Next Article in Journal
Acute Sulcal FLAIR Hyperintensity in Severe Tick-Borne Encephalitis: A Potential Prognostic Marker
Previous Article in Journal
Phenolic Compounds with Antimicrobial Properties in Mushrooms Frequently Encountered in Temperate Deciduous Forests
Previous Article in Special Issue
Enhancing Bone–Cartilage Interface Healing in Osteochondral Autograft Transplantation: Effects of BMAC Augmentation and Rehabilitation Protocols
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Life
Volume 15
Issue 11
10.3390/life15111654
life-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Systematic Review

Virtual Reality-Based Therapy Improves Balance, Quality of Life, and Mitigates Pain and Fear of Falling in Women with Bone Mineral Density Loss: A Meta-Analysis of Randomized Controlled Trials

by
Irene Cortés-Pérez
1,
Ángeles Díaz-Fernández
1,*,
María Catalina Osuna-Pérez
1,
Héctor García-López
2,
Raúl Romero-Del-Rey
2 and
Esteban Obrero-Gaitán
1,*
1
Department of Health Sciences, University of Jaén, Campus Las Lagunillas s/n, 23071 Jaén, Spain
2
Department of Nursing, Physiotherapy and Medicine, University of Almería, Ctra. Sacramento s/n, La Cañada, 04120 Almería, Spain
*
Authors to whom correspondence should be addressed.
Life 2025, 15(11), 1654; https://doi.org/10.3390/life15111654
Submission received: 30 September 2025 / Revised: 13 October 2025 / Accepted: 21 October 2025 / Published: 23 October 2025
(This article belongs to the Special Issue Recent Advances in Physiotherapy for Musculoskeletal)
Browse Figures
Versions Notes

Abstract

Background/Objectives: Performing therapeutic exercises using video games via virtual reality devices can be effective for preventing or mitigating bone mineral density (BMD) loss. The objective of this paper is to determine the effectiveness of virtual reality-based therapy (VRBT) in improving BMD, postural balance, fear of falling, pain intensity, and quality of life (QoL) in women with BMD loss. Methods: A systematic review with meta-analysis (SRMA), after searching in PubMed Medline, WOS, Scopus, CINAHL, and PEDro up to July 2025, was conducted following PRISMA guidelines. Randomized controlled trials (RCTs), including women with BMD loss, in which VRBT was compared to conventional approaches for the management of BMD loss, were included. Methodological quality and quality of evidence were assessed using the PEDro scale and the GRADE statement, respectively. Effect size was estimated through standardized mean difference (SMD) and 95% confidence interval (95% CI). Results: Seven RCTs, involving 299 women with BMD loss (mean age: 60.5 ± 7.7 years), were included in this SRMA. All VRBT employed non-immersive virtual reality (NIVR) devices.Significant effectiveness on BMD loss (SMD = 0.92; p = 0.002), functional (SMD = 1.7; p < 0.001) and dynamic balance or functional mobility (SMD = −1.7; p = 0.01), fear of falling (SMD = −0.5; p = 0.009), pain intensity (SMD = −2.7; p = 0.039) and QoL (SMD = 3.9; p = 0.002) was reported favors VRBT in women with BMD loss. Conclusions: This SRMA demonstrates that VRBT (especially NIVR) can be effective at improving BMD, postural balance, functional mobility, and QoL, while simultaneously reducing pain intensity and the fear of falling in these women.

1. Introduction

Bone fragility, encompassing pathologies such as osteopenia and osteoporosis, represents a growing global public health challenge, especially among the female population [1]. These conditions, characterized by a progressive decrease in bone mineral density (BMD) and a deterioration of skeletal tissue microarchitecture, predispose women to a higher risk of fractures, even from minor traumas [2]. BMD loss not only impacts the structural integrity of the skeleton but also triggers a series of consequences that reduces quality of life (QoL) [3]. BMD is related firstly to osteopenia and progressively to osteoporosis. On the one hand, osteopenia is defined by a BMD that is lower than normal but not low enough to be classified as osteoporosis [4]. Although often asymptomatic, osteopenia signals an early warning of unfavorable bone metabolism and an increased risk of progression to osteoporosis over time [5]. Osteoporosis, on the other hand, stands as a systemic skeletal disease characterized by pronounced BMD loss and increased bone porosity, compromising bone strength and multiplying susceptibility to fractures [6,7]. These fractures not only cause acute and chronic pain but also lead to high morbidity, long-term disability, decreased functional independence, and in some cases, increased mortality [8]. BMD loss results from an imbalance between bone resorption and formation. Under physiological conditions, these processes are regulated to maintain skeletal homeostasis. However, in osteopenia and osteoporosis, bone resorption outpaces formation, leading to a net decrease in bone mass and a deterioration of bone tissue quality [9]. Hormonal factors, such as decreased estrogen levels during menopause, play a crucial role in accelerating bone loss in women. Other risk factors include advanced age, family history, low body weight, calcium and vitamin D deficiency, smoking, and excessive alcohol consumption [10].
The BMD loss has become a global public trend due to the severity of physical, psychological, functional, and social disabilities and their impacts on these women. Women with BMD loss report reduced physical mobility and functional capability related to daily living activities (DLAs). BMD loss can severely impact a person’s ability to maintain balance, often resulting in a disabling condition. The associated muscle weakness (especially in leg and trunk muscles) [11,12] and alterations in proprioception and visual function related to aging increase the likelihood of trips and loss of balance [13,14], also contributing to an increased risk of falls [15]. The risk of falls is a primary concern in patients with LBMD [16]. The consequences of falls in these women can be devastating, resulting in fractures that require hospitalization, surgery, and long periods of rehabilitation [17]. Even falls without fracture can generate fear of falling in the future and reduce confidence in their own DLA-related balance [18,19]. Additionally, pain, especially after a fracture, can also debilitate and significantly affect the ability to perform DLAs [20]. Recent studies have demonstrated a positive association between osteoporosis and worse QoL, comparable to that of other severe chronic diseases [21,22]. The low self-esteem and functional status, anxiety, and/or depression due to this disabling vicious cycle negatively impact overall well-being [23], limiting participation in DLAs and reducing QoL [24]. For reducing the impact of these disabling consequences of BMD loss, it is crucial to find effective and safe interventions.
Traditionally, the most common interventions for the management of BMD are pharmacotherapy (mainly calcium and vitamin D supplementation) and physical exercise programs for increasing muscle strength and balance skills [25,26]. However, long-term adherence to these treatments can be a challenge, and the need for complementary, innovative, and safe approaches is evident [27,28]. According to this, virtual reality-based therapy (VRBT) emerged as a promising tool for this purpose. Virtual reality (VR) devices are characterized by sophisticated software and hardware that reproduce a virtual environment that users feel to be real [29]. VR devices can be categorized into three different modalities: Non-immersive virtual reality (NIVR), semi-immersive VR, and immersive VR [30]. NIVR is the modality most used in clinical practice related to musculoskeletal and balance disorders and can offer several potential advantages for addressing the challenges associated with osteopenia and osteoporosis [31,32]. NIVR utilizes computer screens, televisions, or projectors to display interactive virtual environments. Users interact with these environments through peripherals such as keyboards, mice, game controllers, or motion sensors [33].
In addition to the growing interest in VRBT as a therapeutic tool in musculoskeletal conditions [34], in the management of osteopenia and osteoporosis, it has also been shown to be effective [35]. Specifically, regarding these conditions, no previous reviews have exclusively assessed the effectiveness of VRBT on BMD loss. Thuilier, E et al. (2024) conducted a heterogeneous systematic review including older adults with musculoskeletal conditions in which virtual and augmented reality effects were assessed [36]. In 2025, He et al. conducted a meta-analysis including five studies where they suggested that VRBT could be effective in increasing BMD and balance, but not QoL [37]. These reviews present common limitations related to language filters in the literature search (excluding studies not in English or French). Additionally, the very low number of studies included in the meta-analyses of He et al. (2005) [37] does not allow us to generalize the findings, requiring a new and more concise systematic review, retrieving more studies. Therefore, the aim of this systematic review with meta-analysis (SRMA) was to assess the effectiveness of VRBT in improving BMD, balance, fear of falling, pain intensity, and QoL in women with BMD loss.

