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<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Physiol.</journal-id>
<journal-title>Frontiers in Physiology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Physiol.</abbrev-journal-title>
<issn pub-type="epub">1664-042X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-id pub-id-type="publisher-id">1612882</article-id>
<article-id pub-id-type="doi">10.3389/fphys.2025.1612882</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Physiology</subject>
<subj-group>
<subject>Systematic Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>The effectiveness of virtual reality in people with osteoporosis or osteopenia: a systematic review and meta-analysis of randomized controlled trials</article-title>
<alt-title alt-title-type="left-running-head">He et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fphys.2025.1612882">10.3389/fphys.2025.1612882</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>He</surname>
<given-names>Shunxia</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2997533/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Dong</surname>
<given-names>Shiqiu</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<uri xlink:href="https://loop.frontiersin.org/people/3113232/overview"/>
<contrib contrib-type="author">
<name>
<surname>Lin</surname>
<given-names>Xiaoguang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2996777/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
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<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Zhijie</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/642700/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
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<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Diao</surname>
<given-names>Yuzi</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2993780/overview"/>
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<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Gao</surname>
<given-names>Xiao</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/3104472/overview"/>
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<aff id="aff1">
<sup>1</sup>
<institution>Heilongjiang University of Chinese Medicine</institution>, <addr-line>Harbin</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Heilongjiang Nursing College</institution>, <addr-line>Harbin</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Graduate School</institution>, <institution>Gachon University</institution>, <addr-line>Seongnam-si</addr-line>, <addr-line>Gyeonggi-do</addr-line>, <country>Republic of Korea</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Shanxi Province Hospital of Traditional Chinese Medicine</institution>, <addr-line>Taiyuan</addr-line>, <country>China</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Heilongjiang Vocational College of Winter Sports</institution>, <addr-line>Harbin</addr-line>, <country>China</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>The Fourth Affiliated Hospital of Heilongjiang University of Chinese Medicine</institution>, <addr-line>Harbin</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1228916/overview">M&#xe1;rio Cunha Espada</ext-link>, Instituto Politecnico de Setubal (IPS), Portugal</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2186969/overview">Djandan Tadum Arthur Vithran</ext-link>, Central South University, China</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3053715/overview">Danish Hassan</ext-link>, Riphah International University (Lahore), Pakistan</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Xiao Gao, <email>arthur2557@126.com</email>
</corresp>
</author-notes>
<pub-date pub-type="epub">
<day>02</day>
<month>07</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1612882</elocation-id>
<history>
<date date-type="received">
<day>16</day>
<month>04</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>23</day>
<month>06</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 He, Dong, Lin, Wang, Diao and Gao.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>He, Dong, Lin, Wang, Diao and Gao</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). 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.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>Osteoporosis is a global bone disease, and drug therapy carries the risk of side effects, requiring exploration of safe and effective alternative therapies. Virtual reality (VR) has shown potential in rehabilitation medicine, but its efficacy in the management of osteoporosis and osteopenia has not been systematically evaluated.</p>
</sec>
<sec>
<title>Method</title>
<p>Using PubMed, Embase, the Cochrane Library, and Web of Science, we conducted a comprehensive database search to identify randomized controlled trials (RCTs) investigating the effects of VR on osteoporosis and bone loss. Trials published up to 30 March 2025 met our predefined inclusion and exclusion criteria. We extracted data, reviewed the literature. We assessed the methodological quality of the included trials and the certainty of the pooled evidence. Meta-analyses were performed using StataSE version 16.</p>
</sec>
<sec>
<title>Results</title>
<p>Our meta-analysis included 216 patients from 5 RCTs. All cases included in our study adopted the non-immersive VR intervention approach. Femoral neck bone mineral density (BMD) (standardized mean difference [SMD] &#x3d; 0.77, 95% confidence interval [CI] &#x3d; 0.35&#x2013;1.19, P &#x3c; 0.0001, I<sup>2</sup> &#x3d; 0%), balance (SMD &#x3d; 2.58, 95% CI &#x3d; 1.10&#x2013;4.05, P &#x3d; 0.001, I<sup>2</sup> &#x3d; 91.2%) and mobility (SMD &#x3d; 1.63, 95% CI &#x3d; 0.14&#x2013;3.13, P &#x3d; 0.032, I<sup>2</sup> &#x3d; 93.7%) were improved compared to the control group. However, lumbar BMD (SMD &#x3d; 0.39, 95% CI: &#x2212;0.02, 0.80, P &#x3d; 0.062, I<sup>2</sup> &#x3d; 0%) and quality of life (QOL) (SMD &#x3d; 2.50, 95% CI: &#x2212;2.15, 7.16, P &#x3d; 0.292, I<sup>2</sup> &#x3d; 97.4%) were not significantly improved compared to the control group. None of the included studies reported adverse events or safety data.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>This systematic evaluation provides valuable evidence for the management of osteoporosis and osteopenia through VR. However, given the overall low and very low level of evidence, the results need to be treated with caution. In the future, VR may be a potential treatment for osteoporosis and osteopenia.</p>
