Effects of Active Video Games Combined with Conventional Physical Therapy on Perceived Functionality in Older Adults with Knee or Hip Osteoarthritis: A Randomized Controlled Trial

Abstract

Background: Osteoarthritis (OA) leads to functional decline in older adults. This study aimed to evaluate the effectiveness of active video games (AVGs) as a complement to conventional physical therapy (CPT) in improving functional disability. Methods: Sixty participants were randomly assigned to an experimental group (EG, n = 30, 68.7 ± 5.4 years), which received CPT combined with AVGs, or to a control group (CG, n = 30, 69.0 ± 5.5 years), which received CPT alone. Sessions were performed three times a week for ten weeks. Functional disability was assessed using the WOMAC index before, during, and after the intervention. Secondary outcomes included the Global Rating of Change (GRoC), the Minimal Clinically Important Difference, and patient trajectories through functional disability strata. Results: The EG showed progressive improvements in all WOMAC scores, with moderate to large increases by the end of the intervention, while the CG only showed significant changes in the later stages. The EG demonstrated greater improvements in WOMAC pain and the GroC scale (p < 0.05), maintaining most of the gains at follow-up, whereas the CG showed regression. Additionally, the EG had a higher proportion of responders, particularly for pain, while the CG had a predominance of non-responders and adverse responders. In the EG, 70% improved their functional disability stratification compared to 50% in the CG. Conclusion: Integration of AVGs with CPT further improves perceived functional disability in older adults with OA. Future research should explore these findings further.

1. Introduction

Osteoarthritis (OA) is the most prevalent musculoskeletal disease in older adults, affecting up to 50% of this population, and it is the leading cause of functional decline and reduced quality of life in this age group [1]. The global prevalence of OA is increasing, with over 527 million individuals affected worldwide. This number is expected to rise as the population ages, leading to higher incidence rates and more symptomatic cases, including knee pain and joint dysfunction [2]. OA imposes significant disability-adjusted life years [3] and high socioeconomic costs, accounting for 1% to 2.5% of the gross domestic product in developed countries [4].

Key risk factors for OA include obesity, previous joint injuries, genetic predisposition, and occupational hazards, such as repetitive movements and heavy lifting [2]. Knee OA is particularly associated with older age, female sex, obesity, prior knee injuries, and certain occupational factors, like knee bending and squatting [5]. Structural abnormalities, such as varus or valgus alignment of the knee, also contribute to its development, while recreational physical activity does not appear to increase the risk of knee OA [5]. Overall, OA represents a significant health burden, impacting both individuals and healthcare systems globally.

OA is a progressive disease characterized by periarticular connective tissue deterioration, inflammation, pain, stiffness, muscle weakness, and functional limitation [5]. It primarily affects women and commonly involves the knee, followed by the hands and hips, although other joints may also be affected [6]. Moreover, OA is associated with comorbidities, such as hypertension, hyperlipidemia, osteoporosis, and depression, which amplify its overall health impact [5,7]. OA treatment is based on non-pharmacological interventions, with physical exercise as the first-line therapy due to its ability to reduce pain, improve function, and enhance quality of life [8]. A personalized approach is recommended, combining strength training, aerobic exercise, and flexibility exercises, with education and continuous support [8]. Thus, assessing self-reported functional disability is essential to determine the extent of impairment in daily activities, allowing for tailored interventions and monitoring therapeutic progress [9].

Despite the benefits of exercise, many older adults discontinue these programs, limiting their effectiveness [10]. In OA patients, exercise adherence depends on intrinsic factors, such as physical condition and perceived treatment value, as well as extrinsic factors, like social support and the relationship with the therapist [11]. In this context, virtual reality (VR) and gamification have been explored as strategies to enhance motivation and enjoyment, thereby improving adherence and intervention effectiveness [12].

VR, defined as interaction with a computerized virtual environment, has been primarily integrated into neurological rehabilitation, while its use in the musculoskeletal field remains limited [13]. Based on its degree of immersion, VR is categorized as immersive, semi-immersive, and non-immersive, with the immersive modality offering a more intense sensory experience by inducing a “sense of presence” in the virtual environment [14]. However, this modality can cause adverse effects, such as “cybersickness”, including dizziness, nausea, and headaches [15]. In contrast, non-immersive VR offers advantages like better tolerance, ease of use, and lower cost [16].