2. Materials and Methods

2.1. Study Design

Authors followed PRISMA 2020 guidelines [38] and the Cochrane Handbook for Systematic Reviews of Interventions recommendations [39]. The AMSTAR 2 checklist evaluated the methodological quality of this SRMA [40]. This SRMA has been previously registered in PROSPERO (CRD420251057144).

2.2. Data Sources

The literature search process was conducted exhaustively by two independent authors (I.C.-P. and E.O.-G.) from inception up to July 2025, without publication date or language limitations, in PubMed Medline, WOS, Scopus, CINAHL, and PEDro. Additionally, authors screened the reference lists of previous studies, including congress abstracts and proceedings. The PICOS framework was followed to define the search strategy [41]: population (women with LBMD), intervention (VRBT), comparison (conventional exercise therapy), outcomes (BMD, postural balance, fear of falling, pain, and QoL), and study design (randomized controlled trials [RCTs] or pilot RCTs). Sensitivity in search strategy was increased by combining only terms related to the population and intervention with the Boolean operators “AND” and “OR”. Keywords combined in the search, according to the PubMed thesaurus, were “osteoporosis”, “osteoporosis postmenopausal”, “virtual reality”, and “exergaming” (Table 1).

2.3. Study Selection: Inclusion and Exclusion Criteria

Two authors (A.D.-F. and M.C.O.-P.) independently conducted a screening of studies retrieved by title and abstract. Inter-rater agreement was estimated using the Cohen’s kappa coefficient (κ) [42], with κ values interpreted as follows: null (κ = 0), low (0 < κ ≤ 0.20), medium (0.41 ≤ κ ≤ 0.60), or excellent (0.81 ≤ κ ≤ 1) [43]. Disagreements were resolved by a third researcher (I.C.-P.) Authors included studies that met the PICOS items (named in the previous section). As additional inclusion criteria, authors reported that the RCTs included must provide statistical data (mean and standard deviation) of the variables of interest to conduct the meta-analysis. Authors excluded studies that included patients with and without BMD loss in the same sample.

2.4. Data Extraction

Two authors (A.D.-F. and M.C.O.-P.) independently compiled data from the studies selected in a data collection form with the participation of a third author (I.C.-P.) in resolving doubts according to this process. The data extracted can be categorized as (1) overall characteristics (authorship, date of publication, country, blinding status, setting, and financing); (2) characteristics of the participants (total sample size and sample size per group, age, sex, and diagnosis of BMD loss); (3) VRBT characteristics (software and modality of VRBT employed, as well as protocol of application in total number of sessions, weeks, and time of use of VR in each session); (4) comparison intervention (type of comparison and protocol of application); and (5) variables (name, method of evaluation, and statistics data needed for meta-analysis [mean and standard deviation]).

2.5. Variables

BMD is defined in clinical practice as the amount of mineral per square centimeter of bone. Postural balance is categorized as functional (ability to maintain balance during functional activities) and dynamic balance (skill to maintain standing and stability during movement or displacement); fear of falling; pain; and QoL.

2.6. Methodological Quality, Risk of Bias, and Quality of Evidence Assessment

On the one hand, the PEDro Scale, an 11-item scale designed to evaluate the methodological quality in RCTs [44], was used to assess the methodological quality of the studies included. Methodological quality was categorized as follows: excellent (10–9 points), good (8–6 points), moderate (5–4 points), and poor (≤3 points) [45]. Related to identifying potential biases in RCTS using the PEDro scale, selection, performance, and detection biases can be identified through items 2–3, 5–6, and 7, respectively.
On the other hand, the level of evidence for each outcome was determined through the GRADE assessment and Meader’s GRADE checklist [46,47], considering if the following items (risk of bias, inconsistency, imprecision, indirectness, and risk of publication bias) are met. The level of evidence, which could be categorized as high, moderate, low, or very low, was downgraded for each item not met.
These assessments were conducted by two authors (H.G.-L. and R.R.-R.), independently, supervised by a third author (E.O.-G.).

2.7. Statistical Analysis

The meta-analysis was conducted by two authors (I.C.-P. and E.O.-G.) using Comprehensive Meta-Analysis software version 4 (Biostat, Englewood, NJ, USA) [48]. The Cohen’s standardized mean difference (SMD) and 95% confidence intervals (95% CI) were used as the effect size measure in a random-effects model [49,50]. According to Kinney et al. (2020), the effect size was interpreted as null (SMD = 0), low (SMD = 0.08 − 0.15), medium (SMD = 0.19 − 0.36), and large (SMD > 0.4) [51]. The findings were displayed in the forest plots [52]. Publication bias was estimated through the funnel plot visualization, Egger’s test, and the trim-and-fill calculation [53,54,55]. If the difference between the original and adjusted pooled effect size exceeded 10%, the level of evidence was downgraded by one level when the difference between the effect size and adjusted effect size was greater than 10% [56]. The degree of inconsistency of Higgins (I2), the χ-square test, and its p-value were considered to calculate the inconsistency or heterogeneity [57,58], which can be large (I2 > 50%), moderate (I2 25–50%), low (I2 5–25%), or null (I2 ≤ 5%) [59]. Additionally, the contribution of the studies to the global effect size was estimated by applying the leave-one-out method.

3. Results

3.1. Study Selection

A total of 154 records were retrieved, 151 from databases (PubMed Medline n = 27; Scopus n = 67; WOS n = 46; CINAHL n = 3; and PEDro n = 5), and 3 references were from others. After removing 37 duplicates, 114 references were examined by title and abstract, of which 79 references were removed for not being relevant. In total, 28 studies did not meet the inclusion criteria (non-RCT or non-pilot RCT n = 5, non-VRBT n = 5, non-BMD loss patients n = 14, and non-outcomes of interest n = 4). Finally, this SRMA included seven RCTs [60,61,62,63,64,65,66]. The authors reported an excellent inter-rater agreement (κ = 0.94) in this stage. Figure 1 shows the PRISMA flow diagram for study selection.

3.2. Characteristics of the Studies Included

The included RCTs, conducted between 2016 and 2024 in Iran, Italy, Saudi Arabia, Pakistan, Turkey, and China, enrolled 299 women with BMD loss (mean age: 60.5 ± 7.7 years). The intervention group included 143 women who received VRBT. All VRBT interventions conducted by the RCTs included were NIVR, ranging from 6 to 48 weeks, including sessions from 16 to 144 sessions, lasting between 45 and 60 min per session. VRBT interventions included strength, balance, and aerobic exercises using NIVR headsets such as the Nintendo Wii, Xbox Kinect, Pro-Kin system, and VR rehabilitation system. The comparison group included 156 women who received conventional training, such as strength exercises, balance, aerobics, and walking outdoors. All RCTs only provided post-intervention data. Four RCTs reported receiving grants to carry out the study [60,63,64,65]. Table 2 summarizes the characteristics of these studies.

3.3. Methodological Quality and Risk of Bias

The included RCTs exhibited good methodological quality (6.6 ± 0.5 points in PEDro). The score of four RCTs had been previously confirmed on the PEDro database [60,63,64,66]. All RCTs ranged from 6 to 7 points. Selection bias was present in two RCTs due to inadequate concealed allocation (item 3 was not met) [63,64]. All RCTs reported risk of performance bias, due to the inadequate blinding of participants and therapists (items 5 and 6 were not met). Finally, detection bias, due to evaluators not being blinded (item 7 not met), was present in two RCTs [63,64]. Table 3 shows the PEDro assessment of each RCT included in this SRMA.

3.4. Meta-Analysis

3.4.1. Bone Mineral Density

The effectiveness of VRBT in increasing the BMD was assessed through three RCTS with four independent comparisons [64,65,66]. These studies provided data from 153 women (38.3 per study) using dual-energy X-ray absorptiometry. The meta-analysis exhibited that VRBT is largely effective (SMD = 0.92; 95% CI 0.35 to 1.5; p = 0.002; I2 = 4.9%; χ2 = 3.1; df = 3; p = 0.38) in increasing the BMD in these women (Figure 2). Risk of publication was not reported (Egger p = 0.78).