</sec>
<sec>
<title>Systematic Review Registration</title>
<p>
<ext-link ext-link-type="uri" xlink:href="https://www.crd.york.ac.uk/PROSPERO/view/CRD420251023178">https://www.crd.york.ac.uk/PROSPERO/view/CRD420251023178</ext-link>, PROSPERO, identifier CRD420251023178.</p>
</sec>
</abstract>
<kwd-group>
<kwd>osteopenia</kwd>
<kwd>virtual reality</kwd>
<kwd>exercise</kwd>
<kwd>aging</kwd>
<kwd>osteoporosis</kwd>
</kwd-group>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Exercise Physiology</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1">
<title>1 Introduction</title>
<p>Osteoporosis is a systemic skeletal disease characterized by decreased bone mass and deterioration of bone microarchitecture, with a core diagnostic criterion of bone mineral density (BMD) T-value &#x2264; &#x2212;2.5 (<xref ref-type="bibr" rid="B18">Kanis, 1990</xref>; <xref ref-type="bibr" rid="B37">Rosen, 2018</xref>). Osteopenia is a transitional state between normal and osteoporotic BMD, with a T-value of &#x2212;1.0 to &#x2212;2.5 (<xref ref-type="bibr" rid="B19">Karaguzel and Holick, 2010</xref>). Osteopenia is often considered a precursor of osteoporosis, and may signal a further loss of BMD (<xref ref-type="bibr" rid="B19">Karaguzel and Holick, 2010</xref>). Aging and feminization are associated with osteoporosis, and women have a significantly increased risk of osteoporosis after menopause (<xref ref-type="bibr" rid="B1">Aspray and Hill, 2019</xref>; <xref ref-type="bibr" rid="B10">Fan et al., 2024</xref>). One study showed that the number of new cases of osteoporosis is expected to reach 41.5 million globally in 2019, and is expected to increase to 263.2 million cases between 2030 and 2034 (<xref ref-type="bibr" rid="B46">Zhu et al., 2023</xref>). Osteoporosis is a huge medical and economic burden in all regions of the world (<xref ref-type="bibr" rid="B15">Hopkins et al., 2016</xref>; <xref ref-type="bibr" rid="B2">Aziziyeh et al., 2019</xref>; <xref ref-type="bibr" rid="B40">Tatangelo et al., 2019</xref>). Currently in osteoporosis, medication reduces the risk of fracture and stimulates bone formation, increasing BMD (<xref ref-type="bibr" rid="B34">Reid and Billington, 2022</xref>). However, medication also has some side effects, which need to be treated with caution (<xref ref-type="bibr" rid="B20">Khan et al., 2017</xref>). Therefore, there is a need to develop alternative therapies that are safe, accessible and have a high level of participation.</p>
<p>In addition to pharmacological interventions, various nonpharmacological therapies have been shown to improve balance and mobility in patients with osteoporosis or osteopenia. For example, traditional physical therapy programs focusing on strength training, balance exercises, and aerobic exercise have been shown to have positive effects on physical function and quality of life in patients with osteoporosis and osteopenia (<xref ref-type="bibr" rid="B6">Chen et al., 2019</xref>). Similarly, exercises such as Tai Chi have gained recognition for their potential to enhance balance and reduce the risk of falls in older adults. These traditional interventions play a vital role in the management of osteoporosis and osteopenia (<xref ref-type="bibr" rid="B23">Li et al., 2004</xref>). However, they can face challenges in terms of patient engagement and compliance, especially in those who find the exercises monotonous or lack motivation.</p>
<p>Virtual Reality (VR) is a technology that provides multi-sensory interactive experiences through computer simulation of three-dimensional environments, and its core classifications include immersive and non-immersive (<xref ref-type="bibr" rid="B32">Prinz et al., 2023</xref>). In recent years, the application of VR in medicine has expanded from surgical training to rehabilitation, and has demonstrated unique advantages in neurorehabilitation and chronic pain management (<xref ref-type="bibr" rid="B31">Pourmand et al., 2017</xref>). VR-based rehabilitation is more conducive to the development of physical health than conventional rehabilitation, positively affecting recovery of aerobic function, balance, pain levels, psychological and motor function, in addition to improving patient motivation (<xref ref-type="bibr" rid="B16">Howard, 2017</xref>; <xref ref-type="bibr" rid="B9">de Ara&#xfa;jo et al., 2019</xref>). However, as an emerging treatment modality, VR initially faced implementation barriers, including large financial investments, technical challenges, and operator training (<xref ref-type="bibr" rid="B13">Glegg and Levac, 2018</xref>; <xref ref-type="bibr" rid="B7">Chung et al., 2021</xref>; <xref ref-type="bibr" rid="B38">Sarkar et al., 2021</xref>). Based on the development of VR in rehabilitation, researchers have begun to explore its use in patients with osteoporosis or osteopenia, but the dispersed nature of the available evidence and the lack of systematic summarization have hindered the clinical translation process.</p>
