ANZCTR - Registration

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Trial registered on ANZCTR

Registration number

ACTRN12626001299392

Ethics application status

Approved

Date submitted

2/10/2026

Date registered

28/10/2026

Date last updated

28/10/2026

Date data sharing statement initially provided

28/10/2026

Type of registration

Prospectively registered

Titles & IDs

Public title

The effect of virtual reality induced optic flow manipulations during cycling on exercise engagement, experiences, and clinical outcomes in people with knee osteoarthritis

Scientific title

The effect of virtual reality induced optic flow manipulations during cycling on exercise engagement, experiences, and clinical outcomes in people with knee osteoarthritis

Additional trial identifiers [1]

Nil known

Universal Trial Number (UTN)

U1111-1343-8528

Trial acronym

Related trial records

The record is an extension of previous work (ACTRN12624000122550) – exploring the effects of two types of optic flow in VR cycling (increased vs decreased) on clinical outcomes.

Health condition

Health condition(s) studied:

Knee osteoarthritis

Condition category

Condition code

Musculoskeletal

Osteoarthritis

Physical Medicine / Rehabilitation

Physiotherapy

Physical Medicine / Rehabilitation

Occupational therapy

Intervention/exposure

Study type

Interventional

Description of the intervention or exposure

Participants randomised to this group will receive a 6-week virtual reality (VR)-enhanced cycling intervention, involving twice-weekly 30-minute sessions (n = 12 sessions in total), delivered one-on-one by an allied health professional at the Clinical Trials Centre, Adelaide University. The intervention aims to enhance exercise engagement and enjoyment by manipulating visual feedback of cycling speed (optic flow) within a virtual environment.

During each session, participants will ride a stationary bike mounted on a Wahoo KICKR Smart Trainer while wearing a head-mounted display (Oculus Quest 2). The smart trainer continuously records cycling performance (including work [joules], cadence [revolutions per minute], and power output [watts]), while the head-mounted display provides a first-person perspective of cycling through a virtual environment comprising a road surrounded by natural or urban landscapes. Participants will cycle at a self-selected speed and resistance for as long as they feel comfortable, up to a maximum of 30 minutes. Resistance may be adjusted by either the participant or supervising clinician as needed to ensure comfort and safety while maintaining consistency with the allocated or selected VR cycling program. Cycling duration (actual and estimated), cycling performance, affective valence, knee pain intensity, perceived exertion, cybersickness symptoms, adverse events, and reasons for stopping or non-completion will be recorded.

Participants in this group will receive an ‘increased optic flow’ VR program in which the visual speed of the virtual environment is manipulated to appear 20% faster than their actual cycling speed (true physical effort). This enhanced visual feedback is intended to increase exercise engagement and improve the cycling experience.

If participants experience discomfort or cybersickness during the intervention, safety and tolerability will be prioritised. Participants will be allowed to take a rest, and the optic flow speed may be slightly adjusted while remaining within the allocated condition category (between 5% and 20% faster). Any changes to the settings will be recorded.

Intervention code [1]

Rehabilitation

Intervention code [2]

Treatment: Devices

Intervention code [3]

Treatment: Other

Description of the comparator or control

Participants randomised to this group will receive a 6-week virtual reality (VR)-enhanced cycling comparator intervention, involving twice-weekly 30-minute sessions (n = 12 sessions in total), delivered one-on-one by an allied health professional at the Clinical Trials Centre, Adelaide University. The comparator intervention will use the opposite optic flow setting to the intervention group (i.e., decreased optic flow).

During each session, participants will ride a stationary bike mounted on a Wahoo KICKR Smart Trainer while wearing a head-mounted display (Oculus Quest 2). The smart trainer continuously records cycling performance (including work [joules], cadence [revolutions per minute], and power output [watts]), while the head-mounted display provides a first-person perspective of cycling through a virtual environment comprising a road surrounded by natural or urban landscapes. Participants will cycle at a self-selected speed and resistance for as long as they feel comfortable, up to a maximum of 30 minutes. Resistance may be adjusted by either the participant or supervising clinician as needed to ensure comfort and safety while maintaining consistency with the allocated VR cycling program. Cycling duration (actual and estimated), cycling performance, affective valence, knee pain intensity, perceived exertion, cybersickness symptoms, adverse events, and reasons for stopping or non-completion will be recorded.