3.4.2. Functional Balance

Three RCTs with three independent comparisons [61,63,64] provided data from 148 women (49.3 per study) to assess the effectiveness of VRBT on functional balance through the Berg Balance Scale (BBS). The meta-analysis showed a large effect (SMD = 1.7; 95% CI 1.03 to 2.36; p < 0.001; I2 = 1%; χ2 = 2.1; df = 2; p = 0.36), favoring VRBT in increasing functional balance (Figure 3) without risk of publication bias (Egger p = 0.47).

3.4.3. Dynamic Balance/Functional Mobility

Three RCTs with three independent comparisons [62,63,64] that provided data from 153 participants (51 per study) using the Timed Up and Go Test (TUG) were included to assess the effect of VRBT on dynamic balance or functional mobility. The TUG test is a measurement used to assess both dynamic balance and functional mobility [67]. Our findings showed that VRBT is largely effective (SMD = −1.7; 95% CI −2.9 to −0.4; p = 0.01; I2 = 0%; χ2 = 1.8; df = 2; p = 0.41) in increasing dynamic balance and functional mobility (Figure 4) without risk of publication bias (Egger p = 0.19).

3.4.4. Fear of Falling

The effectiveness of VRBT in reducing the fear of falling was assessed through three RCTs with three independent comparisons [60,61,63]. These studies provided data from 118 women (39.3 per study) using the Falls Efficacy Scale (FES). The meta-analysis determined that VRBT is largely effective (SMD = −0.5; 95% CI −0.9 to −0.13; p = 0.009; I2 = 29%; χ2 = 2.7; df = 2; p = 0.3) in reducing the fear of falling in these patients (Figure 5). No risk of publication was found (Egger p = 0.21).

3.4.5. Pain

Three RCTs with four independent comparisons [60,61,65] provided data from 118 women (29.5 per study) to assess the effectiveness of VRBT in alleviating pain intensity through the Visual Analog Scale (VAS), Qualeffo-41, and the Quality of Life questionnaire for pain. The meta-analysis showed a large effect (SMD = −2.7; 95% CI −5.2 to −0.13; p = 0.039 I2 = 27.1%; χ2 = 4.2; df = 3; p = 0.24), favoring VRBT in reducing pain (Figure 6). These findings were influenced by the risk of publication bias (Egger p = 0.03), confirmed using the trim-and-fill estimation that showed that the risk of publication bias could be overestimating 60% of the original pooled effect of NIVR (adjusted SMD = −1.6).

3.4.6. Quality of Life

Four RCTs with five independent comparisons [60,61,62,65] provided data from 103 women (20.6 per study) to assess the effectiveness of VRBT in improving QoL through the Qualeffo-41, SF-36, and Quality of Life questionnaire. The meta-analysis showed a large effect (SMD = 3.9; 95% CI 1.4 to 6.3; p = 0.002; I2 = 44.7%; χ2 = 8.8; df = 4; p = 0.06), favoring NIVR in increasing QOL (Figure 7). No risk of publication was found (Egger p = 0.11).

4. Discussion

To our knowledge, this is the first SRMA to retrieve the largest number of RCTs available to date, specifically focused on VRBT through NIVR devices, in women with BMD loss, which adds originality and clinical relevance to the previous findings [36,37]. Due to the lack of previous reviews that assessed the effect of VRBT for the management of BMD loss in women, the objective of our SRMA was to assess it, including the largest number of RCTs available to date. Therefore, this SRMA retrieved seven RCTs [60,61,62,63,64,65,66] that provided data from 299 women with BMD loss that compared VRBT with traditional approaches for the management of clinical and functional outcomes in women with BMD loss. All RCTs conducted VRBT with NIVR. The studies reviewed varied in duration (6 to 48 weeks), frequency (2 to 5 sessions per week), and devices used (Nintendo™ Wii, Xbox™ Kinect, Pro-Kin, or custom VR platforms), but all implemented interventions were based on movement simulation, visual feedback, and task-oriented exercises. The findings support the potential of NIVR to increase BMD, postural balance, functional mobility, and QoL, as well as reduce the fear of falling and pain in these women, with varying degrees of evidence across domains. One strength of this SRMA is that it is the first to elucidate the use of VRBT in the management of BMD loss.
At first, our findings showed a significant effect of VRBT for increasing BMD in these women. This finding aligns with the meta-analysis by He et al., although their research only identified effectiveness for VRBT in increasing femoral neck BMD [37]. It points to the potential of NIVR devices to promote osteogenesis indirectly through improved compliance, increased movement variability, and longer total training exposure [36]. The RCTs included in this meta-analysis carried out physical, mobility, and walking exercises using NIVR devices [64,65,66], with physical exercise being one of the most important strategies to prevent the age-associated BMD loss [68]. The combination of physical exercises in virtual, gamified, and ludic environments can be responsible for this improvement in BMD.
Due to postural balance as a general concept, this SRMA assessed the effectiveness of VRBT in different balance domains (functional and dynamic). Our findings reported that VRBT is largely effective for increasing functional and dynamic balance as well as functional mobility in women with BMD loss. However, the low number of studies included in the meta-analysis of each outcome can reduce the generalization and precision of the findings. All VRBT included combined balance-specific exercises performed in dynamic contexts, suggesting that postural control can benefit from consistent exposure to VR-based multisensory stimulus (visual, auditory, and proprioceptive) necessary to maintain balance [69], promoting improved spatial orientation and dynamic stability [32,70,71]. While the magnitude of improvement varied, the convergence of outcomes suggests that NIVR enhances anticipatory postural adjustments and motor planning through repeated exposure to functional movement simulations [72,73]. Additionally, some video games used in NIVR devices, such as Nintendo™ Wii or Kinect™, reproduce real-world functional and ambulatory tasks, such as arm movement-oriented tasks or walking, whose repetitive practice can be responsible for the improvement in functional balance.
Consequently, regarding the improvement of balance and functional mobility, our SRMA also reported that the use of NIVR, as VRBT in these women, could largely reduce fear of falling. The confidence gains observed in the studies included in this SRMA may reflect not only physical improvements, but also cognitive reframing associated with repetitive success in virtual tasks. In particular, the studies by Morone et al. and Yilmaz et al., both using Wii-based training, involved tasks resembling real-life activities such as stepping, shifting weight, or reaching—scenarios that participants often perceive as threatening in daily life. The ability to practice these actions in a safe and controlled VR environment likely contributed to the psychological dimension of fall prevention [74,75].
Finally, we assessed the effectiveness of VRBT on pain and QoL. Our findings reported that VRBT was largely effective in reducing pain intensity and increasing QoL. On the one hand, related to pain, no previous SRMA has assessed this variable, highlighting the novelty of these findings. Additionally, the NIVR devices used combined balance and strength exercises with virtual feedback, which could have facilitated attentional diversion, movement confidence, and reduced guarding. Although the exact mechanisms remain speculative, it is plausible that repeated exposure to functional movement in a VR setting may contribute to neuroplastic adaptations in pain-processing circuits [76], a hypothesis that deserves further exploration in future studies. Nonetheless, these findings should be interpreted with caution, as the publication bias analysis indicated a potential overestimation of the pooled analgesic effect by approximately 60%, raising concerns about the robustness of this outcome. On the other hand, in relation to QoL, these findings disagree with the meta-analysis of He et al., who did not find statistically significant differences favoring VRBT in improving QoL [37]. Participants in NIVR groups experienced broad improvements in physical, emotional, and social well-being. Notably, the strongest effects were observed in studies that combined VR with walking or longer-duration interventions, such as in Riaz et al., where participants trained for 24 weeks. These results suggest that NIVR may influence biopsychosocial outcomes through multiple mechanisms—by increasing autonomy, decreasing isolation, and enhancing motivation to engage in physical activity [77].
Clinical implications include the dual capacity of NIVR to address both physical impairments (e.g., balance and strength) and psychosocial barriers (fear of falling and low motivation) by simulating real-life tasks within a controlled, engaging environment. This gamified approach not only delivers clinically meaningful improvements in mobility but also enhances treatment adherence and emotional well-being. Given the accessibility and affordability of many NIVR systems, including those based on commercial gaming platforms, these interventions are particularly well suited for integration into community health programs, outpatient clinics, and even home-based rehabilitation formats [78].
Although our findings are clinically relevant for improving BMD loss, several limitations should be considered. First, the analyses included a low number of RCTs with small sample sizes. This could negatively impact the quality of evidence and the generalizability of these novel findings. However, the search strategy employed allowed for the retrieval of all RCTs published to date, without language or publication date restrictions. Second, the presence of selection, performance, and detection biases in the included RCTs might affect the generalization of the findings and overestimate or underestimate the true effect of VRBT [79,80]. Third, the presence of risk of publication bias in meta-analysis concerning pain suggested that it overestimated the original effect, although it was corrected by applying the trim-and-fill calculation. While it is generally recommended to include at least 10 studies for a reliable assessment of publication bias, the limited number of RCTs conducted to date restricts the availability of such a quantity of studies in any meta-analysis. Furthermore, the heterogeneity among included RCTs regarding the characteristics of the VRBT may complicate inter-study comparisons, a common limitation in RCTs conducted in physiotherapy. Future studies should prioritize the adoption of stricter, standardized methodological designs. By expanding sample sizes and unifying intervention protocols and outcome measures, the field can ensure greater evidentiary reliability and thus better support evidence-based clinical practice.

