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<journal-id journal-id-type="publisher-id">Front. Med.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Medicine</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Med.</abbrev-journal-title>
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<issn pub-type="epub">2296-858X</issn>
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<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-meta>
<article-id pub-id-type="doi">10.3389/fmed.2026.1762807</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Systematic Review</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Identifying the most recommended novel teaching strategy in orthopaedics education: a systematic review and network meta-analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Cao</surname>
<given-names>Hongxin</given-names>
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<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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<contrib contrib-type="author">
<name>
<surname>Ji</surname>
<given-names>Zhongjie</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author">
<name>
<surname>Song</surname>
<given-names>Linyang</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Hongliang</given-names>
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<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Yunzhen</given-names>
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<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name>
<surname>Jiao</surname>
<given-names>Guangjun</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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<aff id="aff1"><label>1</label><institution>Department of Medical Oncology, Qilu Hospital of Shandong University</institution>, <city>Jinan</city>, <state>Shandong</state>, <country country="cn">China</country></aff>
<aff id="aff2"><label>2</label><institution>Department of Spine Surgery, Qilu Hospital of Shandong University</institution>, <city>Jinan</city>, <state>Shandong</state>, <country country="cn">China</country></aff>
<author-notes>
<corresp id="c001"><label>&#x002A;</label>Correspondence: Guangjun Jiao, <email xlink:href="mailto:jiaoguangjun@sdu.edu.cn">jiaoguangjun@sdu.edu.cn</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-02-10">
<day>10</day>
<month>02</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>13</volume>
<elocation-id>1762807</elocation-id>
<history>
<date date-type="received">
<day>09</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>25</day>
<month>01</month>
<year>2026</year>
</date>
<date date-type="accepted">
<day>27</day>
<month>01</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2026 Cao, Ji, Song, Wang, Chen and Jiao.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Cao, Ji, Song, Wang, Chen and Jiao</copyright-holder>
<license>
<ali:license_ref start_date="2026-02-10">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>Despite the growing adoption of novel teaching strategies in orthopaedics education, their comparative effectiveness remains unclear. This network meta-analysis (NMA) evaluates and ranks the efficacy of problem-based learning (PBL), virtual reality (VR), Video, three dimensions (3D) simulations, flipped classrooms (FC), 3D combined PBL, FC combined team based learning (TBL), and traditional lecture-based learning (LBL) in orthopaedic education.</p>
</sec>
<sec>
<title>Methods</title>
<p>A systematic search of PubMed, Web of Science, Embase, and Cochrane Library was conducted up to December 31, 2024. Randomized controlled trials (RCTs) comparing teaching strategies in orthopaedics education were included. Specific criteria were utilized to identify relevant studies, and data extraction was subsequently carried out. Outcomes included theoretical knowledge, procedural or clinical skills, and learner satisfaction. Pairwise and network meta-analyses were performed using R software.</p>
</sec>
<sec>
<title>Results</title>
<p>After screening 893 studies, 11 RCTs involving 690 medical students or residents were included in the NMA. VR was more effective than LBL for procedural or clinical skills (SMD&#x202F;=&#x202F;6.88, 95% CI: 1.05&#x2013;12.13), while FC&#x202F;+&#x202F;TBL improved theoretical test scores with the highest SUCRA probability (81.73%). FC&#x202F;+&#x202F;TBL also enhanced student satisfaction (SMD&#x202F;=&#x202F;1.42, 95% CI: 0.04&#x2013;2.79), with PBL having the highest SUCRA probability (61.53%) for this outcome.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>Our NMA found FC&#x202F;+&#x202F;TBL and VR to be the most effective novel teaching strategies in orthopaedics education for improving theoretical and clinical skill scores, respectively. However, differences among strategies were minor. Future studies with larger samples, diverse populations, and more outcome measures are needed for a comprehensive evaluation.</p>
</sec>
</abstract>
<kwd-group>
<kwd>network meta-analysis</kwd>
<kwd>orthopaedics education</kwd>
<kwd>problem-based learning</kwd>
<kwd>teaching strategies</kwd>
<kwd>team based learning (TBL)</kwd>
<kwd>VR</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was not received for this work and/or its publication.</funding-statement>
</funding-group>
<counts>
<fig-count count="5"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="48"/>
<page-count count="10"/>
<word-count count="7548"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Healthcare Professions Education</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="sec1">
<title>Background</title>
<p>Orthopedics, a field deeply rooted in anatomical mastery, biomechanical logic, and dynamic surgical decision-making, faces persistent challenges in fostering well-rounded competencies. Traditional lecture-based learning (LBL), which emphasizes rote memorization of concepts like fracture classifications or implant protocols, struggles to bridge the gap between theory and real-world application. Studies have revealed that under LBL, orthopedic residents exhibit a 31% error rate in biomechanical analysis of complex cases and significantly lag in managing postoperative complications compared to active learning approaches (<xref ref-type="bibr" rid="ref1">1</xref>). In China&#x2019;s current system, the fourth year of medical school focuses on theory, while the fifth shifts to clinical practice, yet both phases rely heavily on standardized curricula. This rigid structure stifles critical thinking and teamwork skills&#x2014;72% of trainees report limited exposure to real surgical challenges during internships, as lessons remain textbook-bound (<xref ref-type="bibr" rid="ref2">2</xref>). This &#x201C;theory-practice divide&#x201D; contributes to burnout (affecting 18% of students) and skill gaps: only 43% of graduates from top Chinese medical schools meet competency standards in emerging technologies like robot-assisted surgery (<xref ref-type="bibr" rid="ref3">3</xref>), far below global benchmarks. Thus, reforming orthopedic education to integrate active learning, dynamic feedback, and adaptability to new technologies has become urgent.</p>