Active video games (AVGs) or exergames, typically implemented through non-immersive VR, combine digital entertainment with physical activity, promoting interaction through body movements to achieve in-game goals, which require both physical and cognitive skills [17]. Several studies have shown that AVGs can enhance older adults’ physical health, cognitive function, and emotional well-being [18,19]. Moreover, their use, either combined with conventional physical therapy (CPT) [20,21] or as a standalone intervention [22,23], has demonstrated positive effects on self-reported functionality in patients with OA. However, their implementation is currently recommended primarily as a complementary therapy [24,25]. Because AVGs are a form of exercise, their beneficial effects in patients with OA may be attributed to cellular mechanisms of protection and tissue maintenance [26]. Additionally, the cognitive demands inherent to AVGs could stimulate neuroplasticity through an increase in neurotrophin release, enhancing cognitive function and promoting structural adaptations in key brain areas [27]. Finally, through gamification elements, AVGs not only foster positive emotions and a sense of self-efficacy; they also increase engagement and motivation towards exercise, which is especially relevant in the rehabilitation of patients with chronic pain, such as OA [18].

Although AVGs have shown benefits across various health conditions, their application in OA management remains limited. Recent systematic reviews emphasize the need for studies evaluating their specific outcomes in knee and hip OA, underscoring the current lack of conclusive evidence [28,29]. Furthermore, to the authors’ knowledge, no studies have examined the impact of AVGs on clinically meaningful measures, such as the minimum clinically important difference (MCID) for pain and function. Additionally, no research has stratified WOMAC scores to assess patient progress following AVG interventions. Therefore, a clinical trial is warranted as an optimal strategy to provide evidence on AVG efficacy within this population.

The present study aims to evaluate the effects of an AVG protocol as a complementary treatment to CPT on functional disability, measured by the Western Ontario and McMaster Osteoarthritis Index (WOMAC), in older adults with knee and/or hip OA. Additionally, the study introduces an innovative approach to assessing clinically meaningful changes by establishing MCID thresholds across each WOMAC dimension and the Global Rating of Change (GRoC) scale. Furthermore, it seeks to identify responders to the intervention and classify participants into quartiles based on their baseline functional disability levels to observe their clinical behavior post-intervention. This comprehensive approach enables a holistic analysis of clinical outcomes and subjective improvements, providing deeper insights into the perceived and measured impact of AVGs as a complement to CPT in OA management.

2. Materials and Methods

2.1. Study Design

We conducted a parallel two-arm randomized controlled trial (RCT) with a 1:1 allocation ratio, where the experimental group (EG) performed AVGs complementary to CPT and the control group (CG) performed CPT alone. The protocol was approved by the Scientific Ethics Committee of the Concepción Health Service (No. 22-12-59) and registered on clinicaltrials.gov (NCT05839262).

2.2. Participants

Participants were recruited from the physical rehabilitation unit of a community health center in Concepción, Chile. A professional from the center systematically invited patients with a physician referral for physical therapy to participate in the study, contacting them in person or by telephone. Interested individuals were summoned to a personal meeting to receive more information about the study’s requirements and characteristics, and those who agreed to participate subsequently signed an informed consent form voluntarily, in accordance with the principles established in the Declaration of Helsinki.

Before starting the protocol, participants were familiarized with all procedures, and their sociodemographic characteristics were recorded (

Table 1. Baseline sociodemographic characteristics of the participants.

	CG (n = 30)	EG (n = 30)	p-Value
Age (years), M ± SD	69.0 ± 5.5	68.7 ± 5.4	0.852
Height (cm), M ± SD	1.5 ± 0.0	1.5 ± 0.0	0.621
Weight (kg), M ± SD	72.2 ± 11.0	70.7 ± 12.5	0.612
BMI (kg/m2), M ± SD	30.1 ± 4.3	29.8 ± 4.4	0.761
Sex (female/male), no.	25/5	25/5	1.000

CG, control group; EG, experimental group; M, mean; SD, standard deviation; no., number; BMI, body mass index.

). The participants’ flow throughout the study phases is shown in Figure 1.

The inclusion criteria were individuals aged between 60 and 84 years with a medical diagnosis of mild to moderate knee and/or hip OA based on ACR criteria and a Kellgren and Lawrence radiographic grade of 2 or 3 [30,31] who did not require arthroplasty and who had the ability to walk independently for at least 15 m. The exclusion criteria included individuals with uncontrolled or decompensated physical, cognitive, or chronic conditions that limit or prevent interaction with AVGs, those undergoing treatment with opioids or other medications that could affect the outcome measures, those scoring below 13 on the abbreviated version of the Mini-Mental State Examination (MMSE-EFAM) [32], those with OA linked to infectious or autoimmune diseases, fractures, or surgeries, and those involved in another physical–cognitive rehabilitation program within the previous three months.

For a moderate effect size (ES), the a priori sample estimation using G*Power 3.1.9.7 was 50 subjects (α = 0.05 and 1-β = 0.8). However, 10 additional subjects were included to ensure internal validity in the event of a potential 20% dropout rate, resulting in a total sample of 60 participants.