<p>Preliminary clinical trials suggest that VR interventions are effective in improving balance function in patients with osteoporosis (<xref ref-type="bibr" rid="B43">Yilmaz and K&#xf6;sehasano&#x11f;ullar&#x131;, 2024</xref>). A study of patients with postmenopausal osteoporosis showed that VR was effective in improving physical performance and quality of life (QOL) (<xref ref-type="bibr" rid="B36">Riaz et al., 2024b</xref>). In addition, Meta-analyses for other musculoskeletal disorders further support the efficacy of VR. Both non-immersive and immersive VR-assisted active training are effective in reducing back and neck pain symptoms (<xref ref-type="bibr" rid="B24">Lo et al., 2024</xref>). VR-based rehabilitation improves pain, motor function, and anxiety in total knee replacement patients within 1 month after surgery. However, no study has comprehensively evaluated the effects of VR on functional outcomes in patients with osteoporosis or osteopenia.</p>
<p>To fill this knowledge gap, this study aimed to integrate the existing evidence through systematic evaluation and Meta-analysis to provide an evidence-based basis for the clinical application of VR in the management of osteoporosis and osteopenia. These findings specifically focus on BMD, the effects of balance, mobility and QOL.</p>
</sec>
<sec sec-type="methods" id="s2">
<title>2 Methods</title>
<p>This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (<xref ref-type="bibr" rid="B30">Moher et al., 2009</xref>). Comprehensive methodological details are outlined in <xref ref-type="sec" rid="s12">Supplementary Table 1</xref>. The study protocol has been registered with International Prospective Register of Systematic Reviews (PROSPERO) under the identifier CRD420251023178.</p>
<sec id="s2-1">
<title>2.1 Search strategy</title>
<p>We searched PubMed, Embase, Web of Science, and Cochrane databases from inception to 30 March 2025, using the terms &#x201c;virtual reality,&#x201d; &#x201c;osteoporosis,&#x201d; and &#x201c;randomized controlled trial.&#x201d; To minimize missed studies, we also reviewed the references of included studies. The search strategies for each database are detailed in <xref ref-type="sec" rid="s12">Supplementary Table 2</xref>.</p>
</sec>
<sec id="s2-2">
<title>2.2 Eligibility criteria and study selection</title>
<p>Studies were included based on the PICOs criteria:<list list-type="simple">
<list-item>
<p>(1) Populations: Patients aged &#x2265;18 years with a clinical diagnosis of osteoporosis or osteopenia (<xref ref-type="bibr" rid="B42">WHO Study Group, 1994</xref>);</p>
</list-item>
<list-item>
<p>(2) Interventions: VR;</p>
</list-item>
<list-item>
<p>(3) Comparator: Non-VR interventions such as active control (traditional training); passive control (health education, walking or placebo);</p>
</list-item>
<list-item>
<p>(4) Outcomes: BMD, Balance, Mobility, and Quality of life (QOL);</p>
</list-item>
<list-item>
<p>(5) Study Design: Randomized controlled trials (RCTs).</p>
</list-item>
</list>
</p>
<p>Studies were excluded if they were (1) conference abstracts, (2) animal studies, (3) unpublished papers, (4) non-English language studies, or (5) ongoing studies or protocols. Two independent reviewers (SXH and XGL) conducted parallel title/abstract screening using predefined eligibility criteria. Articles meeting preliminary inclusion thresholds underwent subsequent full-text evaluation by both reviewers. Inter-rater discrepancies were resolved via consensus-based adjudication involving a senior researcher (XGL). Search results were imported into EndNote version X9 (Thomson Research Software, Stamford, CT, United States).</p>
</sec>
<sec id="s2-3">
<title>2.3 Data extraction</title>
<p>Extracted data included study characteristics (authors&#x2019; names, year of publication, and study location), participant details (sample size and mean age), intervention characteristics (intervention specifics for both groups, frequency, and duration), and outcome metrics. For missing data within the studies, we chose to contact the corresponding author via email. If data could not be obtained, we excluded the studies. We uniformly transformed the data into means and standard deviations to summarize the results. Two reviewers (SXH and XGL) independently performed data extraction, with verification by a third reviewer (XG). We calculated Cohen&#x2019;s kappa coefficients (&#x3ba;) for a randomly selected subset of 20% of the included studies (n &#x3d; 1/5) to validate the consistency of screening by two independent researchers (<xref ref-type="bibr" rid="B22">Landis and Koch, 1977</xref>).</p>
</sec>
<sec id="s2-4">
<title>2.4 Quality assessment and certainty of evidence</title>
<p>The methodological quality of the studies was assessed by using the Physiotherapy Evidence Database (PEDro) scale (<xref ref-type="bibr" rid="B5">Cashin and McAuley, 2020</xref>). Higher scores (lowest score &#x3d; 0; highest score &#x3d; 10) indicate better methodological quality on the 11-item PEDro scale. To classify studies according to their quality, the following cut-off points were proposed: excellent (9&#x2013;10), good (6&#x2013;8), fair (4&#x2013;5), and poor (&#x2264;3). The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology was used to assess the certainty of evidence, with rankings ranging from high to very low (<xref ref-type="bibr" rid="B28">Meader et al., 2014</xref>).</p>
</sec>
<sec id="s2-5">
<title>2.5 Data analysis</title>
<p>Data from included studies were converted to means and standard deviations for summary. Graphical data were extracted via GetData Graph Digitizer (v2.22) for numerical conversion. Random-effects models were used to summarize each outcome, reporting the standard mean difference (SMD) and 95% confidence interval (CI) (<xref ref-type="bibr" rid="B30">Moher et al., 2009</xref>). Heterogeneity quantification employed Cochran&#x2019;s Q statistic supplemented by I<sup>2</sup> metrics, applying conventional interpretation thresholds: I<sup>2</sup> &#x3c;50% (low), 50%&#x2013;75% (moderate), and &#x3e;75% (substantial). A P-value &#x3c;0.05 was considered statistically significant.</p>