<p>To address these limitations, innovative strategies like virtual reality (VR), 3D interactive systems, and flipped classrooms (FC) are transforming training. VR simulations replicate real surgical environments, boosting skill transfer efficiency. Vall&#x00E9;e et al. (<xref ref-type="bibr" rid="ref1">1</xref>) found VR-trained residents completed arthroscopic procedures 42% faster, with 14% higher accuracy in tissue identification than traditional apprenticeship trainees. Xue et al. (<xref ref-type="bibr" rid="ref3">3</xref>) developed a 3D Training System that integrates real imaging with live anatomical guides, tripling femoral neck fracture classification accuracy while reducing cognitive load by 28%. Meanwhile, FC combined with team-based learning (TBL) redefines roles: pre-class self-study, in-case debates, and post-surgery debriefs raised clinical decision-making scores by 9.2% and complication prediction accuracy to 72.3% (<xref ref-type="bibr" rid="ref4">4</xref>). A study of 130 students found that podcast/videos users significantly outperformed text users in posttests and knowledge gain, with higher approval ratings for podcasts/videos (<xref ref-type="bibr" rid="ref5">5</xref>). Recent quasi-experimental work further supports the efficacy of integrated digital approaches; for instance, massive open online course (MOOC)&#x2013;virtual simulation combinations have demonstrated significant improvements in surgical skill acquisition, including wound debridement and basic operative techniques (<xref ref-type="bibr" rid="ref6">6</xref>, <xref ref-type="bibr" rid="ref7">7</xref>). Beyond building muscle memory for procedures, these tools provide visual data and instant feedback to correct errors&#x2014;opportunities missing in traditional teaching.</p>
<p>Despite their clear benefits, debates persist regarding the best strategies. A key issue is the lack of direct comparisons between methods. Moreover, conflicting conclusions across meta-analyses could limit the scalable implementation of innovative teaching methods in educational and clinical environments (<xref ref-type="bibr" rid="ref8 ref9 ref10 ref11">8&#x2013;11</xref>). Despite the suggestion that specific teaching environments should undergo thorough evaluation when introducing new teaching strategies (<xref ref-type="bibr" rid="ref12">12</xref>), there remains a dearth of research to substantiate this notion. Here, systematic reviews and network meta-analysis (NMA)&#x2014;considered the highest level of evidence&#x2014;can help by comparing multiple methods at once. In this study, we employ NMA integrated with statistical ranking to systematically evaluate eight mainstream educational approaches (LBL, problem-based learning (PBL), video, VR, 3D, 3D&#x202F;+&#x202F;PBL, FC and FC&#x202F;+&#x202F;TBL) in fostering theoretical knowledge assimilation and clinical skill proficiency. The findings aim to establish a data-driven decision-making framework for optimizing resource allocation across diverse educational and clinical contexts.</p>
</sec>
<sec sec-type="methods" id="sec2">
<title>Methods</title>
<p>The systematic review and NMA adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension statement (<xref ref-type="bibr" rid="ref13">13</xref>), with the objective of assessing and comparing the efficacy of eight individual teaching strategies in enhancing orthopedic education by examining three specific indicators (<xref ref-type="bibr" rid="ref14">14</xref>). This review did not require ethical approval as it utilized data from published studies, and no detailed participant information was made public.</p>
<sec id="sec3">
<title>Literature retrieval strategy</title>
<p>Two authors (Jiao G and Cao H) conducted a thorough literature review by employing both database searches and manual search methods. The electronic databases listed below were searched through December 2024: PubMed, Web of Science, Embase, and Cochrane library. The search strategies, designed for reproducibility, were conducted based on the Population, Intervention, Comparison, and Outcome (PICO) framework, as detailed in <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 1</xref>. Moreover, pertinent randomized controlled trials (RCTs) were located through manual searches of the reference lists in relevant meta-analyses and prominent medical education journals. In cases of disagreement between the two pairs of authors (e.g., during literature screening, data extraction, or quality assessment), the discrepancies were first resolved through joint discussion. If consensus could not be reached, a third independent senior researcher (Chen Y) with expertise in orthopaedic education and systematic reviews was consulted to provide an objective judgment. The final decision was made based on the third researcher&#x2019;s recommendations, and all resolution processes were documented in detail to ensure transparency and minimize bias.</p>
</sec>
<sec id="sec4">
<title>Inclusion and exclusion criteria</title>
<sec id="sec5">
<title>Inclusion criteria</title>
<p>Two authors (Ji Z and Song L) independently screened all retrieved studies using Zotero (version 7.0.11) literature management software, developed by the Corporation for Digital Scholarship, USA, based on predetermined inclusion and exclusion criteria. Studies that satisfied the following inclusion criteria were included: (1) participants were medical students, interns, or resident doctors, without regard to gender, age, grade, ethnicity, nationality, or educational background; (2) the focus was on orthopedic-related education; (3) comparisons were made between eight novel teaching methods and LBL method; (4) outcomes were assessed using: knowledge scores to gauge theoretical understanding; procedural skill scores for operational skills like fracture reduction and trauma management; clinical skill scores for practical clinical problem-solving abilities, including history taking, examination, diagnosis, and treatment planning; total scores combining the above to evaluate overall abilities; and questionnaire surveys to assess teaching methods, including interest, satisfaction, problem-solving ability, learning time/pressure, independence, teamwork, communication, and clinical reasoning.; (5) RCTs were included; and (6) the publications were in English.</p>
</sec>
<sec id="sec6">
<title>Exclusion criteria</title>
<p>Studies were excluded if: (1) full-text data were unavailable after attempts to retrieve from authors or institutional repositories; (2) no quantifiable outcome measures (e.g., knowledge scores, skill performance, satisfaction ratings) were reported; (3) they were retracted, or published as abstracts only.</p>
</sec>
<sec id="sec7">
<title>Data extraction</title>
