classify the effects of the interventions in terms of learning, changes in skills and attitudes, and their potential impact on practice. The simulation zone was analyzed according to the framework proposed by Roussin [20] and Díaz-Guio [27].

This table enabled the organization, comparison, and interpretation of findings, identifying patterns, similarities, and differences across the included studies.

Systematic literature review flow diagram

Two tools were applied to evaluate the risk of bias: ROBINS-E for quasi-experimental studies (Table 3) and RoB-2 for experimental studies (Table 4).

Table 3.

Risk of bias assessment using the ROBINS-E tool. [30–38]

The judgments are as follows: Low risk of bias (green), Some concerns (yellow), High risk of bias (orange), and Very high risk of bias (red). The domains are defined as follows: Domain 1: Risk of bias due to confounding factors. Domain 2: Risk of bias arising from the measurement of exposure. Domain 3: Risk of bias in the selection of participants for the study (or for analysis). Domain 4: Risk of bias due to post-exposure interventions. Domain 5: Risk of bias due to missing data. Domain 6: Risk of bias in the measurement of outcomes. Domain 7: Risk of bias in the selection of the reported result

Table 4.

Risk of bias assessment using the RoB-2 tool. [39, 40]

The judgments are as follows: Low risk of bias (green), Some concerns (yellow), and High risk of bias (red). N/A = Not applicable.The domains are defined as follows: Domain 1a: Risk of bias arising from the randomization process. Domain 1b: Risk of bias arising from the timing of identification or recruitment of participants in a cluster-randomized trial. Domain 2: Risk of bias due to deviations from intended interventions (effect of assignment to intervention). Domain 3: Risk of bias due to missing outcome data. Domain 4: Risk of bias in the measurement of the outcome. Domain 5: Risk of bias in the selection of the reported result

The ROBINS-E analysis revealed that, among the quasi-experimental studies, there was a high level of concern regarding bias due to confounding factors. Conversely, the risk of bias related to exposure measurement was generally low. Regarding participant selection, most studies presented some concerns. In relation to bias due to post-exposure interventions and bias due to missing data, the studies predominantly showed low to moderate risk (some concerns). For bias in outcome measurement, a high risk of bias was identified. Finally, for bias in the selection of the reported result, some concerns were mainly observed.

The RoB-2 analysis indicated that, for experimental studies, the risk of bias in the selection of the reported result was low, while some concerns were noted across most of the other domains.

Results

Study characteristics

Across the 11 articles analyzed, the total sample included 860 students, with individual study samples ranging from 31 to 226 participants. A total of 107 peer tutors participated across the included studies, with numbers varying from 1 to 47 per study.

Between the studies 82% were quasi-experimental. Four studies focused on developing practical clinical skills through simulators or virtual reality [35, 36, 39, 40]. Three explored how to guide reflection after simulation and examined feedback and debriefing models [31, 37, 38]. Two emphasized patient interaction and interpersonal skills [30, 34], while the remaining two implemented structured near-peer teaching designs within simulated scenarios—one based on the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model [33] and another using the Objective Structured Clinical Examination (OSCE) framework [32].

Characteristics of the Interventions

Measurements focused on technical skills such as laparoscopic surgery, lumbar puncture, cardiovascular examination, aseptic technique and suprapubic catheter insertion [35, 36, 38–40], as well as non-technical skills including self-confidence, general self-efficacy, disposition toward critical thinking, communication, problem-solving, clinical reasoning and motivation [30, 31, 33–36, 38], alongside conceptual learning and information retention [31, 34–36].

Some studies focused on the quality of feedback or debriefing [31, 37, 38], while others examined perceptions of training programs of technical and non-technical skills [30, 32–36, 39, 40].

The simulation zones in which peer tutors participated were: Zone 0 [34, 35, 39], Zone 1 [32, 33, 36–40], Zone 2 A [30], and Zone 2B [31, 33].