2.3. Randomization and Allocation Concealment

An independent researcher not involved in participant recruitment generated a stratified random allocation sequence using R software v.4.1.2 to balance the groups by “age” (60–69, 70–79, and 80–84 years) and “sex” (male, female). Subsequently, a healthcare professional at the center assigned participants to the groups according to the random allocation sequence, concealing them in consecutively numbered, sealed, opaque envelopes.

2.4. Interventions

Two experienced physiotherapists conducted the interventions in the center’s therapeutic gym. For both groups, the protocol lasted ten weeks, with three non-consecutive sessions per week (total of 30 sessions), and participants were considered adherent if they attended ≥20 sessions (2/3 of the total) [33]. The exercise intensity ranged from light to moderate according to a perceived exertion scale of 0–10 points, with an equivalent weekly volume of 150 min across groups [34]. Attendance, adverse events, and overall health status were monitored throughout the experimental period. The interventions for each group are described below.

Control group: This group followed a protocol consisting of the following phases: (i) physical agents (10 min): simultaneous use of electrotherapy (TENS) and superficial thermotherapy (hot packs); (ii) warm-up (5 min): free joint movements; (iii) exercise blocks (50 min): aerobic exercises (e.g., stationary cycling and treadmill walking), muscle strengthening for limbs/trunk (e.g., elastic bands, dumbbells, and bodyweight exercises), postural balance (e.g., unstable surfaces, single-leg stance, tandem and obstacle walking), and general flexibility for limbs/trunk; (iv) cool-down (5 min): breathing exercises; and (v) physical agents (10 min): simultaneous use of electrotherapy (TENS) and superficial thermotherapy (hot packs). The specific exercises of each block (aerobic, strength, balance, and flexibility) were alternated in each session and indicated with an individualized approach in series and repetitions according to the tolerance of each participant, considering an approximate rest period of two minutes between blocks. The Supplementary Material in Table S1 provides further description of the conventional exercises incorporated into the protocol.

Experimental group: This group performed the same phases as the CG, but the exercise block phase lasted 30 min, which reduced the number of sets and repetitions. After this phase, 20 min of AVGs was added, thus ensuring an equivalent exercise time in both groups (50 min per session). The AVGs were organized into three sets (one for each weekly session). They included a series of analytical exercises, yoga postures, and playful physical activities from the game Ring Fit Adventure (Nintendo Switch^®). Sixteen exercise games were selected according to the clinical characteristics of the population, which were balanced to cover the basic components of functional fitness (aerobic endurance, strength, balance, and flexibility). Exercises, such as “Dorsal rotation” and “Rotation with inclination”, involve active trunk mobility, the first one in an upright posture and the second one combined with a semi-squat and pauses at the point of maximum rotation. In “Knee raises”, participants alternately lift their knees, integrating arm flexion and extension, while in “Squats”, controlled squats with pauses in semi-flexion are performed. “Lunge with rotation” requires a forward lunge step, rotating the torso towards the leading leg. “Lateral inclination” involves controlled trunk inclinations, while “Squats with extension” combines squats with external foot rotation and pauses in semi-flexion. Additionally, three yoga-inspired activities that demand alignment and stability are included: “The warrior”, “The chair”, and “Crescent moon”. Other activities include dynamic games requiring precision, postural control, and strength. In “Equilibrism”, the participant must move swiftly to avoid obstacles and collect coins. “Moto adductors” is performed seated and requires controlling the movement of a cart by applying pressure on the exercise ring between the knees. “Trunk swinging” requires quick, coordinated trunk movements with raised arms. Finally, three running games were included, “Running path”, “Monster’s lair”, and “Jogging bridge”, which demand continuous walking or jogging, pace adjustments, and coordinated activities to overcome obstacles in dynamic environments.

To ensure proper visualization, AVGs were displayed on a 43-inch TV. During each game, participants were required to closely follow the instructions of a virtual trainer and control an avatar while receiving simultaneous visual, auditory, and haptic feedback. Figure 2 shows a participant using an AVG and an image of the visual feedback from the game. The Supplementary Material in Table S2 describes the AVGs used and their distribution per session in the protocol.

2.5. Outcome Measures

A healthcare professional blinded to group allocation administered the instruments the week before the intervention (pre-test), after 10 sessions (post-test 1), after 20 sessions (post-test 2), after 30 sessions (post-test 3), and four weeks after the intervention ended (follow-up). The tests applied were the following.