<p>Sensitivity analyses were performed using a stepwise exclusion of single studies to ensure the robustness of findings. Subgroup analyses and meta-regression were performed to explore heterogeneity according to the type of control group (<xref ref-type="bibr" rid="B3">Berkey et al., 1995</xref>). Data analysis was performed using StataSE (version 16. 0; Stata Corp LP, College Station, Texas, The United States of America).</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>3 Results</title>
<sec id="s3-1">
<title>3.1 Search result</title>
<p>From the databases used for the initial search, 33 potentially relevant studies were identified (PubMed, n &#x3d; 5; Embase, n &#x3d; 5; Cochrane Library, n &#x3d; 15; Web of Science, n &#x3d; 8). After de-duplication, 19 studies were screened on the basis of title and abstract. Subsequently, after deleting 15 studies, 4 studies remained for meta-analysis. In addition, 1 study was screened by manually searching the reference list. Finally, a total of 5 studies (<xref ref-type="bibr" rid="B12">Gilani et al., 2023</xref>; <xref ref-type="bibr" rid="B45">Zhao et al., 2023</xref>; <xref ref-type="bibr" rid="B35">Riaz et al., 2024a</xref>; <xref ref-type="bibr" rid="B36">Riaz et al., 2024b</xref>; <xref ref-type="bibr" rid="B43">Yilmaz and K&#xf6;sehasano&#x11f;ullar&#x131;, 2024</xref>) were included for data summarization (<xref ref-type="fig" rid="F1">Figure 1</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>PRISMA flow chart for the study selection.</p>
</caption>
<graphic xlink:href="fphys-16-1612882-g001.tif">
<alt-text content-type="machine-generated">Flowchart outlining a study selection process for a meta-analysis. It begins with 33 records identified through database searches from PubMed, Embase, Cochrane Library, and Web of Science. After removing duplicates, 19 records remain. Ten were excluded at the title and abstract level. Nine full-text articles were assessed for eligibility, with five excluded for reasons like non-RCTs and irrelevant topics. Five studies met inclusion criteria and additional records were identified through reference searching.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-2">
<title>3.2 Characteristics of included studies</title>
<p>Inter-rater reliability of data extraction was assessed using the Cohen&#x2019;s kappa coefficient (&#x3ba;) for a 20% sample of randomized studies. &#x3ba; value of 0.82 (95% CI 0.72&#x2013;0.92) reflects a high degree of agreement among reviewers, ensuring the robustness of the data extraction process. All five studies involved a total of 216 patients. The five studies were from Pakistan, China, Iran and Turkey. The mean age of the patients in the experimental group ranged from 58.3 to 72.2 years, and the mean age of the patients in the control group ranged from 58 to 73.4 years. The VR sessions ranged from 45 to 51 min each, three times a week, for 6&#x2013;48 weeks. The control group received conventional training, home exercise, or walking, while the experimental group had VR interventions. None of the studies reported follow-up data. <xref ref-type="table" rid="T1">Table 1</xref> summarizes the characteristics of the included studies.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Characteristics of included articles.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="center">Study</th>
<th rowspan="2" align="center">Country</th>
<th rowspan="2" align="center">Design</th>
<th rowspan="2" align="center">Diagnosis</th>
<th rowspan="2" align="center">Inclusion criteria</th>
<th colspan="4" align="center">Experimental group</th>
<th colspan="4" align="center">Control group</th>
<th rowspan="2" align="center">Outcome</th>
</tr>
<tr>
<th align="center">Sample size</th>
<th align="center">Age (year)</th>
<th align="center">Intervention</th>
<th align="center">Time, frequency</th>
<th align="center">Sample size</th>
<th align="center">Age (year)</th>
<th align="center">Intervention</th>
<th align="center">Time, frequency</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">
<xref ref-type="bibr" rid="B35">Riaz et al. (2024a)</xref> (1)</td>
<td align="center">Pakistan</td>
<td align="center">RCT</td>
<td align="center">osteopenia</td>
<td align="center">Lumbar or femoral T-scores between &#x2212;1 and &#x2212;2.5</td>
<td align="center">22</td>
<td align="center">58.3 &#xb1; 5.1</td>
<td align="center">VR provided by Xbox Kinect; Walking Outdoors</td>
<td align="center">VR: 45 min per session, 3 times per week for 24 weeks; Walking outdoor: 30 min per day</td>
<td align="center">21</td>
<td align="center">58.0 &#xb1; 5.5</td>
<td align="center">Walking Outdoors</td>
<td align="center">30 min per day</td>
<td align="center">BMD</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B36">Riaz et al. (2024b)</xref> (2)</td>
<td align="center">Pakistan</td>
<td align="center">RCT</td>
<td align="center">osteopenia</td>
<td align="center">Lumbar or femoral T-scores between &#x2212;1 and &#x2212;2.5</td>
<td align="center">22</td>
<td align="center">58.3 &#xb1; 5.2</td>
<td align="center">VR provided by Xbox Kinect; Walking Outdoors</td>
<td align="center">VR: 45 min per session, 3 times per week for 24 weeks; Walking outdoor: 30 min per day</td>
<td align="center">21</td>
<td align="center">58.0 &#xb1; 5.6</td>
<td align="center">Walking Outdoors</td>
<td align="center">30 min per day</td>
<td align="center">Balance, Mobility, QOL</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B43">Yilmaz and K&#xf6;sehasano&#x11f;ullar&#x131; (2024)</xref>
</td>
<td align="center">Turkey</td>
<td align="center">RCT</td>
<td align="center">osteoporosis</td>
<td align="center">Lumbar spine and femoral neck T score &#x3c; -2.5</td>
<td align="center">30</td>
<td align="center">67 &#xb1; 10.6</td>
<td align="center">VR provided by Nintendo Wii-based</td>
<td align="center">3 times per week for 12 weeks</td>
<td align="center">30</td>
<td align="center">68 &#xb1; 9.1</td>