5. Conclusions

This SRMA evaluates the effectiveness of VRBT (specifically NIVR) on women with BMD loss and is notable for including the largest number of RCTs published to date. Our findings elucidate that the integration of VRBT in rehabilitation programs for women with BMD loss increases BMD, balance, functional mobility, and QoL; it also reduces fear of falling and pain intensity compared to conventional therapies. These findings are of great clinical relevance to practitioners (including physiotherapists and nurses) because they highlight that the practice of different physical exercises in virtual, gamified, and ludic environments is appropriate for the management of BMD loss in these women. However, continued research is needed to clarify long-term effects and to optimize the parameters of these interventions for routine clinical use.

Author Contributions

Conceptualization, I.C.-P., Á.D.-F., M.C.O.-P., H.G.-L., R.R.-D.-R., and E.O.-G.; methodology, I.C.-P., Á.D.-F., M.C.O.-P., H.G.-L., R.R.-D.-R., and E.O.-G.; software, I.C.-P. and E.O.-G.; validation, I.C.-P., Á.D.-F., M.C.O.-P., H.G.-L., R.R.-D.-R., and E.O.-G.; formal analysis, I.C.-P., Á.D.-F., M.C.O.-P., H.G.-L., R.R.-D.-R., and E.O.-G.; investigation, I.C.-P., Á.D.-F., M.C.O.-P., H.G.-L., R.R.-D.-R., and E.O.-G.; data curation, I.C.-P., Á.D.-F., M.C.O.-P., and E.O.-G.; writing—original draft preparation, I.C.-P., Á.D.-F., M.C.O.-P., and R.R.-D.-R.; writing—review and editing, I.C.-P., R.R.-D.-R., and H.G.-L.; visualization, I.C.-P., Á.D.-F., M.C.O.-P., H.G.-L., R.R.-D.-R., and E.O.-G.; supervision, I.C.-P., Á.D.-F., and E.O.-G.; project administration, I.C.-P. and E.O.-G. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to (specify the reason for the restriction).

Acknowledgments

The authors have reviewed and edited the output and take full responsibility for the content of this publication.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
BMDBone mineral density
VRBTVirtual reality-based therapy
NIVRNon-immersive virtual reality
DLAsDaily living activities
SRMASystematic review with meta-analysis
QoLQuality of life
SMDStandardized mean differences
95% CI95% confidence interval
RCTsRandomized controlled trials