Functional disability: This primary outcome was measured using the Spanish version of the WOMAC index [35]. The questionnaire consists of 24 items scored on a Likert scale from 0 to 4 points (0 = none, 1 = mild, 2 = moderate, 3 = severe, and 4 = extreme), with a total score of 98 points (higher scores indicate greater self-perceived functional disability). The items are grouped into three subscales, pain (5 items; 20 points), stiffness (2 items; 8 points), and physical function (17 items; 68 points), which are considered core outcomes in patients with OA [36].

Perceived functional change: This outcome is assessed only at post-test 3 using a GRoC scale. This scale has been used as an outcome measure and an external anchor for comparing other outcomes [37,38]. The GRoC is a 15-point scale ranging from +7 (“a very great deal better”) to 0 (“about the same”) to −7 (“a very great deal worse”), with magnitude categories defined as 1–3 points = small, 4–5 points = moderate, and 6–7 points = large [38].

2.6. Statistical Analysis

Data were analyzed using an intention-to-treat (ITT) approach, a recommended strategy to minimize bias by analyzing all participants according to their original assignment [39]. This analysis was conducted by an investigator who was blinded to group allocation. The multiple imputation technique was applied using the predictive mean matching method to handle missing data and ensure the inclusion of all participants in the analysis [40]. Subsequently, data were described using normal distribution statistics, verified using the Shapiro–Wilk test, which is sensitive to deviations in small sample sizes, allowing confirmation of whether parametric tests were appropriate [41].

Homoscedasticity between groups was verified using Levene’s test; thus, for WOMAC, a two-way repeated measures analysis of variance (ANOVA) was performed, followed by Tukey’s post hoc test to analyze intragroup differences (post-tests 1, 2, 3, and follow-up versus pre-test) and intergroup differences at each time point. For GRoC, an independent sample Student’s t-test was applied. The ES was calculated using Cohen’s d, which provides a standardized measure of the magnitude of differences, categorized as <0.2 (negligible), 0.2–0.49 (small), 0.5–0.79 (moderate), and ≥0.8 (large) [42].

The MCID threshold for each WOMAC score (total and subscales of pain, stiffness, and function) was calculated using a standardized ES multiplied by the standard deviation, as proposed by Nascimento et al. (2024) [43]. This approach helps assess inter-individual variability by identifying responders whose improvements exceed the MCID, indicating significant clinical benefits. Participants were then classified based on the change (Δ) in scores (post-test 3 vs. pre-test) as responders (Rs), non-responders (NRs), and adverse responders (ARs) [44]. Because a lower WOMAC score indicates improvement, the upper MCID threshold (favorable) was expressed as a negative value, and the lower MCID threshold (unfavorable) is expressed as a positive value. The classification was defined as follows: Rs if Δ score ≥ −MCID, NRs if Δ score < −MCID and < +MCID, and ARs if Δ score ≥ +MCID. Associations between groups and response categories (Rs, NRs, ARs) for each WOMAC score were analyzed using the chi-square test (χ²) due to its ability to assess independence between categorical variables [45]. Next, the two-proportion z-test was applied to perform specific comparisons within response categories, providing detailed insight into intergroup differences in response proportions [46]. The MCID thresholds were illustrated using GraphPad Prism 9.4.1 (GraphPad Software Inc.; San Diego, CA, USA).

Finally, the sample was stratified based on the 25th, 50th, and 75th percentiles of the baseline total WOMAC score, allowing observation of participant distribution across quartiles from pre-test to post-test 3. This stratification approach, which is equivalent to that used by Karsdal et al. (2015), allows for precise categorization of patients by disability level, facilitating outcome assessment in patients with knee and hip OA [47]. Statistical analyses were performed using SPSS v.25 (IBM Corp., Armonk, NY, USA) and JASP v.0.18.3 (https://jasp-stats.org/; accessed on 3 June 2024) with an alpha level of 0.05.

3. Results

At baseline, the groups were homogeneous in terms of their sociodemographic characteristics (Table 1) and functional disability (

Table 2. Functional disability comparison between study groups according to WOMAC questionnaire scores.