Participants in this group will receive a ‘decreased optic flow’ VR program in which the visual speed of the virtual environment is manipulated to appear 20% slower than their actual cycling speed (true physical effort). Decreased optic flow is common in many commercial cycling programs. The decreased optic flow manipulation provides an active VR cycling comparator while controlling for the use of VR, manipulation of visual feedback, cycling exercise, session duration, supervision, and exposure to the virtual environment.

If participants experience discomfort or cybersickness during the intervention, safety and tolerability will be prioritised. Participants will be allowed to take a rest, and the optic flow speed may be slightly adjusted while remaining within the allocated condition category (between 5% and 20% slower). Any changes to the settings will be recorded.

Control group

Active

Outcomes

Primary outcome [1]

Exercise engagement - Total work

Timepoint [1]

Each intervention session (Sessions 1–12; all sessions are primary assessment timepoints)

Primary outcome [2]

Exercise experiences - Affective valence

Timepoint [2]

During each intervention session (Sessions 1–12), affective valence will be assessed every 5 minutes during cycling and at the end of cycling. The mean of all measurements within each session will be used as the session-level outcome. All 12 sessions constitute the primary assessment period.

Secondary outcome [1]

Knee pain

Timepoint [1]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [2]

Physical function

Timepoint [2]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [3]

Rating of perceived exertion (RPE)

Timepoint [3]

During each intervention session (Sessions 1–12), Rating of perceived exertion (RPE) will be assessed every 5 minutes during cycling and at the end of cycling.

Secondary outcome [4]

Knee pain intensity during cycling

Timepoint [4]

During each intervention session (Sessions 1–12), Knee pain intensity will be assessed every 5 minutes during cycling and at the end of cycling.

Secondary outcome [5]

Motion Sickness

Timepoint [5]

During each intervention session (Sessions 1–12), Motion sickness will be assessed every 5 minutes during cycling and at the end of cycling.

Secondary outcome [6]

Perceived exercise enjoyment

Timepoint [6]

Each intervention session (Sessions 1-12) – one overall rating at the end of cycling

Secondary outcome [7]

Exercise Engagement – Average power (watts)

Timepoint [7]

Each intervention session (Sessions 1-12)

Secondary outcome [8]

Exercise Engagement – Maximum power (watts)

Timepoint [8]

Each intervention session (Sessions 1-12)

Secondary outcome [9]

Perceived cycling duration

Timepoint [9]

Each intervention session (Sessions 1-12)

Secondary outcome [10]

Exercise engagement - Actual cycling duration

Timepoint [10]

Each intervention session (Sessions 1-12)

Secondary outcome [11]

Overall exercise enjoyment

Timepoint [11]

post-intervention (Session 1 and Session 12)

Secondary outcome [12]

Physical activity over the past week

Timepoint [12]

Baseline, at session 2,4,6,8,10, post-intervention (6 weeks), and at 1-month follow-up (10 weeks)

Secondary outcome [13]

Pain interference over the past 24 hours

Timepoint [13]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [14]

Knee pain intensity over the past 48 hours

Timepoint [14]

Baseline; post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [15]

Pain self-efficacy

Timepoint [15]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [16]

Health related quality of life

Timepoint [16]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [17]

Pain-related fear of movement

Timepoint [17]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [18]

Bodily perception of the knee

Timepoint [18]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [19]

Knee osteoarthritis conceptualisation

Timepoint [19]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [20]

Pain catastrophizing

Timepoint [20]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [21]

Psychological Distress

Timepoint [21]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [22]

Fatigue Level

Timepoint [22]

During each intervention session (Sessions 1–12: immediately before and after cycling).