<td align="center">Traditional training (strength training, aerobic training, and balance exercises)</td>
<td align="center">3 times per week for 12 weeks</td>
<td align="center">Balance, Mobility</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B12">Gilani et al. (2023)</xref>
</td>
<td align="center">Iran</td>
<td align="center">RCT</td>
<td align="center">osteoporosis</td>
<td align="center">Lumbar spine and femoral neck T score &#x3c; -2.5</td>
<td align="center">10</td>
<td align="center">58.5 &#xb1; 6.2</td>
<td align="center">VR provided by Xbox Kinect</td>
<td align="center">51 min per day, 3 times per week for 6 weeks</td>
<td align="center">10</td>
<td align="center">59.4 &#xb1; 4.7</td>
<td align="center">Traditional training (strength training and balance training)</td>
<td align="center">45&#x2013;50 min per day, 3 times per week for 6 weeks</td>
<td align="center">Mobility, QOL</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B45">Zhao et al. (2023)</xref>
</td>
<td align="center">China</td>
<td align="center">RCT</td>
<td align="center">osteoporosis</td>
<td align="center">Lumbar spine and femoral neck T score &#x3c; -2.5</td>
<td align="center">25</td>
<td align="center">72.2 &#xb1; 3.6</td>
<td align="center">VR rehabilitation training system</td>
<td align="center">50 min per session, 3 times per week for 12 months</td>
<td align="center">25</td>
<td align="center">73.4 &#xb1; 3.3</td>
<td align="center">Traditional training (core muscle training, lower extremity muscle strength training, balance training and gait function training)</td>
<td align="center">50 min per session, 3 times per week for 12 months</td>
<td align="center">Balance, Mobility, BMD</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>RCTs, randomized controlled trials; VR, virtual reality; QOL, quality of life; BMD, bone mineral density.</p>
</fn>
<fn>
<p>Data are shown as mean standard deviation where appropriate.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-3">
<title>3.3 Risk of bias assessment and certainty of evidence</title>
<p>To assess the quality of the five included studies, the PEDro scale was used, which ranged from 5 to 8. Four (<xref ref-type="bibr" rid="B12">Gilani et al., 2023</xref>; <xref ref-type="bibr" rid="B45">Zhao et al., 2023</xref>; <xref ref-type="bibr" rid="B35">Riaz et al., 2024a</xref>; <xref ref-type="bibr" rid="B36">2024b</xref>) of the five studies were considered to be of good quality and one study (<xref ref-type="bibr" rid="B43">Yilmaz and K&#xf6;sehasano&#x11f;ullar&#x131;, 2024</xref>) was considered to be of fair quality. The primary methodological flaws in our included studies were: lack of intention-to-treat analysis (0/5), inadequate therapist blinding (1/5), and absence of participant blinding (1/5). <xref ref-type="table" rid="T2">Table 2</xref> shows the PEDro scores of the included studies. Ratings using the GRADE methodology for all outcome measurements were inconsistent and ranged from low to very low certainty in <xref ref-type="sec" rid="s12">Supplementary Table 3</xref>. Evidence certainty was downgraded by one level for serious concerns in two domains: risk of bias and imprecision.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>The methodological quality of included studies on the PEDro scale.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="center">Study</th>
<th colspan="11" align="center">Items of PEDro scale</th>
<th rowspan="2" align="center">Total scores</th>
</tr>
<tr>
<th align="center">1</th>
<th align="center">2</th>
<th align="center">3</th>
<th align="center">4</th>
<th align="center">5</th>
<th align="center">6</th>
<th align="center">7</th>
<th align="center">8</th>
<th align="center">9</th>
<th align="center">10</th>
<th align="center">11</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">
<xref ref-type="bibr" rid="B35">Riaz et al. (2024a)</xref> (1)</td>
<td align="center">Yes</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">7</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B36">Riaz et al. (2024b)</xref> (2)</td>
<td align="center">Yes</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">7</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B43">Yilmaz and K&#xf6;sehasano&#x11f;ullar&#x131; (2024)</xref>
</td>
<td align="center">Yes</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">0</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">5</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B12">Gilani et al. (2023)</xref>
</td>
<td align="center">Yes</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">8</td>
</tr>
<tr>
<td align="center">
<xref ref-type="bibr" rid="B45">Zhao et al. (2023)</xref>
</td>
<td align="center">Yes</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">0</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">6</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Items of the PEDro, scale: 1 &#x3d; specified eligibility criteria (yes/no); 2 &#x3d; random allocation; 3 &#x3d; concealed allocation; 4 &#x3d; comparability at baseline; 5, blinded subjects; 6, blinded therapists; 7, blinded assessors; 8, sufficient follow-up; 9, intention-to-treat analysis 10 &#x3d; comparison between groups; 11 &#x3d; point estimates and variability. For terms 2&#x2013;11:1, the corresponding criterion is satisfied; 0, the criterion is not satisfied.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-4">
<title>3.4 Outcomes synthesis</title>
<p>This section summarizes the results of VR acting on the osteoporotic population. At least two or more included studies reported on BMD, balance, mobility and QOL. Details of the tools involved in the included studies can be found in <xref ref-type="sec" rid="s12">Supplementary Table 4</xref>.</p>
<sec id="s3-4-1">
<title>3.4.1 BMD</title>