	Control Group (n = 30)					Experimental Group (n = 30)
	Pre-Test	Post-Test 1	Post-Test 2	Post-Test 3	Follow-Up	Pre-Test	Post-Test 1	Post-Test 2	Post-Test 3	Follow-Up
W-pain	9.2 ± 3.3	8.3 ± 2.8 s	7.8 ± 3.6 s	7.8 ± 3.3 s	8.1 ± 3.0 s	9.1 ± 2.6	6.2 ± 2.7 *,l	6.0 ± 3.2 *,l	4.5 ± 2.6 *,l,†	6.1 ± 3.2 *,l
W-stiffness	3.4 ± 1.0	3.2 ± 1.4 n	3.1 ± 1.4 s	2.7 ± 1.5 m	3.1 ± 1.3 s	3.3 ± 1.8	2.7 ± 0.9 s	2.7 ± 1.5 s	2.2 ± 1.6 *,m	2.5 ± 1.3 m
W-function	31.7 ± 12.3	29.5 ± 11.5 n	27.4 ± 11.8 s	23.6 ± 8.5 *,m	27.2 ± 9.3 s	30.1 ± 11.7	23.6 ± 9.7 *,m	23.1 ± 10.9 *,m	16.8 ± 11.1 *,l	20.8 ± 12.0 *,l
W-total	44.4 ± 15.9	41.0 ± 15.1 s	38.4 ± 15.9 s	34.2 ± 11.6 *,m	38.5 ± 12.9 s	42.5 ± 14.4	32.6 ± 12.0 *,m	31.9 ± 14.1 *,m	23.6 ± 14.4 *,l	29.5 ± 15.2 *,l

Data expressed as means ± standard deviations; W, WOMAC. Cohen’s d (effect size): n, negligible; s, small; m, moderate; l, large. * Intragroup difference p < 0.05; ^† intergroup difference p < 0.05.

). Initially, 99 subjects were assessed for eligibility, of which 60 were enrolled, and 13 participants withdrew for reasons unrelated to the research protocol (Figure 1). The recruitment and follow-up periods were between April 2023 and March 2024, with no adverse events (falls, fainting, nausea, or incapacitating pain) occurring, and adherence rates were 73.3% in the CG and 76.7% in the EG, respectively.

The intragroup analysis shows that the EG had statistically significant improvements in WOMAC-pain (post-tests 1, 2, 3, and follow-up), WOMAC-stiffness (post-test 3), WOMAC-function (post-tests 1, 2, 3, and follow-up), and WOMAC-total (post-tests 1, 2, 3, and follow-up), with a moderate to large ES (d = 0.59 to 1.46). In contrast, the CG showed significant improvements only in WOMAC-function and WOMAC-total at post-test 3, with a moderate ES (d = 0.71 to 0.73). Additionally, the intergroup analysis indicates that at post-test 3, the EG outperformed the CG (p < 0.05) in WOMAC-pain, with a large ES (d = 1.46) (Table 2).

The GRoC results showed that the mean score for the EG was categorized as a moderate favorable change, while the CG score indicated a small to moderate favorable change. The difference between groups was statistically significant (4.7 ± 1.2 and 3.5 ± 1.4 for the mean and the standard deviation of the EG and CG, respectively), with a large ES (d = 0.85).

Figure 3 presents the ±MCID thresholds for WOMAC scores, along with bars representing each participant’s Δ scores for their classification as Rs, NRs, or ARs. In the EG, the most frequent category was Rs, except for WOMAC-function, while in the CG, NRs were the most frequent. Compared to the CG, and except for WOMAC-function, the EG had higher frequencies of Rs, with a statistically significant difference in WOMAC-pain (χ² test, p < 0.01; z-test, p < 0.01). For the NRs category, except for WOMAC-function, the EG had lower frequencies, with a statistically significant difference in WOMAC-pain (χ² test, p < 0.01; z-test, p < 0.01). Finally, for the ARs category, the frequencies were lower in the EG, except for WOMAC-function, where they were the same between groups.

Table 3. Frequency of responders, non-responders, and adverse responders in the study groups.

	Control Group (n = 30)			Experimental Group (n = 30)
	Rs	NRs	ARs	Rs	NRs	ARs
W-pain, no. (%)	10 (33.3)	17 (56.7)	3 (10.0)	22 (73.3) †	8 (26.7) ‡	0 (0.0)
W-stiffness, no. (%)	13 (43.3)	15 (50.0)	2 (6.7)	15 (50.0)	14 (46.7)	1 (3.3)
W-function, no. (%)	11 (36.7)	16 (53.3)	3 (10.0)	9 (30.0)	18 (60.0)	3 (10.0)
W-total, no. (%)	13 (43.3)	14 (46.7)	3 (10.0)	18 (60.0)	12 (40.0)	0 (0.0)

W, WOMAC; no., number; %, percentage; Rs, responders; NRs, non-responders; ARs, adverse responders; ^† Rs, intergroup difference p < 0.05; ^‡ NRs, intergroup difference p < 0.05.

shows the frequency distribution of these categories in the study groups.