Secondary outcome [23]

Positive Affect

Timepoint [23]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [24]

Negative Affect

Timepoint [24]

Baseline, post-intervention (6 weeks), 1 month follow-up (10 weeks)

Secondary outcome [25]

Treatment Expectation - Expected Treatment Effectiveness

Timepoint [25]

post-intervention (session 1)

Secondary outcome [26]

Treatment Expectation – How Logicalness

Timepoint [26]

post-intervention (session 1)

Secondary outcome [27]

Treatment Expectation - Usefulness

Timepoint [27]

post-intervention (session 1)

Secondary outcome [28]

Treatment Expectation – Perceived Successful

Timepoint [28]

post-intervention (session 1)

Secondary outcome [29]

Treatment Expectation - Recommendation Confidence

Timepoint [29]

post-intervention (session 1)

Eligibility

Key inclusion criteria

i) Aged greater than or equal to 45 years
ii) Average knee pain intensity of at least 4/10 (overall and/or while walking) over past week using a 0-10 Numerical Rating Scale, where “0 = no pain at all” and “10 = worst pain possible”
iii) Painful knee osteoarthritis at least 6 months duration that meets the National Institute for Health Care Excellence diagnostic criteria for symptomatic knee osteoarthritis

Minimum age

45 Years

Maximum age

No limit

Sex

Both males and females

Healthy volunteers

Key exclusion criteria

i) Conditions that prevent safe participation in physical activity as listed in the American College of Sports Medicine guidelines (e.g., cardiac or lung disease)
ii) Pain in other body areas that currently limits cycling ability (e.g., back pain, foot pain, hip pain)
iii) Neurological disorders affecting lower limb movement (e.g., multiple sclerosis, stroke)
iv) Alzheimer’s disease or dementia (Or any condition that impacts decision-making/memory)
v) Inflammatory arthritis (including rheumatoid arthritis)
vi) Fibromyalgia
vii) Previous knee replacement (on painful knee) or planned knee replacement/surgery (next 6 months) or recent knee replacement on the non- or less-painful knee
xi) Current exercising 30 mins or more per day on 5 or more days per week (150 minutes/week; assessed using the Active Australia Survey).

Study design

Purpose of the study

Treatment

Allocation to intervention

Randomised controlled trial

Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)

Allocation will be concealed using central automated allocation, with security in place to ensure data cannot be accessed/influenced. It will be stored within an electronic system (REDCap) that will be password-protected (as well as via a hardcopy of the raw randomisation schedule in case the electronic system fails, which will be stored in a secure location). The person who determines if a participant is eligible for inclusion in the trial will be unaware, when this decision is made, to which group the participant will be allocated.

Methods used to generate the sequence in which subjects will be randomised (sequence generation)

An independent statistician will create the randomisation schedule (using computer generated random numbers).

Masking / blinding

Blinded (masking used)

Who is / are masked / blinded?

The people receiving the treatment/s

The people assessing the outcomes

Intervention assignment

Parallel

Other design features

Phase

Not Applicable

Type of endpoint/s

Safety/efficacy

Statistical methods / analysis

The primary outcomes of Exercise Engagement (Total Work) and Affective Valence will be assessed at each intervention session (Sessions 1-12) while participants undertake the VR cycling intervention. These outcomes will be analysed using a linear mixed-effects model with group, time, and the group-by-time interaction as fixed effects, and participant as a random effect. This approach will allow us to examine both the overall change over time and whether the pattern of change differs between groups. The primary comparison will be the between-group difference in change from Session 1 to Session 12 (6 weeks), corresponding to the end of treatment intervention. Additional model-based estimates across the repeated measurement points will be used to describe the trajectory of change over the intervention period.