<p>Two studies (n &#x3d; 93) assessed the severity of osteoporosis in patients with osteoporosis using BMD. The results showed that VR improved femoral neck BMD (SMD &#x3d; 0.77, 95% CI: 0.35, 1.19, P &#x3c; 0.0001, I<sup>2</sup> &#x3d; 0%) but not lumbar spine BMD (SMD &#x3d; 0.39, 95% CI: &#x2212;0.02, 0.80, P &#x3d; 0.062, I<sup>2</sup> &#x3d; 0%) compared to controls (<xref ref-type="fig" rid="F2">Figure 2</xref>). The certainty of evidence was low for both (<xref ref-type="sec" rid="s12">Supplementary Table 3</xref>).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Forest plot of the effect of virtual reality on bone mineral density (BMD). <bold>(A)</bold> Femoral neck BMD; <bold>(B)</bold> Lumbar spine BMD.</p>
</caption>
<graphic xlink:href="fphys-16-1612882-g002.tif">
<alt-text content-type="machine-generated">Forest plots labeled A and B show meta-analysis results. Plot A includes studies by Riaz (2024) and Zhao (2023) with an overall SMD of 0.77. Plot B shows the same studies with an overall SMD of 0.39. Both plots indicate no heterogeneity.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-4-2">
<title>3.4.2 Balance</title>
<p>Three studies (n &#x3d; 153) assessed balance in osteoporotic patients. The results showed that VR improved balance compared to controls (SMD &#x3d; 2.58, 95% CI: 1.10, 4.05, P &#x3d; 0.001, I<sup>2</sup> &#x3d; 91.2%) (<xref ref-type="fig" rid="F3">Figure 3</xref>). The certainty of the evidence was very low (<xref ref-type="sec" rid="s12">Supplementary Table 3</xref>). Robust result was obtained by excluding one Riaz study from the sensitivity analysis and reducing heterogeneity to 0% (<xref ref-type="sec" rid="s12">Supplementary Figure 1A</xref>). Subgroup analysis based on the intervention in the control group revealed a greater advantage of VR in the passive control (SMD &#x3d; 4.69, 95% CI: 3.51, 5.87, P &#x3c; 0.0001) compared to the active control (SMD &#x3d; 1.67, 95% CI: 1.24, 2.11, P &#x3c; 0.0001, I<sup>2</sup> &#x3d; 0%) (<xref ref-type="sec" rid="s12">Supplementary Figure 2A</xref>). The meta-regression results showed that the type of control group was a contributing factor to heterogeneity (P &#x3d; 0.043).</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Forest plot of the effect of virtual reality on balance.</p>
</caption>
<graphic xlink:href="fphys-16-1612882-g003.tif">
<alt-text content-type="machine-generated">Forest plot showing the standardized mean differences (SMD) with 95% confidence intervals (CI) for three studies: Riaz 2024, Yilmaz 2024, and Zhao 2023. Riaz shows SMD of 4.69, CI 3.51 to 5.87; Yilmaz shows SMD of 1.84, CI 1.24 to 2.45; Zhao shows SMD of 1.49, CI 0.86 to 2.12. The overall estimate is 2.58, CI 1.10 to 4.05. I-squared is 91.2%, p-value is 0.000.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-4-3">
<title>3.4.3 Mobility</title>
<p>Four studies (n &#x3d; 173) assessed mobility in patients with osteoporosis. Results showed that VR improved mobility compared to controls (SMD &#x3d; 1.63, 95% CI: 0.14, 3.13, P &#x3d; 0.032, I<sup>2</sup> &#x3d; 93.7%) (<xref ref-type="fig" rid="F4">Figure 4</xref>). The certainty of evidence was very low (<xref ref-type="sec" rid="s12">Supplementary Table 3</xref>). Sensitivity analyses did not reduce the heterogeneity of result (&#x3e;90%) (<xref ref-type="sec" rid="s12">Supplementary Figure 1B</xref>). Subgroup analysis based on the intervention in the control group revealed a greater advantage of VR in the passive control (SMD &#x3d; 3.28, 95% CI: 2.35, 4.21, P &#x3c; 0.0001) compared to the active control (SMD &#x3d; 1.10, 95% CI: &#x2212;0.41, 2.61, P &#x3d; 0.151, I<sup>2</sup> &#x3d; 92.6%) (<xref ref-type="sec" rid="s12">Supplementary Figure 2B</xref>). The meta-regression result showed that the type of control group was not a contributing factor to heterogeneity (P &#x3d; 0.314).</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>Forest plot of the effect of virtual reality on mobility.</p>
</caption>
<graphic xlink:href="fphys-16-1612882-g004.tif">
<alt-text content-type="machine-generated">Forest plot displaying meta-analysis results for four studies from 2023 and 2024, each with different standard mean differences (SMD) and confidence intervals. The plot includes weights for each study and an overall summary with an I-squared value of 93.7 percent and p-value of 0.000, indicating high heterogeneity. The overall effect size is 1.63 with a 95 percent confidence interval of 0.14 to 3.13, calculated using random effects analysis.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-4-4">
<title>3.4.4 QOL</title>
<p>Two studies (n &#x3d; 63) assessed QOL in patients with osteoporosis. The result showed that VR did not improve QOL compared to controls (SMD &#x3d; 2.50, 95% CI: &#x2212;2.15, 7.16, P &#x3d; 0.292, I<sup>2</sup> &#x3d; 97.4%) (<xref ref-type="fig" rid="F5">Figure 5</xref>
<bold>)</bold>. The certainty of evidence was very low (<xref ref-type="sec" rid="s12">Supplementary Table 3</xref>).</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption>
<p>Forest plot of the effect of virtual reality on quality of life (QOL).</p>
</caption>
<graphic xlink:href="fphys-16-1612882-g005.tif">
<alt-text content-type="machine-generated">Forest plot depicting a meta-analysis of two studies: Riaz, 2024 and Gilani, 2023. The effect size (SMD) for Riaz is 4.90 with a confidence interval of 3.68 to 6.11 and a weight of 49.59%. Gilani shows an effect size of 0.15 with a confidence interval of -0.73 to 1.02 and a weight of 50.41%. The overall combined effect size is 2.50 with a confidence interval of -2.15 to 7.16. Heterogeneity is high with an I-squared of 97.4% and p-value of 0.000. Weights are calculated using a random effects model.</alt-text>
</graphic>
</fig>
</sec>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>4 Discussion</title>