According to Kirkpatrick’s evaluation model [26], the highest level achieved among the reviewed studies was Level 2, reported in nine out of ten studies, which assessed knowledge, skills, and attitudes [31–40]. The remaining study reached only Level 1, as it evaluated participant reaction exclusively [30].

Most studies were conducted within medical education, while three were in nursing, one in occupational therapy, and one in physiotherapy. The tutoring modalities varied: some involved a single short session focused on specific skills [31, 35–39]; others comprised a single extended session integrating theory, simulation, and practice [34, 40]; and several implemented multiple tutoring sessions [30, 32, 33]. Regarding the academic stage at which the interventions were implemented, four programs were conducted in the third year [31, 32, 34, 40], three in the first year [37–39], one in the second year [30], one across the fourth [38] and fifth years [35], and one did not specify the academic level [36]. The frequency and duration of tutoring sessions varied considerably, ranging from 1 to 12 sessions, with durations from 10 min to 3 h per session.

Definition, role, and functions of the peer tutor

Regarding conceptual definitions of peer tutoring, some studies did not provide an explicit definition but described it as the role of advanced students teaching their peers [33, 34, 36]. Other studies referred to Peer-Assisted Learning (PAL), defined as practical teaching among students at different academic levels [35]. Additional terms such as Near-Peer Teaching (NPT)—where tutors possess greater experience or a more advanced level—were also identified [30–32, 39]. Likewise, the concept of peer-led learning appeared, emphasizing experiences in which the advanced student leads the teaching process [37, 40]. Among these conceptual approaches, Peer-Assisted Learning (PAL) emerged as the most frequently cited and recognized term within the field of medical education [30, 34, 40]. Another study defined it under the concept of peer feedback (PF) as a form of peer learning in which students reflect on the practice of an academic subject and performance standards [38].

The profile of the peer tutor in clinical simulation was characterized by the selection of outstanding students from advanced courses who, although not yet experts, were trained to fulfill their role [30–40].

The roles of peer tutors identified across the included studies can be grouped into five main dimensions: (1) teaching and practicing technical skills, (2) facilitation of learning in safe environments, (3) provision of structured, constructive, and real-time feedback, (4) design, leadership, and management of activities, and (5) support beyond technical aspects. These dimensions reflect the multifaceted nature of the peer tutor role, which extends beyond knowledge transmission to include guidance, feedback, leadership, and the promotion of a supportive learning environment.

The specific roles and functions of peer tutors identified in the reviewed studies are summarized in Table 5.

Table 5.

Roles of the peer tutor in clinical simulation

Peer Tutor Roles	Description	Simulation Zones	References
1. Teaching and practicing technical skills	Supporting peers in learning specific clinical procedures.	Zone 0; Zone 1	[35, 36, 39, 40]
2. Facilitation of learning in a safe environment	Creating a climate of trust, motivation, and psychological safety for learning.	Zone 0; Zone 1; Zone 2B	[31, 33, 34, 36–39]
3. Structured, constructive, and real-time feedback	Providing clear, constructive, and timely feedback to enhance learning outcomes.	Zone 0; Zone 1; Zone 2B	[32–34, 36–40].
4. Design, leadership, and management of activities	Planning, coordinating, and leading learning dynamics or simulation sessions.	Zone 0; Zone 1; Zone 2 A	[30, 34, 35, 38, 40].
5. Support beyond technical aspects	Providing motivation, study strategies, and sharing personal learning experiences.	Zone 1; Zone 2B	[31, 33, 37, 38].

The theoretical frameworks supporting the implementation of peer tutoring are primarily grounded in social and cognitive congruence, Bandura’s social learning theory, and the status–power theory, which suggests that proximity in age and experience reduces hierarchical barriers and promotes a more equitable learning environment [30, 31, 33, 36–38].

In addition, the protégé effect is highlighted—a phenomenon in which tutors deepen and enhance their own understanding of course content as they prepare to teach it to others [37].

