Teaching Clinical Communication Skills Through virtual patient-based Learning: An Umbrella Review of Systematic Reviews

Teaching Clinical Communication Skills Through virtual patient-based Learning: An Umbrella Review of Systematic Reviews | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Teaching Clinical Communication Skills Through virtual patient-based Learning: An Umbrella Review of Systematic Reviews Matthias Kalmring, Sabine Chmelar, Philipp Greimel, Manuel Kaider, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8549978/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Background Effective clinical communication is a core component of patient-centered care. Immersive learning technologies, including virtual patients, virtual reality, and augmented reality, are increasingly used to train clinical communication skills in undergraduate health professions education. However, the existing evidence is fragmented and methodologically heterogeneous. This umbrella review synthesizes evidence on the effectiveness of immersive technologies and virtual patients for developing clinical communication skills in undergraduate medical and healthcare students and explores barriers to curricular integration and research gaps. Methods An umbrella review of systematic reviews (with or without meta-analysis) was conducted following PRISMA guidelines. Searches were performed in PubMed, ScienceDirect, CINAHL, and Cochrane Library. Eligible reviews examined immersive technologies (e.g., VR, AR, MR, XR, virtual patients) targeting clinical communication skills in undergraduate learners. Methodological quality was assessed using AMSTAR-2. No pooled meta-analysis was possible due to heterogeneity in interventions, comparators, and outcome measures. Results Nine systematic reviews were included. All were rated as critically low in methodological quality according to AMSTAR-2, limiting certainty of conclusions. Across reviews, immersive technologies showed promising short-term gains in communication performance, learner engagement, and perceived confidence compared to no intervention or traditional teaching. However, evidence for long-term retention, empathy development, non-verbal communication, and transfer to clinical practice was inconsistent. Heterogeneity in intervention design, outcome measures, and feedback structures reduced comparability and generalizability. Clinical communication Immersive technologies Virtual patients Learning Healthcare students Medical students Education Figures Figure 1 Figure 2 Background Communication is a non-linear process in which verbal and nonverbal information is actively exchanged between sender and receiver ( 1 ). It requires core skills such as active listening, empathy, trust-building, and clarity, expressed through spoken language, writing, or body language ( 2 ). In healthcare, clinical communication refers to a structured, empathic, and patient-centered framework that supports information gathering and health-related decision-making in a manner that is understandable and accessible to patients ( 3 , 4 ). Despite broad agreement on its importance, clinical communication can be understood as a multifaceted construct that is conceptualized and operationalized differently across educational and clinical contexts ( 3 – 5 ). Over recent decades, increased attention has been paid to patient education, with strong clinical communication skills now widely recognized as essential for achieving effective, patient-centered care and improved treatment outcomes. Within this context, psychosocial factors, such as cultural background, and patients’ broader lived experiences, play a crucial role in shaping clinical communication quality and, when adequately addressed are associated with higher patient satisfaction and health outcomes ( 6 – 8 ). However, the integration of these psychosocial dimensions into clinical communication training varies considerably, and such communication skills remain insufficiently developed across healthcare professions ( 9 – 12 ). To address these gaps, a variety of instructional approaches, including workshops, lectures, and standardized patient encounters have been implemented. Nevertheless, substantial heterogeneity persists in intervention design, instructional intensity, and reporting quality, limiting reproducibility and comparability across studies ( 5 , 13 , 14 ). In this context, immersive learning technologies such as virtual patients, augmented reality (AR), virtual reality (VR), and mixed reality (MR) have gained attention for their potential to create interactive learning environments and to support clinical communication training through realism, presence, and repeated practice opportunities ( 15 – 17 ). Low-immersion virtual patients typically offer structured communication scenarios ( 18 , 19 ), whereas AR or MR integrate digital elements into real-world settings ( 20 ) and high-immersion VR provides three-dimensional environments that may enhance learner engagement ( 15 ). However, existing reviews report a fragmented and heterogeneous evidence base, characterized by variability in intervention design, feedback mechanisms, and curricular integration, as well as limited evidence on long-term retention and transfer to clinical practice ( 13 , 15 , 16 , 21 ). This heterogeneity constrains the interpretability of findings and hinders evidence-informed curricular decision-making, underscoring the need for a higher-level synthesis of review-level evidence. To date, no umbrella review has synthesized the existing systematic reviews on immersive learning approaches on clinical communication skills training in undergraduate healthcare professions education. This umbrella review therefore aims to evaluate the effectiveness of immersive learning methods in fostering clinical communication skills among undergraduate learners and to identify implementation-related challenges. By consolidating the current review-level evidence, this work seeks to support curriculum development and guide future research in digital, clinical communication-focused education. Methods Umbrella reviews provide a comprehensive, narrative synthesis of evidence by consolidating findings from systematic reviews and meta-analyses addressing specific topics ( 22 ). This umbrella review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines ( 23 ) and was preregistered in the Open Science Framework (OSF) ( https://doi.org/10.17605/OSF.IO/EJ7XB ). All methods described in this manuscript were conducted in accordance with the final, updated version of the OSF-registered protocol. Eligibility criteria were defined using the PICO framework. Included were students in healthcare professions education, with no restrictions regarding age, sex, or geographic location. Systematic reviews, with or without meta-analyses, were eligible if they investigated immersive and virtual patient learning technologies, specifically VR, AR, MR or extended reality (XR), and technology-based simulations, aimed at enhancing clinical communication skills. No restrictions were applied regarding comparator interventions; therefore, systematic reviews without a comparator group were also included, which may limit the certainty with which effectiveness can be inferred. Clinical communication skills were conceptualized as an umbrella term encompassing both practical abilities and contextual dimensions of patient-provider interaction. For the purposes of this review, this includes constructs such as empathy, understanding of patient perspective, and the formulation of appropriate questions within patient-centered assessment ( 18 ). Reviews were eligible if they reported at least one outcome related to clinical communication, irrespective of whether this outcome constituted the primary focus of the review. Reviews were excluded if they addressed communication outcomes exclusively in other domains, such as interprofessional, leadership, or organizational communication. Only articles published in peer-reviewed journals were included to ensure a robust evidence base. Given that English is the predominant language in high-impact scientific publishing and higher education ( 24 , 25 ), only English-language publications were considered to ensure methodological consistency and comparability of findings. In light of evidence suggesting that approximately half of systematic reviews become outdated within 5.5 years ( 26 ); the initial search was restricted to publications published between December 31, 2019, and December 31, 2024. An update search was conducted on August 1, 2025, to ensure that the evidence base remained current. Search Strategy In March 2025, a systematic literature was conducted by the lead author using the databases PubMed, ScienceDirect, CINAHL, and Cochrane Library. Key Concepts and their respective synonyms were grouped using Boolean operator OR and combined concepts using AND . The search strategy included combinations such as: (healthcare student* OR medical student* OR health occupations student*) AND ("Health communication"[MeSH] OR interpersonal communication OR patient-provider communication) AND (immersive learning OR simulated learning OR immersive education OR immersive technologies OR educational technology) AND ("virtual reality"[MeSH] OR augmented reality OR mixed reality OR extended reality OR virtual patient). A detailed overview of the complete search strategy, including all search terms, database-specific adaptations, and applied filters, is provided in the Supplementary Materials. The search was restricted using predefined filters for publication period, language (English), and publication type (systematic reviews, meta- analysis). All retrieved records were managed using Zotero (version 7.0 for Windows). In addition, forward and backward citation tracking included systematic reviews was performed as a supplementary hand-search strategy ( 27 ). Any publications identified through this process were required to meet the predefined eligibility criteria for inclusion. Title and Abstract Screening A Microsoft Excel ( 28 ) spreadsheet was used to manage all identified articles. Two researchers independently conducted a pilot screening of titles and abstracts of a subset (20%) of the retrieved articles. The purpose of this pilot phase was to identify potential ambiguities, refine the screening criteria where necessary, and assess inter-rater reliability, in accordance with the Cochrane Handbook for Systematic of Interventions ( 29 ). During this phase, researchers had access only to the titles and abstracts and were blinded to the full texts or each other's assessments, ensuring independent and unbiased judgements. Inter-rater agreement for the pilot screening was calculated using Cohen’s kappa. Although the resulting kappa value of 0.66 indicated moderate agreement, the overall percentage agreement was very high (98.6%). This discrepancy is consistent with the Cohen’s kappa paradox, where imbalanced category distributions, where most records are classified into the same category despite substantial agreement ( 30 ). Given the high overall agreement and the satisfactory performance of the screening criteria, both researchers proceeded to independently screen all remaining titles and abstracts. Disagreements during the pilot and title and abstract screening were resolved through discussion, with a