<p>This study is the first meta-analysis to assess the effectiveness of a VR intervention on functional outcomes in patients with osteoporosis or osteopenia. The results showed that VR improved femoral neck BMD but had no significant effect on lumbar spine BMD. In terms of balance function and mobility, the VR intervention group was better than the control group, but the improvement in QOL did not reach statistical significance. Regarding the quality of the literature, four of the five included papers were of high quality. Sensitivity analyses further confirmed the robustness of the results for balance function, but heterogeneity in mobility remained high. GRADE scores for all evidence ranged from low to very low. This stems from risk of bias and imprecision, mainly because the evidence includes studies that are at risk of bias. In addition, the total sample size for each piece of evidence was low. Therefore, results need to be interpreted with caution.</p>
<p>The results of this study correlate with previous trends in the use of VR in rehabilitation medicine. VR highlights the importance of integrating games into rehabilitation programs as they allow observation of movement and control of activity levels. Games using Kinect technology have been shown to be highly effective in treating chronic diseases (<xref ref-type="bibr" rid="B39">Tarakci et al., 2016</xref>). The improvement of balance function and mobility in osteoporosis and osteopenia by VR echoes research in the field of neurorehabilitation, which may involve enhanced proprioceptive input and motor learning efficiency (<xref ref-type="bibr" rid="B4">Cano Porras et al., 2018</xref>; <xref ref-type="bibr" rid="B44">Zhang et al., 2021</xref>). BMD can be used as an indicator to define the severity of osteoporosis and the effectiveness of treatment (<xref ref-type="bibr" rid="B25">L&#xf6;ffler et al., 2020</xref>). A study has shown that VR biofeedback systems greatly enhance tissue regeneration, exercise efficacy and participation in training (<xref ref-type="bibr" rid="B41">Wang, 2024</xref>). Improvements in femoral neck BMD suggest that VR may stimulate local bone remodeling in the lower limb through mechanical loading. However, lumbar spine BMD did not significantly improve. This may be due to the fact that the VR rehabilitation programs focused on lower limb training and less on trunk training, which could be validated by adjusting the protocol in the future. On the other hand, nonsignificant lumbar BMD results may reflect inadequate statistical power rather than true biological invalidity. Small sample sizes are prone to Type II errors, resulting in false negatives (<xref ref-type="bibr" rid="B29">Mittendorf et al., 1995</xref>). In addition, negative QOL results may be influenced by multidimensional factors, such as psychological state and sociability, and existing studies have not targeted interventions in these areas (<xref ref-type="bibr" rid="B12">Gilani et al., 2023</xref>; <xref ref-type="bibr" rid="B45">Zhao et al., 2023</xref>).</p>
<p>Confounding factors can increase the heterogeneity of results, which may also be responsible for biased results. In the balanced results, subgroup analyses, meta-regression, and sensitivity analyses showed that VR showed better efficacy and decreased outcome heterogeneity in passive controls. The significant advantage of VR in passive controls may stem from the low intensity of the control measures, while the effectiveness of the active controls themselves may have diluted the effect of VR. Notably, the dominance of VR in the passive control group may reflect its potential as a stand-alone intervention, particularly in scenarios where structured rehabilitation resources are lacking. In addition, Mobility showed less effect of control group type on heterogeneity in all tests. The high heterogeneity in mobility and QOL may be related to differences in assessment tools and small sample sizes. Heterogeneity may also come from VR type. However, the types of VRs included in the study were all non-immersive VRs, and it was not possible to identify the effect of VR type on the results from the nature of the VRs. On the other hand, it is also possible that the heterogeneity originated from the systems of different non-immersive VRs, due to differences in the design of each system (<xref ref-type="bibr" rid="B39">Tarakci et al., 2016</xref>; <xref ref-type="bibr" rid="B21">Kumar et al., 2017</xref>). It is also possible that the heterogeneity was influenced by the duration of the intervention, which ranged from a minimum of 6 weeks to a maximum of 12 months for the included studies using VR. Subgroup analyses were not possible due to the small number of studies with the same factors. Future studies need to standardize outcome assessment methods and expand sample sizes to reduce confounding bias.</p>
<p>The mechanism of action of VR in osteoporosis management may involve multi-pathway synergies. Firstly, VR training optimizes neuromuscular coordination by inducing motor control and learning in an immersive virtual environment where patients combine visual, motor and haptic signals to perform high-quality exercises (<xref ref-type="bibr" rid="B26">Maden et al., 2025</xref>). Secondly, the real-time visual feedback provided by VR may improve proprioceptive integration, reduce the risk of falls and indirectly protect the bone microstructure (<xref ref-type="bibr" rid="B33">Raffegeau et al., 2023</xref>). In addition, unlike the repetitive nature of traditional training, VR training is full of motivation and fun, which can significantly improve patient compliance (<xref ref-type="bibr" rid="B35">Riaz et al., 2024a</xref>). VR can guide patients to make postural changes during training, thereby increasing localized loads on the body. However, the negative results of lumbar spine BMD suggest that the intensity of mechanical stimulation of the spine by VR may be insufficient and further optimization of the exercise programs design is required.</p>