Regarding the concept of clinical simulation, some studies did not provide an explicit definition [32, 36, 37]. Others defined it as the recreation of real clinical scenarios [31, 33, 38], or as an artificial representation of real-world processes characterized by immersion, realism, and fidelity for educational purposes [30, 39, 40]. Some studies also referred to the use of virtual learning environments for simulation-based teaching [34, 35]. All definitions indicate that simulation aims to foster the development of skills [30, 31, 33–35, 38–40].

Main findings, limitations, and future research directions

The main findings of the reviewed studies suggest that peer tutoring promotes the development of both technical and non-technical skills. Reported improvements included enhanced speed, confidence, and procedural knowledge in laparoscopic tasks [36], increased accuracy in lumbar puncture technique [39], and improved cardiovascular examination performance, with a significant reduction in errors [40].

Regarding non-technical skills, increases were observed in self-efficacy [33], self-confidence [31, 32], self-perception of learning [37] and reflective abilities [38]. Peer tutoring also contributed to higher student satisfaction [30, 33, 37], greater motivation [30], and the creation of a more relaxed learning environment that helped reduce anxiety [33].

Additional findings highlighted both pedagogical and economic advantages, as simulation through Peer-Assisted Learning (PAL) was reported to be more cost-effective [36, 39]. However, concerns were raised regarding its sustainability, given the time required, reliance on volunteer participation [37], and the additional time investment needed for tutor training [31]. Peer tutoring was also found to enhance psychological safety, contributing to lower anxiety levels in demanding learning environments [33, 35, 38].

Beyond student outcomes, several studies also identified benefits for the tutors themselves, including the development of confidence, autonomy, leadership, teamwork skills and greater empowerment [30, 32, 38].

The reviewed studies also reported several challenges, particularly regarding the lack of prior experience among some peer tutors, highlighting the need for specific training before assuming the tutoring role [34, 40].

Of the 11 studies, 9 reported having provided training for peer tutors. These trainings focused on the standards of best practice established by the International Nursing Association for Clinical Simulation and Learning (INACSL) [31], including brief online modules on adult education, simulation frameworks, feedback, and time management [30, 37, 38]. Other training initiatives focused on the practice and teaching of skills, as well as on preparing students for their roles as peer tutors [33, 35, 36, 39, 40].

In terms of limitations and future research directions, several studies acknowledged that small sample sizes and potential selection bias limited the generalizability of their findings [9, 31, 35, 36, 38]. Additional methodological limitations included the non-random allocation of participants, implementation within a single institution, and the absence of post-intervention follow-up [32, 33, 37, 40]. Some studies also identified baseline group differences [37] and an unequal training time load in intervention groups that was not controlled for in the analysis [40].

Based on these limitations, the authors recommend that future studies include larger sample sizes, adopt randomized designs, and incorporate longitudinal follow-up to evaluate the lasting effects of peer tutoring [32, 33, 37, 40]. They also suggest the need for greater experimental control, the use of more objective assessment tools, and the inclusion of standardized faculty supervision during implementation [37, 40]. Furthermore, they recommend employing qualitative methods to explore the experiences of both tutors and students [38].

Discussion

Characteristics of the Interventions

The reviewed interventions were characterized by high heterogeneity in terms of duration, frequency, academic timing, and type of simulation. Most were implemented within medical education, although experiences were also reported in nursing, occupational therapy, and physiotherapy programs. The most frequently represented simulation zone was Zone 1 (as described by Roussin [20], and Díaz-Guío et al., [27], indicating a predominance of scenarios focused on the development of skills and feedback processes.

Quasi-experimental designs predominated over experimental ones, with a notable absence of longitudinal follow-up. Most studies reached Level 2 of Kirkpatrick’s model, indicating that they primarily assessed knowledge, skills, and attitudes, without evaluating sustained behavioral change or impact on clinical practice.

A deeper analysis of heterogeneity reveals important patterns that may influence the interpretation of the findings. The predominance of studies in medical education may reflect a greater curricular integration of simulation in these programs, which limits the transferability of the findings to other disciplines. Likewise, although intervention duration varied substantially (from 10 min to 3 h), it is not possible to determine clearly whether this variation influenced the reported effects, given the limited number of included studies and the heterogeneity in study designs, outcomes, and intervention modalities.

