Research on the effectiveness of virtual simulation in Interprofessional collaboration:A meta-analysis

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Research on the effectiveness of virtual simulation in Interprofessional collaboration:A meta-analysis

https://doi.org/10.21203/rs.3.rs-2409766/v1

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With the development of science and technology and the improvement of education level, the importance of virtual simulation teaching has been paid more and more attention. Virtual simulation makes up for the shortcomings of traditional practical teaching and provides strong support for interprofessional practical teaching. To explore the effectiveness of virtual simulation in interprofessional collaboration, a meta-analysis was performed. The Review Manager5.4 Software was used to perform the traditional meta-analysis. A systematic search of databases was conducted and a total of 14 studies were included in the meta-analysis.

The conclusions are as follows: (1) Virtual simulation can significantly promote interprofessional collaboration. The overall effect value (Hedges's g) is 1.26, (95% CI: 0.54–1.26, p < 0.001). (2) Both the number of professions and the intervention duration affect the effect of interprofessional collaboration.

This study provides insight into the efficacy of virtual simulation as a pedagogy and contributes to our understanding of the educational value of service learning for virtual simulation.

Virtual simulation

Interprofessional collaboration

effectiveness

Meta analysis

Professional knowledge in many fields is often needed in real work scenes to solve complex problems in society and in teams. Interprofessional collaboration is challenging, due to the different knowledge bases and related working methods of each professional grouping involved (Arja Tuulikki Haapakorpi, 2020).

Virtual simulation as a teaching method has attracted more and more attention. Due to the influence of COVID-19, it may be challenging to provide students with a realistic interprofessional learning experience. The traditional practice teaching mode is fixed and difficult to apply, and the application of virtual simulation technology in interprofessional education makes up for the shortcomings of traditional practice teaching and has unlimited potential.

However, because of the importance of preparing students for interprofessional practice, especially during the pandemic, it was necessary to create new approaches to provide meaningful learning interprofessional experiences (Bennie et al., 2022). The application of virtual teaching provides strong support for the cultivation of skilled talents and interprofessional practice teaching. Virtual simulation environment is equipped situational, interactive, sharing, and interesting characteristics. It is helpful for students to better understand the real situation, standardize the operation methods, stimulate their interest in learning, promote efficient team cooperation, and cultivate students' interprofessional competencies.

Showstark M, et al. (2022) suggested that there is another possibility for the improvement of interprofessional education—the integration of virtual interprofessional education (VIPE). COVID-19 has accelerated the application of virtual interprofessional education. By adopting this method, more students can be enrolled whose self-cultivation scheme does not involve interprofessional education, but only need electronic equipment and access to the network. Interprofessional virtual education is expected to break the barriers of collaboration and cultivate outstanding talents without regional restrictions.

Therefore, it is necessary to have a deeper understanding of virtual simulation as a teaching method, how it can become an effective tool for cultivating students' practice in professional courses and explore its effectiveness in interprofessional collaboration.

1.1 Interprofessional collaboration

1.1.1 Interprofessional

Baldwin (1996) combed the history of "interprofessional" and pointed out that after 1975, the word "interprofessional" was used more frequently, especially in the field of medical care practice.

The terms ‘multiprofessional learning’ and ‘interprofessional learning’ have all been referred to and are often used interchangeably. there are slight differences between them. Interprofessional learning suggests two or three professions learning together on an interactive basis, whereas multi-professional learning suggests any number of professions learning together (Rita Goble,1994).

Danielle D'amour & Ivy Oandasan (2005) proposes a new concept, that is named ‘interprofessional’ and aims to draw a clear distinction with another concept, that of interdisciplinarity. The utilization of the concept of interprofessional, which originally concerns the development of integrated knowledge in response to fragmented disciplinary knowledge. Specifically, the concept of Interprofessional concerns the development of a cohesive practice among different professionals from the same or different organizations and the factors influencing it.

Interprofessional education (IPE) is a process in which two or more professionals work and study together to improve collaboration and communication (Blakely&Biehle,2021;Mahmood et al., 2021).