Based on the 25th, 50th, and 75th percentile values of the baseline WOMAC-total score, the quartile ranges were as follows: quartile 1 (Q1): 0 to 33 points; quartile 2 (Q2): 34 to 43 points; quartile 3 (Q3): 44 to 55 points; and quartile 4 (Q4): ≥56 points. At the end of the intervention, in the CG, 50% of participants were stratified within Q1, 20% in Q2, 20% in Q3, and 10% in Q4. According to interquartile flow (pre-test to post-test 3), 40% of participants remained in their initial quartile, 50% moved to a better quartile, and 10% shifted to a worse quartile. In the EG, 76.6% of participants were stratified within Q1, 16.6% in Q2, 3.3% in Q3, and 3.3% in Q4. According to interquartile flow, 23.3% of participants remained in their initial quartile, 70% moved to a better quartile, and 6.6% shifted to a worse quartile (Figure 4).

4. Discussion

The main results of this study, which evaluated the effects of a complementary intervention combining AVGs and CPT on perceived functional disability in older adults with knee or hip OA, were the following. (i) The EG showed progressive improvement at all time points, achieving moderate to large improvements in all WOMAC scores by the end of the intervention, while the CG only showed significant changes at the end, with moderate improvements in WOMAC-function and total scores. (ii) The EG showed greater improvements in WOMAC-pain and the GRoC scale compared to the CG. (iii) At follow-up, the EG maintained most of the improvements, whereas the CG tended to regress. (iv) The EG had a higher proportion of Rs, particularly in WOMAC-pain, with a low proportion of ARs, while the CG had a predominance of NRs, with a higher proportion of ARs compared to the EG. (v) In the EG, 70% of participants improved their quartile position, 23.3% remained in their initial quartile, and only 6.6% worsened. In contrast, 50% of the CG improved their quartile, 40% remained, and 10% worsened. These results suggest that complementing CPT with AVGs optimizes gains in self-perceived functionality, enhancing the rehabilitation process. Additionally, no adverse events related to AVGs were reported, demonstrating the safety of the intervention.

Improving WOMAC scores is relevant because it increases the perceived ability to perform daily activities with less pain and joint stiffness [36], which can positively influence quality of life by enhancing functional status [48]. Additionally, greater mobility is key to preventing falls, preserving cognitive function, reducing the impact of sedentary behavior, and promoting emotional well-being. These factors also help reduce costs and alleviate the burden on healthcare systems [49].

Previous studies suggest that using AVGs as a complementary therapy in patients with OA leads to significant improvements in perceived functional disability, which is consistent with the present research. In the studies by Elshazly et al. (2016) and Mete and Sari (2022), the use of systems like the Xbox 360 and MarVAJED, respectively, combined with conventional exercise, was more effective than conventional exercise alone in improving WOMAC scores [20,21]. Similarly, Ozlu et al. (2023) found that immersive VR combined with CPT generated additional benefits [50]. These findings, which are in line with those of the present study, highlight the synergistic enhancing effect of different AVG modalities on functional perception. On the other hand, trials where AVGs were used as a standalone intervention have also shown favorable results compared to CPT for WOMAC [22,23,51]. However, Lin et al. (2020) reported no significant differences between groups [51]. The latter approach differs from the current study; however, it is also noteworthy, given the robust scientific evidence supporting the positive effects of physical exercise as a first-line treatment for OA [8].

Our protocol included the complementary use of AVGs, which aligns with previous recommendations [25,52]. In this regard, although the review by Chen et al. (2021) reports positive outcomes from AVGs alone, it concludes that their combination with physical training is particularly promising for improving postural balance and reducing the risk of falls in older adults [52]. These results are relevant considering the observed associations between various postural control strategies and self-reported symptoms on the WOMAC in patients with knee OA [53,54]. Additionally, the recent review by Hernández et al. (2024) suggests that AVGs could serve as a complementary strategy alongside other interventions in clinical practice, recommending their use in primary care and community centers, among other settings [24], which aligns with our research.

AVGs share the same effects and mechanisms as conventional physical exercise when applied with equivalent modalities and parameters. Well-dosed, preferably multicomponent exercise is key to managing the cardinal symptoms of OA [55]. It also improves functional performance, cardiorespiratory capacity, postural balance, fall risk, proprioception, sensorimotor control, body composition, cognitive function, psychological well-being, and quality of life, among other benefits [55]. From a mechanistic perspective, exercise favorably influences the pathological changes in OA by reducing extracellular matrix degradation (decreased MMP-13, increased type II collagen), inhibiting apoptosis (decreased caspase-3), modulating the inflammatory response (reduced IL-1β, IL-6, and TNF-α), inducing autophagy (regulation of the IRE1–mTOR–PERK pathway), and regulating the expression of non-coding RNA [26]. In this study, both groups showed improvements in certain WOMAC dimensions; however, the greater psychomotor diversity offered by incorporating AVGs may explain the better results of the EG.