third reviewer consulted in cases of persisting uncertainty. Full Text Screening Two researchers independently retrieved and assessed the full texts of all potentially eligible articles using the predefined criteria. Blinding was not applied during the full-text screening phase, as detailed information on study characteristics (e.g., methodology, population, and interventions) was required to make informed eligibility decisions. Disagreements were resolved through discussion between the researchers. If consensus could not be reached, a third reviewer was consulted. The study selection process and the resolution of disagreements are summarized in the PRISMA 2020 flow diagram (Fig. 1 ) ( 23 , 29 ). Data Extraction A standardized data extraction form was developed using Microsoft Excel ( 28 ). For each included systematic review, the following data was extracted: study metadata (authors, year, journal, DOI, database source), review characteristics (type of review, number of included primary studies, inclusion/exclusion criteria), sample characteristics (number and type of participants, profession, demographics where available), intervention details (type of technology for clinical communication training, learning modality, duration, comparator), outcome measures (instruments for assessing clinical communication skills, primary and secondary outcomes), reported effect sizes and statistical results (Cohen’s d, Pearson’s r, standardized mean differences, confidence intervals, heterogeneity estimates) were also extracted. In addition, the methodological quality of each review was recorded using AMSTAR 2 tool ( 31 ). Data extraction was performed independently by two researchers. Extracted data were subsequently compared and discussed in a consensus meeting to resolve discrepancies. To address the risk of double counting primary studies across researchers, the Corrected Covered Area was calculated according to Pieper et al. ( 32 ). This metric quantifies the degree of overlap among primary studies and is recommended for use in umbrella reviews ( 32 ). Based on this consideration, umbrella reviews were excluded from the synthesis, as their inclusion may introduce methodological bias through duplicated evidence ( 33 ). Assessment of Bias Risk The methodological quality of the included studies was assessed using the AMSTAR 2 tool ( 31 ). The assessment was conducted by one researcher and subsequently cross-checked by a second researcher. Any discrepancies were resolved through discussion. Synthesis Given the anticipated substantial heterogeneity across included reviews, a qualitative synthesis was conducted. Extracted data were organized according to intervention type, population characteristics, outcome measures, intervention setting, and comparator intervention. To enhance reliability, data extraction and categorization were independently reviewed by two authors. Where appropriate, inductive codes were developed in addition to the predefined thematic categories. All categories were subsequently reviewed and discussed; in cases where consensus could not be reached a third researcher was consulted. Prior to finalizing the synthesis, both researchers conducted a cross-examination of interpretations to guarantee consistency, transparency, and alignment with extracted data. Data not reported in the original reviews were labeled as not reported (NR), and reviews that were marked as retracted were excluded from the synthesis. ( 31 ). Given that all included reviews were rated as critically low methodological quality, findings were interpreted with caution rather than formally weighted by quality ( 31 ).Owing to the absence of meta-analysis, statistical assessment of publication bias was not performed. Instead, potential reporting bias was evaluated qualitatively, for example by examining whether reviews exclude grey literature or selectively reported positive outcomes. Potential influences of methodological quality were explored narratively; however, meaningful comparisons across quality levels were precluded by the uniformly critically low ratings of the included reviews. Results The search strategy yielded 1,093 records, of which 10 duplicates were removed. Following title and abstract screening, 20 full-text articles were assessed for eligibility. After application of the inclusion criteria, nine systematic reviews were included in the qualitative synthesis (Fig. 1 ). Reasons for exclusion were categorized into five different aspects: 1) absence of clinical communication outcomes; 2) insufficient primary studies related to our research question; 3) use of non-eligible technologies regarding our inclusion criteria; 4) inclusion of a limited number of relevant primary studies with low coverage, which overlapped with primary studies identified in other included reviews; 5) umbrella reviews due to the risk of double counting. (Supplementary Table S1 . Full-text articles excluded with reasons). Overlap of primary studies across the included systematic reviews was assessed using the Corrected Covered Area (CCA). The calculated CCA was 0.9%, indicating slight overlap and suggesting a minimal risk of double-counting bias within the synthesized evidence base ( 32 ). Overview of Included Reviews We included eight systematic reviews and one meta-analysis published between 2020 and 2025. Together, these studies provided a broad evidence base on the effectiveness of immersive and VP-based educational interventions for the development of clinical communication skills in undergraduate health professions education. The included reviews focused on undergraduate students across a range of healthcare disciplines, including pharmacy (n = 1571), medicine (n = 5359), nursing (n = 5170), psychology/psychiatry (n = 5904), and physiotherapy (n = 309). Learners were at different stages of undergraduate education, from first-year to the final-year students. Most primary studies originated from the systematic reviews are from the United States, followed by Australia and several European countries (e.g., United Kingdom, Netherlands, and Denmark), with a smaller proportion conducted in Asia and South America. Across the included reviews, a wide range of immersive and VP-based technologies were examined. Most interventions involved low- to medium-immersion VP approaches delivered via web-based simulation platforms, interactive VP serious games, or VR-based simulations ( 18 , 19 , 34 , 35 ). High-immersion VR interventions additionally incorporated virtual ward environments and contextualized clinical settings ( 36 ). Rodda et al. ( 37 ) included a heterogeneous set of immersive interventions, ranging from VR- and AR-based symptom simulations to virtual patient systems with predefined response formats, while one meta-analysis and one systematic review specifically focused on AR, VR, and metaverse-based simulations ( 20 , 38 ). One review included virtual simulation-based education combining 2D elements (e.g., photos, videos) and 3D-video, and sensory stimuli ( 39 ). Interventions were implemented across diverse educational contexts, including university-based courses, clinical training environments, medical practices, and community pharmacy settings. Comparator conditions varied widely and included no intervention, traditional or alternative teaching methods, real patient encounters, non-VR simulation formats, or were not reported. Several reviews also included studies without comparator groups. The effectiveness of immersive technologies was examined across multiple clinical communication-related learning scenarios, such as counseling encounters situations, clinical consultations, suicide and mental health risk assessments, routine clinical visits, and the delivery of unfavorable or sensitive information to patients and their families ( 18 , 19 , 34 – 37 ). In addition, VR-based interventions were used to simulate patient perspectives associated with conditions such as dementia or schizophrenia ( 37 ). A wide range of outcome measures were employed to assess communication-related learning outcomes. These included self-assessment instruments, course evaluations, and self-developed tools ( 18 , 19 , 34 , 39 ). Several reviews reported the use of Objective Structured Clinical Examinations (OSCEs) ( 40 ) and established communication scales (e.g., Empathic Communication Coding Scheme (ECCS)) ( 18 , 19 , 36 – 38 ). Qualitative methods, including interviews and focus groups were also applied in some reviews ( 34 , 36 ). One review did not report specific outcome instruments and instead relied primarily on self-reported student perceptions and course evaluations ( 35 ). An overview of the study characteristics is presented in Supplementary Table S2 , with a visual summary of outcome variability illustrated in the harvest plot (Fig. 2 ). Risk of Bias in Studies The methodological quality of the included systematic review was assessed using AMSTAR 2 tool ( 31 ). All nine reviews were rated as critically low in quality due to shortcomings in several critical AMSTAR 2 domains ( 2 , 4 , 7 , 9 , and 13 ). The most frequent limitations included insufficient justification for excluded studies and incomplete reporting of search strategies. In addition, most reviews conducted only partially comprehensive literature searches and did not adequately consider the potential impact of risk of bias when interpreting their findings. Further methodological weaknesses included the absence of preregistered protocols, a lack of reporting on protocol amendments, and limited transparency regarding exclusion procedures. Although some of the included reviews reported external funding, all authors and contributors declared no conflict of interest. Detailed AMSTAR 2 item-level ratings are presented in Table 1 . Table 1 AMSTAR 2 Item ( 1 – 16 ) evaluation of the included systematic reviews Systematic Review 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Lee et al. ( 19 ) - - + ± + + - - - + Ø Ø - + Ø + Jensen et al. ( 18 ) + + - - + - - ± - - Ø Ø - - Ø + Phanudulkitti et al. ( 35 ) - - - - + + - - - - Ø Ø - - Ø + Cho & Kim ( 20 ) + + + ± + + - - + + + + - + + + Dong et al. ( 36 ) + - - ± + + - - - - Ø Ø - - Ø - Chae et al. ( 39 ) + - + ± + + - ± - - Ø Ø - + Ø + Richardson et al. ( 34 ) + - + ± - - - - - - Ø Ø - - Ø + Alsharari et al. ( 38 ) - - - - + + - ± ± - Ø Ø - + Ø + Rodda et al. ( 37 ) + ± - - + + + ± + - Ø Ø - - Ø - Note. AMSTAR-2 item-level ratings are shown for items 1–16. + = yes; ± = partial yes; - = no; Ø = not applicable. Two reviewers independently rated each review; disagreements were resolved by consensus (or third reviewer). Primary Outcomes For screen-based VPs, four reviews reported mixed effects on clinical communication outcomes. Lee et al. ( 19 ) identified improvements in such communication skills and selected clinical outcomes among medical students; however, non-verbal communication components were often insufficiently represented, and effects on empathy were weaker compared with interactions involving real patients. Jensen et al. ( 18 ) reported advantages over no intervention or traditional teaching methods, but no superiority compared with non-technology-based simulations approaches; moreover, students frequently perceived VPs as lacking realism. Phanudulkitti et al. ( 35 ) observed positive effects on pharmacy students’ confidence and consultation skills, although