The World Health Organization (WHO) defines MPE as a process in which a group of students (or workers) in health-related fields and with different educational backgrounds study together.

The premise of interprofessional education is that it does not affect the cultivation of each major, and students still need to reach a higher level of technology and knowledge in this major training.

1.1.2 Collaborative learning

Collaborative learning is the educational approach to enhance learning by using groups working together. It refers to methodologies and environments in which learners engage in a common task where individuals depend on and are accountable to each other (Chiu, M. M.,2008). Collaborative learning is based on the model that knowledge can be created within a population where members actively interact by sharing experiences and taking on asymmetric roles (Mitnik, R.et al,2009).

Under a certain incentive mechanism, collaborative learning can maximize the acquisition results of individuals and others. Teamwork and shared values help break down walls and improve process efficiency. When students share information and interact with other students' ideas, it is helpful to cultivate higher-order thinking abilities.

To better realize learners' meaning and construction of knowledge, collaborative learning needs to formulate collaborative rules and be supplemented by appropriate collaborative tools. Deep learning occurs when students are involved in constructing meaning from their learning experiences by integrating ideas, bringing personal experiences to learning tasks, using evidence to analyze claims, applying knowledge to new situations, and reflecting on the significance of content information (Rose, 2016).

1.1.3 Interprofessional collaborative practice

To achieve the learning goal of IPE, it can be achieved through planned collaborative learning practice. Interprofessional collaborative practice has been defined as a process that includes communication and decision-making, enabling a synergistic influence of grouped knowledge and skills (Kasperski M,2010).

In 2010, six health professional associations set up interprofessional educational cooperation organizations. And they identified the core competencies of interprofessional collaborative practice, including roles and responsibilities, values, interprofessional communication, and teamwork (IPEC, 2011).

To ensure the cultivation of interprofessional competencies, interprofessional learning activities need teamwork practice (Caylor, 2015). The goal of IPE is to enable students to learn how to play a role in an interprofessional team and incorporating this knowledge, skills, and values into their future practice (Greiner AC,&Knebel E,2003). In an interprofessional team, each member contributes a personalized knowledge base and specific skills and functions, keeps the communication channels open, and demonstrates common decision-making while insisting on mutual accountability (Hall & Weaver, 2001).

Barry Zucherman (1993) director of pediatrics at Boston Medical Center in the United States put forward an interprofessional collaboration model of Medical-Legal Partnership(MLP). The main content is to build a collaboration platform that integrates medicine, law, social work, and other professions, and the professional departments in the platform form a team collaboration relationship. This model was later popularized in 46 states in the United States. The value of interprofessional team collaboration has been highlighted in MLP mode.

There are important characteristics that determine team effectiveness, including members considering their roles important to the team, the open communication, the existence of autonomy, and the equality of resources (Morrison S,2007). Several factors are essential to the success of interprofessional programs and activities:

Administrative support;
Interprofessional programmatic infrastructure;
ommitted, experienced faculty;(d)Acknowledge student efforts through awards, certificates, or grades (Bridges, DianeR.et al.,2011).

Therefore, interprofessional education provides critical competencies for working in an interprofessional team.

1.2 Virtual simulation

1.2.1 Simulation

Simulation is an interactive education process in which learners engage with people, simulators, computers, or task trainers to accomplish learning goals that are representative of the learner's real-world responsibilities (Lopreiato et al., 2016).

Simulation teaching is an indispensable part of talent training, which relates to the development of talents' practical and innovative abilities.

Simulation-based learning has been gaining increasing attention from higher education and professional training in various professional domains. In higher education and professional training, simulations are often designed to help learners to acuqire how to engage in professional practices (Fischer et al.,2022).

Simulation can be an effective method of IPE experience and prepare students for practice.

1.2.2 Team simulation

Thavikulwat (2009) defines team simulations as exercises that allow participants to experience reality in an artificial environment. In other words, team simulations are simplified versions of reality.