Definition, role, and functions of the peer tutor

Peer tutoring in clinical simulation is grounded in the principles of social and cognitive congruence between the tutor and the tutee. This proximity in age, academic level, and learning experiences fosters a climate of empathy, trust, and equality, which students perceive as facilitators of their learning [35, 36]. The peer tutor’s role involves supporting the training of technical skills while simultaneously acting as a co-learner, providing feedback and promoting motivation—processes that reinforce both their own learning and the development of pedagogical competencies and empowerment.

The peer tutor’s role focuses on teaching clinical procedures, facilitating safe learning environments, providing feedback, and leading formative activities. These elements suggest that peer tutoring extends beyond the simple transmission of knowledge, as it also promotes the development of social skills and emotional support competencies within the learning process.

Peer learning leverages cognitive and social congruence among learners, creating safe and egalitarian environments that foster camaraderie, shared purpose, and mutual support [7, 8] Tamachi et al., [12]. These environments encourage active participation, belonging, and skills development. Within the notion of belonging, students are able to contribute authentically and integrate into the workplace community, supporting identity maturation and social integration [9]. The proximity between peer tutors and learners appears to facilitate more open communication, reduce hierarchical barriers, and promote active engagement, thereby enhancing both technical and non-technical skill development.

Medical students who experience belonging report greater engagement, psychological safety, and capacity for growth in clinical settings. Psychological safety—characterized by high-quality relationships, absence of social hierarchy, and learner-driven agendas—also facilitates belonging and supports learning and inclusion within clinical teams [33, 35].

Main findings, limitations, and future research directions

The studies included in this review reported benefits in both technical skills (e.g., laparoscopy, lumbar puncture, cardiovascular examination) and non-technical skills such as self-confidence, self-efficacy, motivation, and communication. These findings suggest that peer tutoring strengthens immediate clinical performance while fostering psychological safety and an active learning disposition among students.

Peer-Assisted Learning (PAL) demonstrates strong potential as a cost-effective educational strategy in health professions education. However, some studies have raised concerns about its sustainability, given its reliance on voluntary participation and the additional time investment required for tutor training [31]. At the same time, benefits for the tutors themselves have been observed, including the development of autonomy, leadership, and interpersonal competencies that complement their professional profiles.

Limitations of this review and future research lines

This review identified several recurring limitations: (1) Small sample sizes and potential selection biases, (2) non-randomized designs and a lack of rigorous control groups, 3. Single-institution settings, which limit the generalizability of results, and 4. A lack of longitudinal follow-up, preventing the evaluation of skill retention and long-term professional impact.

The interpretation of these findings should be considered in light of the identified risk of bias. Several studies were classified as having a high risk of bias or presenting some concerns, particularly in relation to confounding and outcome measurement.

This reduces the certainty of the evidence and may lead to an overestimation of the effects of peer tutoring. Furthermore, the predominance of quasi-experimental designs limits causal inference.

Future research should therefore aim to include larger sample sizes, adopt experimental designs with random assignment, and incorporate medium- and long-term evaluations. Moreover, the standardization of assessment instruments and the integration of hybrid models—combining peer tutoring with expert faculty supervision—are recommended to enhance methodological rigor and educational impact.

It is also suggested that formal peer tutor training programs be implemented within undergraduate simulation curricula. Such initiatives could optimize faculty resources, strengthen collaborative learning, and promote the continuity of skill development in high-demand academic settings. Furthermore, the structured development of pedagogical competencies among advanced students could enhance the sustainability of the model, fostering leadership, autonomy, and psychological safety throughout the tutoring process.

Conclusions

The novelty of this review lies in the integration of Simulation Zones and Kirkpatrick’s model as complementary analytical frameworks, providing a more comprehensive and structured understanding of educational interventions in clinical simulation. This approach enables not only the analysis of learning outcomes but also the characterization of the educational contexts in which peer tutoring is implemented.

The analyzed evidence suggests that peer tutoring in Simulation-Based Education (SBE) contexts may contribute to the improvement of both technical and non-technical skills among health sciences students. However, these observations should be interpreted with caution due to the limited number of included studies and the high heterogeneity in terms of disciplines, intervention duration, types of simulation, and outcome measures. In this sense, although some studies report benefits in the acquisition of procedural competencies and the strengthening of non-technical skills, it is not possible to establish firm or generalizable conclusions.

In clinical simulation, the peer tutor functions as a facilitator of learning, capable of creating an environment of trust and psychological safety that promotes active participation and reduces student anxiety. Furthermore, tutors gain additional benefits by reinforcing their own learning, enhancing leadership skills, and developing pedagogical competencies.

Given the methodological limitations identified across the included studies, future research should employ larger samples, adopt more rigorous experimental designs, and include medium- and long-term evaluations to assess the impact of peer tutoring on clinical performance and professional competence.

Regarding the limitations of this review, publication bias could not be formally assessed, as a meta-analysis was not feasible due to the high heterogeneity in study designs, interventions, outcome measures, and reporting methods among the included studies. This heterogeneity prevented the establishment of a common framework for comparison and limits the generalizability of the findings. Consequently, the potential overrepresentation of studies with positive results cannot be ruled out.

Additionally, this review may be affected by the temporal restriction to studies published between 2020 and 2025 and the exclusion of qualitative components in mixed-methods studies. The temporal restriction was established to synthesize recent and up-to-date evidence, considering the methodological and technological advances in clinical simulation and peer tutoring in recent years.

The search strategy was limited to three major databases (Web of Science, Scopus, and PubMed) to ensure the inclusion of studies indexed in high-quality and widely recognized scientific sources. However, this decision may have excluded relevant studies indexed in specialized databases such as ERIC, CINAHL, or PsycINFO, particularly in the fields of education and social sciences. Furthermore, the exclusion of grey literature was intended to prioritize peer-reviewed studies and ensure a consistent methodological standard; however, this decision may have introduced publication bias by favoring the inclusion of studies with positive findings.

Although no studies reported negative effects, the predominance of positive findings should be interpreted with caution, considering the methodological limitations. Furthermore, the included studies did not reach Levels 3 or 4 of Kirkpatrick’s model.

In summary, the combination of Simulation-Based Education (SBE) and peer tutoring may be potentially beneficial, with pedagogical foundations consistent with social learning theory. However, given the limited evidence base and its heterogeneity, these conclusions should be considered preliminary. Further studies are needed to more accurately determine its effectiveness, as well as its potential impact on teaching and learning processes in the education of health professionals.

Abbreviations

SBE

Simulation-based education

PICO

Population, intervention, comparison, outcome

PAL

Peer-assisted learning

Authors’ contributions

All authors made substantial contributions to the conception and design of the study, literature search and selection, data extraction and analysis, and drafting and critical revision of the manuscript. All authors read and approved the final version of the manuscript.

Data availability

All data generated or analyzed during this study are included in this published article and its supplementary materials. Additional information is available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicableAvailability of data and materials: All data generated or analyzed during this study are included in this published article and its supplementary materials. Additional information is available from the corresponding author upon reasonable request.Competing interests: The authors declare that they have no competing financial or non-financial interests.Funding: Project 2024-030: Peer Tutoring in Clinical Simulation for strengthening technical, non-technical, and metacognitive skills in nursing, funded by the USS 2024–2025 Competitive Fund for Innovation and Research in University Teaching from the Center for Research in Higher Education of the Academic Vice-Rectorate at Universidad San Sebastián.Authors’ contributions: All authors made substantial contributions to the conception and design of the study, literature search and selection, data extraction and analysis, and drafting and critical revision of the manuscript. All authors read and approved the final version of the manuscript.Acknowledgement: The authors thank Universidad San Sebastián for the development of this study.

Competing interests

The authors declare no competing interests.