<p>When considering incorporating VR interventions into routine clinical practice, it is important to weigh these costs against the potential benefits of VR interventions. Although the initial investment in VR technology is substantial, the long-term cost-effectiveness may be greater because reduced healthcare costs are associated with improved patient outcomes (e.g., fewer fractures and hospitalizations). In addition, as VR technology becomes more popular and market competition increases, the costs of VR interventions may decrease (<xref ref-type="bibr" rid="B11">Geraets et al., 2021</xref>). The feasibility of implementing VR interventions in a clinical setting is another key consideration. VR requires specialized equipment and trained personnel to operate and maintain the system. However, as technology advances, VR systems are becoming more user-friendly and accessible (<xref ref-type="bibr" rid="B8">Ciccone et al., 2023</xref>). Furthermore, it is also important to consider whether healthcare providers have access to technical support and training to ensure smooth implementation of VR interventions (<xref ref-type="bibr" rid="B14">Hood et al., 2021</xref>; <xref ref-type="bibr" rid="B17">Iqbal et al., 2024</xref>). Patient compliance is a key factor in the success of any intervention, and VR is no exception. The engaging and interactive nature of VR can enhance patient motivation and compliance. One study has shown that patients are more likely to complete VR exercises than traditional rehabilitation exercises due to the fun and immersive experience VR provides (<xref ref-type="bibr" rid="B4">Cano Porras et al., 2018</xref>). It is also critical to select appropriate VR content and adjust the length and intensity of VR sessions to minimize these side effects (<xref ref-type="bibr" rid="B27">Mao et al., 2021</xref>).</p>
<p>There are some limitations to this study. Firstly, the small number of included studies and limited sample size may reduce statistical validity. The small number of included studies also resulted in an inability to detect publication bias. Second, the high heterogeneity of the intervention protocols, such as differences in the type of VR equipment and training duration, limits the generalizability of the findings. Finally, there was a lack of long-term follow-up data to assess the persistence effect of the results. Future multicenter large-sample RCTs and in-depth investigation of the mechanisms of VR in osteoporosis and bone loss are needed. In addition, VR combined with artificial intelligence to adjust the intensity or in combination with anti-bone resorption drugs may be a new direction to optimize the efficacy. Despite the positive effects of VR on osteoporosis and bone loss, certain uncertainties remain and further research is needed. The results of the meta-analyses showed only effectiveness. However, the adverse effects and safety of VR remain unknown. More comprehensive studies of VR therapy are necessary in the future to more fully understand its effects. In addition, future research also needs to verify different VR types and different VR training parameters. In addition to verifying the effectiveness of VR, it is also possible to compare several commonly used treatment parameters in previous studies and establish standards for VR treatment of osteoporosis and osteopenia.</p>
</sec>
<sec sec-type="conclusion" id="s5">
<title>5 Conclusion</title>
<p>VR-based rehabilitation is a novel and promising treatment modality that is increasingly being implemented in clinical settings. This study is the first to assess the impact of VR intervention on functional outcomes in patients with osteoporosis or bone loss through systematic evaluation and meta-analysis. Given the overall low and very low level of evidence, the results need to be treated with caution. While these results suggest that VR has potential as an adjunctive therapy, its clinical application is still in the research phase. In addition, no study has conclusively demonstrated the clinical safety of virtual reality interventions for individuals with osteoporosis or osteopenia. The sustained effects, safety and potential side effects of VR still need to be further evaluated. Future RCTs need to focus on extending follow-up, exploring bone remodeling effects and stratifying the baseline population.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s6">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s12">Supplementary Material</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="author-contributions" id="s7">
<title>Author contributions</title>
<p>SH: Conceptualization, Writing &#x2013; review and editing, Formal Analysis, Data curation, Writing &#x2013; original draft. SD: Methodology, Supervision, Validation, Writing &#x2013; review and editing. XL: Formal Analysis, Data curation, Writing &#x2013; review and editing, Investigation. ZW: Writing &#x2013; review and editing, Methodology, Supervision. YD: Supervision, Writing &#x2013; review and editing. XG: Funding acquisition, Writing &#x2013; review and editing, Resources, Supervision, Project administration.</p>
</sec>
<sec sec-type="funding-information" id="s8">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This research is funded by the Humanities and Social Sciences Research Planning Project of Heilongjiang Province (23SHD138).</p>
</sec>
<sec sec-type="COI-statement" id="s9">
<title>Conflict of interest</title>
<p>The authors declare that the research 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="s10">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
</sec>
<sec sec-type="disclaimer" id="s11">
<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="s12">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fphys.2025.1612882/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fphys.2025.1612882/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Supplementaryfile1.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
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