Team-based simulation provides an authentic experiential learning activity by placing the learners in a realistic situation to prepare them for working life (van Soreen et al., 2011).

Previous studies have shown that TBS has the potential to enhance learning from the two following aspects:

(a)TBS facilitates better transfer of knowledge.

(b)TBS enhances knowledge retention (Shapira-Lishchinsky, O., 2013).

TTS is a novel learning activity that is underpinned by the tenets of theatre or drama and is designed for larger groups of students in which participants and observers have active roles in a scenario (Levett-Jones et al., 2015). TTS created opportunities for students to deliberately connect theory with practice promptly, receive immediate feedback, and enhance self-understanding through reflection (Harvey, G.2021).

1.2.3 Virtual simulation

Traditional simulation teaching has certain limitations. Students can't break through the time and space constraints but can only use limited learning resources for training, which restricts students' practical and innovative abilities.

Virtual simulation has its roots in military training pilots in World War II and continues with modern-day military medicine funding much of the research regarding virtual worlds (Foronda et al., 2013).

Virtual simulation allows users to participate in simulation activities without being in the same location and removes time-constraint barriers to successfully meeting certain IPE competencies (Jenson & Forsyth, 2012).

Virtual simulation (VS) environments improve convenience and flexibility, as well as the capacity to scale and distribute simulations widely with lower costs.

The ultimate goal of virtual simulation in teaching is to better support students' learning. Virtual teaching is based on virtual reality and other technologies, relying on rich virtual teaching resources. By using a virtual simulation system, it can bring immersion experience to students, increase interest, greatly meet students' ability training needs, enrich teaching forms and improve the learning effect.

Virtual simulation allows trainees to make and correct mistakes while exposing them to circumstances that may not easily be recreated in the real world due to ethical, financial and time concerns (Williams-Bell, F. et al. 2015).

1.3 Purpose of the study

In order to understand the effect of virtual simulation on interprofessional collaboration as a whole, this study takes the relevant empirical research results as the object, adopts a quantitative and comprehensive meta-analysis method, and deeply explores the effectiveness of virtual simulation for cross-professional collaboration, to provide a reference for designing and improving interprofessional collaborative learning.

The problem of the study is summarized as follows:

(a) Does virtual simulation effectively promote interprofessional collaboration?

(b) Is the effectiveness of virtual simulation in interprofessional collaboration affected by the number of disciplines?

(c) Is the effectiveness of virtual simulation in interprofessional collaboration affected by the duration of the experiment?

Meta-analysis is increasingly being utilized in the education field. The hypotheses of the above research were verified by meta-analysis in this study. Meta-analysis refers to the process of combining, synthesizing, or integrating results or evidence from different studies by applying quantitative methods (Zuizhi Xing, 1990). It is essential to synthesize and summarize the numerous works of literature with varying conclusions and to discover their greater significance.

2.1 Literature Search Stage

This study followed PRISMA criteria (Stovold et al., 2014). All the literature searches were conducted from January 2010 and concluded in October 2022.

The keywords are as follows: “Virtual simulation” or “Virtual Reality” or “Virtual Environment” and “Interprofessional collaboration” or “Interprofessional team training” or “Interprofessional competencies”.

A combined search of Web of Science, Science Direct, and Springer databases was conducted to retrieve 3345 papers, and the retrieved papers were imported into Zotero software to remove duplicates.

The inclusion of the literature in the meta-analysis was judged based on the following criteria:

Empirical studies must be quasi-experimental or randomized controlled trials;

Studies must be the impact of Virtual Simulation on Interprofessional Education;

Clear sample size and complete data, reporting mean and standard deviation.

Based on the above criteria, we screened the valid literature after careful reading and obtained 14 papers that met the requirements of meta-analysis.

The flow chart of the study selection process are shown in Fig. 1.

2.2 Literature Data Extraction

The literature included in the meta-analysis was coded as follows: Literature Information, Sample size, Number of professions, and Experiment duration. The results are shown in Table 1.