<p>Two independent reviewers (Cao H and Song L) extracted data from the included studies, adhering to the guidelines set forth by the Cochrane Collaboration for Systematic Reviews. They each independently reviewed the full texts of studies that potentially met the inclusion and exclusion criteria, and subsequently extracted the relevant data as followed: name of the first author, year of publication, participants characteristics, number of participants, intervention, comparison, study duration, outcome assessment measures and study design type.</p>
</sec>
<sec id="sec8">
<title>Quality assessment</title>
<p>Utilizing the Cochrane Collaboration&#x2019;s Risk of Bias 2.0 tool (RoB2) (<xref ref-type="bibr" rid="ref15">15</xref>), two independent investigators (Ji Z and Song L) systematically evaluated six following biases of the included articles: (1) bias arising from the randomization process; (2) bias due to deviations from intended interventions; (3) bias due to missing outcome data; (4) bias in the measurement of the outcome; (5) bias in selection of the reported result and (6) overall bias (<xref ref-type="bibr" rid="ref16">16</xref>). Each item was classified as high risk, low risk or some concern.</p>
</sec>
</sec>
<sec id="sec9">
<title>Statistical analyses</title>
<sec id="sec10">
<title>Pairwise meta-analysis</title>
<p>The pairwise meta-analyses were performed using a random-effects model in R 4.3.3 software (R Core Team) with the &#x201C;meta,&#x201D; &#x201C;netmeta,&#x201D; &#x201C;gemtc,&#x201D; and &#x201C;ggplot2&#x201D; packages to examine the direct evidence. Because all outcome measures were continuous, we opted to use standardized mean differences (SMDs) as the measure of effect size, along with 95% confidence intervals (CIs), to account for the variety of rating scales employed in the studies included (<xref ref-type="bibr" rid="ref17">17</xref>). To assess statistical heterogeneity in each pairwise comparison, we utilized the <italic>p</italic>-value of the Q-test, the <italic>I</italic><sup>2</sup> statistic, and the between-study variance (&#x03C4;<sup>2</sup>).</p>
</sec>
<sec id="sec11">
<title>Network meta-analysis</title>
<p>This NMA was conducted to assess and rank seven innovative teaching strategies in orthopaedics education by integrating both direct and indirect comparative analyses. The three outcome measures were presented as SMDs with accompanying 95% CIs, and each was analyzed separately. To ensure more cautious conclusions, irrespective of heterogeneity, a random-effects model was adopted (<xref ref-type="bibr" rid="ref18">18</xref>). The network plots were created using R 4.3.3 software. Furthermore, league tables and forest plots were constructed to showcase the effectiveness of all pairwise comparisons of teaching strategies in terms of effect sizes. The surface under the cumulative ranking curve (SUCRA) was used to rank the relative effectiveness of the teaching strategies. SUCRA is a key metric in NMA that quantifies the probability of an intervention (here, a teaching strategy) being the best, second-best, or worst among all compared options. It ranges from 0 to 100%, where a higher SUCRA value indicates a greater likelihood of being the most effective strategy. Unlike traditional pairwise meta-analysis, SUCRA integrates both direct and indirect comparative evidence from the network, providing a comprehensive and intuitive ranking of multiple interventions. We used SUCRA because it addresses the limitation of pairwise comparisons by synthesizing all available evidence, making it particularly valuable for our study&#x2014;where we compared eight distinct teaching strategies&#x2014;to identify the most promising approaches for orthopaedic education. A bar graph was also used to visually depict the SUCRA probabilities for each teaching strategy, aiding in a comparative examination of their influence on the three outcome indicators. To identify any discrepancies between direct and indirect comparisons, the node-splitting approach was utilized (<xref ref-type="bibr" rid="ref19">19</xref>, <xref ref-type="bibr" rid="ref20">20</xref>).</p>
</sec>
</sec>
</sec>
<sec sec-type="results" id="sec12">
<title>Results</title>
<sec id="sec13">
<title>Characteristics of included studies</title>
<p>After conducting thorough searches and removing duplicates, we identified 893 potential studies for further evaluation. These studies were then screened for eligibility based on their titles and abstracts, leading to the exclusion of 860 studies, leaving 33 for further consideration. Following a full-text assessment, 22 articles were excluded for various reasons. Ultimately, 11 articles (<xref ref-type="bibr" rid="ref1 ref2 ref3 ref4 ref5">1&#x2013;5</xref>, <xref ref-type="bibr" rid="ref21 ref22 ref23 ref24 ref25 ref26">21&#x2013;26</xref>) met the predefined inclusion and exclusion criteria and were chosen for inclusion in the NMA, as illustrated in <xref ref-type="fig" rid="fig1">Figure 1</xref>.</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>The flowchart of the study.</p>
</caption>
<graphic xlink:href="fmed-13-1762807-g001.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">PRISMA flowchart illustrating the systematic review process: initial records identified from four databases and reference lists, duplicates removed, titles and abstracts screened, records excluded with reasons, full-text articles assessed, and a final set of eleven studies included in the network meta-analysis with evaluation categories listed.</alt-text>
</graphic>
</fig>
<p><xref ref-type="table" rid="tab1">Table 1</xref> presents an overview of the key features of the 11 RCTs involving 690 medical education students or residents. Among these studies, three reported that 54.20% (374 out of 690) of the participants were undergraduate students. The outcome measures differed across the trials: 7 concentrated on theoretical exam scores, 7 on practical or experimental exam scores, and 4 assessed student satisfaction levels.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Basic characteristics of the included literature.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Study ID</th>
<th align="left" valign="top">Nation</th>
<th align="left" valign="top">Participants</th>
<th align="center" valign="top">Intervention</th>
<th align="center" valign="top">Control</th>
<th align="center" valign="top">Number (Interv./Ctl)</th>
<th align="center" valign="top">Outcome measurements</th>
<th align="left" valign="top">Teaching subjects</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">Xue et al. (2024) (<xref ref-type="bibr" rid="ref3">3</xref>)</td>
<td align="left" valign="middle">China</td>
<td align="left" valign="middle">Resident</td>
<td align="center" valign="middle">3D</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">30/30</td>
<td align="center" valign="middle">&#x2460; &#x2461;</td>
<td align="left" valign="middle">Proximal humerus fractures</td>
</tr>
<tr>
<td align="left" valign="middle">Xue et al. (2024) (<xref ref-type="bibr" rid="ref3">3</xref>)</td>
<td align="left" valign="middle">China</td>
<td align="left" valign="middle">Resident</td>