A sample size calculation was conducted using G*Power for a repeated-measures within-between interaction, with two groups and 12 measurement time points. Assuming a small-to-moderate effect size (f of 0.15, based on past work assessing these outcomes), a significance level (alpha) of 0.05, a target statistical power of 0.80, a correlation among repeated measures of 0.50, and a nonsphericity correction of 1, the required total sample size was estimated to be 34 participants (17 per group). To allow for attrition and missing data, we aim to recruit approximately 40 participants.

Secondary outcomes will be analysed using appropriate linear mixed-effects models. For questionnaire-based outcomes, models will include group, time (baseline, post-intervention, 1 month follow-up), and the group-by-time interaction as fixed effects. For session-level outcomes, such as perceived exertion and cycling duration, models will include group, session number (1-12), and the group-by-session interaction as fixed effects. Participant will be included as a random effect in both.

Analyses will follow the intention-to-treat principle, with participants analysed according to their randomised group allocation. Reasons for withdrawal, non-completion, and missing data will be recorded. Sensitivity analyses may be conducted if there is substantial (greater than 10%) missing data.

Recruitment

Recruitment status

Not yet recruiting

Date of first participant enrolment

Anticipated

9/11/2026

Actual

Date of last participant enrolment

Anticipated

4/06/2027

Actual

Date of last data collection

Anticipated

16/07/2027

Actual

Sample size

Target

Accrual to date

Final

Recruitment in Australia

Recruitment state(s)

Funding & Sponsors

Funding source category [1]

Government body

Name [1]

Japan Society for the Promotion of Science (JSPS)

Address [1]

Country [1]

Japan

Primary sponsor type

University

Name

Adelaide University

Address

Country

Australia

Secondary sponsor category [1]

None

Name [1]

Address [1]

Country [1]

Ethics approval

Ethics application status

Approved

Ethics committee name [1]

University of Adelaide Human Research Ethics Committee

Ethics committee address [1]

https://www.adelaide.edu.au/research-services/ethics-compliance-integrity/human-research-ethics/human-research-ethics-committee

Ethics committee country [1]

Australia

Date submitted for ethics approval [1]

08/05/2026

Approval date [1]

23/09/2026

Ethics approval number [1]

HREC/HREC-2/2026/7178 (v4)

Summary

Brief summary

Despite clinical guidelines recommending exercise for the management of knee osteoarthritis (OA), many Australians with painful knee OA are physically inactive. Pain during exercise can reduce initial and sustained exercise engagement, making it difficult for people with knee OA to maintain regular exercise. Although exercise can improve pain, function, and long-term health outcomes, new strategies are needed to improve exercise uptake and engagement in people with arthritis. Virtual reality (VR) technology holds promise as a strategy to reduce exercise barriers and increase exercise engagement and experiences, and thus, have greater effects on clinical outcomes including knee pain and physical function.

This study will use a parallel-group randomised trial design. Participants will be randomised to one of two active treatment groups: VR-enhanced cycling with increased optic flow or VR-enhanced cycling with decreased optic flow. Both groups will receive two in-person, one-on-one treatment sessions per week over six weeks (total of twelve sessions). The sessions will be delivered by an allied health professional (physiotherapist, occupational therapist).

The primary outcomes will be exercise engagement (total work during cycling) and experiences (affective valance via Feeling Scale). Secondary outcomes will include knee pain (WOMAC pain subscale), physical function (WOMAC function subscale), knee pain intensity during cycling (101-point NRS), perceived exertion during cycling (Borg scale), exercise engagement (average/maximal power, cycling duration), exercise enjoyment (101-point NRS, Physical Activity Enjoyment Scale), physical activity (The Active Australia survey), pain interference (BPI-PI), and motion sickness symptoms during cycling (FMS), pain self-efficacy (PSEQ), health related quality of life (EQ-5D), pain-related fear of movement (Brief FoM), bodily perception of the knee (FreKAQ), knee osteoarthritis conceptualization (OACS), pain catastrophizing (PCS), positive and negative affect (PANAS-SF), psychological distress (PHQ-4), fatigue level (ROF) and treatment expectation.

