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Received: 14 October 2024
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Accepted: 30 November 2024
Published: 26 December 2024
Citation: Guede-Rojas, F.; Mendoza,
C.; Fuentes-Contreras, J.; Alvarez, C.;
Agurto Tarbes, B.; Muñoz-Gutiérrez,
J.K.; Soto-Martínez, A.; Carvajal-
Parodi, C. 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. Appl.
Sci. 2025,15, 93. https://doi.org/
10.3390/app15010093
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license
(https://creativecommons.org/
licenses/by/4.0/).
Article
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
Francisco Guede-Rojas 1, Cristhian Mendoza 2, Jorge Fuentes-Contreras 3,4 , Cristian Alvarez 1,
Bárbara Agurto Tarbes 5, Javiera Karina Muñoz-Gutiérrez 5, Adolfo Soto-Martínez 6
and Claudio Carvajal-Parodi 7, 8, *
1
Exercise and Rehabilitation Sciences Institute, School of Physical Therapy, Faculty of Rehabilitation Sciences,
Universidad Andres Bello, Santiago 7591538, Chile; francisco.guede@unab.cl (F.G.-R.);
cristian.alvarez@unab.cl (C.A.)
2
Escuela de Medicina, Facultad de Medicina y Ciencia, Universidad San Sebastián, Concepción 4030000, Chile;
cristhian.mendoza@uss.cl
3Clinical Research Lab, Department of Physical Therapy, Catholic University of Maule, Talca 3460000, Chile;
jorgef@ualberta.ca
4Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB T6G 2G4, Canada
5Programa Magíster Kinesiología Musculoesquelética, Universidad San Sebastián, Lientur #1457,
Concepción 4030000, Chile; barbara.agurtot@gmail.com (B.A.T.); klgajavieram.g@gmail.com (J.K.M.-G.)
6Departamento de Kinesiología, Facultad de Medicina, Universidad de Concepción,
Concepción 4030000, Chile; adosoto@udec.cl
7
Escuela de Kinesiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián,
Lientur #1457, Concepción 4030000, Chile
8Programa de Doctorado en Ciencias de la Actividad Física y del Deporte, Universidad de Cádiz, Avda,
República Saharaui s/n, Campus Puerto Real 11519, Puerto Real, 11510 Cádiz, Spain
*Correspondence: claudio.carvajal@uss.cl; Tel.: +56 41 2487240
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 comple-
ment to conventional physical therapy (CPT) in improving functional disability. Meth-
ods: 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 be-
fore, 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.
Keywords: osteoarthritis; active video games; WOMAC; functional disability; MCID
Appl. Sci. 2025,15, 93 https://doi.org/10.3390/app15010093
Appl. Sci. 2025,15, 93 2 of 17
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 deteri-
oration, 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 rec-
ommended, 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, limit-
ing 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 primar-
ily 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
]. How-
ever, 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 interven-
tion
[22,23]
, has demonstrated positive effects on self-reported functionality in patients
with OA. However, their implementation is currently recommended primarily as a com-
Appl. Sci. 2025,15, 93 3 of 17
plementary 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 appli-
cation 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 interven-
tions. 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 al-
location 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). The participants’ flow
throughout the study phases is shown in Figure 1.
Appl. Sci. 2025,15, 93 4 of 17
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 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.
Appl.Sci.2024,14,xFORPEERREVIEW4of18
Sex(female/male),no. 25/525/51.000
CG,controlgroup;EG,experimentalgroup;M,mean;SD,standarddeviation;no.,number;BMI,
bodymassindex.
Figure1.Studyflowchart.
Theinclusioncriteriawereindividualsagedbetween60and84yearswithamedical
diagnosisofmildtomoderatekneeand/orhipOAbasedonACRcriteriaandaKellgren
andLawrenceradiographicgradeof2or3[30,31]whodidnotrequirearthroplastyand
whohadtheabilitytowalkindependentlyforatleast15m.Theexclusioncriteriain-
cludedindividualswithuncontrolledordecompensatedphysical,cognitive,orchronic
conditionsthatlimitorpreventinteractionwithAVG s , thoseundergoingtreatmentwith
opioidsorothermedicationsthatcouldaffecttheoutcomemeasures,thosescoringbelow
13ontheabbreviatedversionoftheMini-MentalStateExamination(MMSE-EFAM)[32],
thosewithOAlinkedtoinfectiousorautoimmunediseases,fractures,orsurgeries,and
thoseinvolvedinanotherphysical–cognitiverehabilitationprogramwithintheprevious
threemonths.
Foramoderateeffectsize(ES),theapriorisampleestimationusingG*Power3.1.9.7
was50subjects(α=0.05and1-β=0.8).However,10additionalsubjectswereincludedto
ensureinternalvalidityintheeventofapotential20%dropoutrate,resultinginatotal
sampleof60participants.
2.3.RandomizationandAllocationConcealment
Anindependentresearchernotinvolvedinparticipantrecruitmentgeneratedastrat-
ifiedrandomallocationsequenceusingRsoftwarev.4.1.2tobalancethegroupsby“age”
(60–69,70–79,and80–84years)and“sex”(male,female).Subsequently,ahealthcarepro-
fessionalatthecenterassignedparticipantstothegroupsaccordingtotherandomallo-
cationsequence,concealingtheminconsecutivelynumbered,sealed,opaqueenvelopes.
Figure 1. Study flow chart.
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 strati-
fied random allocation sequence using R software v.4.1.2 to balance the groups by “age”
Appl. Sci. 2025,15, 93 5 of 17
(60–69, 70–79, and 80–84 years) and “sex” (male, female). Subsequently, a healthcare profes-
sional 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 thera-
peutic 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”,
Appl. Sci. 2025,15, 93 6 of 17
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 2shows 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.
Appl.Sci.2024,14,xFORPEERREVIEW6of18
Figure2.ParticipantusingAVG(A).Imageofthevisualfeedbackfromthegame(B).
2.5.OutcomeMeasures
Ahealthcareprofessionalblindedtogroupallocationadministeredtheinstruments
theweekbeforetheintervention(pre-test),after10sessions(post-test1),after20sessions
(post-test2),after30sessions(post-test3),andfourweeksaftertheinterventionended
(follow-up).Thetestsappliedwerethefollowing.
Functionaldisability:ThisprimaryoutcomewasmeasuredusingtheSpanishversion
oftheWOMACindex[35].Thequestionnaireconsistsof24itemsscoredonaLikertscale
from0to4points(0=none,1=mild,2=moderate,3=severe,and4=extreme),witha
totalscoreof98points(higherscoresindicategreaterself-perceivedfunctionaldisability).
Theitemsaregroupedintothreesubscales,pain(5items;20points),stiffness(2items;8
points),andphysicalfunction(17items;68points),whichareconsideredcoreoutcomes
inpatientswithOA[36].
Perceivedfunctionalchange:Thisoutcomeisassessedonlyatpost-test3usinga
GRoCscale.Thisscalehasbeenusedasanoutcomemeasureandanexternalanchorfor
comparingotheroutcomes[37,38].TheGRoCisa15-pointscalerangingfrom+7(“avery
greatdealbeer”)to0(“aboutthesame”)to−7(“averygreatdealworse”),withmagni-
tudecategoriesdefinedas1–3points=small,4–5points=moderate,and6–7points=large
[38].
2.6.StatisticalAnalysis
Datawereanalyzedusinganintention-to-treat(ITT)approach,arecommendedstrat-
egytominimizebiasbyanalyzingallparticipantsaccordingtotheiroriginalassignment
[39].Thisanalysiswasconductedbyaninvestigatorwhowasblindedtogroupallocation.
Themultipleimputationtechniquewasappliedusingthepredictivemeanmatching
methodtohandlemissingdataandensuretheinclusionofallparticipantsintheanalysis
[40].Subsequently,dataweredescribedusingnormaldistributionstatistics,verifiedusing
theShapiro–Wilktest,whichissensitivetodeviationsinsmallsamplesizes,allowingcon-
firmationofwhetherparametrictestswereappropriate[41].
HomoscedasticitybetweengroupswasverifiedusingLevene’stest;thus,for
WOMAC,atwo-wayrepeatedmeasuresanalysisofvariance(ANOVA)wasperformed,
followedbyTukey’sposthoctesttoanalyzeintragroupdifferences(post-tests1,2,3,and
follow-upversuspre-test)andintergroupdifferencesateachtimepoint.ForGRoC,an
independentsampleStudent’st-testwasapplied.TheESwascalculatedusingCohen’sd,
Figure 2. Participant using AVG (A). Image of the visual feedback from the game (B).
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 strat-
egy to minimize bias by analyzing all participants according to their original assign-
ment [
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].
Appl. Sci. 2025,15, 93 7 of 17
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 (
∆
) 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
∆
score
≥ −
MCID, NRs if
∆
score <
−
MCID and < +MCID, and ARs if
∆
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 charac-
teristics (Table 1) and functional disability (Table 2). 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 moder-
ate 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
).
Appl. Sci. 2025,15, 93 8 of 17
Table 2. Functional disability comparison between study groups according to WOMAC question-
naire 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 s7.8 ±
3.6 s7.8 ±
3.3 s8.1 ±
3.0 s9.1 ±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 n3.1 ±
1.4 s2.7 ±
1.5 m3.1 ±
1.3 s3.3 ±1.8 2.7 ±
0.9 s2.7 ±
1.5 s2.2 ±
1.6 *,m 2.5 ±
1.3 m
W-function
31.7
±
12.3
29.5 ±
11.5 n27.4 ±
11.8 s23.6 ±
8.5 *,m 27.2 ±
9.3 s30.1 ±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 s38.4 ±
15.9 s34.2 ±
11.6 *,m 38.5 ±
12.9 s42.5 ±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.
Figure 3presents the
±
MCID thresholds for WOMAC scores, along with bars repre-
senting each participant’s
∆
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
shows the frequency distribution of these categories in the study 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.
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).
Appl. Sci. 2025,15, 93 9 of 17
Appl.Sci.2024,14,xFORPEERREVIEW9of18
Tab le2.FunctionaldisabilitycomparisonbetweenstudygroupsaccordingtoWOMACquestion-
nairescores.
ControlGroup(n=30)ExperimentalGroup(n=30)
Pre-TestPost-Test1Post-Test2Post-Test3Follow-UpPre-TestPost-Test1Post-Test2Post-Test3Follow-Up
W-pain9.2±3.38.3±2.8
s
7.8±3.6
s
7.8±3.3
s
8.1±3.0
s
9.1±2.66.2±2.7*
,l
6.0±3.2*
,l
4.5±2.6*
,l†
6.1±3.2*
,l
W-stiffness3.4±1.03.2±1.4
n
3.1±1.4
s
2.7±1.5
m
3.1±1.3
s
3.3±1.82.7±0.9
s
2.7±1.5
s
2.2±1.6*
,m
2.5±1.3
m
W-function31.7±12.329.5±11.5
n
27.4±11.8
s
23.6±8.5
*
,m
27.2±9.3
s
30.1±11.723.6±9.7*
,m
23.1±10.9
*
,m
16.8±11.1
*
,l
20.8±12.0*
,l
W-total44.4±15.941.0±15.1
s
38.4±15.9
s
34.2±11.6
*
,m
38.5±12.9
s
42.5±14.432.6±12.0*
,m
31.9±14.1
*
,m
23.6±14.4
*
,l
29.5±15.2*
,l
Dataexpressedasmeans±standarddeviations;W,WOMAC.Cohen’sd(effectsize):n,negligible;
s,small;m,moderate;l,large.*Intragroupdifferencep<0.05;
†
intergroupdifferencep<0.05.
Figure3.MCIDthresholdsforWOMACscores(upperandlowerdashedlines)andchange(Δ)in
eachparticipant’sscores(verticalbars)forclassificationasresponders,non-responders,andadverse
responders.SubfiguresA,B,andCrepresentthepain,stiffness,andfunctionsubscalesofthe
WOMAC,respectively,whileSubfigureDillustratesthetotalWOMACscore.CG,controlgroup;
EG,experimentalgroup.
Tab le3.Frequencyofresponders,non-responders,andadverserespondersinthestudygroups.
ControlGroup(n=30)ExperimentalGroup(n=30)
RsNRsARsRsNRsARs
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,adversere-
sponders;
†
Rs,intergroupdifferencep<0.05;
‡
NRs,intergroupdifferencep<0.05.
Figure 3. MCID thresholds for WOMAC scores (upper and lower dashed lines) and change (
∆
) in
each participant’s scores (vertical bars) for classification as responders, non-responders, and adverse
responders. Subfigures A, B, and C represent the pain, stiffness, and function subscales of the
WOMAC, respectively, while Subfigure D illustrates the total WOMAC score. CG, control group; EG,
experimental group.
Appl.Sci.2024,14,xFORPEERREVIEW10of18
Basedonthe25th,50th,and75thpercentilevaluesofthebaselineWOMAC-total
score,thequartilerangeswereasfollows:quartile1(Q1):0to33points;quartile2(Q2):
34to43points;quartile3(Q3):44to55points;andquartile4(Q4):≥56points.Attheend
oftheintervention,intheCG,50%ofparticipantswerestratifiedwithinQ1,20%inQ2,
20%inQ3,and10%inQ4.Accordingtointerquartileflow(pre-testtopost-test3),40%of
participantsremainedintheirinitialquartile,50%movedtoabeerquartile,and10%
shiftedtoaworsequartile.IntheEG,76.6%ofparticipantswerestratifiedwithinQ1,
16.6%inQ2,3.3%inQ3,and3.3%inQ4.Accordingtointerquartileflow,23.3%ofpartic-
ipantsremainedintheirinitialquartile,70%movedtoabeerquartile,and6.6%shifted
toaworsequartile(Figure4).
Figure4.Flowofparticipantsaccordingtochangeintheirfunctionaldisabilitystratification(total
WOMACscore)betweenquartiles.CG,controlgroup;EG,experimentalgroup.
4.Discussion
Themainresultsofthisstudy,whichevaluatedtheeffectsofacomplementaryinter-
ventioncombiningAVGsandCPTonperceivedfunctionaldisabilityinolderadultswith
kneeorhipOA,werethefollowing.(i)TheEGshowedprogressiveimprovementatall
timepoints,achievingmoderatetolargeimprovementsinallWOMACscoresbytheend
oftheintervention,whiletheCGonlyshowedsignificantchangesattheend,withmod-
erateimprovementsinWOMAC-functionandtotalscores.(ii)TheEGshowedgreater
improvementsinWOMAC-painandtheGRoCscalecomparedtotheCG.(iii)Atfollow-
up,theEGmaintainedmostoftheimprovements,whereastheCGtendedtoregress.(iv)
TheEGhadahigherproportionofRs,particularlyinWOMAC-pain,withalowpropor-
tionofARs,whiletheCGhadapredominanceofNRs,withahigherproportionofARs
comparedtotheEG.(v)IntheEG,70%ofparticipantsimprovedtheirquartileposition,
23.3%remainedintheirinitialquartile,andonly6.6%worsened.Incontrast,50%ofthe
CGimprovedtheirquartile,40%remained,and10%worsened.Theseresultssuggestthat
complementingCPTwithAVGsoptimizesgainsinself-perceivedfunctionality,enhanc-
ingtherehabilitationprocess.Additionally,noadverseeventsrelatedtoAVGswerere-
ported,demonstratingthesafetyoftheintervention.
ImprovingWOMACscoresisrelevantbecauseitincreasestheperceivedabilityto
performdailyactivitieswithlesspainandjointstiffness[36],whichcanpositivelyinflu-
encequalityoflifebyenhancingfunctionalstatus[48].Additionally,greatermobilityis
keytopreventingfalls,preservingcognitivefunction,reducingtheimpactofsedentary
behavior,andpromotingemotionalwell-being.Thesefactorsalsohelpreducecostsand
alleviatetheburdenonhealthcaresystems[49].