References

  1. Hernlund, E.; Svedbom, A.; Ivergård, M.; Compston, J.; Cooper, C.; Stenmark, J.; McCloskey, E.V.; Jönsson, B.; Kanis, J.A. Osteoporosis in the European Union: Medical Management, Epidemiology and Economic Burden. Arch. Osteoporos. 2013, 8, 136. [Google Scholar] [CrossRef]
  2. Nicholson, W.K.; Silverstein, M.; Wong, J.B.; Chelmow, D.; Coker, T.R.; Davis, E.M.; Jaén, C.R.; Krousel-Wood, M.; Lee, S.; Li, L.; et al. Screening for Osteoporosis to Prevent Fractures. JAMA 2025, 333, 498. [Google Scholar] [CrossRef] [PubMed]
  3. Compston, J.E.; McClung, M.R.; Leslie, W.D. Osteoporosis. Lancet 2019, 393, 364–376. [Google Scholar] [CrossRef] [PubMed]
  4. Reid, I.R.; McClung, M.R. Osteopenia: A Key Target for Fracture Prevention. Lancet Diabetes Endocrinol. 2024, 12, 856–864. [Google Scholar] [CrossRef]
  5. Kienberger, Y.; Sassmann, R.; Rieder, F.; Johansson, T.; Kässmann, H.; Pirich, C.; Wicker, A.; Niebauer, J. Effects of Whole Body Vibration in Postmenopausal Osteopenic Women on Bone Mineral Density, Muscle Strength, Postural Control and Quality of Life: The T-Bone Randomized Trial. Eur. J. Appl. Physiol. 2022, 122, 2331–2342. [Google Scholar] [CrossRef]
  6. Lorentzon, M.; Johansson, H.; Harvey, N.C.; Liu, E.; Vandenput, L.; McCloskey, E.V.; Kanis, J.A. Osteoporosis and Fractures in Women: The Burden of Disease. Climacteric 2022, 25, 4–10. [Google Scholar] [CrossRef] [PubMed]
  7. Uusi-Rasi, K.; Karinkanta, S.; Tokola, K.; Kannus, P.; Sievänen, H. Bone Mass and Strength and Fall-Related Fractures in Older Age. J. Osteoporos. 2019, 2019, 5134690. [Google Scholar] [CrossRef]
  8. Johnell, O.; Kanis, J.A. An Estimate of the Worldwide Prevalence and Disability Associated with Osteoporotic Fractures. Osteoporos. Int. 2006, 17, 1726–1733. [Google Scholar] [CrossRef]
  9. Rachner, T.D.; Khosla, S.; Hofbauer, L.C. Osteoporosis: Now and the Future. Lancet 2011, 377, 1276–1287. [Google Scholar] [CrossRef]
  10. Eastell, R.; Rosen, C.J.; Black, D.M.; Cheung, A.M.; Murad, M.H.; Shoback, D. Pharmacological Management of Osteoporosis in Postmenopausal Women: An Endocrine Society Clinical Practice Guideline. J. Clin. Endocrinol. Metab. 2019, 104, 1595–1622. [Google Scholar] [CrossRef]
  11. Moreland, J.D.; Richardson, J.A.; Goldsmith, C.H.; Clase, C.M. Muscle Weakness and Falls in Older Adults: A Systematic Review and Meta-Analysis. J. Am. Geriatr. Soc. 2004, 52, 1121–1129. [Google Scholar] [CrossRef]
  12. Larsson, L.; Degens, H.; Li, M.; Salviati, L.; Lee, Y.I.; Thompson, W.; Kirkland, J.L.; Sandri, M. Sarcopenia: Aging-Related Loss of Muscle Mass and Function. Physiol. Rev. 2019, 99, 427–511. [Google Scholar] [CrossRef] [PubMed]
  13. Yeung, S.S.Y.; Reijnierse, E.M.; Pham, V.K.; Trappenburg, M.C.; Lim, W.K.; Meskers, C.G.M.; Maier, A.B. Sarcopenia and Its Association with Falls and Fractures in Older Adults: A Systematic Review and Meta-analysis. J. Cachexia Sarcopenia Muscle 2019, 10, 485–500. [Google Scholar] [CrossRef]
  14. Mahoney, J.R.; Cotton, K.; Verghese, J. Multisensory Integration Predicts Balance and Falls in Older Adults. J. Gerontol. Ser. A 2019, 74, 1429–1435. [Google Scholar] [CrossRef]
  15. Singh, R.R.; Maurya, P. Visual Impairment and Falls among Older Adults and Elderly: Evidence from Longitudinal Study of Ageing in India. BMC Public Health 2022, 22, 2324. [Google Scholar] [CrossRef] [PubMed]
  16. McVeigh, L.G.; Perugini, A.J.; Fehrenbacher, J.C.; White, F.A.; Kacena, M.A. Assessment, Quantification, and Management of Fracture Pain: From Animals to the Clinic. Curr. Osteoporos. Rep. 2020, 18, 460–470. [Google Scholar] [CrossRef] [PubMed]
  17. Liu, L.-K.; Lee, W.-J.; Chen, L.-Y.; Hwang, A.-C.; Lin, M.-H.; Peng, L.-N.; Chen, L.-K. Association between Frailty, Osteoporosis, Falls and Hip Fractures among Community-Dwelling People Aged 50 Years and Older in Taiwan: Results from I-Lan Longitudinal Aging Study. PLoS ONE 2015, 10, e0136968. [Google Scholar] [CrossRef]
  18. Martínez-Arnau, F.M.; Prieto-Contreras, L.; Pérez-Ros, P. Factors Associated with Fear of Falling among Frail Older Adults. Geriatr. Nurs. 2021, 42, 1035–1041. [Google Scholar] [CrossRef]
  19. Golubić, A.; Šarabon, N.; Marković, G. Association between Trunk Muscle Strength and Static Balance in Older Women. J. Women Aging 2021, 33, 288–297. [Google Scholar] [CrossRef]
  20. Genev, I.K.; Tobin, M.K.; Zaidi, S.P.; Khan, S.R.; Amirouche, F.M.L.; Mehta, A.I. Spinal Compression Fracture Management. Glob. Spine J. 2017, 7, 71–82. [Google Scholar] [CrossRef]
  21. Zarinfar, Y.; Panahi, N.; Hosseinpour, M.; Sedokani, A.; Hajivalizadeh, S.; Nabipour, I.; Larijani, B.; Fahimfar, N.; Ostovar, A. The Association between Osteoporosis and Quality of Life among Older Adults in Southern Iran: Findings from the Bushehr Elderly Health Program. BMC Geriatr. 2024, 24, 766. [Google Scholar] [CrossRef]
  22. Rajabi, M.; Ostovar, A.; Sari, A.A.; Sajjadi-Jazi, S.M.; Mousavi, A.; Larijani, B.; Fahimfar, N.; Daroudi, R. Health-Related Quality of Life in Osteoporosis Patients with and without Fractures in Tehran, Iran. J. Bone Metab. 2023, 30, 37–46. [Google Scholar] [CrossRef]
  23. van der Leeuw, G.; Ayers, E.; Leveille, S.G.; Blankenstein, A.H.; van der Horst, H.E.; Verghese, J. The Effect of Pain on Major Cognitive Impairment in Older Adults. J. Pain 2018, 19, 1435–1444. [Google Scholar] [CrossRef]
  24. Gao, S.; Zhao, Y. Quality of Life in Postmenopausal Women with Osteoporosis: A Systematic Review and Meta-Analysis. Qual. Life Res. 2023, 32, 1551–1565. [Google Scholar] [CrossRef] [PubMed]
  25. Liu, C.; Kuang, X.; Li, K.; Guo, X.; Deng, Q.; Li, D. Effects of Combined Calcium and Vitamin D Supplementation on Osteoporosis in Postmenopausal Women: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Food Funct. 2020, 11, 10817–10827. [Google Scholar] [CrossRef]
  26. Anupama, D.S.; Norohna, J.A.; Acharya, K.KV.; Ravishankar; George, A. Effect of Exercise on Bone Mineral Density and Quality of Life among Postmenopausal Women with Osteoporosis without Fracture: A Systematic Review. Int. J. Orthop. Trauma Nurs. 2020, 39, 100796. [Google Scholar] [CrossRef]
  27. Rodrigues, I.B.; Armstrong, J.J.; Adachi, J.D.; MacDermid, J.C. Facilitators and Barriers to Exercise Adherence in Patients with Osteopenia and Osteoporosis: A Systematic Review. Osteoporos. Int. 2017, 28, 735–745. [Google Scholar] [CrossRef]
  28. Mangano, G.R.A.; Avola, M.; Blatti, C.; Caldaci, A.; Sapienza, M.; Chiaramonte, R.; Vecchio, M.; Pavone, V.; Testa, G. Non-Adherence to Anti-Osteoporosis Medication: Factors Influencing and Strategies to Overcome It. A Narratice Review. J. Clin. Med. 2022, 12, 14. [Google Scholar] [CrossRef] [PubMed]
  29. Weiss, P.L.; Keshner, E.A.; Levin, M.F. Virtual Reality for Physical and Motor Rehabilitation. In Virtual Reality Technologies for Health and Clinical Applications; Springer: New York, NY, USA, 2014. [Google Scholar]
  30. Nieto-Escamez, F.; Cortés-Pérez, I.; Obrero-Gaitán, E.; Fusco, A. Virtual Reality Applications in Neurorehabilitation: Current Panorama and Challenges. Brain Sci. 2023, 13, 819. [Google Scholar] [CrossRef] [PubMed]
  31. Mirelman, A.; Rochester, L.; Maidan, I.; Del Din, S.; Alcock, L.; Nieuwhof, F.; Rikkert, M.O.; Bloem, B.R.; Pelosin, E.; Avanzino, L.; et al. Addition of a Non-Immersive Virtual Reality Component to Treadmill Training to Reduce Fall Risk in Older Adults (V-TIME): A Randomised Controlled Trial. Lancet 2016, 388, 1170–1182. [Google Scholar] [CrossRef]
  32. Park, J.-H.; Jeon, H.-S.; Kim, J.-H.; Kim, Y.J.; Moon, G.A. Effectiveness of Non-Immersive Virtual Reality Exercises for Balance and Gait Improvement in Older Adults: A Meta-Analysis. Technol. Health Care 2024, 32, 1223–1238. [Google Scholar] [CrossRef] [PubMed]
  33. Montoro-Cárdenas, D.; Cortés-Pérez, I.; Ibancos-Losada, M.d.R.; Zagalaz-Anula, N.; Obrero-Gaitán, E.; Osuna-Pérez, M.C. Nintendo® Wii Therapy Improves Upper Extremity Motor Function in Children with Cerebral Palsy: A Systematic Review with Meta-Analysis. Int. J. Environ. Res. Public Health 2022, 19, 12343. [Google Scholar] [CrossRef] [PubMed]
  34. Opara Zupančič, M.; Šarabon, N. The Current State of Virtual Reality in the Management of Musculoskeletal Conditions and Associated Chronic Pain: Terminology, Technology, and Associations. Appl. Sci. 2025, 15, 2564. [Google Scholar] [CrossRef]
  35. Chitjamnogchai, C.; Yuenyongchaiwat, K.; Sermsinsaithong, N.; Tavonudomgit, W.; Mahawong, L.; Buranapuntalug, S.; Thanawattano, C. Home-Based Virtual Reality Exercise and Resistance Training for Enhanced Cardiorespiratory Fitness in Community-Dwelling Older People with Sarcopenia: A Randomized, Double-Blind Controlled Trial. Life 2025, 15, 986. [Google Scholar] [CrossRef]
  36. Thuilier, E.; Carey, J.; Dempsey, M.; Dingliana, J.; Whelan, B.; Brennan, A. Virtual Rehabilitation for Patients with Osteoporosis or Other Musculoskeletal Disorders: A Systematic Review. Virtual Real 2024, 28, 93. [Google Scholar] [CrossRef]
  37. He, S.; Dong, S.; Lin, X.; Wang, Z.; Diao, Y.; Gao, X. The Effectiveness of Virtual Reality in People with Osteoporosis or Osteopenia: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Front. Physiol. 2025, 16, 1612882. [Google Scholar] [CrossRef]
  38. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef]
  39. Higgins, J.; Thomas, J. Cochrane Handbook for Systematic Reviews of Interventions, 2nd ed.; Wiley Blackwell & Sons: Hoboken, NJ, USA, 2020. [Google Scholar]