<td align="center" valign="middle">Video</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">29/30</td>
<td align="center" valign="middle">&#x2460; &#x2461;</td>
<td align="left" valign="middle">Proximal humerus fractures</td>
</tr>
<tr>
<td align="left" valign="middle">Xue et al. (2024) (<xref ref-type="bibr" rid="ref3">3</xref>)</td>
<td align="left" valign="middle">China</td>
<td align="left" valign="middle">Resident</td>
<td align="center" valign="middle">3D</td>
<td align="center" valign="middle">Video</td>
<td align="center" valign="middle">30/29</td>
<td align="center" valign="middle">&#x2460; &#x2461;</td>
<td align="left" valign="middle">Proximal humerus fractures</td>
</tr>
<tr>
<td align="left" valign="middle">Wang et al. (2024) (<xref ref-type="bibr" rid="ref2">2</xref>)</td>
<td align="left" valign="middle">China</td>
<td align="left" valign="middle">Undergraduate</td>
<td align="center" valign="middle">FC</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">69/69</td>
<td align="center" valign="middle">&#x2460; &#x2461;&#x2462;</td>
<td align="left" valign="middle">Basic theory</td>
</tr>
<tr>
<td align="left" valign="middle">Vall&#x00E9;e et al. (2024) (<xref ref-type="bibr" rid="ref1">1</xref>)</td>
<td align="left" valign="middle">France</td>
<td align="left" valign="middle">Orthopaedic residents</td>
<td align="center" valign="middle">VR</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">13/13</td>
<td align="center" valign="middle">&#x2461;</td>
<td align="left" valign="middle">Rotator cuff repair</td>
</tr>
<tr>
<td align="left" valign="middle">Capitani et al. (2024) (<xref ref-type="bibr" rid="ref21">21</xref>)</td>
<td align="left" valign="middle">Italy</td>
<td align="left" valign="middle">Orthopaedic residents</td>
<td align="center" valign="middle">VR</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">3/3</td>
<td align="center" valign="middle">&#x2460;</td>
<td align="left" valign="middle">Kyphoplasty</td>
</tr>
<tr>
<td align="left" valign="middle">Shuai et al. (2023) (<xref ref-type="bibr" rid="ref4">4</xref>)</td>
<td align="left" valign="middle">China</td>
<td align="left" valign="middle">Clinical internship students</td>
<td align="center" valign="middle">FC&#x202F;+&#x202F;TBL</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">55/54</td>
<td align="center" valign="middle">&#x2460; &#x2462;</td>
<td align="left" valign="middle">Basic theory</td>
</tr>
<tr>
<td align="left" valign="middle">Sun et al. (2022) (<xref ref-type="bibr" rid="ref22">22</xref>)</td>
<td align="left" valign="middle">China</td>
<td align="left" valign="middle">5-year undergraduate students</td>
<td align="center" valign="middle">3D&#x202F;+&#x202F;PBL</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">53/53</td>
<td align="center" valign="middle">&#x2460; &#x2462;</td>
<td align="left" valign="middle">Spinal anatomy, basic steps of common spinal surgery</td>
</tr>
<tr>
<td align="left" valign="middle">Lohre et al. (2020) (<xref ref-type="bibr" rid="ref23">23</xref>)</td>
<td align="left" valign="middle">Canada</td>
<td align="left" valign="middle">Orthopaedic residents</td>
<td align="center" valign="middle">VR</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">9/9</td>
<td align="center" valign="middle">&#x2461;</td>
<td align="left" valign="middle">Reverse shoulder arthroplasty</td>
</tr>
<tr>
<td align="left" valign="middle">Logishetty et al. (2019) (<xref ref-type="bibr" rid="ref24">24</xref>)</td>
<td align="left" valign="middle">United Kingdom</td>
<td align="left" valign="middle">Orthopaedic residents</td>
<td align="center" valign="middle">VR</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">12/12</td>
<td align="center" valign="middle">&#x2461;</td>
<td align="left" valign="middle">Total hip arthroplasty</td>
</tr>
<tr>
<td align="left" valign="middle">Hooper et al. (2019) (<xref ref-type="bibr" rid="ref25">25</xref>)</td>
<td align="left" valign="middle">United States</td>
<td align="left" valign="middle">Orthopaedic residents</td>
<td align="center" valign="middle">VR</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">7/7</td>
<td align="center" valign="middle">&#x2461;</td>
<td align="left" valign="middle">Total hip arthroplasty</td>
</tr>
<tr>
<td align="left" valign="middle">Cong et al. (2017) (<xref ref-type="bibr" rid="ref26">26</xref>)</td>
<td align="left" valign="middle">China</td>
<td align="left" valign="middle">Orthopaedic residents</td>
<td align="center" valign="middle">PBL</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">15/15</td>
<td align="center" valign="middle">&#x2460; &#x2461;&#x2462;</td>
<td align="left" valign="middle">Spine surgical skills</td>
</tr>
<tr>
<td align="left" valign="middle">Back et al. (2017) (<xref ref-type="bibr" rid="ref5">5</xref>)</td>
<td align="left" valign="middle">Germany</td>
<td align="left" valign="middle">Medical students</td>
<td align="center" valign="middle">Video</td>
<td align="center" valign="middle">LBL</td>
<td align="center" valign="middle">75/55</td>
<td align="center" valign="middle">&#x2460;</td>
<td align="left" valign="middle">Basic theory</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>&#x2460; Theoretical test scores; &#x2461; procedural or clinical skill scores; &#x2462; students&#x2019; satisfaction scores. PBL, problem-based learning; VR, virtual reality; 3D, three dimensions; FC, flipped classrooms; TBL, team-based learning; LBL, lecture-based learning; FC&#x202F;+&#x202F;TBL, flipped classrooms combined with team-based learning.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec14">
<title>Quality of included studies</title>
<p>Using the RoB2 tool for quality evaluation, <xref ref-type="fig" rid="fig2">Figure 2</xref> presents an overview of the results assessed from the 11 RCTs included. Among these studies, one study (9%) was determined to have a high risk of bias, two (18%) raised some concerns, and eight (73%) were considered to have a low risk of bias.</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Risk assessment of bias using the RoB2. Risk of bias items of all included studies are indicated as the percentages.</p>
</caption>
<graphic xlink:href="fmed-13-1762807-g002.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Horizontal stacked bar chart showing risk of bias assessments across six categories. Most domains display predominantly low risk of bias in green, with &#x201C;Randomization process&#x201D; and &#x201C;Overall Bias&#x201D; also including yellow for unclear risk and red for high risk. &#x201C;Selection of the reported result&#x201D; is marked gray as not applicable. A legend defines colors representing not applicable, low, unclear, and high risk of bias.</alt-text>
</graphic>
</fig>