Table 1

Literature Information Table
No.	Author	Year	Number of professions	Experiment duration	Experimental group			Control group
No.	Author	Year	Number of professions	Experiment duration	M	SD	Sample size	M	SD	Sample size
1	Turkelson, C.et al.	2020	3	1 hour and 45 minutes	10	5.2	22	13	4	22
2	Liaw, S.Y.et al.	2020	2	3 hours	22.6	5.31	60	23.97	4.55	60
3	Liaw, S.Y.et al.	2019	6	3 days	101.5	10.5	26	90.25	9.55	26
4	Sarah O.et al.	2022	4	5 semesters	133.9	16.9	676	133.4	21.2	763
5	Yobelli A.et al.	2018	2	4 hours	92.3	9.63	27	89.7	11.03	27
6	Wei Ling Chua.et al.	2022	2	2 months	17.66	3.01	415	14.62	3.51	415
7	Nataly D. Martini,Craig S.Webster	2021	2	< 1 days	82.3	6	20	78.8	6.6	20
8	SarahPiraniac et al.	2022	3	1.5 hours	4.52	0.6	90	3.4	1.14	90
9	David W. Donley	2021	2	> 1 days	2.3	0.4	20	1.4	0.5	20
10	Amanda J.et al.	2022	2	15 weeks	4.75	0.44	23	4.38	0.65	23
11	Sok Ying Liaw RN, et al.	2022	2	2 hours	32.05	9.62	60	31.8	8.17	60
12	Janet Yuen-Ha Wong. et al.	2022	2	2 hours	94.27	10.46	62	91.26	8.75	62
13	Bak, Jacqueline Rita.	2021	2	2 years	90.4	7	41	88.2	6.8	44
14	Pamela B. Andreatta EdD.	2010	2	1 hour	16.7	3.04	7	18.5	2.62	8

2.3 Data Analysis

The main procedures for meta-analysis are as follows:

Assessment of risk bias in the literature;

Test for overall effect values and the detection of heterogeneity;

Identification of publication biases;

Sensitivity analyses.

This study used RevMan 5.4 for data analysis, and for those continuous variables, mean differences (MD) with 95% confidence intervals (CI) were calculated.

Statistical methods for Meta-analysis include the fixed effect model and the random effect model. Choice of the fixed-effects model (P > 0.1, I² < 50%) or random-effects model (0 < P < 0.1, I² ≥ 50%) based on the values of P and I².

3.1 Risk of bias

Two investigators referred to the 《Cochrane Handbook for Systematic Reviews of Interventions》to inspect the internal veracity of experiments by evaluating the possible risk of bias in the design, implementation, and evaluation of experiments. The risk of bias was evaluated in the following seven main areas:

Random sequence generation(selection bias);

Allocation concealment(selection bias);

Building of participants and personnel(performance bias);

Blindness of outcome assessment(detection bias);

Incomplete outcome data(attrition bias);

Selective reporting(reporting bias);

Other bias.

The evaluation of each indicator is divided into 3 levels: low risk of bias, unclear risk of bias, and high risk of bias. When there is a disagreement in the assessment, another reviewer (Yuxin Tang) makes the final decision. The Fig. 2 shows the risk of bias.

3.2 Overall effect value estimation and heterogeneity test

The test for heterogeneity of effect values is an important part of the meta-analysis. Heterogeneity is defined as the variability in the data that can be explained by differences between the study estimates included in the meta-analysis.

In the meta-analysis, I² was used to measure heterogeneity between studies (Thorlund et al., 2012) to test for between-group variance. The I² statistic responds to the weight of the heterogeneity component in the total variance of the effect size. (Wang, Dan et al. 2009).

I² below 25% indicates low heterogeneity, 50%-75% indicates moderate heterogeneity, and greater than 75% indicates strong heterogeneity (Ahn and Kang, 2018). As a consequence, low I² values are desirable because they indicate the consistency of the results of separate studies.