Recently, the importance of cognitive functioning for the ability to perform daily activities has been emphasized [56], suggesting that the cognitive demands inherent in AVGs may have also contributed to the observed results. Although with small effects, exercise has been shown to enhance executive functions, particularly in individuals with normal cognitive function compared to those with mild cognitive impairment [57]. Simultaneous physical–cognitive training through dual-task exercises appears more effective than physical or cognitive training alone, and even more so than AVGs [58]. This is noteworthy, as some authors consider AVGs to be dual tasks that can enhance physical and cognitive performance [19,59]. The underlying mechanisms of AVGs may be mediated by increased neurotrophin signal transduction, protecting neuronal structure and function [27]. In this regard, biomarker proteins, such as brain-derived neurotrophic factor (BDNF), insulin-like growth factor 1 (IGF-1), and vascular endothelial growth factor (VEGF), among other neurotrophins, are considered essential in mediating the effects of exercise and cognitive activities on cognitive function and brain structure (e.g., the hippocampus, the lateral prefrontal cortex, the caudate nucleus, and the cerebellar hemisphere) by promoting neuroplastic processes, such as neurogenesis, synaptogenesis, and angiogenesis [27,59]. In this way, it has been proposed that the combination of physical and cognitive activity enhances neuroplasticity through the synergy between a “facilitating effect” stemming from specific neurophysiological mechanisms (e.g., the release of neurotrophins) and a “guiding effect” from cognitive stimulation, which appropriately directs these neuroplastic changes [60]. However, their effectiveness seems to depend on the level of integration of metabolic activity with (neuro)muscular, physical, perceptual–motor, and cognitive stimuli, which facilitate exploration and adaptation in challenging and everyday environments [61]. The AVGs used in this study were not specifically designed for rehabilitation; however, we hypothesize that their cognitive demands also contributed to the favorable outcomes in the EG.

Another explanation for the benefits associated with the complementary use of AVGs in our study relates to the psychosocial and motivational perspective, as these aspects can influence perceptions of self-efficacy and emotional well-being [62]. Unlike conventional physical training, AVGs incorporate gamification elements, such as immediate feedback (visual, auditory, and haptic) and the opportunity to surpass scores, which can enhance confidence in one’s abilities, satisfaction, and engagement with the intervention, generating positive emotions [18]. Additionally, AVGs have been shown to promote emotions like happiness and reduce symptoms of anxiety and depression, thereby improving subjective well-being and perceived self-efficacy [18]. On the other hand, some features, such as adaptive difficulty, immersion, and a sense of accomplishment, are key factors in motivating and sustaining older adults’ participation in exergame interventions, underscoring the importance of these elements in maintaining commitment [63]. All of these factors are particularly relevant in patients with chronic joint pain, as psychological well-being and positive beliefs about pain can play a protective role and enhance coping capacity [64]. Thus, AVGs, by fostering positive emotions and a sense of control over pain, could contribute not only to improving emotional well-being but also to facilitating more effective pain management, promoting a better quality of life in this population.

Our study is pioneering the reporting of MCID thresholds for WOMAC concerning the complementary use of AVGs in older adults with knee and/or hip OA. The MCID threshold is a fundamental tool for assessing treatment effectiveness, and its calculation can be performed using anchor-based, distribution-based, or sensitivity and specificity analysis approaches, each with its advantages and limitations [65]. In this study, the MCID was determined using a distribution-based Bayesian model, which allows for a better understanding of data variability and effect size, providing clinically relevant information even in the absence of statistical significance, complementing traditional tests, and minimizing the risk of errors due to exclusive reliance on p-values [43]. Tubach et al. (2005) reported an MCID of 9.1 for WOMAC-function in knee OA and 7.9 for hip OA, consistent with our MCID of ±9.61 [66]. Meanwhile, the review by MacKay et al. (2019) on prosthetic replacements showed considerable variations depending on the calculation method. In the case of total knee arthroplasty (TKA), the MCIDs (on the original scale) ranged from 2.66 to 7.20 for WOMAC-pain and from 1.22 to 22.45 for WOMAC-function; for total hip arthroplasty (THA), the ranges were from 1.66 to 8.20 for pain and from 6.60 to 23.13 for function [67]. In addition to the MCID for WOMAC-function, we obtained values for WOMAC-stiffness, WOMAC-pain, and WOMAC-total, which expands the clinical applicability of our results; however, although the obtained values largely coincide with those previously reported, methodological and therapeutic variations highlight the need for further research.