<p>When assessing the randomization process, it was found that 8 studies (73%) were deemed to have a low risk of bias due to the proper use of random sequence generation methods. Two article (18%) raised some concerns in this regard. Furthermore, all studies reported outcomes for every participant, leading to a low risk of bias assessment concerning missing outcome data in all cases (<xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 2</xref>). Given that preregistration and protocols are not mandatory in medical education research trials (<xref ref-type="bibr" rid="ref27">27</xref>), the risk of bias related to selective reporting of results is not applicable in this context.</p>
</sec>
<sec id="sec15">
<title>Heterogeneity assessment</title>
<p>We conducted a heterogeneity analysis for each variable and observed significant heterogeneity (<italic>I</italic><sup>2</sup> &#x2265;&#x202F;50%) in the comparison of Video versus LBL (77.6%) in theoretical test scores and VR versus LBL (67.9%) in procedural or clinical skill scores (<xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 4A,B</xref>). Regarding the students&#x2019; satisfaction score, since only a single study was included for each teaching method, heterogeneity test could not be performed. Consequently, the certainty of evidence for this outcome is very low. Future research should employ standardized, psychometrically validated tools to enable meaningful cross-intervention comparisons.</p>
</sec>
<sec id="sec16">
<title>Pairwise meta-analyses</title>
<p>When it comes to the impact of theoretical test results, seven innovative teaching methods&#x2014;namely 3D, video, VR, FC, FC combined with TBL, PBL, and PBL integrated with 3D&#x2014;did not show any significant advantage over the traditional LBL approach (<xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 3A</xref>). However, in terms of procedural or clinical skill assessments, VR emerged as a more effective method compared to LBL (SMD&#x202F;=&#x202F;6.88, 95% CI: 1.05&#x2013;12.13; <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 3B</xref>). Additionally, student satisfaction ratings indicated that FC paired with TBL was more effective than LBL (SMD&#x202F;=&#x202F;1.42, 95% CI: 0.04&#x2013;2.79; <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 3C</xref>).</p>
</sec>
<sec id="sec17">
<title>Network meta-analyses</title>
<sec id="sec18">
<title>The theoretical test scores</title>
<p>Out of the 11 studies conducted, 7 involving 608 students and residents provided data on theoretical test scores (<xref ref-type="bibr" rid="ref2 ref3 ref4 ref5">2&#x2013;5</xref>, <xref ref-type="bibr" rid="ref21">21</xref>, <xref ref-type="bibr" rid="ref22">22</xref>, <xref ref-type="bibr" rid="ref26">26</xref>). This NMA comprehensively assessed the impact of various teaching methods, including video (2 studies), 3D (1 study), FC (1 study), PBL (1 study), FC combined with TBL (1 study), VR (1 study), and 3D integrated with PBL (1 study). A detailed network diagram illustrating all comparisons is shown in <xref ref-type="fig" rid="fig3">Figure 3A</xref>.</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>A network diagram of comparable studies for each outcome in the Bayesian network meta-analysis. <bold>(A)</bold> Theoretical test scores; <bold>(B)</bold> procedural or clinical skill scores; <bold>(C)</bold> students&#x2019; satisfaction scores. PBL, problem-based learning; VR, virtual reality; 3D, three dimensions; FC, flipped classrooms; TBL, team-based learning; LBL, lecture-based learning; FC&#x202F;+&#x202F;TBL, flipped classrooms combined with team-based learning.</p>
</caption>
<graphic xlink:href="fmed-13-1762807-g003.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Three network diagrams labeled A, B, and C compare different educational strategies. Diagram A centers on LBL, connected to eight strategies: FC, 3D, video, VR, FC+TBL, 3D+PBL, PBL, and LBL. Diagram B centers on TC/TT, connecting to FC, 3D, video, VR, and PBL. Diagram C centers on LBL, connected only to FC, FC+TBL, 3D+PBL, and PBL. Each strategy is represented by a red node with blue text.</alt-text>
</graphic>
</fig>
<p>The SMD values and 95% CI derived from NMA are shown in <xref ref-type="fig" rid="fig4">Figure 4A</xref>. The 95% CI for the comparisons of these teaching strategies included zero, indicating that there was no statistically significant difference among the seven innovative teaching approaches. The SUCRA rankings and probability values presented in <xref ref-type="fig" rid="fig5">Figure 5A</xref> indicate that FC&#x202F;+&#x202F;TBL has the highest likelihood of improving theoretical test scores in orthopedic education, with a probability of 81.73%. FC&#x202F;+&#x202F;TBL ranked first for theoretical performance; however, its estimated effect versus LBL was not statistically significant (SMD&#x202F;=&#x202F;14.16, 95% CI: &#x2212;1.5 to 29.24).</p>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>Pooled estimates of the network meta-analysis. <bold>(A)</bold> Standard mean differences (SMDs) (95% CI) of the theoretical test scores; <bold>(B)</bold> SMDs (95% CI) of the procedural or clinical skill scores; <bold>(C)</bold> SMDs (95% CI) of the students&#x2019; satisfaction scores. SMDs greater than zero indicate preference for the method defined by the column. Significant findings are emphasized in bold with background shading. PBL, problem-based learning; VR, virtual reality; 3D, three dimensions; FC, flipped classrooms; TBL, team-based learning; LBL, lecture-based learning; FC&#x202F;+&#x202F;TBL, flipped classrooms combined with team-based learning.</p>
</caption>
<graphic xlink:href="fmed-13-1762807-g004.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Heatmap comparing LBL, Video, 3D, FC, VR, FC+TBL, 3D+PBL, and PBL teaching methods across three panels labeled A, B, and C. Each cell shows mean differences and confidence intervals, with statistically significant results highlighted in red text and red shading. Blue shading highlights method labels. Data are arranged in triangular matrices to facilitate pairwise comparison.</alt-text>
</graphic>
</fig>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>The results of Bayesian ranking for primary outcomes. The line graph presents the ranking probabilities of various treatment options from first to last in terms of theoretical test scores <bold>(A)</bold>, procedural or clinical skill scores <bold>(B)</bold>, and students&#x2019; satisfaction scores <bold>(C)</bold>. The abscissa represents &#x201C;Rank,&#x201D; and the ordinate represents &#x201C;Probability.&#x201D; Different intervention measures are distinguished by lines of different colors. The ranking probability for each intervention corresponds to the position of the circle on the ordinate. PBL, problem-based learning; VR, virtual reality; 3D, three dimensions; FC, flipped classrooms; TBL, team-based learning; LBL, lecture-based learning; FC&#x202F;+&#x202F;TBL, flipped classrooms combined with team-based learning.</p>
</caption>
<graphic xlink:href="fmed-13-1762807-g005.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Three line charts labeled A, B, and C display probability versus rank for various educational groups, with each group represented by a different colored line. The x-axis shows rank and the y-axis shows probability, with a legend indicating groups such as 3D, FC, LBL, video, 3D+PBL, FC+TBL, PBL, and VR. Each chart presents distinct patterns in how group probabilities change by rank.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec19">