the absence of comparator interventions limits the interpretability of effectiveness. Richardson et al. ( 34 ) corroborated these findings in simulated pharmacy consultations settings, highlighting experiential learning benefits alongside persistent technical and usability barriers. Across the included reviews, VR and AR interventions were more frequently associated with positive outcomes than low-immersion methods. Cho and Kim ( 20 ) identified a moderate effect in favor of VR/AR compared with traditional formats, although heterogeneity was high. Dong et al. ( 36 ) identified measurable improvements in clinical communication skills among nursing students but noted persistent limitations regarding the authenticity of patient interaction. Similarly, Rodda et al. ( 37 ) reported gains in learner engagement, attitudes, and perceived competence among medical and pharmacy students. Despite these positive findings, technical limitations and usability challenges were consistently reported across reviews. For simulation-based education with mixed levels of immersion, Alsharari et al. ( 38 ) reported improvements in both communication skills and clinical competence among nursing students when compared with conventional pre-clinical practice. However, variability in study quality limited certainty of the evidence. Similarly, Chae et al. ( 39 ) found virtual simulation interventions to be beneficial for enhancing empathy and cultural awareness in medical and healthcare students. Secondary Outcomes – Barriers For screen-based VPs, reported barriers included limited authenticity resulting from insufficient integration of non-verbal communication ( 19 , 36 ), students’ perceptions of unrealistic interactions ( 18 ), high institutional resource requirements ( 35 ), and technical challenges such as software glitches and navigation difficulties ( 34 ). For VR/AR and Metaverse-based interventions, scalability emerged as a key challenge. Cho and Kim ( 20 ) highlighted contextual barriers related to geographic and institutional variability, while Dong et al. ( 36 ) emphasized persistent concerns regarding the authenticity in VR-based teaching. Rodda et al. ( 37 ) reported heterogeneous student experiences, including usability issues, which negatively affected acceptance of immersive learning technologies. In the context of mixed-immersion simulation-based education, Chae et al. ( 39 ) identified substantial heterogeneity in outcomes as a major research gap. Alsharari et al. ( 38 ) did not report specific implementations within the included primary studies. Collectively, these findings underscore the need for more systematic evaluation of curricular challenges across immersive learning approaches. Strength of Evidence All nine included reviews were rated as critically low in methodological quality according to the AMSTAR 2 tool, indicating that the overall strength of evidence is limited and that findings should be interpreted with caution. Despite these methodological limitations, several consistent patterns emerged across the reviews. Interventions using VR/AR and metaverse-based approaches were frequently associated with positive effects on clinical communication skills, empathy, and learner engagement. Notably, two out of three systematic reviews investigated the effects against a comparator intervention ( 20 , 36 ). However, confidence in these findings remains low due to the substantial heterogeneity in intervention design, outcome measures, and study populations. Screen-based VP interventions demonstrated mixed results. While these approaches were generally superior to no intervention, they showed no clear advantage over non-technology-based simulation methods, particularly with regards to empathy and non-verbal communication skills. For simulation-based education incorporating mixed immersion, potential benefits were reported. However, the corresponding reviews consistently emphasized methodological weaknesses in the underlying studies. Overall, immersive and VP learning technologies appear promising for development of clinical communication skills. Nevertheless, the critically low methodological quality of the included reviews necessitates cautious interpretation. Future research should prioritize rigorously conducted systematic reviews with transparent methodologies, standardized outcome measures, and comprehensive reporting to strengthen the evidence base and clarify the conditions under which immersive learning technologies are most effective. Discussion This umbrella review examined how effectively immersive technologies and virtual patient (VP)-based approaches support the development of clinical communication skills in undergraduate healthcare education. The synthesis of recent systematic reviews provides an integrated overview of reported effectiveness, highlights key implementation challenges, and identifies gaps that currently limit the strength of conclusions. Overall, the findings offer a structured foundation for interpreting the current evidence base and informing priorities for future research and curriculum design. Although all included systematic reviews were rated as critically low according to AMSTAR-2 ( 31 ), this finding should not be interpreted as evidence against the educational value of immersive learning technologies. Rather, it indicates that the current evidence base lacks the methodological robustness needed to draw high-confidence conclusions about effectiveness or superiority over established teaching methods. In this context, the results of the present umbrella review are best understood as indicative evidence that highlights promising directions, while simultaneously underscoring the need for greater standardization in outcome measures, clearer reporting, and longitudinal research designs to determine skill transfer into clinical practice. Given the limitations of the current evidence base, immersive learning technologies and virtual patients are best positioned as supplementary components within a blended-learning structure, rather than as stand-alone replacements for established clinical communication training formats. Their pedagogical value appears most promising where they address needs that traditional methods meet only partially, for example, in preparing students for sensitive communication encounters in a clinical setting, rehearsing risk-free scenarios before meeting real patients, exploring perspective-taking experiences (e.g., dementia or mental health simulations), or providing repeated practice opportunities without requiring clinical placement resources. Therefore, immersive technologies and virtual patient approaches should not be implemented as a default innovation but rather strategically, where ( 1 ) learning objectives clearly match the affordances of the technology, ( 2 ) educator support and feedback structures are in place, and ( 3 ) institutional resources allow for sustainable integration. Until higher-certainty evidence becomes available, the most defensible position is a measured adoption strategy, using immersive tools as targeted enhancers of existing curricula rather than as curricular disruptors. Previous reviews have consistently highlighted fragmented evidence, heterogeneous outcomes, and the absence of comprehensive synthesis across immersive learning interventions ( 15 , 17 , 21 ). The present umbrella corroborates these observations. Across the included reviews, interventions varied substantially in duration, instructional design, and curricular integration, and frequently lacked structured feedback mechanisms, factors that limit both comparability and interpretability of findings ( 18 – 20 , 34 – 38 , 41 ). In line with Kelly et al. ( 21 ), many interventions were implemented as isolated or single-session activities and were insufficiently embedded within broader curricular frameworks. Evidence regarding skill retention was inconsistent: whereas Jensen et al. ( 18 ) explicitly reported a lack of sustained effects, Richardson et al. ( 34 ) identified retention over several months, though it declined gradually over time. Importantly, none of the included reviews provided robust evidence on long-term outcomes or the transfer of communication skills into clinical practice ( 18 , 19 , 35 ). Across the including reviews, substantial challenges were identified in assessing non-verbal communication and empathy. Only a small number of studies explicitly addressed these dimensions, and those that did report limited success in replicating the complexity and richness of real interpersonal interactions ( 19 , 36 ). As a result, the impact of immersive technologies and VP`s on patient-related outcomes, such as satisfaction, adherence, or health-related improvements, remains largely unclear, underscoring the difficulty of capturing core elements of clinical communication, particularly empathy, within digital environments ( 3 ). Notably, only five of the nine included reviews focused primarily on clinical communication skills, whereas the remaining reviews assessed communication as one outcome within broader educational evaluations. This limited and inconsistent focus reduces the depth of available evidence and contributes to the observed heterogeneity ( 18 , 20 , 34 , 36 , 37 ). Implementation-related barriers were also reported inconsistently and predominantly as secondary outcomes, with several reviews highlighting resource-related challenges such as institutional capacity, staffing requirements, and financial demands ( 19 , 35 , 36 ). Additional obstacles included technical limitations, such as system glitches and navigation difficulties, which may negatively affect learner acceptance and feasibility ( 34 ). Further heterogeneity arose from diverse study populations, varying curricular contexts, and inconsistent learning objectives across primary studies, as reported in the included reviews. Combined with the frequent use of non-standardized and non-validated outcome measures, these factors substantially limit comparability and constrain the ability to draw robust, generalizable conclusions. Taken together, these findings highlight the need for greater methodological rigor in both primary studies and systematic reviews. Future research should prioritize the use of standardized and validated outcome measures, incorporate longitudinal follow-up designs, and apply methodologies capable of examining whether educational gains translate into patient-relevant outcomes. Mixed-method approaches and multilevel study designs, may be particularly valuable in capturing how changes in learners’ clinical communication skills influence patient satisfaction, trust, and other patient centered outcomes ( 12 , 42 – 46 ). Such approaches align with Level 4 of Kirkpatrick’s evaluation model, which emphasizes behavioral change and improvements in patient outcomes ( 47 ). Limitations This umbrella review has several limitations that should be considered when interpreting findings. First, the methodological quality of all included reviews was rated critically low according to AMSTAR 2, substantially limiting confidence in their results and, extensions, in the conclusions of this synthesis. Second, pronounced heterogeneity was observed across the included reviews, encompassing outcome measures, study populations, curricular contexts, and intervention designs. This variability restricts comparability across studies and complicates the synthesis of consistent conclusions. Third, most reviews reported outcomes primarily in the short term, with little or no evidence regarding the retention of clinical communication skills or their transfer into clinical practice. As a result, conclusions regarding sustained educational impact remain limited. Fourth, barriers to curricular integration were reported inconsistently and were often addressed only as secondary outcomes. This limits insight into contextual, institutional and resource-related challenges that are critical for real-world adoption and scalability of immersive and VP-based interventions. Fifth, the literature search was restricted to peer-reviewed systematic reviews indexed in major databases and published in English. The exclusion of grey literature, preprints, and non-English publications, may have contributed to publication bias and the omission of relevant evidence. Given all these limitations, particularly the pervasive lack of methodological rigor across the included reviews, conclusions cannot be drawn based on the magnitude of reported effect sizes or the strength of individual findings. Instead, the primary contribution of this umbrella review lies in identifying overarching patterns, recurrent methodological shortcomings, and consistent research gaps within the field. Accordingly, all conclusions are presented conservatively and should be interpreted as indications of prevailing trends rather than as definitive evidence of effectiveness. Conclusion This umbrella review provides the first comprehensive synthesis of systematic reviews examining immersive and VP learning technologies for the development of clinical communication skills in undergraduate healthcare professionals. Overall, the findings suggest that immersive approaches - such as VPs, VR, AR, MR or XR - offer engaging and structured opportunities for practicing clinical communication skills. These technologies appear to support learner engagement and experiential learning. However, the current evidence base remains fragmented and methodologically weak, with a predominant focus on short-term outcomes. Notably, only approximately half of the included reviews addressed clinical communication as a primary outcome, with the remainder addressing it as a secondary component within broader evaluations of immersive educational technologies. This limited focus constrains the depth and interpretability of the available evidence. Further research should adhere to rigorous methodological standards, employ validated and standardized assessment instruments, and include longitudinal design to evaluate sustainability of learning effects and the transfer of communication skills into clinical practice. Greater emphasis should be placed on curricular integration, structured feedback mechanisms, and resource considerations to support feasibility and scalability within educational programs. At present, immersive and VP-based learning technologies should be viewed as adjunctive components within healthcare education rather than as stand-alone instructional approaches, as the available evidence does not yet justify their replacement of established teaching methods. High-quality primary studies and systematic reviews are needed to clarify under which conditions these technologies most effectively contribute to the sustainable development of clinical communication training. Abbreviations AR Augmented Reality CCA Corrected Covered Area ECCS Empathic Communication Coding Scheme MR Mixed Reality OSCE Objective Structured Clinical Examination VP Virtual Patient VR Virtual Reality XR Extended Reality Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Competing interests The authors declare that they have no competing interests. Funding The authors received no financial support for the research, authorship, and/or publication of this article. Author Contribution MK drafted the original manuscript and was responsible for protocol development, literature search, title and abstract screening, full text screening, data extraction, and conducted the AMSTAR 2 critical appraisal of the included systematic reviews, including independent rating and consensus discussions. SC contributed to protocol development, full text screening, data extraction and drafting the manuscript. PG contributed to protocol development, title and abstract screening and critically reviewed and edited the manuscript. ManK title and abstract screening; writing - review & editing. CL carried out the AMSTAR-2 critical appraisal of the included systematic reviews, including independent rating and consensus discussions. BR critically reviewed the manuscript with particular emphasis on alignment with the overall aim, scope and coherence. All authors read and approved the final manuscript. Acknowledgement The authors would like to thank [St. Pölten University of Applied Sciences, Sankt Pölten, Austria] for providing an academically supportive environment that enabled the conceptual development, methodological rigor, and completion of this umbrella review. An AI-supported editing tool (ChatGPT, GPT-5; OpenAI) was used to enhance language fluency during manuscript preparation. 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Verfügbar unter: https://esmed.org/MRA/mra/article/view/6557 Additional Declarations No competing interests reported. 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00:41:12","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":156640,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8549978/v1/7c6d99d5f0d9a0f5369dc68e.html"},{"id":101019972,"identity":"c4b82c51-7501-4d4e-a1f1-4149f6717143","added_by":"auto","created_at":"2026-01-24 00:41:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":45023,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA 2020 flow chart; note: After the pilot title and abstract screening, 17 (3,9%) conflicts (including update search) and 2 (20%) conflicts during the full-text screening were resolved by consensus.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8549978/v1/f56f01a4f0e80f125bc7f0af.png"},{"id":101019971,"identity":"974d7d4e-68da-4aa2-b0cb-4adc0bc70787","added_by":"auto","created_at":"2026-01-24 00:41:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":34343,"visible":true,"origin":"","legend":"\u003cp\u003eHarvest plot of the included studies. The plot is weighted according to the number of integrated relevant primary studies (as shown by the length of the bars). The direction of the effect is marked as follows: black = positive without comparison; grey = favors technology over control; not filled = mixed result\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8549978/v1/b087da01fa38da3ef70af8d1.png"},{"id":101207941,"identity":"2cf515f9-4224-4362-9a07-03fabdc932ee","added_by":"auto","created_at":"2026-01-27 10:07:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":904596,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8549978/v1/eef640f9-0540-498a-abe5-e027eb163e13.pdf"},{"id":101019988,"identity":"0880f827-34f6-49a3-b4be-2941ee04835a","added_by":"auto","created_at":"2026-01-24 00:41:12","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15099,"visible":true,"origin":"","legend":"","description":"","filename":"TermsFilters.docx","url":"https://assets-eu.researchsquare.com/files/rs-8549978/v1/51e6381db37e820f802a03d4.docx"},{"id":101019973,"identity":"344e5371-fcab-465f-b438-7700325c1321","added_by":"auto","created_at":"2026-01-24 00:41:11","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":23705,"visible":true,"origin":"","legend":"","description":"","filename":"FulltextarticlesexcludedwithreasonsTab.S1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8549978/v1/4c737339e965b38360ddf428.xlsx"},{"id":101019990,"identity":"4dd247e7-0310-4d41-a9c9-102f9eaa246c","added_by":"auto","created_at":"2026-01-24 00:41:12","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":26429,"visible":true,"origin":"","legend":"","description":"","filename":"StudycharacteristicsTab.S2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8549978/v1/ba7c5fedbce50b1d0dfb0f13.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Teaching Clinical Communication Skills Through virtual patient-based Learning: An Umbrella Review of Systematic Reviews","fulltext":[{"header":"Background","content":"\u003cp\u003eCommunication is a non-linear process in which verbal and nonverbal information is actively exchanged between sender and receiver (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). It requires core skills such as active listening, empathy, trust-building, and clarity, expressed through spoken language, writing, or body language (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In healthcare, clinical communication refers to a structured, empathic, and patient-centered framework that supports information gathering and health-related decision-making in a manner that is understandable and accessible to patients (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Despite broad agreement on its importance, clinical communication can be understood as a multifaceted construct that is conceptualized and operationalized differently across educational and clinical contexts (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOver recent decades, increased attention has been paid to patient education, with strong clinical communication skills now widely recognized as essential for achieving effective, patient-centered care and improved treatment outcomes. Within this context, psychosocial factors, such as cultural background, and patients\u0026rsquo; broader lived experiences, play a crucial role in shaping clinical communication quality and, when adequately addressed are associated with higher patient satisfaction and health outcomes (\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). However, the integration of these psychosocial dimensions into clinical communication training varies considerably, and such communication skills remain insufficiently developed across healthcare professions (\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). To address these gaps, a variety of instructional approaches, including workshops, lectures, and standardized patient encounters have been implemented. Nevertheless, substantial heterogeneity persists in intervention design, instructional intensity, and reporting quality, limiting reproducibility and comparability across studies (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In this context, immersive learning technologies such as virtual patients, augmented reality (AR), virtual reality (VR), and mixed reality (MR) have gained attention for their potential to create interactive learning environments and to support clinical communication training through realism, presence, and repeated practice opportunities (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Low-immersion virtual patients typically offer structured communication scenarios (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), whereas AR or MR integrate digital elements into real-world settings (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) and high-immersion VR provides three-dimensional environments that may enhance learner engagement (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). However, existing reviews report a fragmented and heterogeneous evidence base, characterized by variability in intervention design, feedback mechanisms, and curricular integration, as well as limited evidence on long-term retention and transfer to clinical practice (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). This heterogeneity constrains the interpretability of findings and hinders evidence-informed curricular decision-making, underscoring the need for a higher-level synthesis of review-level evidence.\u003c/p\u003e \u003cp\u003eTo date, no umbrella review has synthesized the existing systematic reviews on immersive learning approaches on clinical communication skills training in undergraduate healthcare professions education. This umbrella review therefore aims to evaluate the effectiveness of immersive learning methods in fostering clinical communication skills among undergraduate learners and to identify implementation-related challenges. By consolidating the current review-level evidence, this work seeks to support curriculum development and guide future research in digital, clinical communication-focused education.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eUmbrella reviews provide a comprehensive, narrative synthesis of evidence by consolidating findings from systematic reviews and meta-analyses addressing specific topics (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). This umbrella review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) and was preregistered in the Open Science Framework (OSF) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.17605/OSF.IO/EJ7XB\u003c/span\u003e\u003cspan address=\"10.17605/OSF.IO/EJ7XB\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). All methods described in this manuscript were conducted in accordance with the final, updated version of the OSF-registered protocol.\u003c/p\u003e \u003cp\u003eEligibility criteria were defined using the PICO framework. Included were students in healthcare professions education, with no restrictions regarding age, sex, or geographic location. Systematic reviews, with or without meta-analyses, were eligible if they investigated immersive and virtual patient learning technologies, specifically VR, AR, MR or extended reality (XR), and technology-based simulations, aimed at enhancing clinical communication skills. No restrictions were applied regarding comparator interventions; therefore, systematic reviews without a comparator group were also included, which may limit the certainty with which effectiveness can be inferred.\u003c/p\u003e \u003cp\u003eClinical communication skills were conceptualized as an umbrella term encompassing both practical abilities and contextual dimensions of patient-provider interaction. For the purposes of this review, this includes constructs such as empathy, understanding of patient perspective, and the formulation of appropriate questions within patient-centered assessment (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Reviews were eligible if they reported at least one outcome related to clinical communication, irrespective of whether this outcome constituted the primary focus of the review. Reviews were excluded if they addressed communication outcomes exclusively in other domains, such as interprofessional, leadership, or organizational communication. Only articles published in peer-reviewed journals were included to ensure a robust evidence base. Given that English is the predominant language in high-impact scientific publishing and higher education (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), only English-language publications were considered to ensure methodological consistency and comparability of findings. In light of evidence suggesting that approximately half of systematic reviews become outdated within 5.5 years (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e); the initial search was restricted to publications published between December 31, 2019, and December 31, 2024. An update search was conducted on August 1, 2025, to ensure that the evidence base remained current.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSearch Strategy\u003c/h2\u003e \u003cp\u003eIn March 2025, a systematic literature was conducted by the lead author using the databases PubMed, ScienceDirect, CINAHL, and Cochrane Library. Key Concepts and their respective synonyms were grouped using Boolean operator \u003cem\u003eOR\u003c/em\u003e and combined concepts using \u003cem\u003eAND\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eThe search strategy included combinations such as: (healthcare student* OR medical student* OR health occupations student*) AND (\"Health communication\"[MeSH] OR interpersonal communication OR patient-provider communication) AND (immersive learning OR simulated learning OR immersive education OR immersive technologies OR educational technology) AND (\"virtual reality\"[MeSH] OR augmented reality OR mixed reality OR extended reality OR virtual patient). A detailed overview of the complete search strategy, including all search terms, database-specific adaptations, and applied filters, is provided in the Supplementary Materials.\u003c/p\u003e \u003cp\u003eThe search was restricted using predefined filters for publication period, language (English), and publication type (systematic reviews, meta- analysis). All retrieved records were managed using Zotero (version 7.0 for Windows). In addition, forward and backward citation tracking included systematic reviews was performed as a supplementary hand-search strategy (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Any publications identified through this process were required to meet the predefined eligibility criteria for inclusion.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTitle and Abstract Screening\u003c/h3\u003e\n\u003cp\u003eA Microsoft Excel (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) spreadsheet was used to manage all identified articles. Two researchers independently conducted a pilot screening of titles and abstracts of a subset (20%) of the retrieved articles. The purpose of this pilot phase was to identify potential ambiguities, refine the screening criteria where necessary, and assess inter-rater reliability, in accordance with the Cochrane Handbook for Systematic of Interventions (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDuring this phase, researchers had access only to the titles and abstracts and were blinded to the full texts or each other's assessments, ensuring independent and unbiased judgements. Inter-rater agreement for the pilot screening was calculated using Cohen\u0026rsquo;s kappa. Although the resulting kappa value of 0.66 indicated moderate agreement, the overall percentage agreement was very high (98.6%). This discrepancy is consistent with the Cohen\u0026rsquo;s kappa paradox, where imbalanced category distributions, where most records are classified into the same category despite substantial agreement (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Given the high overall agreement and the satisfactory performance of the screening criteria, both researchers proceeded to independently screen all remaining titles and abstracts. Disagreements during the pilot and title and abstract screening were resolved through discussion, with a third reviewer consulted in cases of persisting uncertainty.\u003c/p\u003e\n\u003ch3\u003eFull Text Screening\u003c/h3\u003e\n\u003cp\u003eTwo researchers independently retrieved and assessed the full texts of all potentially eligible articles using the predefined criteria. Blinding was not applied during the full-text screening phase, as detailed information on study characteristics (e.g., methodology, population, and interventions) was required to make informed eligibility decisions. Disagreements were resolved through discussion between the researchers. If consensus could not be reached, a third reviewer was consulted. The study selection process and the resolution of disagreements are summarized in the PRISMA 2020 flow diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eData Extraction\u003c/h3\u003e\n\u003cp\u003eA standardized data extraction form was developed using Microsoft Excel (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e For each included systematic review, the following data was extracted: study metadata (authors, year, journal, DOI, database source), review characteristics (type of review, number of included primary studies, inclusion/exclusion criteria), sample characteristics (number and type of participants, profession, demographics where available), intervention details (type of technology for clinical communication training, learning modality, duration, comparator), outcome measures (instruments for assessing clinical communication skills, primary and secondary outcomes), reported effect sizes and statistical results (Cohen\u0026rsquo;s d, Pearson\u0026rsquo;s r, standardized mean differences, confidence intervals, heterogeneity estimates) were also extracted. In addition, the methodological quality of each review was recorded using AMSTAR 2 tool (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eData extraction was performed independently by two researchers. Extracted data were subsequently compared and discussed in a consensus meeting to resolve discrepancies.\u003c/p\u003e \u003cp\u003eTo address the risk of double counting primary studies across researchers, the Corrected Covered Area was calculated according to Pieper et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). This metric quantifies the degree of overlap among primary studies and is recommended for use in umbrella reviews (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Based on this consideration, umbrella reviews were excluded from the synthesis, as their inclusion may introduce methodological bias through duplicated evidence (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eAssessment of Bias Risk\u003c/h3\u003e\n\u003cp\u003eThe methodological quality of the included studies was assessed using the AMSTAR 2 tool (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The assessment was conducted by one researcher and subsequently cross-checked by a second researcher. Any discrepancies were resolved through discussion.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis\u003c/h2\u003e \u003cp\u003e Given the anticipated substantial heterogeneity across included reviews, a qualitative synthesis was conducted. Extracted data were organized according to intervention type, population characteristics, outcome measures, intervention setting, and comparator intervention. To enhance reliability, data extraction and categorization were independently reviewed by two authors. Where appropriate, inductive codes were developed in addition to the predefined thematic categories. All categories were subsequently reviewed and discussed; in cases where consensus could not be reached a third researcher was consulted.\u003c/p\u003e \u003cp\u003ePrior to finalizing the synthesis, both researchers conducted a cross-examination of interpretations to guarantee consistency, transparency, and alignment with extracted data. Data not reported in the original reviews were labeled as not reported (NR), and reviews that were marked as retracted were excluded from the synthesis. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Given that all included reviews were rated as critically low methodological quality, findings were interpreted with caution rather than formally weighted by quality (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).Owing to the absence of meta-analysis, statistical assessment of publication bias was not performed. Instead, potential reporting bias was evaluated qualitatively, for example by examining whether reviews exclude grey literature or selectively reported positive outcomes.\u003c/p\u003e \u003cp\u003e Potential influences of methodological quality were explored narratively; however, meaningful comparisons across quality levels were precluded by the uniformly critically low ratings of the included reviews.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe search strategy yielded 1,093 records, of which 10 duplicates were removed. Following title and abstract screening, 20 full-text articles were assessed for eligibility. After application of the inclusion criteria, nine systematic reviews were included in the qualitative synthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Reasons for exclusion were categorized into five different aspects: 1) absence of clinical communication outcomes; 2) insufficient primary studies related to our research question; 3) use of non-eligible technologies regarding our inclusion criteria; 4) inclusion of a limited number of relevant primary studies with low coverage, which overlapped with primary studies identified in other included reviews; 5) umbrella reviews due to the risk of double counting. (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Full-text articles excluded with reasons).\u003c/p\u003e \u003cp\u003e Overlap of primary studies across the included systematic reviews was assessed using the Corrected Covered Area (CCA). The calculated CCA was 0.9%, indicating slight overlap and suggesting a minimal risk of double-counting bias within the synthesized evidence base (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eOverview of Included Reviews\u003c/h3\u003e\n\u003cp\u003e We included eight systematic reviews and one meta-analysis published between 2020 and 2025. Together, these studies provided a broad evidence base on the effectiveness of immersive and VP-based educational interventions for the development of clinical communication skills in undergraduate health professions education. The included reviews focused on undergraduate students across a range of healthcare disciplines, including pharmacy (n\u0026thinsp;=\u0026thinsp;1571), medicine (n\u0026thinsp;=\u0026thinsp;5359), nursing (n\u0026thinsp;=\u0026thinsp;5170), psychology/psychiatry (n\u0026thinsp;=\u0026thinsp;5904), and physiotherapy (n\u0026thinsp;=\u0026thinsp;309). Learners were at different stages of undergraduate education, from first-year to the final-year students. Most primary studies originated from the systematic reviews are from the United States, followed by Australia and several European countries (e.g., United Kingdom, Netherlands, and Denmark), with a smaller proportion conducted in Asia and South America.\u003c/p\u003e \u003cp\u003eAcross the included reviews, a wide range of immersive and VP-based technologies were examined. Most interventions involved low- to medium-immersion VP approaches delivered via web-based simulation platforms, interactive VP serious games, or VR-based simulations (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). High-immersion VR interventions additionally incorporated virtual ward environments and contextualized clinical settings (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Rodda et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) included a heterogeneous set of immersive interventions, ranging from VR- and AR-based symptom simulations to virtual patient systems with predefined response formats, while one meta-analysis and one systematic review specifically focused on AR, VR, and metaverse-based simulations (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). One review included virtual simulation-based education combining 2D elements (e.g., photos, videos) and 3D-video, and sensory stimuli (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Interventions were implemented across diverse educational contexts, including university-based courses, clinical training environments, medical practices, and community pharmacy settings. Comparator conditions varied widely and included no intervention, traditional or alternative teaching methods, real patient encounters, non-VR simulation formats, or were not reported. Several reviews also included studies without comparator groups.\u003c/p\u003e \u003cp\u003eThe effectiveness of immersive technologies was examined across multiple clinical communication-related learning scenarios, such as counseling encounters situations, clinical consultations, suicide and mental health risk assessments, routine clinical visits, and the delivery of unfavorable or sensitive information to patients and their families (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). In addition, VR-based interventions were used to simulate patient perspectives associated with conditions such as dementia or schizophrenia (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA wide range of outcome measures were employed to assess communication-related learning outcomes. These included self-assessment instruments, course evaluations, and self-developed tools (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Several reviews reported the use of Objective Structured Clinical Examinations (OSCEs) (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) and established communication scales (e.g., Empathic Communication Coding Scheme (ECCS)) (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Qualitative methods, including interviews and focus groups were also applied in some reviews (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). One review did not report specific outcome instruments and instead relied primarily on self-reported student perceptions and course evaluations (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). An overview of the study characteristics is presented in Supplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e, with a visual summary of outcome variability illustrated in the harvest plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRisk of Bias in Studies\u003c/h2\u003e \u003cp\u003eThe methodological quality of the included systematic review was assessed using AMSTAR 2 tool (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). All nine reviews were rated as critically low in quality due to shortcomings in several critical AMSTAR 2 domains (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, and \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe most frequent limitations included insufficient justification for excluded studies and incomplete reporting of search strategies. In addition, most reviews conducted only partially comprehensive literature searches and did not adequately consider the potential impact of risk of bias when interpreting their findings. Further methodological weaknesses included the absence of preregistered protocols, a lack of reporting on protocol amendments, and limited transparency regarding exclusion procedures. Although some of the included reviews reported external funding, all authors and contributors declared no conflict of interest. Detailed AMSTAR 2 item-level ratings are presented in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAMSTAR 2 Item (\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13 CR14 CR15\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) evaluation of the included systematic reviews\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"17\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystematic Review\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLee et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJensen et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhanudulkitti et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCho \u0026amp; Kim (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDong et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChae et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichardson et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlsharari et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRodda et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u0026Oslash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eNote. AMSTAR-2 item-level ratings are shown for items 1\u0026ndash;16.\u003c/b\u003e + \u003cb\u003e= yes;\u003c/b\u003e \u0026plusmn; \u003cb\u003e= partial yes; - = no; \u0026Oslash; = not applicable. Two reviewers independently rated each review; disagreements were resolved by consensus (or third reviewer).\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePrimary Outcomes\u003c/h2\u003e \u003cp\u003eFor screen-based VPs, four reviews reported mixed effects on clinical communication outcomes. Lee et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) identified improvements in such communication skills and selected clinical outcomes among medical students; however, non-verbal communication components were often insufficiently represented, and effects on empathy were weaker compared with interactions involving real patients. Jensen et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) reported advantages over no intervention or traditional teaching methods, but no superiority compared with non-technology-based simulations approaches; moreover, students frequently perceived VPs as lacking realism. Phanudulkitti et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) observed positive effects on pharmacy students\u0026rsquo; confidence and consultation skills, although the absence of comparator interventions limits the interpretability of effectiveness. Richardson et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) corroborated these findings in simulated pharmacy consultations settings, highlighting experiential learning benefits alongside persistent technical and usability barriers.\u003c/p\u003e \u003cp\u003eAcross the included reviews, VR and AR interventions were more frequently associated with positive outcomes than low-immersion methods. Cho and Kim (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) identified a moderate effect in favor of VR/AR compared with traditional formats, although heterogeneity was high. Dong et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) identified measurable improvements in clinical communication skills among nursing students but noted persistent limitations regarding the authenticity of patient interaction. Similarly, Rodda et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) reported gains in learner engagement, attitudes, and perceived competence among medical and pharmacy students. Despite these positive findings, technical limitations and usability challenges were consistently reported across reviews.\u003c/p\u003e \u003cp\u003eFor simulation-based education with mixed levels of immersion, Alsharari et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) reported improvements in both communication skills and clinical competence among nursing students when compared with conventional pre-clinical practice. However, variability in study quality limited certainty of the evidence. Similarly, Chae et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) found virtual simulation interventions to be beneficial for enhancing empathy and cultural awareness in medical and healthcare students.