  40. Shea, B.J.; Reeves, B.C.; Wells, G.; Thuku, M.; Hamel, C.; Moran, J.; Moher, D.; Tugwell, P.; Welch, V.; Kristjansson, E.; et al. AMSTAR 2: A Critical Appraisal Tool for Systematic Reviews That Include Randomised or Non-Randomised Studies of Healthcare Interventions, or Both. BMJ 2017, 358, j4008. [Google Scholar] [CrossRef] [PubMed]
  41. Amir-Behghadami, M.; Janati, A. Population, Intervention, Comparison, Outcomes and Study (PICOS) Design as a Framework to Formulate Eligibility Criteria in Systematic Reviews. Emerg. Med. J. 2020, 37, 387. [Google Scholar] [CrossRef]
  42. Cohen, J. A Coefficient of Agreement for Nominal Scales. Educ. Psychol. Meas. 1960, 20, 37–46. [Google Scholar] [CrossRef]
  43. Landis, J.R.; Koch, G.G. The Measurement of Observer Agreement for Categorical Data. Biometrics 1977, 33, 159. [Google Scholar] [CrossRef]
  44. Maher, C.G.; Sherrington, C.; Herbert, R.D.; Moseley, A.M.; Elkins, M. Reliability of the PEDro Scale for Rating Quality of Randomized Controlled Trials. Phys. Ther. 2003, 83, 713–721. [Google Scholar] [CrossRef] [PubMed]
  45. Gonzalez, G.Z.; Moseley, A.M.; Maher, C.G.; Nascimento, D.P.; Costa, L.d.C.M.; Costa, L.O. Methodologic Quality and Statistical Reporting of Physical Therapy Randomized Controlled Trials Relevant to Musculoskeletal Conditions. Arch. Phys. Med. Rehabil. 2018, 99, 129–136. [Google Scholar] [CrossRef]
  46. Atkins, D.; Best, D.; Briss, P.A.; Eccles, M.; Falck-Ytter, Y.; Flottorp, S.; Guyatt, G.H.; Harbour, R.T. Grading Quality of Evidence and Strength of Recommendations. BMJ 2004, 328, 1490. [Google Scholar] [CrossRef]
  47. Meader, N.; King, K.; Llewellyn, A.; Norman, G.; Brown, J.; Rodgers, M.; Moe-Byrne, T.; Higgins, J.P.; Sowden, A.; Stewart, G. A Checklist Designed to Aid Consistency and Reproducibility of GRADE Assessments: Development and Pilot Validation. Syst. Rev. 2014, 3, 82. [Google Scholar] [CrossRef]
  48. Borenstein, M.; Hedges, L.; Higgins, J.; Rothstein, H. Comprehensive Meta-Analysis Software, Version 4; Biostat: Englewood, NJ, USA, 2023. [Google Scholar]
  49. Cohen, J. Statistical Power Analysis for the Behavioral Sciences; Academic Press: New York, NY, USA, 1977. [Google Scholar]
  50. DerSimonian, R.; Laird, N. Meta-Analysis in Clinical Trials. Control. Clin. Trials 1986, 7, 177–188. [Google Scholar] [CrossRef]
  51. Kinney, A.R.; Eakman, A.M.; Graham, J.E. Novel Effect Size Interpretation Guidelines and an Evaluation of Statistical Power in Rehabilitation Research. Arch. Phys. Med. Rehabil. 2020, 101, 2219–2226. [Google Scholar] [CrossRef] [PubMed]
  52. Rücker, G.; Schwarzer, G. Beyond the Forest Plot: The Drapery Plot. Res. Synth. Methods 2021, 12, 13–19. [Google Scholar] [CrossRef] [PubMed]
  53. Egger, M.; Smith, G.D.; Schneider, M.; Minder, C. Bias in Meta-Analysis Detected by a Simple, Graphical Test. Br. Med. J. 1997, 315, 629–634. [Google Scholar] [CrossRef]
  54. Sterne, J.A.C.; Egger, M. Funnel Plots for Detecting Bias in Meta-Analysis: Guidelines on Choice of Axis. J. Clin. Epidemiol. 2001, 54, 1046–1055. [Google Scholar] [CrossRef]
  55. Duval, S.; Tweedie, R. Trim and Fill: A Simple Funnel-Plot-Based Method of Testing and Adjusting for Publication Bias in Meta-Analysis. Biometrics 2000, 56, 455–463. [Google Scholar] [CrossRef] [PubMed]
  56. Rothman, K.; Greenland, S.; Lash, T. Modern Epidemiology; Lippincott Williams & Wilkins: Philadelphia, PA, USA, 2008. [Google Scholar]
  57. Higgins, J.P.T.; Thompson, S.G. Quantifying Heterogeneity in a Meta-analysis. Stat. Med. 2002, 21, 1539–1558. [Google Scholar] [CrossRef] [PubMed]
  58. Higgins, J.; Thompson, S.; Altman, D. Statistical Heterogeneity in Systematic Reviews of Clinical Trials: A Critical Appraisal of Guidelines and Practice. J. Health Serv. Res. Policy 2002, 7, 51–61. [Google Scholar] [CrossRef]
  59. Higgins, J.; Thompson, S.; Deeks, J.; Altman, D. Measuring Inconsistency in Meta-Analyses. BMJ 2003, 327, 557–560. [Google Scholar] [CrossRef] [PubMed]
  60. Gilani, M.; Torkaman, G.; Bahrami, F.; Bayat, N. Virtual Reality Exergaming Capability to Change Muscle Strategy During the Limits of Stability Test and Reduce Fear of Falling in Primary Osteoporotic Women. Games Health J. 2023, 12, 310–322. [Google Scholar] [CrossRef]
  61. Morone, G.; Paolucci, T.; Luziatelli, S.; Iosa, M.; Piermattei, C.; Zangrando, F.; Paolucci, S.; Vulpiani, M.C.; Saraceni, V.M.; Baldari, C.; et al. Wii Fit Is Effective in Women with Bone Loss Condition Associated with Balance Disorders: A Randomized Controlled Trial. Aging Clin. Exp. Res. 2016, 28, 1187–1193. [Google Scholar] [CrossRef]
  62. Riaz, S.; Shakil Ur Rehman, S.; Hassan, D.; Hafeez, S. Gamified Exercise with Kinect: Can Kinect-Based Virtual Reality Training Improve Physical Performance and Quality of Life in Postmenopausal Women with Osteopenia? A Randomized Controlled Trial. Sensors 2024, 24, 3577. [Google Scholar] [CrossRef]
  63. Yilmaz, N.; Kösehasanoğulları, M. The Effectiveness of Virtual Reality Exercise Games on Balance Functions and Fear of Falling in Women with Osteoporosis. Rheumatol. Int. 2024, 44, 1071–1076. [Google Scholar] [CrossRef]
  64. Zhao, R.; Zhao, X.; Guan, J.; Zhang, C.; Zhu, K. The Effect of Virtual Reality Technology on Anti-Fall Ability and Bone Mineral Density of the Elderly with Osteoporosis in an Elderly Care Institution. Eur. J. Med. Res. 2023, 28, 204. [Google Scholar] [CrossRef]
  65. Nambi, G.; Kamal-Abdelbasset, W.; Alsaid-Moawd, S.; Reda-Sakr, H.; Emam-Elnegamy, T.; Saji-George, J. Effect of Virtual Reality Training on Post-Menopausal Osteoporotic Women. Arch. Pharm. Pract. 2020, 11, 6–12. [Google Scholar]
  66. Riaz, S.; Shakil Ur Rehman, S.; Hafeez, S.; Hassan, D. Effects of Kinect-Based Virtual Reality Training on Bone Mineral Density and Fracture Risk in Postmenopausal Women with Osteopenia: A Randomized Controlled Trial. Sci. Rep. 2024, 14, 6650. [Google Scholar] [CrossRef]
  67. Negm, A.M.; Papaioannou, A. Diagnosis of Osteosarcopenia—Clinical. In Osteosarcopenia; Duque, G., Troen, B.R., Eds.; Elsevier: Amsterdam, The Netherlands, 2022; pp. 181–204. [Google Scholar]
  68. Kerschan-Schindl, K.; Hasenoehrl, T. Exercise in the Prevention of Age-Related Fragility Fractures (Narrative Review). Gerontology 2025, 71, 173–184. [Google Scholar] [CrossRef] [PubMed]
  69. Horak, F.B. Postural Orientation and Equilibrium: What Do We Need to Know about Neural Control of Balance to Prevent Falls? Age Ageing 2006, 35 (Suppl 2), ii7–ii11. [Google Scholar] [CrossRef] [PubMed]
  70. Huang, W.-Y.; Chang, S.-T.; Lee, C.-H.; Liou, I.-H.; Cherng, R.-J. Effects of Virtual Reality on the Balance Performance of Older Adults: A Systematic Review and Meta-Analysis. J. Phys. Ther. Sci. 2024, 36, 2024–2027. [Google Scholar] [CrossRef]
  71. García-López, H.; Obrero-Gaitán, E.; Castro-Sánchez, A.M.; Lara-Palomo, I.C.; Nieto-Escamez, F.A.; Cortés-Pérez, I. Non-Immersive Virtual Reality to Improve Balance and Reduce Risk of Falls in People Diagnosed with Parkinson’s Disease: A Systematic Review. Brain Sci. 2021, 11, 1435. [Google Scholar] [CrossRef] [PubMed]
  72. Oliveira, L.K.R.; Marques, A.P.; Andrade, K.F.A.; de Assis, J.C.S.; Brito, A.L.; Souza, G.S.; Callegari, B. Virtual Reality in Improving Anticipatory Postural Adjustments to Step Initiation in Individuals with Knee Osteoarthritis: A Randomized Controlled Trial. Games Health J. 2024, 13, 100–108. [Google Scholar] [CrossRef]
  73. Gofredo, M.; Baglio, F.; De Icco, R.; Proietti, S.; Maggioni, G.; Turolla, A.; Pournajaf, S.; Jonsdottir, J.; Zeni, F.; Federico, S.; et al. Efficacy of Non-Immersive Virtual Reality-Based Telerehabilitation on Postural Stability in Parkinson’s Disease: A Multicenter Randomized Controlled Trial. Eur. J. Phys. Rehabil. Med. 2024, 59, 689–696. [Google Scholar] [CrossRef]
  74. Saragih, I.D.; Chen, Y.; Suarilah, I.; Susanto, H.; Lee, B. Virtual Reality Intervention for Fall Prevention in Older Adults: A Meta-Analysis. J. Nurs. Sch. 2025, 57, 759–775. [Google Scholar] [CrossRef]
  75. Rodríguez-Almagro, D.; Achalandabaso-Ochoa, A.; Ibáñez-Vera, A.J.; Góngora-Rodríguez, J.; Rodríguez-Huguet, M. Effectiveness of Virtual Reality Therapy on Balance and Gait in the Elderly: A Systematic Review. Healthcare 2024, 12, 158. [Google Scholar] [CrossRef]
  76. Saby, A.; Alvarez, A.; Smolins, D.; Petros, J.; Nguyen, L.; Trujillo, M.; Aygün, O. Effects of Embodiment in Virtual Reality for Treatment of Chronic Pain: Pilot Open-Label Study. JMIR Form. Res. 2024, 8, e34162. [Google Scholar] [CrossRef]
  77. Maheta, B.; Kraft, A.; Interrante, N.; Fereydooni, S.; Bailenson, J.; Beams, B.; Keny, C.; Osborne, T.; Giannitrapani, K.; Lorenz, K. Using Virtual Reality to Improve Outcomes Related to Quality of Life Among Older Adults With Serious Illnesses: Systematic Review of Randomized Controlled Trials. J. Med. Internet Res. 2025, 27, e54452. [Google Scholar] [CrossRef] [PubMed]
  78. Sheehy, L.; Bharadwaj, L.; Nissen, K.; Estey, J. Non-Immersive Virtual Reality Exercise Can Increase Exercise in Older Adults Living in the Community and in Long-Term Care: A Randomized Controlled Trial. Clin. Interv. Aging 2025, 20, 109–124. [Google Scholar] [CrossRef] [PubMed]
  79. Armijo-Olivo, S.; Fuentes, J.; da Costa, B.R.; Saltaji, H.; Ha, C.; Cummings, G.G. Blinding in Physical Therapy Trials and Its Association with Treatment Effects. Am. J. Phys. Med. Rehabil. 2017, 96, 34–44. [Google Scholar] [CrossRef] [PubMed]
  80. Armijo-Olivo, S.; Saltaji, H.; da Costa, B.R.; Fuentes, J.; Ha, C.; Cummings, G.G. What Is the Influence of Randomisation Sequence Generation and Allocation Concealment on Treatment Effects of Physical Therapy Trials? A Meta-Epidemiological Study. BMJ Open 2015, 5, e008562. [Google Scholar] [CrossRef]