<title>Procedural or clinical skill scores</title>
<p>Seven studies, encompassing 337 students or residents, reported on this indicator (<xref ref-type="bibr" rid="ref1 ref2 ref3">1&#x2013;3</xref>, <xref ref-type="bibr" rid="ref23 ref24 ref25 ref26">23&#x2013;26</xref>). The NMA included various methods: video (<italic>n</italic>&#x202F;=&#x202F;1), 3D (<italic>n</italic>&#x202F;=&#x202F;1), FC (<italic>n</italic>&#x202F;=&#x202F;1), PBL (<italic>n</italic>&#x202F;=&#x202F;4), and VR (<italic>n</italic>&#x202F;=&#x202F;4). The specifics of other comparisons can be found in the network diagram presented in <xref ref-type="fig" rid="fig3">Figure 3B</xref>.</p>
<p><xref ref-type="fig" rid="fig4">Figure 4B</xref> showcased the precise SMD figures along with their 95% CI derived from the NMA. Students utilizing VR strategies attained markedly higher scores in procedural or clinical skill assessments when compared to those employing LBL strategies, with an SMD of 6.88 (95% CI: 1.05&#x2013;12.13). It&#x2019;s worth noting that no discernible differences were found in the indirect comparisons between the various novel teaching approaches. The SUCRA ranking and probability values presented in <xref ref-type="fig" rid="fig5">Figure 5B</xref> suggested that VR (with a probability of 62.07%) was the most probable approach to enhance scores in procedural or clinical skill tests.</p>
</sec>
<sec id="sec20">
<title>The students&#x2019; satisfaction score</title>
<p>A thorough examination of four studies (<xref ref-type="bibr" rid="ref2">2</xref>, <xref ref-type="bibr" rid="ref4">4</xref>, <xref ref-type="bibr" rid="ref22">22</xref>, <xref ref-type="bibr" rid="ref26">26</xref>) involving 383 students presented their satisfaction ratings, which reflect the students&#x2019; subjective assessments and perspectives on diverse teaching approaches. The teaching methods examined in this NMA included FC (<italic>n</italic>&#x202F;=&#x202F;1), FC combined with TBL (<italic>n</italic>&#x202F;=&#x202F;1), 3D integrated with PBL (<italic>n</italic>&#x202F;=&#x202F;1), and PBL alone (<italic>n</italic>&#x202F;=&#x202F;1). <xref ref-type="fig" rid="fig3">Figure 3C</xref> presents the network diagram illustrating all the comparisons made.</p>
<p>As depicted in <xref ref-type="fig" rid="fig4">Figure 4C</xref>, students who learned using the FC&#x202F;+&#x202F;TBL strategy exhibited significantly higher satisfaction scores compared to those who learned using LBL (1.42, with a 95% CI ranging from 0.04 to 2.79). These results consistent with the findings from the pairwise meta-analyses. Furthermore, the SUCRA analyses presented in <xref ref-type="fig" rid="fig5">Figure 5C</xref> indicated a high likelihood (61.53%) that PBL would be the most effective in boosting student satisfaction scores and subjective evaluations.</p>
</sec>
</sec>
</sec>
<sec sec-type="discussion" id="sec21">
<title>Discussion</title>
<p>Recently, progress in computer technology and changes in the healthcare service system have made it challenging for medical students trained in traditional settings to fully adapt to the growing needs of public healthcare (<xref ref-type="bibr" rid="ref28">28</xref>). Numerous innovative teaching methods have gained widespread adoption worldwide and shown promising results in improving teaching efficacy. However, there is uncertainty regarding the most effective teaching strategy for enhancing orthopedic teaching effectiveness due to the lack of direct comparative evidence. Compared to traditional pairwise meta-analysis, the NMA approach offers a more straightforward method and yields more insightful information (<xref ref-type="bibr" rid="ref29">29</xref>). Consequently, we undertook this NMA to assess the impact of various teaching methods on student performance and satisfaction, considering theoretical exam scores, practical or clinical skill assessments, and student satisfaction ratings. By synthesizing all available evidence from 11 RCTs involving 690 medical students or residents in orthopaedics, our findings revealed that VR stands out as the most effective method for enhancing the practical or clinical skills of medical students or residents, whereas PBL has proven to offer a more effective overall learning experience throughout the educational journey.</p>
<p>The training of orthopedic interns has shifted from a primary focus on theoretical mastery to an emphasis on clinical application. Traditional LBL teaching tends to concentrate on imparting theoretical knowledge, which can hinder the development of students&#x2019; creativity and individual traits, and overlooks their subjective initiative and potential (<xref ref-type="bibr" rid="ref30">30</xref>). Previous meta-analyses have found that PBL can improve knowledge scores compared to LBL. However, due to the relatively limited research on orthopedic education, no meta-analysis has been conducted to compare the effects of FC combined with TBL (FC&#x202F;+&#x202F;TBL) versus LBL on orthopedic teaching outcomes. While research indicates that both TBL and FC are more effective in enhancing student learning compared to traditional LBL, each method has its limitations (<xref ref-type="bibr" rid="ref31">31</xref>, <xref ref-type="bibr" rid="ref32">32</xref>). Some students have provided feedback indicating that although the FC offers high-quality instructional resources, it demands strong self-learning abilities and offers limited opportunities for student interaction, potentially hindering the learning effectiveness of certain students (<xref ref-type="bibr" rid="ref33">33</xref>, <xref ref-type="bibr" rid="ref34">34</xref>). Others have highlighted that TBL requires a substantial amount of time to master and necessitates a consistent schedule among team members (<xref ref-type="bibr" rid="ref15">15</xref>). However, when these two approaches are integrated, they compensate for each other&#x2019;s shortcomings, enabling students to engage with one another, acquire a broad range of knowledge in a brief period, and allocate more time to preparing for in-class problem discussions. More crucially, this combination fosters group discussions and critical thinking, enhances active communication abilities, and promotes a more relaxed atmosphere in the classroom (<xref ref-type="bibr" rid="ref35">35</xref>). The apparent advantage of FC&#x202F;+&#x202F;TBL may arise from synergistic pedagogical mechanisms. The FC fosters self-directed cognitive preparation, while TBL promotes collaborative knowledge application through structured problem-solving. This combination aligns with constructivist theory&#x2014;where learners actively construct knowledge through experience&#x2014;and social interdependence theory, which posits that positive group interdependence enhances motivation, accountability, and deep learning. In our study, when assessing the impact of orthopedic teaching on exam scores, we also found that FC&#x202F;+&#x202F;TBL is the most effective teaching method, with an 81.73% likelihood of effectiveness. This is consistent with the findings of previous study (<xref ref-type="bibr" rid="ref36">36</xref>).</p>
<p>The clinical skill test scores, which assess students&#x2019; competence in essential surgical techniques, offer a direct indication of the efficacy of hands-on training. Multiple systematic reviews have examined the advantages of incorporating VR technology into orthopaedic training programs. These reviews have consistently shown that VR notably improves both the theoretical understanding and practical abilities of learners, ranging from beginners to seasoned professionals like orthopaedists and neurosurgeons (<xref ref-type="bibr" rid="ref37">37</xref>). Particularly, the integration of VR into surgical training for spinal interventions marks a novel approach to honing residents&#x2019; skills and enhancing their self-assurance (<xref ref-type="bibr" rid="ref21">21</xref>). Our NMA revealed that VR significantly outperforms traditional LBL significantly (SMD&#x202F;=&#x202F;6.88, 95% CI: 1.05 to 12.13), with a 62.07% probability of being the most effective method for improving procedural or clinical skill test scores. These results further highlight VR&#x2019;s potential as a highly efficient and cost-effective training tool, effectively bridging the gap between theoretical knowledge and practical application.</p>
<p>A crucial metric for assessing teaching methods is student satisfaction. Prior systematic reviews have indicated that students in the PBL group exhibit greater interest in and satisfaction with teaching (<xref ref-type="bibr" rid="ref38">38</xref>). Our analysis revealed that according to the SUCRA analysis, there is a 61.53% probability that PBL is the most effective approach for enhancing student satisfaction scores and subjective evaluations. PBL encourages students&#x2019; proactive participation, fosters their learning abilities, and boosts their enthusiasm for learning. Norman et al. (<xref ref-type="bibr" rid="ref39">39</xref>) demonstrated that PBL enhances students&#x2019; learning interest, self-learning capabilities, and sustains these interests over time. Another study found that students in the PBL group outperformed those in the traditional teaching group in terms of professional knowledge and classroom satisfaction (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05) (<xref ref-type="bibr" rid="ref22">22</xref>). Likewise, Ren et al. (<xref ref-type="bibr" rid="ref40">40</xref>) reported that PBL significantly improved satisfaction among both students and teachers, aligning with our meta-analysis findings. Nevertheless, several pivotal factors, such as small group sizes and realistic case scenarios, influence teaching satisfaction (<xref ref-type="bibr" rid="ref41">41</xref>).</p>
<p>This research consolidates and strengthens the existing evidence base in the academic literature on orthopedic education, advocating for innovative teaching approaches. To our understanding, previous systematic reviews and NMAs have assessed the impact of novel teaching methods on particular majors and curricula, including medicine (<xref ref-type="bibr" rid="ref27">27</xref>), nursing (<xref ref-type="bibr" rid="ref42">42</xref>), and pharmacology (<xref ref-type="bibr" rid="ref43">43</xref>). However, our study represents the inaugural systematic review and NMA to explore the effects of innovative teaching strategies specifically in orthopaedics, thereby addressing a gap in orthopedic education. Orthopaedics differs from other surgical specialties (e.g., neurosurgery, general surgery) in several critical ways that shape educational needs: (1) it emphasizes hands-on psychomotor skills (e.g., fracture reduction, implant placement, arthroscopic manipulation) that require precise spatial reasoning and muscle memory&#x2014;skills that may respond differently to instructional strategies than the cognitive or procedural focus of other fields; (2) orthopaedic training covers a broad spectrum of subspecialties (e.g., trauma, spine, sports medicine, joint replacement), each with distinct technical and decision-making demands; (3) orthopaedic trainees often balance high operative volume with didactic learning, creating unique time constraints that influence the applicability of teaching strategies (e.g., concise, simulation-based training may be more feasible than lengthy group discussions). Additionally, orthopaedic surgeons-in-training face distinct challenges, such as adapting to rapidly evolving implant technologies and navigating the physical demands of surgical procedures, which differ from the training priorities of other surgical specialists (e.g., neurosurgeons may focus more on imaging interpretation and microsurgical precision). By focusing exclusively on orthopaedics, our study provides targeted evidence for educators in this specialty, who previously lacked a synthesized overview of which innovative strategies align with their trainees&#x2019; unique needs. This specificity enhances the translatability of our findings to clinical practice, making it a core strength of the study. The NMA findings offer a ranked order of eight teaching strategies based on their effectiveness in mesh fixation, guiding curriculum designers and educators in adopting these novel instructional techniques. Furthermore, to ensure comprehensiveness and minimize selection bias, two authors independently conducted the study selection, data extraction, and quality assessment processes.</p>
<p>While FC&#x202F;+&#x202F;TBL and VR show promise, their real-world adoption requires careful consideration of feasibility. VR implementation entails significant costs for hardware, software licensing, and faculty training. FC&#x202F;+&#x202F;TBL demands curriculum redesign and skilled facilitation. We recommend phased integration&#x2014;starting with pilot programs in well-resourced institutions&#x2014;and the development of open-access TBL modules to support scalability in low-resource settings.</p>