The results of the heterogeneity test are shown as a forest plot in Fig. 3. The value of I² is 90%, indicating that the study samples are of high heterogeneity. Therefore, the random effects model was chosen for data merging and the combined effect size with a 95% confidence interval was calculated.

When the effect value d < = 0.2, the effect is insignificant; d = 0.5, moderate effect; d > = 0.8, very significant effect (Cohen J,1988). From the calculated results, the overall effect value (Hedges's g) was 1.26,greater than 0.8, with a 95% confidence interval of 0.54–1.26 (p < 0.001). Twelve articles had positive results (86%) and only two articles (14%) reported negative effects. This suggests that virtual simulation has a significant contribution to interprofessional collaboration.

3.3 Publication bias

Publication bias refers to the fact that the published research literature does not systematically and comprehensively represent the total amount of research that has been done in the field. The main tests for publication bias are the funnel plot method, the cut-and-patch method, and the formula method. This study used a funnel plot method to test for publication bias. The funnel plot is a scatter plot of the estimates for each study included in the meta-analysis after considering the sample size used for each study. Symmetric funnel plots indicate no identifiable publication bias, whereas asymmetric funnel plots indicate the presence of publication bias (Sterne et al., 2005).

When there is publication bias, then the funnel plot appears asymmetric, then the distribution is skewed. To draw a funnel plot, a larger number of studies needs to be included. In principle, more than 5 points are required to proceed (Kang Deying et al. 2003). As shown in Fig. 4, the relevant research literature is distributed on both sides of the total effect size, indicating that there is little possibility of publication bias in the research on the relationship between virtual simulation and interprofessional collaboration.

3.4 Subgroup Analysis

In this study, subgroup analyses were conducted for two types of variables: the number of professions and the length of intervention.

3.4.1 Professional Quantitative Subgroup Analysis

Of the 14 studies, 9 studies were interprofessional teams of 2 majors and 5 studies were interprofessional teams of more than 2 majors. The results (as in Fig. 5) showed that the effective value for 2 specialties (MD = 1.64, 95% CI: 0.41–2.86) is greater than the effective value for more than 2 specialties (MD = 0.66, 95% CI: -0.30-1.63). As a result, the number of specialties affected the effectiveness of interprofessional collaboration.

3.4.2 Intervention duration subgroup analysis

Of the 14 studies, 8 studies had an intervention length of less than one day and 7 studies had an intervention length of more than one day. The results (as in Fig. 6) showed that the effect values for intervention length of more than one day (MD = 1.76, 95% CI: 0.57–2.95) were greater than those for less than one day (MD = 0.75, 95% CI: -0.51-2.00). Therefore, the longer the duration of the intervention was, the more significant the collaboration effect was.

3.5 Sensitivity Analysis

Since there was significant heterogeneity in the studies (> 75%), sensitivity analysis was used to examine the sources of heterogeneity and to verify the reliability of the results. In this study, we chose to eliminate the relatively poor-quality literature from the included studies and then re-run the Meta-analysis to compare whether there was a significant difference between the before- and after-combined effects. When the literature was removed from the model on a case-by-case basis, it was found, as in Fig. 7, that remove the data from Wei Ling Chua. et al. 2022 resulted in a significant reduction in heterogeneity (I² = 73%) and improved heterogeneity with a significant effect (MD = 0.89, 95% CI: 0.34–1.44). The results indicated that the literature Wei Ling Chua. et al. 2022 is the main cause of heterogeneity.

This meta-analysis, without publication bias and with acceptable stability of results. The heterogeneity of virtual simulation on interprofessional collaboration is high (I² = 90%), and the heterogeneity is improved after sensitivity analysis (I² = 73%, p < 0.0001). 14 studies were analyzed by using the method of meta-analysis and the random effect model. The purpose was to study the effectiveness of virtual simulation in interprofessional collaboration and to investigate the influence of the number of specialties and the intervention duration on the effectiveness of interprofessional collaboration in virtual simulation teaching.

Question 1: Does virtual simulation effectively promote interprofessional collaboration?

This study comfirmed the value of virtual simulation in interprofessional collaboration. The overall effect value (Hedges's g) is 1.26 (95% CI: 0.54–1.26, p < 0.001). Virtual simulation can significantly promote interprofessional collaboration. The effect values before and after sensitivity analysis were all greater than 0.8.

For the measurement of related secondary variables, a total of 7 studies reported the attitude of team collaboration, among which 6 studies improved their attitude towards interprofessional collaboration after virtual simulation, and recognized the necessity of team collaboration. Students of different majors also have a better understanding of the roles of team members.

A total of three studies have reported communication skills, all of which show that communication skills have been significantly improved in a virtual simulation. Two studies reported improved self-efficacy. The dependency relationship among team members in collaboration can enhance the self-efficacy of team members when they complete complex tasks, and then stimulate high-level cognitive activities. (Ma Zhiqiang et al., 2021). Through effective cooperation with other professional members, students have enhanced their ability to solve problems and their sense of responsibility and reflection. Students may have a high degree of acceptance and satisfaction with virtual training.

Question 2: Is the effectiveness of virtual simulation in interprofessional collaboration affected by the number of professions?

The effect value of teams with two professions (MD = 1.64, 95% CI: 0.41–2.86) is greater than that of teams with more than two majors (MD = 0.66, 95% CI:-0.30–1.63). It can be inferred that the number of team professions affects the effect of interprofessional collaboration. Virtual simulation may have more advantages in teams with fewer professions.

Group size determines the interaction among peers.(Liu, Y.&Pásztor, A., 2022. )Group size sometimes affects the effectiveness of teamwork. Communication and collaboration in a larger team are more complicated than in a smaller group. This kind of complexity may mean that more information needs to be considered in team decision-making, and team tasks are more challenging and take longer time.

Differences in professions and team roles in interprofessional teams affect team cohesion, communication efficiency, and team decision-making. If the management or collaboration is improper, it may lead to the decrease of team effectiveness.

Question 3: Is the effectiveness of virtual simulation in interprofessional collaboration affected by the intervention duration?

The duration of intervention affects the effect of interprofessional collaboration. The effect value (MD = 1.76, 95% CI: 0.57–2.95) of more than one day is greater than that of less than one day (MD = 0.75, 95% CI:-0.51–2.00). With the longer intervention time, the effect of interprofessional team collaboration may be more significant.

There are significant differences in the influence of virtual experiment teaching on the learning effect of different learning duration (Tian Yuan & Zhou Xiaolei, 2021). For freshmen, working in groups with unfamiliar peers can be challenging (Jackson D et al.2014), especially in the first few weeks of study. Students must quickly acquire communication and teamwork skills to provide follow-up learning (Tidbury, L.et al. 2020).

Virtual simulation has the function of human-computer interaction. When an interprofessional team conducts virtual simulation, it needs to interact not only with team members but also with the virtual environment. In order to achieve effective teamwork, students should establish a reliable relationship with their peers, environment, and environment. In the virtual simulation, adaptation time must be provided to students.

In recent years, the number of related studies has been increasing, which indicates that academia are increasingly interested in interprofessional collaboration based on virtual simulation.

Based on the above research results, the following implications are obtained:

(1) It is more advantageous to carry out virtual experiment teaching in higher education.

The research target of this study is college students. The World Health Organization's Action Framework for Interprofessional Education and Cooperative Practice in 2010 demosntrated that students at the undergraduate level seem to be more receptive to IPL, which may involve various initiatives, including the use of mannequins or computer games for simulation-based learning (World Health Organization,2010). The effect value of primary school students and college students in virtual simulation experiments is not as good as that of college students (Wang Cixiao et al., 2022)

Virtual simulation brings enormous advantages to higher education. Virtual simulation can create a virtual environment similar to the actual operation scene, so that participants can experience the training environment visually and audibly, and have a strong sense of immersion, which is beneficial for students to devote themselves to the collaborative process. As an auxiliary teaching tool, it can meet students' learning needs to a greater extent and is conducive to the improvement of students' autonomous learning and collaborative learning ability across professional teams.