Life 15 01654 g001
Figure 1. PRISMA flow diagram.
Figure 1. PRISMA flow diagram.
Life 15 01654 g001
Life 15 01654 g002
Figure 2. Forest plot of the effectiveness of virtual reality-based interventions on bone mineral density [64,65,66].
Figure 2. Forest plot of the effectiveness of virtual reality-based interventions on bone mineral density [64,65,66].
Life 15 01654 g002
Life 15 01654 g003
Figure 3. Forest plot of the effectiveness of virtual reality-based interventions on functional balance [61,63,64].
Figure 3. Forest plot of the effectiveness of virtual reality-based interventions on functional balance [61,63,64].
Life 15 01654 g003
Life 15 01654 g004
Figure 4. Forest plot of the effectiveness of virtual reality-based interventions on dynamic balance and functional mobility [62,63,64].
Figure 4. Forest plot of the effectiveness of virtual reality-based interventions on dynamic balance and functional mobility [62,63,64].
Life 15 01654 g004
Life 15 01654 g005
Figure 5. Forest plot of the effectiveness of virtual reality-based interventions on fear of falling [60,61,63].
Figure 5. Forest plot of the effectiveness of virtual reality-based interventions on fear of falling [60,61,63].
Life 15 01654 g005
Life 15 01654 g006
Figure 6. Forest plot of the effectiveness of virtual reality-based interventions on pain intensity [60,61,65].
Figure 6. Forest plot of the effectiveness of virtual reality-based interventions on pain intensity [60,61,65].
Life 15 01654 g006
Life 15 01654 g007
Figure 7. Forest plot of the effectiveness of virtual reality-based interventions on quality of life [60,61,62,65].
Figure 7. Forest plot of the effectiveness of virtual reality-based interventions on quality of life [60,61,62,65].
Life 15 01654 g007
Table 1. Search strategies in databases.
Table 1. Search strategies in databases.
DatabaseSearch Strategy
PubMed Medline(Osteoporosis[mh] or osteoporosis[tiab] or low bone density[tiab] or osteoporosis postmenopausal[mh] or osteoporosis postmenopausal[tiab] or osteopenia[tiab]) and (virtual reality[mh] or virtual reality[tiab] or exergaming[mh] or exergame *[tiab] or virtual reality exposure therapy[mh] or virtual reality exposure therapy[tiab] or wii[tiab] or Nintendo[tiab] or videogame *[tiab] or non-immersive virtual reality[tiab] or kinect[tiab] or virtual environment[tiab] or seious game[tiab])
SCOPUS(“Osteoporosis” or “low bone density” or “osteoporosis postmenopausal” or “osteopenia”) and (“virtual reality” or “exergaming” or “virtual reality exposure therapy” or “wii” or “Nintendo” or “videogamame” or “immersive virtual reality” or “Kinect” or “virtual environment” or “seious game”)
Web of ScienceTOPIC(*Osteoporosis* or *low bone density* or *osteoporosis postmenopausal* or *osteopenia*) and TOPIC(*virtual reality* or *exergaming* or *virtual reality exposure therapy* or *wii* or *Nintendo* or *videogamame* or *immersive virtual reality* or *Kinect* or *virtual environment* or *seious game*)
CINAHL CompleteAB (Osteoporosis or low bone density or osteoporosis postmenopausal or osteopenia) and AB (virtual reality or exergaming or virtual reality exposure therapy or Wii or Nintendo or videogame or immersive virtual reality or kinect or virtual environment or serious game)
PEDroOsteoporosis and virtual reality
Table 2. Characteristics of the studies included.
Table 2. Characteristics of the studies included.
StudyParticipants (N, Diagnosis, Age)VR GroupControl groupOutcomes
N, Characteristics of the InterventionN, Characteristics of the InterventionVariable (Test)
Gilani, M et al., 2023 (Iran) [60]
Non-blinded RCT
Setting: Physical Therapy Department at Tarbiat Modares University
Funding: Yes		20 women diagnosed with primary osteoporosis
Mean age: 58.9 ± 0.6 years		10 women performed strength and balance training in non-immersive virtual reality using the Xbox Kinect 360 system, 60 min per day, 3 days per week for 6 weeks.10 women performed conventional training with balance and strength exercises, 60 min a day, 3 days a week for 6 weeks.Fear of falling (FES-I)
Quality of life (Qualeffo-41)
Pain (Qualeffo-41)
Morone, G et al., 2016 (Italy)
[61]
Single-blinded RCT
Setting: Physical Medicine and Rehabilitation, Policlinico Umberto I
Funding: NR		38 women diagnosed with bone loss condition
Mean age: 68.9 ± 1.6 years		19 women performed balance and strength training using the non-immersive virtual reality system Nintendo Wii, 60 min a day, 2 days a week for 8 weeks.19 women performed conventional training with balance and strength exercises, 60 min a day, 2 days a week for 8 weeks.Fear of falling (FES-I)
Quality of life (SF-36)
Pain (VAS)
Functional balance (BBS)
Nambi, G et al., 2020 (Saudi Arabia) [65]
Double-blinded RCT
Setting: Physical Therapy Department
Funding: Yes		45 women diagnosed with osteoporosis
Mean age: 56.9 ± 0.9 years		15 women performed non-immersive virtual reality training with the Pro-Kin system for 45 min a day, 4 days a week, for 12 weeks. The training consisted of weight-bearing hip and knee mobility exercises.Control group 1: 15 women performed aerobic exercise training for 30 min, 4 days a week, for 12 weeks.
Control group 2: 15 women did not perform any specific exercise protocol for 12 weeks.		Quality of life (Quality of Life questionnaire)
Pain (Quality of Life questionnaire)
Bone mineral density (dual energy X-ray absorptiometry)
Riaz, S et al., 2024a (Pakistan) [64]
Double-blinded RCT
Setting: Riphah Rehabilitation Center
Funding: No.		43 women diagnosed with osteopenia
Mean age: 58.1 ± 0.2 years		22 women performed non-immersive virtual reality with Xbox Kinect, 45 min per session, 3 days a week for 24 weeks + outdoor walk 30 min per day, 7 days a week for 24 weeks.21 women performed outdoor walks for 30 min a day, 7 days a week, for 24 weeks.Quality of life (ECOS-16)
Dynamic balance/mobility (TUG)
Riaz, S et al., 2024b (Pakistan) [66]
Double-blinded RCT
Setting: Riphah Rehabilitation Center
Funding: No.		43 women diagnosed with osteopenia
Mean age: 58.1 ± 0.2 years		22 women performed non-immersive virtual reality with Xbox Kinect, 45 min per session, 3 days a week for 24 weeks + outdoor walk 30 min per day, 7 days a week for 24 weeks.21 women performed outdoor walks for 30 min a day, 7 days a week. for 24 weeks.Bone mineral density (dual energy X-ray absorptiometry)
Yilmaz, N et al., 2024 (Turkey)
[63]
Non-blinded RCT
Setting: NR.
Funding: Yes.		60 women diagnosed with osteoporosis
Mean age: 50 ± 4.1 years		30 women performed balance exercises with the non-immersive virtual reality system Nintendo Wii balance board, 45 min per session, 3 days a week for 12 weeks + walking and upper and lower limb mobility exercises as a warm-up.30 women performed mobility, strengthening, stretching, and balance exercises, 45 min per session, 3 days a week for 12 weeks + walking and upper and lower limb exercises as a warm-up.Fear of falling (FES-I)
Functional balance (BBS)
Dynamic balance/mobility (TUG)
Zhao, R et al., 2023 (China) [64]
Nom-blinded RCT
Setting: Elderly Healthcare Institution
Funding: Yes.		50 women diagnosed with osteoporosis
Mean age: 72.7 ± 0.8 years		25 women performed non-immersive virtual reality exercises with the VR rehabilitation training device, 50 min per session, 3 days a week for 12 months.25 women performed an exercise routine to prevent falls, including aerobic and machine exercises, 50 min per session, 3 days a week for 12 months.Functional balance (BBS)
Dynamic balance/mobility (TUG)
Bone mineral density (dual energy X-ray absorptiometry)
Abbreviations: RCT, Randomized Controlled Trial; NR, Non-Reported; FES-I, Falls Efficacy Scale International; VAS, Visual Analog Scale; TUG, Timed Up and Go Test; ECOS-16, Escala de la Calidad de Vida Osteoporosis; BBS, Berg Balance Scale.
Table 3. PEDro score of the studies included.
Table 3. PEDro score of the studies included.
StudyItemsTotalQualityBiases
i1i2i3i4i5i6i7i8i9i10i11
Gilani, M et al., 2023 * [60]YYYYNNY YNYY7/10GoodPerformance
Morone, G et al., 2016 [61]Y Y Y Y NN Y Y N Y Y 7/10GoodPerformance
Nambi, G et al., 2020 [65]Y Y Y Y Y N Y N N Y Y 7/10Good Performance
Riaz, S et al., 2024 * [64]Y Y Y Y N NY N N Y Y 6/10GoodPerformance
Riaz, S et al., 2024b [66]Y Y Y Y Y N Y N N Y Y 7/10GoodPerformance
Yilmaz, N et al., 2024 * [63]N Y N Y N N NY Y Y Y 6/10Good Selection, performance and detection
Zhao, R et al., 2023 * [64]Y Y N Y N N N Y Y Y Y6/10Good Selection, performance and detection
Abbreviations: i1: Eligibility criteria; i2: Random allocation; i3: Concealed allocation; i4: Baseline comparability; i5: Blind subjects; i6: Blind therapists; i7: Blind assessors; i8. Measures of at least one key outcome were obtained from more than 85% of the subjects initially allocated to groups; i9: Intention-to-treat analysis; i10: Between-group comparisons; i11: Point estimates and variability; Y: Yes; N: No. Notes: The Eligibility criteria item does not contribute to the total score. The score of the studies marked with * was confirmed in the PEDro database (www.pedro.org.au, accessed on 14 September 2025).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Cortés-Pérez, I.; Díaz-Fernández, Á.; Osuna-Pérez, M.C.; García-López, H.; Romero-Del-Rey, R.; Obrero-Gaitán, E. Virtual Reality-Based Therapy Improves Balance, Quality of Life, and Mitigates Pain and Fear of Falling in Women with Bone Mineral Density Loss: A Meta-Analysis of Randomized Controlled Trials. Life 2025, 15, 1654. https://doi.org/10.3390/life15111654