Trial website

Trial related presentations / publications

Public notes

Cycling preference test
At baseline (at least 2 days prior to intervention commencement), participants will undertake a cycling preference test. During this test, participants will undertake four cycling conditions (each lasting 4 minutes) in a randomised order: i) increased optic flow (20% faster); ii) decreased optic flow (20% slower); iii) no change in optic flow; and iv) no-VR use while cycling. During each condition, perceived exertion (Borg scale), affective valence (Feeling scale), knee pain intensity (101-point NRS), and fast motion sickness (FMS) will be assessed every 2 minutes. Fatigue level (ROF) will also be assessed at the beginning of each condition, and after the 5-minute rest interval that will occur between conditions. After completing all four conditions, participants will be asked to identify which condition they preferred the most and which condition they preferred the least. If participants experience discomfort or cybersickness during the cycling conditions, the condition will be discontinued.

Preference-Allocation Congruence
Participant preference will not influence the randomisation schedule or treatment allocation. Participants will be randomised independently of the results of the cycling preference test. Preference data will only be used after randomisation to assess Preference–Allocation Congruence and for the exploratory analyses described below.

People often have individualised preferences for the optic flow of the virtual environment while cycling and being allocated to the VR cycling intervention that is congruent with their preferred optic flow may influence exercise enjoyment and engagement. While most people prefer increased optic flow, others may prefer decreased optic flow. Capturing preferences surrounding optic flow allows us to determine whether the condition a participant is randomised to for the clinical trial is congruent (or not) with their optic flow preferences and to explore whether preference–allocation congruence is associated with our study outcomes.
We will use the most preferred VR condition rating and the VR condition allocation (which group a participant was randomised to) to create an exploratory variable termed Preference–Allocation Congruence. Specifically, participants will be classified as congruent or incongruent based on whether their most preferred optic flow condition matches their randomly allocated intervention condition.
As a further exploratory analysis, participants may also be classified into three categories based on whether their allocated condition corresponds to (1) their most preferred optic flow condition, (2) their least preferred optic flow condition, or (3) neither their most nor least preferred condition. The feasibility of this additional analysis will depend on the number of participants in each category.

Contacts

Principal investigator

Name

Prof Tasha Stanton

Address

Adelaide University, IIMPACT in Health, School of Allied Health & Human Performance, GPO Box 2471, Adelaide SA 5001.

Country

Australia

Phone

+61 883022090

Fax

[email protected]

Contact person for public queries

Name

Tasha Stanton

Address

Adelaide University, IIMPACT in Health, School of Allied Health & Human Performance, GPO Box 2471, Adelaide SA 5001.

Country

Australia

Phone

+61 883022090

Fax

[email protected]

Contact person for scientific queries

Name

Tasha Stanton

Address

Adelaide University, IIMPACT in Health, School of Allied Health & Human Performance, GPO Box 2471, Adelaide SA 5001.

Country

Australia

Phone

+61 883022090

Fax

[email protected]

Data sharing statement

Will the study consider sharing individual participant data?

Yes

Will there be any conditions when requesting access to individual participant data?

Persons/groups eligible to request access:
• Researchers
Conditions for requesting access:
• Yes, conditions apply:
• Requires review on a case-by-case basis by the trial custodian, sponsor or data sharing committee

What individual participant data might be shared?

• All de-identified individual participant data

What types of analyses could be done with individual participant data?

• Systematic reviews and meta-analyses
• Studies exploring new research questions

When can requests for individual participant data be made (start and end dates)?

From:
After publication of main results
To:
A finite period of: 10 years

Where can requests to access individual participant data be made, or data be obtained directly?

• Access subject to approvals by Primary Investigator (email contact: [email protected])

Are there extra considerations when requesting access to individual participant data?

What supporting documents are/will be available?

No Supporting Document Provided

Results publications and other study-related documents

Documents added manually

No documents have been uploaded by study researchers.

Documents added automatically

No additional documents have been identified.

Trial Review

Documents added manually

Documents added automatically