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSecondary Outcomes \u0026ndash; Barriers\u003c/h2\u003e \u003cp\u003eFor screen-based VPs, reported barriers included limited authenticity resulting from insufficient integration of non-verbal communication (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), students\u0026rsquo; perceptions of unrealistic interactions (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), high institutional resource requirements (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), and technical challenges such as software glitches and navigation difficulties (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor VR/AR and Metaverse-based interventions, scalability emerged as a key challenge. Cho and Kim (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) highlighted contextual barriers related to geographic and institutional variability, while Dong et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) emphasized persistent concerns regarding the authenticity in VR-based teaching. Rodda et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) reported heterogeneous student experiences, including usability issues, which negatively affected acceptance of immersive learning technologies.\u003c/p\u003e \u003cp\u003eIn the context of mixed-immersion simulation-based education, Chae et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) identified substantial heterogeneity in outcomes as a major research gap. Alsharari et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) did not report specific implementations within the included primary studies. Collectively, these findings underscore the need for more systematic evaluation of curricular challenges across immersive learning approaches.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStrength of Evidence\u003c/h2\u003e \u003cp\u003eAll nine included reviews were rated as critically low in methodological quality according to the AMSTAR 2 tool, indicating that the overall strength of evidence is limited and that findings should be interpreted with caution.\u003c/p\u003e \u003cp\u003eDespite these methodological limitations, several consistent patterns emerged across the reviews. Interventions using VR/AR and metaverse-based approaches were frequently associated with positive effects on clinical communication skills, empathy, and learner engagement. Notably, two out of three systematic reviews investigated the effects against a comparator intervention (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, confidence in these findings remains low due to the substantial heterogeneity in intervention design, outcome measures, and study populations.\u003c/p\u003e \u003cp\u003eScreen-based VP interventions demonstrated mixed results. While these approaches were generally superior to no intervention, they showed no clear advantage over non-technology-based simulation methods, particularly with regards to empathy and non-verbal communication skills.\u003c/p\u003e \u003cp\u003eFor simulation-based education incorporating mixed immersion, potential benefits were reported. However, the corresponding reviews consistently emphasized methodological weaknesses in the underlying studies.\u003c/p\u003e \u003cp\u003eOverall, immersive and VP learning technologies appear promising for development of clinical communication skills. Nevertheless, the critically low methodological quality of the included reviews necessitates cautious interpretation. Future research should prioritize rigorously conducted systematic reviews with transparent methodologies, standardized outcome measures, and comprehensive reporting to strengthen the evidence base and clarify the conditions under which immersive learning technologies are most effective.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis umbrella review examined how effectively immersive technologies and virtual patient (VP)-based approaches support the development of clinical communication skills in undergraduate healthcare education. The synthesis of recent systematic reviews provides an integrated overview of reported effectiveness, highlights key implementation challenges, and identifies gaps that currently limit the strength of conclusions. Overall, the findings offer a structured foundation for interpreting the current evidence base and informing priorities for future research and curriculum design.\u003c/p\u003e \u003cp\u003eAlthough all included systematic reviews were rated as critically low according to AMSTAR-2 (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), this finding should not be interpreted as evidence against the educational value of immersive learning technologies. Rather, it indicates that the current evidence base lacks the methodological robustness needed to draw high-confidence conclusions about effectiveness or superiority over established teaching methods. In this context, the results of the present umbrella review are best understood as indicative evidence that highlights promising directions, while simultaneously underscoring the need for greater standardization in outcome measures, clearer reporting, and longitudinal research designs to determine skill transfer into clinical practice.\u003c/p\u003e \u003cp\u003eGiven the limitations of the current evidence base, immersive learning technologies and virtual patients are best positioned as supplementary components within a blended-learning structure, rather than as stand-alone replacements for established clinical communication training formats. Their pedagogical value appears most promising where they address needs that traditional methods meet only partially, for example, in preparing students for sensitive communication encounters in a clinical setting, rehearsing risk-free scenarios before meeting real patients, exploring perspective-taking experiences (e.g., dementia or mental health simulations), or providing repeated practice opportunities without requiring clinical placement resources.\u003c/p\u003e \u003cp\u003eTherefore, immersive technologies and virtual patient approaches should not be implemented as a default innovation but rather strategically, where (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) learning objectives clearly match the affordances of the technology, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) educator support and feedback structures are in place, and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) institutional resources allow for sustainable integration. Until higher-certainty evidence becomes available, the most defensible position is a measured adoption strategy, using immersive tools as targeted enhancers of existing curricula rather than as curricular disruptors.\u003c/p\u003e \u003cp\u003ePrevious reviews have consistently highlighted fragmented evidence, heterogeneous outcomes, and the absence of comprehensive synthesis across immersive learning interventions (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The present umbrella corroborates these observations. Across the included reviews, interventions varied substantially in duration, instructional design, and curricular integration, and frequently lacked structured feedback mechanisms, factors that limit both comparability and interpretability of findings (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan additionalcitationids=\"CR35 CR36 CR37\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn line with Kelly et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), many interventions were implemented as isolated or single-session activities and were insufficiently embedded within broader curricular frameworks. Evidence regarding skill retention was inconsistent: whereas Jensen et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) explicitly reported a lack of sustained effects, Richardson et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) identified retention over several months, though it declined gradually over time. Importantly, none of the included reviews provided robust evidence on long-term outcomes or the transfer of communication skills into clinical practice (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e Across the including reviews, substantial challenges were identified in assessing non-verbal communication and empathy. Only a small number of studies explicitly addressed these dimensions, and those that did report limited success in replicating the complexity and richness of real interpersonal interactions (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). As a result, the impact of immersive technologies and VP`s on patient-related outcomes, such as satisfaction, adherence, or health-related improvements, remains largely unclear, underscoring the difficulty of capturing core elements of clinical communication, particularly empathy, within digital environments (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNotably, only five of the nine included reviews focused primarily on clinical communication skills, whereas the remaining reviews assessed communication as one outcome within broader educational evaluations. This limited and inconsistent focus reduces the depth of available evidence and contributes to the observed heterogeneity (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImplementation-related barriers were also reported inconsistently and predominantly as secondary outcomes, with several reviews highlighting resource-related challenges such as institutional capacity, staffing requirements, and financial demands (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Additional obstacles included technical limitations, such as system glitches and navigation difficulties, which may negatively affect learner acceptance and feasibility (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurther heterogeneity arose from diverse study populations, varying curricular contexts, and inconsistent learning objectives across primary studies, as reported in the included reviews. Combined with the frequent use of non-standardized and non-validated outcome measures, these factors substantially limit comparability and constrain the ability to draw robust, generalizable conclusions.\u003c/p\u003e \u003cp\u003eTaken together, these findings highlight the need for greater methodological rigor in both primary studies and systematic reviews. Future research should prioritize the use of standardized and validated outcome measures, incorporate longitudinal follow-up designs, and apply methodologies capable of examining whether educational gains translate into patient-relevant outcomes. Mixed-method approaches and multilevel study designs, may be particularly valuable in capturing how changes in learners\u0026rsquo; clinical communication skills influence patient satisfaction, trust, and other patient centered outcomes (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR43 CR44 CR45\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Such approaches align with Level 4 of Kirkpatrick\u0026rsquo;s evaluation model, which emphasizes behavioral change and improvements in patient outcomes (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis umbrella review has several limitations that should be considered when interpreting findings. First, the methodological quality of all included reviews was rated critically low according to AMSTAR 2, substantially limiting confidence in their results and, extensions, in the conclusions of this synthesis. Second, pronounced heterogeneity was observed across the included reviews, encompassing outcome measures, study populations, curricular contexts, and intervention designs. This variability restricts comparability across studies and complicates the synthesis of consistent conclusions. Third, most reviews reported outcomes primarily in the short term, with little or no evidence regarding the retention of clinical communication skills or their transfer into clinical practice. As a result, conclusions regarding sustained educational impact remain limited. Fourth, barriers to curricular integration were reported inconsistently and were often addressed only as secondary outcomes. This limits insight into contextual, institutional and resource-related challenges that are critical for real-world adoption and scalability of immersive and VP-based interventions. Fifth, the literature search was restricted to peer-reviewed systematic reviews indexed in major databases and published in English. The exclusion of grey literature, preprints, and non-English publications, may have contributed to publication bias and the omission of relevant evidence.\u003c/p\u003e \u003cp\u003eGiven all these limitations, particularly the pervasive lack of methodological rigor across the included reviews, conclusions cannot be drawn based on the magnitude of reported effect sizes or the strength of individual findings. Instead, the primary contribution of this umbrella review lies in identifying overarching patterns, recurrent methodological shortcomings, and consistent research gaps within the field. Accordingly, all conclusions are presented conservatively and should be interpreted as indications of prevailing trends rather than as definitive evidence of effectiveness.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003e This umbrella review provides the first comprehensive synthesis of systematic reviews examining immersive and VP learning technologies for the development of clinical communication skills in undergraduate healthcare professionals. Overall, the findings suggest that immersive approaches - such as VPs, VR, AR, MR or XR - offer engaging and structured opportunities for practicing clinical communication skills. These technologies appear to support learner engagement and experiential learning.\u003c/p\u003e \u003cp\u003eHowever, the current evidence base remains fragmented and methodologically weak, with a predominant focus on short-term outcomes. Notably, only approximately half of the included reviews addressed clinical communication as a primary outcome, with the remainder addressing it as a secondary component within broader evaluations of immersive educational technologies. This limited focus constrains the depth and interpretability of the available evidence.\u003c/p\u003e \u003cp\u003eFurther research should adhere to rigorous methodological standards, employ validated and standardized assessment instruments, and include longitudinal design to evaluate sustainability of learning effects and the transfer of communication skills into clinical practice. Greater emphasis should be placed on curricular integration, structured feedback mechanisms, and resource considerations to support feasibility and scalability within educational programs.\u003c/p\u003e \u003cp\u003eAt present, immersive and VP-based learning technologies should be viewed as adjunctive components within healthcare education rather than as stand-alone instructional approaches, as the available evidence does not yet justify their replacement of established teaching methods. High-quality primary studies and systematic reviews are needed to clarify under which conditions these technologies most effectively contribute to the sustainable development of clinical communication training.\u003c/p\u003e"},{"header":"Abbreviations","content":" \u003cp\u003eAR Augmented Reality\u003c/p\u003e \u003cp\u003eCCA Corrected Covered Area\u003c/p\u003e \u003cp\u003eECCS Empathic Communication Coding Scheme\u003c/p\u003e \u003cp\u003eMR Mixed Reality\u003c/p\u003e \u003cp\u003eOSCE Objective Structured Clinical Examination\u003c/p\u003e \u003cp\u003eVP Virtual Patient\u003c/p\u003e \u003cp\u003eVR Virtual Reality\u003c/p\u003e \u003cp\u003eXR Extended Reality\u003c/p\u003e "},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMK drafted the original manuscript and was responsible for protocol development, literature search, title and abstract screening, full text screening, data extraction, and conducted the AMSTAR 2 critical appraisal of the included systematic reviews, including independent rating and consensus discussions. SC contributed to protocol development, full text screening, data extraction and drafting the manuscript. PG contributed to protocol development, title and abstract screening and critically reviewed and edited the manuscript. ManK title and abstract screening; writing - review \u0026amp; editing. CL carried out the AMSTAR-2 critical appraisal of the included systematic reviews, including independent rating and consensus discussions. BR critically reviewed the manuscript with particular emphasis on alignment with the overall aim, scope and coherence. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003e The authors would like to thank [St. P\u0026ouml;lten University of Applied Sciences, Sankt P\u0026ouml;lten, Austria] for providing an academically supportive environment that enabled the conceptual development, methodological rigor, and completion of this umbrella review. An AI-supported editing tool (ChatGPT, GPT-5; OpenAI) was used to enhance language fluency during manuscript preparation. All adjustments were checked and finalised by the authors, who accept responsibility for the final wording and scholarly content.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data generated or analyzed during this study are included in this published article and its supplementary information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDanaher TS, Berry LL, Howard C, Moore SG, Attai DJ. Improving How Clinicians Communicate With Patients: An Integrative Review and Framework. Journal of Service Research [Internet]. November 2023 [zitiert 13. M\u0026auml;rz 2025];26(4):493\u0026ndash;510. 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Verf\u0026uuml;gbar unter: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://journals.sagepub.com/doi/\u003c/span\u003e\u003cspan address=\"https://journals.sagepub.com/doi/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/20597991231217937\u003c/span\u003e\u003cspan address=\"10.1177/20597991231217937\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKusmiati M. A Comprehensive Evaluation in Medical Curriculum Using the Kirkpatrick Hierarchical Approach: A Review and Update. MRAJ [Internet]. 2025 [zitiert 16. Oktober 2025];13(5). Verf\u0026uuml;gbar unter: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://esmed.org/MRA/mra/article/view/6557\u003c/span\u003e\u003cspan address=\"https://esmed.org/MRA/mra/article/view/6557\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Clinical communication, Immersive technologies, Virtual patients, Learning, Healthcare students, Medical students, Education","lastPublishedDoi":"10.21203/rs.3.rs-8549978/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8549978/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEffective clinical communication is a core component of patient-centered care. Immersive learning technologies, including virtual patients, virtual reality, and augmented reality, are increasingly used to train clinical communication skills in undergraduate health professions education. However, the existing evidence is fragmented and methodologically heterogeneous. This umbrella review synthesizes evidence on the effectiveness of immersive technologies and virtual patients for developing clinical communication skills in undergraduate medical and healthcare students and explores barriers to curricular integration and research gaps.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e An umbrella review of systematic reviews (with or without meta-analysis) was conducted following PRISMA guidelines. Searches were performed in PubMed, ScienceDirect, CINAHL, and Cochrane Library. Eligible reviews examined immersive technologies (e.g., VR, AR, MR, XR, virtual patients) targeting clinical communication skills in undergraduate learners. Methodological quality was assessed using AMSTAR-2. No pooled meta-analysis was possible due to heterogeneity in interventions, comparators, and outcome measures.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eNine systematic reviews were included. All were rated as critically low in methodological quality according to AMSTAR-2, limiting certainty of conclusions. Across reviews, immersive technologies showed promising short-term gains in communication performance, learner engagement, and perceived confidence compared to no intervention or traditional teaching. However, evidence for long-term retention, empathy development, non-verbal communication, and transfer to clinical practice was inconsistent. Heterogeneity in intervention design, outcome measures, and feedback structures reduced comparability and generalizability.\u003c/p\u003e","manuscriptTitle":"Teaching Clinical Communication Skills Through virtual patient-based Learning: An Umbrella Review of Systematic Reviews","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-24 00:41:06","doi":"10.21203/rs.3.rs-8549978/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-12T06:17:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-08T05:53:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"174795208985319092000414733673435830930","date":"2026-04-08T04:53:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-20T00:35:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65532819875087326069510116856168961423","date":"2026-03-06T18:17:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303975966234893760067003246150953615990","date":"2026-03-06T15:02:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-04T16:12:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"27345618246897171483337335127876906459","date":"2026-01-27T14:11:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-22T03:24:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-13T11:42:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-12T12:35:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-12T12:31:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2026-01-08T09:45:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4ff7f5e9-aa16-478e-b464-2ef305e001a2","owner":[],"postedDate":"January 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-30T06:53:50+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-24 00:41:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8549978","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8549978","identity":"rs-8549978","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}