AMA Style

Cortés-Pérez I, Díaz-Fernández Á, Osuna-Pérez MC, García-López H, Romero-Del-Rey R, Obrero-Gaitán E. Virtual Reality-Based Therapy Improves Balance, Quality of Life, and Mitigates Pain and Fear of Falling in Women with Bone Mineral Density Loss: A Meta-Analysis of Randomized Controlled Trials. Life. 2025; 15(11):1654. https://doi.org/10.3390/life15111654

Chicago/Turabian Style

Cortés-Pérez, Irene, Ángeles Díaz-Fernández, María Catalina Osuna-Pérez, Héctor García-López, Raúl Romero-Del-Rey, and Esteban Obrero-Gaitán. 2025. "Virtual Reality-Based Therapy Improves Balance, Quality of Life, and Mitigates Pain and Fear of Falling in Women with Bone Mineral Density Loss: A Meta-Analysis of Randomized Controlled Trials" Life 15, no. 11: 1654. https://doi.org/10.3390/life15111654

APA Style

Cortés-Pérez, I., Díaz-Fernández, Á., Osuna-Pérez, M. C., García-López, H., Romero-Del-Rey, R., & Obrero-Gaitán, E. (2025). Virtual Reality-Based Therapy Improves Balance, Quality of Life, and Mitigates Pain and Fear of Falling in Women with Bone Mineral Density Loss: A Meta-Analysis of Randomized Controlled Trials. Life, 15(11), 1654. https://doi.org/10.3390/life15111654

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop