Knee Osteoarthritis, Motor Control, Risk of Falls and Virtual Reality

NCT ID: NCT06362785

Last Updated: 2025-03-17

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

110 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-05-01

Study Completion Date

2026-06-01

Brief Summary

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The goal of this clinical trial is to learn about knee osteoarthritis, functionality, and risk of falls in community-dwelling adults aged 60 years and older. The main questions it aims to answer are:

* What are the characteristics of a community-dwelling population over 60 years and older in terms of knee osteoarthritis, functionality, and risk of falls?
* Does an intervention with virtual reality lower knee osteoarthritis symptoms, raise functionality and prevent falls in community-dwelling adults aged 60 years and older, compared to a control group receiving conventional physiotherapy treatment based on therapeutic exercise?

Participants will:

* Answer questionnaires.
* Perform physical laboratory tests through a camera-based motion capture system.
* Execute task-based exercises in a virtual environment through virtual reality.

Researchers will compare community-dwelling adults aged 60 years and older who execute task based exercises in a virtual environment through virtual reality and community-dwelling adults aged 60 years and older receiving conventional physiotherapy treatment based on therapeutic exercise to see if virtual reality improves knee osteoarthritis symptoms, functionality, and lowers fall risk.

Detailed Description

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Background

Knee osteoarthritis (OA) is prevalent among older adults, affecting a substantial proportion of this population and being linked to various functional impairments such as joint stiffness, reduced mobility, and chronic pain. More specifically, knee OA is one of the most disabling musculoskeletal conditions worldwide, leading to significant healthcare costs and economic burdens. Several studies have demonstrated a strong association between knee OA and falls in older adults. In particular, it has been observed that knee OA is a significant predictor of multiple falls and is closely related to deficits in balance and gait stability.

To properly understand the close relationship between knee OA and falls, it is crucial to consider motor control dysfunctions associated with joint pain and mechanical alterations, as they are often the primary triggers of falls. Research in this field highlights the importance of directing new studies toward functional tasks, as they represent the essence of motor control. Therefore, the observation and analysis of functional tasks are crucial for examining the motor control of older adults, being 3D motion capture systems the gold standard for the measurement and analysis of human movement.

On the other hand, new technologies such as immersive virtual reality (VR) are gaining recognition and popularity as treatment modalities. This is because they allow users to interact with environments and situations that simulate real life, offering activities tailored to their needs while avoiding the potential risks of the real world. Additionally, it provides an opportunity to repeat exercises, improve performance, and achieve effective learning.

Objectives Several objectives are outlined, as a comprehensive approach involving two different phases will be carried out.

* Phase 1 (Cross-Sectional Study) Main objective: to describe the population aged 60 and older living in the community in terms of knee osteoarthritis symptoms, functionality, and fall risk.
* Phase 2 (Experimental Study) Main objective: to assess the efficacy of a virtual reality intervention in a community-dwelling population aged 60 and above in terms of knee osteoarthritis symptoms improvement, functionality improvement, and fall risk reduction.

Methods

* Setting, locations and relevant dates: testing is going to be conducted in the Research Center for Information and Communication Technologies (CITIC) (A Coruña, Spain) and Senior University Center of the University of A Coruña (A Coruña, Spain).
* Data collection is planned for the months of May 2024 to May 2025.
* Participants: the recruitment of participants will be carried out through the dissemination of the study via informative posters distributed in the University of A Coruña, including the Senior University; in the network of civic centers in the city of A Coruña; as well as electronically through the researchers' social media networks (Twitter, Facebook, and Instagram). The participant information process, as well as the request for informed consent, will be conducted in the CITIC, after having answered the pre-selection questionnaires.
* Variables: see "outcomes measures".
* Study size: the sample size is estimated using the G-power program, indicating that the minimum number of participants needed to detect medium effect sizes, with a type I error probability of 0.05 and a power of 0.95, with an effect size of 0.7 and considering the analysis through the t-test: the difference between two independent means would be a total of 110 participants.
* Statistical analysis: a descriptive analysis will be performed to characterize the subjects in detail. Qualitative variables will be presented as absolute figures with their respective percentages, and quantitative variables as measures of central tendency (mean and median) and dispersion (standard deviation, minimum, and maximum values). The Kolmogorov-Smirnov test will be used to assess the normality of data distribution.

To explore significant differences between groups, a bivariate statistical analysis will be conducted. The Student's T-test for independent samples will be used for comparing means if the variables under consideration are normal; otherwise, the Mann-Whitney U test will be employed for non-normal variables. The chi-square statistic (X2) with a 95% confidence interval will be applied for the association of qualitative variables. The correlation between quantitative variables will be assessed using the Pearson or Spearman correlation coefficient. A significance level of p \< 0.05 will be considered. Data processing and analysis will be carried out using the statistical package SPSS, version 24.0 for Windows (Armonk, NY: IBM Corp.).

Conditions

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Knee Osteoarthritis Task Performance and Analysis Accidental Falls Virtual Reality

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

TREATMENT

Blinding Strategy

SINGLE

Investigators

Study Groups

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virtual reality

The intervention group will perform immersive virtual reality sessions with interactive activities involving functional movements of the spine and limb region in a virtual environment using Meta Quest 3 goggles.

Group Type EXPERIMENTAL

Virtual Reality

Intervention Type DEVICE

The intervention group will engage in immersive virtual reality sessions with interactive activities involving functional movements of the spine and limbs in a virtual environment using Meta Quest 3 goggles. The intervention will last for 6 weeks, comprising a total of 12 sessions, with a maximum duration of 30 minutes of virtual reality and 15 minutes of rest (45 minutes in total per session).

Control

The control group will receive conventional physiotherapy treatment based on therapeutic exercise.

Group Type ACTIVE_COMPARATOR

Therapeutic exercise

Intervention Type BEHAVIORAL

The control group will receive conventional therapeutic exercise treatment following the recommendations of the Osteoarthritis Research Society International (OARSI), similar to the exercises performed with VR.

Interventions

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Virtual Reality

The intervention group will engage in immersive virtual reality sessions with interactive activities involving functional movements of the spine and limbs in a virtual environment using Meta Quest 3 goggles. The intervention will last for 6 weeks, comprising a total of 12 sessions, with a maximum duration of 30 minutes of virtual reality and 15 minutes of rest (45 minutes in total per session).

Intervention Type DEVICE

Therapeutic exercise

The control group will receive conventional therapeutic exercise treatment following the recommendations of the Osteoarthritis Research Society International (OARSI), similar to the exercises performed with VR.

Intervention Type BEHAVIORAL

Eligibility Criteria

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Inclusion Criteria

* Age over 60 years.
* Non-institutionalized individuals.
* Subjects who wish and consent through informed consent to participate in the study.
* Have the ability to walk independently (with or without assistive devices).
* Diagnosis of primary knee osteoarthritis according to the clinical and radiological criteria of the American College of Rheumatology.
* Specifically, for phase 1, subjects without a knee osteoarthritis diagnosis will also be included.

Exclusion Criteria

* History of significant previous traumas or surgeries to the spine, pelvis, or legs in the last 12 months.
* Self-reported presence of dizziness, seizures, or epilepsy, aiming to prevent potential exacerbation of symptoms with VR.
* Vestibular disorders (balance).
* Neurological diseases, cardiovascular, or respiratory disorders affecting activity; as well as inflammatory or autoimmune diseases affecting the lower limb joints, and other forms of secondary osteoarthritis.
* Diagnosis of a terminal illness or a health condition that prevents attendance.
* To have a medical contraindication for exercise.
* Body Mass Index (BMI) ≥ 40
Minimum Eligible Age

60 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Centre for Information and Communications Technology Research (CITIC)

UNKNOWN

Sponsor Role collaborator

Faculty of Physiotherapy

UNKNOWN

Sponsor Role collaborator

Universidade da Coruña

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Beatriz Rodríguez-Romero, PhD

Role: STUDY_DIRECTOR

Universidade da Coruña

Central Contacts

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Beatriz Rodríguez-Romero, PhD

Role: CONTACT

00034 981167000 ext. 5841

Silvia Rey Abuín

Role: CONTACT

00034 981167000 ext. 1153

References

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Altenburger P, Ambike SS, Haddad JM. Integrating Motor Variability Evaluation Into Movement System Assessment. Phys Ther. 2023 Oct 3;103(10):pzad075. doi: 10.1093/ptj/pzad075.

Reference Type BACKGROUND
PMID: 37364059 (View on PubMed)

Quinn L, Riley N, Tyrell CM, Judd DL, Gill-Body KM, Hedman LD, Packel A, Brown DA, Nabar N, Scheets P. A Framework for Movement Analysis of Tasks: Recommendations From the Academy of Neurologic Physical Therapy's Movement System Task Force. Phys Ther. 2021 Sep 1;101(9):pzab154. doi: 10.1093/ptj/pzab154.

Reference Type BACKGROUND
PMID: 34160044 (View on PubMed)

Benham S, Kang M, Grampurohit N. Immersive Virtual Reality for the Management of Pain in Community-Dwelling Older Adults. OTJR (Thorofare N J). 2019 Apr;39(2):90-96. doi: 10.1177/1539449218817291. Epub 2018 Dec 29.

Reference Type BACKGROUND
PMID: 30595096 (View on PubMed)

Bannuru RR, Osani MC, Vaysbrot EE, Arden NK, Bennell K, Bierma-Zeinstra SMA, Kraus VB, Lohmander LS, Abbott JH, Bhandari M, Blanco FJ, Espinosa R, Haugen IK, Lin J, Mandl LA, Moilanen E, Nakamura N, Snyder-Mackler L, Trojian T, Underwood M, McAlindon TE. OARSI guidelines for the non-surgical management of knee, hip, and polyarticular osteoarthritis. Osteoarthritis Cartilage. 2019 Nov;27(11):1578-1589. doi: 10.1016/j.joca.2019.06.011. Epub 2019 Jul 3.

Reference Type BACKGROUND
PMID: 31278997 (View on PubMed)

Stratford PW, Kennedy DM, Woodhouse LJ. Performance measures provide assessments of pain and function in people with advanced osteoarthritis of the hip or knee. Phys Ther. 2006 Nov;86(11):1489-96. doi: 10.2522/ptj.20060002.

Reference Type BACKGROUND
PMID: 17079748 (View on PubMed)

Tunas-Maceiras I, Pereira J, Pertega Diaz S, Lopez Campos JA, Rodriguez-Romero B. Virtual reality versus conventional exercise for knee osteoarthritis: protocol for a randomised controlled trial on functionality and fall risk. BMJ Open. 2025 Oct 20;15(10):e102776. doi: 10.1136/bmjopen-2025-102776.

Reference Type DERIVED
PMID: 41120141 (View on PubMed)

Other Identifiers

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Virtual Reality-Seniors

Identifier Type: -

Identifier Source: org_study_id

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