Therefore, this study suggests integrating interprofessional knowledge into undergraduate courses and strengthening the application of virtual simulation technology in interprofessional education in higher education.

(2)Constructing the mechanism of co-construction and sharing of virtual simulation teaching resources.

Socialism emphasizes the importance of social interaction in learning. Compared to individual learning, group learning can make learners have a deeper understanding of knowledge and experience more significance. In practical situations, students often need to cooperate with people outside their major, and the opportunities for students to cooperate with students from other majors in school are very limited. A virtual simulation system can meet the collaboration needs of our school and even more students. By constructing the co-construction and sharing mechanism of virtual simulation teaching resources, the utilization rate of virtual simulation teaching resources can be improved, so as to continuously improve the quality and level of students' interprofessional collaboration.

To promote the development of virtual simulation teaching and give full play to the advantages of virtual simulation, we should strengthen the construction of an open virtual simulation resource-sharing platform, effectively integrate virtual training teaching resources, centrally manage virtual simulation resources, improve the teaching and evaluation functions of virtual simulation, and provide timely teaching feedback. By constructing an open, shared and highly immersive virtual training environment, teaching resources can be co-built and shared, thus effectively solving the problems of students' online training and forming a higher level of the construction cycle.

(3) Broaden the application field of interprofessional collaboration practice.

Interprofessional education has broad prospects. In practice, students need to have the ability to interprofessional collaboration, so as to deal with various complex problems.

In the process of literature retrieval, it is found that most of the interprofessional education in higher education is in the medical field, and some are in other professional fields, such as architecture, aviation, geography, emergency management, and so on. Other professional fields should also carry out interprofessional collaborative practice.

From the trend point of view, the barriers between disciplines will gradually be broken down, and the educational model with structural ability as its core goal will become more and more important. Universities must re-evaluate their methods in medicine, law, public health, social work, public policy, and other professions (Joel Teitelbaum &Ellen Lawton, 2017).

We need to carry out more research, including situational analysis of the feasibility of interprofessional education and the effects of interprofessional education in other fields, to promote the development of interprofessional education and interprofessional collaborative practice.

There are some limitations in this study:

This study only selected experimental or quasi-experimental studies with perfect data for analysis but did not pay attention to related qualitative research. The follow-up plan is combined with qualitative data to form a more comprehensive analysis of the effectiveness of virtual simulation on interprofessional collaboration.

The literature collected in this study is limited to published data, and unpublished literature is not collected. Although the search strategy is comprehensive, there may be other database indexes that have not been selected.

The analysis of this study is not comprehensive enough. Only English literature is selected for analysis, while other languages are not considered.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The data sets supporting the results of this article are included within the article.

Competing interests

The authors declare no conflict of interest.

Funding

Not applicable.

Authors' contributions

Xiaoyu Z contributed to the design of the study,data analysis and wrote the main manuscript text. Ying J and Yuxin T contributed to the data collection and revision of the article. All authors approved the manuscript.

Acknowledgements

Not applicable.

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No competing interests reported.

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Research on the effectiveness of virtual simulation in Interprofessional collaboration:A meta-analysis

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Abstract

Figures

1. Introduction

1.1 Interprofessional collaboration

1.1.1 Interprofessional

1.1.2 Collaborative learning

1.1.3 Interprofessional collaborative practice

1.2 Virtual simulation

1.2.1 Simulation

1.2.2 Team simulation

1.2.3 Virtual simulation

1.3 Purpose of the study

2. Methods

2.3 Data Analysis

3. Results

3.1 Risk of bias

3.2 Overall effect value estimation and heterogeneity test

3.3 Publication bias

3.4 Subgroup Analysis

3.4.1 Professional Quantitative Subgroup Analysis

3.4.2 Intervention duration subgroup analysis

3.5 Sensitivity Analysis

4. Discussion And Conclusions

5. Limitations

Declarations

References

Additional Declarations

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