PreviousstudiessuggestthatusingAVGsasacomplementarytherapyinpatients
withOAleadstosignificantimprovementsinperceivedfunctionaldisability,whichis
consistentwiththepresentresearch.InthestudiesbyElshazlyetal.(2016)andMeteand
Sari(2022),theuseofsystemsliketheXbox360andMarVAJED,respectively,combined
withconventionalexercise,wasmoreeffectivethanconventionalexercisealonein
Figure 4. Flow of participants according to change in their functional disability stratification (total
WOMAC score) between quartiles. CG, control group; EG, experimental group.
4. Discussion
The main results of this study, which evaluated the effects of a complementary inter-
vention 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 improve-
ments 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,
Appl. Sci. 2025,15, 93 10 of 17
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 multicom-
ponent exercise is key to managing the cardinal symptoms of OA [
55
]. It also improves
functional performance, cardiorespiratory capacity, postural balance, fall risk, propriocep-
tion, 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 degra-
dation (decreased MMP-13, increased type II collagen), inhibiting apoptosis (decreased
caspase-3), modulating the inflammatory response (reduced IL-1
β
, IL-6, and TNF-
α
), in-
ducing 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.
Appl. Sci. 2025,15, 93 11 of 17
Recently, the importance of cognitive functioning for the ability to perform daily activ-
ities 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
]. Simultane-
ous 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 neu-
roplastic 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 under-
standing of data variability and effect size, providing clinically relevant information even
Appl. Sci. 2025,15, 93 12 of 17
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 replace-
ments 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
–
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
Appl. Sci. 2025,15, 93 13 of 17
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 over-
look 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, outper-
forming 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. Quar-
tile 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 ef-
fects 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.
Supplementary Materials: The following supporting information can be downloaded at https:
//www.mdpi.com/article/10.3390/app15010093/s1, Table S1: Description of conventional exercises
used in the protocol; Table S2: Description of the AVGs used in the protocol.
Author Contributions: Conceptualization, F.G.-R., C.M. and C.C.-P.; methodology, F.G.-R., A.S.-M.
and C.C.-P.; software, A.S.-M.; validation, F.G.-R., C.M., J.F.-C., C.A., B.A.T., J.K.M.-G., A.S.-M. and
C.C.-P.; formal analysis, F.G.-R., A.S.-M. and C.C.-P.; investigation, F.G.-R., C.M., J.F.-C., C.A., B.A.T.,
J.K.M.-G., A.S.-M. and C.C.-P.; resources, F.G.-R., C.M., J.F.-C., C.A., B.A.T., J.K.M.-G., A.S.-M. and
C.C.-P.; data curation, F.G.-R.; writing—original draft preparation, F.G.-R., B.A.T., J.K.M.-G. and
C.C.-P.; writing—review and editing, F.G.-R., C.M., J.F.-C., C.A., B.A.T., J.K.M.-G., A.S.-M. and C.C.-P.;
visualization, F.G.-R. and C.C.-P.; supervision, F.G.-R. and C.C.-P.; project administration, F.G.-R. and
C.M.; funding acquisition F.G.-R., C.M., J.F.-C., C.A. and C.C.-P. All authors have read and agreed to
the published version of the manuscript.
Appl. Sci. 2025,15, 93 14 of 17
Funding: This research was funded by the Fondo de Investigación y Desarrollo en Salud (FONIS)
2022, Subdirección de investigación aplicada, FONDEF, ANID, Chile, grant number SA22I0092.
Institutional Review Board Statement: The study was conducted in accordance with the Declaration
of Helsinki and approved by the Scientific Ethics Committee of the Concepción Health Service (No.
22-12-59, date: 21 December 2022).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: All relevant data are presented in the manuscript. The datasets
generated and/or analyzed during the current study are available from the corresponding author
upon reasonable request.
Acknowledgments: The authors express their gratitude to the professionals of the rehabilitation unit
of CESFAM Lorenzo Arenas, of the Health Administration Directorate of Concepción, Chile.
Conflicts of Interest: The authors declare no conflicts of interest. The funders had no role in the design
of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or
in the decision to publish the results.
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