<p>Despite its strengths, our study also has some limitations that should be acknowledged. Firstly, this NMA assesses only seven distinct novel teaching strategies, excluding other modes and various combinations of methodologies. Each teaching method incorporates a limited number of studies, with a maximum of five. The intricacy stemming from the amalgamation of diverse teaching approaches may impede the conduct of the NMA. Nonetheless, this NMA can aid in pinpointing effective teaching strategies and optimizing course arrangement. Secondly, the nature of the instructional approach precludes blinding of both students and instructors. Consequently, students may modify their behavior when aware of being studied under different teaching strategies, thereby affecting the reliability of evidence in RCTs. This limitation is an inherent and crucial shortcoming in all primary studies included in this meta-analysis. Given that pre-registration of protocols is not mandatory in educational research, the bias related to selective reporting of results does not apply when assessing literature quality, which impacts the quality evaluation of the included studies. Thirdly, this study is restricted to English-language publications, potentially overlooking trials with negative outcomes that may exist in extensive national databases, such as those in Chinese literature (<xref ref-type="bibr" rid="ref44">44</xref>). Fourthly, differences in baseline characteristics among students, including residents and medical students in the included studies, the broad design framework, and variations in teacher expertise levels may introduce a certain degree of heterogeneity (<xref ref-type="bibr" rid="ref45">45</xref>). Moreover, NMA differs from direct comparison and carries an additional risk of bias, particularly when few direct comparisons exist between the novel teaching strategies in our NMA, potentially leading to imprecision. Significant heterogeneity and imprecision in the data substantially degrade the quality of evidence, reducing the accuracy of results. A further limitation is the overrepresentation of Chinese orthopaedic residents, which may limit generalizability to Western or low-resource settings. Educational and cultural differences may affect engagement with strategies like TBL (<xref ref-type="bibr" rid="ref46">46</xref>). Generational factors also matter: our predominantly Gen Z cohort tends to favor technology-enhanced tools like VR, which may not reflect preferences in other regions or age groups (<xref ref-type="bibr" rid="ref47">47</xref>). Gender disparities in orthopaedics (e.g., lower female representation in some settings) could further influence participation in collaborative methods (<xref ref-type="bibr" rid="ref48">48</xref>). Moreover, promising interventions such as VR and high-fidelity 3D simulations require resources often unavailable in low- and middle-income countries. Future research should test low-cost alternatives (e.g., free online modules, low-fidelity simulations) and include more diverse international samples to improve external validity. These contextual factors likely contributed to the modest effects observed for some innovative strategies, underscoring their context-dependent efficacy. In addition, our analysis included 11 RCTs involving 690 participants; however, many comparisons&#x2014;such as VR for theoretical knowledge&#x2014;were informed by a single study. This sparsity may reduce the precision and stability of effect estimates for certain nodes. Although sensitivity analyses excluding high-risk-of-bias studies yielded consistent rankings, future large-scale, head-to-head randomized trials are essential to validate these findings. Lastly, this study does not comprehensively capture other vital qualities and skills of orthopedic residents or students in the &#x201C;outcomes&#x201D; section, such as case analysis ability, social and communication skills, problem-solving and self-learning capabilities, and subjective enthusiasm. Future research should involve direct comparisons among novel teaching strategies to identify optimal educational approaches for orthopedic education.</p>
</sec>
<sec sec-type="conclusions" id="sec22">
<title>Conclusion</title>
<p>In conclusion, our NMA have provided valuable insights into the effectiveness of novel teaching strategies in orthopaedics education. Among the strategies evaluated, FC&#x202F;+&#x202F;TBL and VR emerged as the most effective methods for improving theoretical test scores and procedural or clinical skill scores, respectively. However, it is important to note that the differences among the teaching strategies were relatively minor, and more research is needed to fully understand their relative advantages and disadvantages. Future studies should focus on larger sample sizes, diverse student populations, and a wider range of outcome measures to provide a more comprehensive evaluation of teaching strategies in orthopaedics education. Overall, our findings have important implications for curriculum designers and educators seeking to optimize the learning experience for orthopaedics students or residents.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec23">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">Supplementary material</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="author-contributions" id="sec24">
<title>Author contributions</title>
<p>HC: Data curation, Formal analysis, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. ZJ: Data curation, Investigation, Methodology, Writing &#x2013; review &#x0026; editing. LS: Data curation, Formal analysis, Methodology, Project administration, Writing &#x2013; review &#x0026; editing. HW: Investigation, Project administration, Supervision, Validation, Writing &#x2013; review &#x0026; editing. YC: Project administration, Supervision, Writing &#x2013; review &#x0026; editing. GJ: Conceptualization, Software, Validation, Visualization, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec sec-type="COI-statement" id="sec25">
<title>Conflict of interest</title>
<p>The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="sec26">
<title>Generative AI statement</title>
<p>The author(s) declared that Generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="sec27">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="sec28">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fmed.2026.1762807/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fmed.2026.1762807/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Supplementary_file_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/>
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<fn fn-type="custom" custom-type="edited-by" id="fn0001">
<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/393873/overview">Arnaud Delafontaine</ext-link>, Universit&#x00E9; libre de Bruxelles, Belgium</p></fn>
<fn fn-type="custom" custom-type="reviewed-by" id="fn0002">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1212857/overview">Vincenzo Giordano</ext-link>, Hospital Municipal Miguel Couto, Brazil</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3061911/overview">Xin Wang</ext-link>, Wuhan University, China</p></fn>
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<fn fn-type="abbr" id="abbrev1"><label>Abbreviations:</label><p>NMA, network meta-analysis; PBL, problem-based learning; VR, virtual reality; 3D, three dimensions; FC, flipped classrooms; TBL, team-based learning; LBL, lecture-based learning; RCTs, randomized controlled trials; SMD, standard mean difference; CI, confidence interval; PRISMA, preferred reporting items for systematic reviews and meta-analyses; SUCRA, surface under the cumulative ranking probabilities analysis; PICO, population, intervention, comparison, and outcome; RoB2, version 2 of risk of bias tool.</p></fn>
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