Various studies have attempted to stratify patients according to their WOMAC scores to identify specific patterns in knee and hip OA, assess their predictive validity, and classify responses to TKA, among other objectives [68,69,70]. However, these also emphasize the complexity of interpreting scores and the need for additional research. In this context, to deepen the clinical analysis, we stratified the sample according to the total WOMAC score using the 25th, 50th, and 75th percentiles to generate four levels of increasing disability [71], and we visualized the trajectory of responses using Sankey diagrams, which have proven helpful in analyzing clinical evolutions [72]. To our knowledge, this is the first study to use this tool in patients with OA treated with AVGs. The diagrams show that incorporating AVGs yields greater clinical benefit (more transitions from higher quartiles to lower ones) and a broader positive response (more individuals improving quartiles) compared to conventional therapy alone. This result is not reflected in inferential statistical analysis.

The GRoC scale is a self-reported measure used to assess patients’ perceptions of changes in symptoms or function, notable for its simplicity and clinical applicability [73]. However, its validity has been questioned, as the correlation with objective functional changes tends to weaken over prolonged follow-up periods, suggesting that the perception of change may be primarily influenced by the patient’s current status [74]. Despite this, it remains a valuable tool as a prognostic indicator and for establishing cut-off points in response to interventions [75,76]. In our study, the GRoC scale showed a significantly greater favorable change in the group that incorporated AVGs; however, this result should be interpreted with caution, given that this scale reflects subjective perception at a specific moment, and its use should be complementary to other instruments that better objectify treatment effectiveness [74].

One of the present study’s main strengths is implementing an RCT with concealed allocation and ITT analysis, which ensures the internal validity of the results and minimizes the risk of bias. Additionally, considering a CG that received a well-structured intervention with a volume equivalent to the EG allowed for an equitable comparison of the additional effects of AVGs as a complementary therapy. Furthermore, selecting clinically relevant outcome measures, such as WOMAC and GRoC, reinforces the clinical applicability of the findings.

The study has certain limitations that must be taken into account. (i) A group that received only AVGs was not included, limiting the ability to evaluate the isolated effect of this intervention modality compared to CPT. (ii) The sample size does not allow for detailed subgroup analyses by age, sex, or clinical characteristics, restricting the ability to identify variations in treatment response. (iii) The follow-up period after the intervention was four weeks, limiting the assessment of the long-term sustainability of the benefits obtained. (iv) This study was conducted in a community rehabilitation center and involved older adults with mild to moderate knee or hip OA, which hinders the extrapolation of the results to other clinical settings or populations with more specific clinical characteristics. (v) The lack of specific measures related to the enjoyment of AVGs implies that participants’ motivation and engagement are only indirectly reflected in the results, which could overlook crucial psychosocial factors that influence adherence and intervention effectiveness. (vi) Certain factors, such as participants’ preferences toward different exercise modalities, were not assessed, which could also influence commitment and effort in the intervention program. (vii) Although AVGs were selected and implemented according to the clinical characteristics of the population, they are not specifically designed for rehabilitation, which could affect their effectiveness compared to systems developed exclusively for this purpose.

To address these limitations, future research should consider groups receiving only AVGs to analyze their isolated effect. It is proposed to conduct analyses of subgroups based on age, sex, and clinical characteristics to identify variations in treatment response. Additionally, extending the follow-up period is necessary to assess the sustainability of outcomes over a longer term and to explore applicability in diverse clinical settings beyond a single community center. It is also recommended to include specific measures of AVG enjoyment to capture relevant motivational and psychosocial factors. Finally, it would be valuable to investigate the impact of personal preferences related to different exercise modalities, as these may influence commitment and effort in the intervention program, and to develop AVGs specifically designed for OA rehabilitation, thus optimizing their suitability and effectiveness.

5. Conclusions

In conclusion, the intervention combining AVGs with CPT resulted in significant improvements in perceived functional disability among individuals with knee and hip OA. The EG demonstrated consistent improvements in pain, stiffness, and function, outperforming the CG, which received CPT alone, particularly at post-test 3. The GRoC analysis indicated a moderate favorable change in the EG, while the CG exhibited more limited progress. Regarding the MCID, the EG showed a higher frequency of pain reductions, particularly in the Rs category, with statistically significant differences compared to the CG. These findings highlight the effectiveness of the combined intervention, as a larger proportion of participants in the EG exhibited positive changes in WOMAC scores. Quartile analysis further revealed that the EG made greater strides toward higher quartiles in WOMAC scores, reflecting clinical improvement, whereas the CG showed less progress. Overall, these results suggest that AVGs may enhance the benefits of traditional exercise and represent a promising approach for optimizing rehabilitation in knee and hip OA, with high adherence and no adverse events. Future research should investigate the long-term effects of AVGs and explore their potential in other therapeutic modalities and contexts, using larger sample sizes and extended follow-up to assess the sustainability of these outcomes.