On-Your Marks, Ready? Exploring the User Experience of a

VR Application for Runners with Cognitive-Behavioral Influences

Fernando Pedro Cardenas Hernandez

1,2 a

, Jan Schneider

, Daniele Di Mitri

and Hendrik Drachsler

1,2 d

DIPF - Leibniz Institute for Research and Information in Education, Rostocker Str. 6, 60323, Frankfurt am Main, Germany

Faculty of Computer Science, Robert-Mayer Str. 11-15, 60325, Goethe University, Frankfurt am Main, Germany

Keywords: User Experience, Virtual Reality, Mental Training, Sport Psychology.

Abstract: Athletes need to train both physical and mental abilities to enhance performance. While technologies such as

sensors and actuators have mainly focused on physical training, few solutions support mental training. Virtual

reality (VR) technology and cognitive behavioral therapy (CBT) open new possibilities for developing

applications targeting this type of training for athletes. We conducted a formative study to investigate the user

experience of integrating CBT techniques into VR technology, focusing on two essential mental factors of

running: strategy and motivation. To address these factors, we developed a CBT-influenced VR application.

We tested the user experience of our VR application with 25 runners. The results revealed that runners had a

positive and valuable experience with the VR application and its associated CBT elements. The perceived

importance of race strategy was a key predictor of user experience assessments. This study suggests that VR

solutions influenced by CBT are a plausible approach to developing suitable mental training tools in sports.

1 INTRODUCTION

Running is an accessible and low-cost sport that can

be practiced almost anywhere by almost anyone.

Nevertheless, running well and efficiently requires

comprehensive development of running skills

through training the physical, technical, and mental

aspects. However, the mental aspect is usually not

systematically trained (Cardenas Hernandez et al.,

2024). Moreover, most running training programs

focus primarily on physical and technical aspects,

often neglecting the crucial mental aspect (Boucher et

al., 2020; Rupprecht & Matkin, 2012).

One potential method to systematically train the

mental aspect could be derived from cognitive

behavioral therapy (CBT). CBT is an evidence-based

treatment for psychological disorders that can be

adapted for sport psychology as a cognitive

behavioral training. It helps athletes transform

dysfunctional performance behaviors and thoughts

into functional ones by blending behavior therapy and

https://orcid.org/0000-0002-0592-163X

https://orcid.org/0000-0001-8578-6409

https://orcid.org/0000-0002-9331-6893

https://orcid.org/0000-0001-8407-5314

cognitive therapy approaches (Gustafsson et al.,

2017). Some of its interventions include anxiety

management, goal-setting, and self-instruction

(Whelan et al., 1991). Virtual reality (VR) allows the

creation of interactive, immersive environments, both

real and imaginary, using graphics, sounds, and other

sensory stimuli (Kim et al., 2020; Scurati et al., 2021).

VR has been used with CBT in what is denominated

as virtual reality exposure-based cognitive behavioral

therapy (VRE-CBT) in mental health conditions (van

Loenen et al., 2022; Wu et al., 2021).

Drawing on the premise that VR can simulate

realistic visual training scenarios that enhance athletic

performance (Ahir et al., 2020), unlike verbal,

written, or 2D video instructions, we suggest that

VRE-CBT can be a useful tool for training optimal

behavior in high-intensity situations, such as running

races. Visualizing and repeating these virtual

scenarios could help athletes reduce errors and

improve their mental and perceptual skills, giving

them a competitive edge (Farley et al., 2019).

Cardenas Hernandez, F. P., Schneider, J., Di Mitri, D. and Drachsler, H.

On-Your Marks, Ready? Exploring the User Experience of a VR Application for Runners with Cognitive-Behavioral Inﬂuences.

DOI: 10.5220/0013271300003932

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 17th International Conference on Computer Supported Education (CSEDU 2025) - Volume 1, pages 331-341

ISBN: 978-989-758-746-7; ISSN: 2184-5026

331

Building on VRE-CBT, we developed a CBT-

influenced VR application for head-mounted displays

(HMDs) in English. It integrates cognitive behavioral

techniques such as imagery (by virtually simulating

the running race), behavioral activation (by visual

and auditory emotionally charged stimuli), and

cognitive restructuring (by effective teaching the race

strategy) (Blackwell, 2021; DeSena et al., 2024;

Hanton et al., 2008). We aimed to investigate strategy

and motivation, which are mental factors that

significantly influence running competition outcomes

(Hammer & Podlog, 2016; Kilduff, 2014;

McCormick et al., 2019; Thiel et al., 2012).

In this work, strategy refers to the cognitive

process of making reflective decisions or choices

without time constraints (Gréhaigne et al., 1999). It

includes plans, principles of play, and guidelines

prepared beforehand. Meanwhile, motivation

describes the behavioral process influencing the

initiation, direction, magnitude, perseverance,

continuation, and quality in achieving a goal (Roberts

et al., 2018).

To explore how to target these mental factors, we

conducted a formative study in which runners of

different experience levels tested the VR application

and examined their end-user needs and preferences.

2 RELATED WORK

CBT is an evidence-based treatment for different

psychological disorders. It follows scientific evidence

that shows that thoughts (cognitions) and behaviors

(actions, choices) affect the way people feel

(emotions) (DeSena et al., 2024). VR has been used

as a technological tool for the behavior-cognitive

exposure component of CBT that, with the help of

virtual environments, facilitates the progressive

exposure to aversive-inducing stimuli within a

contextually appropriate and controlled scenario

(Opriş et al., 2012). In this sense, VRE-CBT can be

seen as a useful psychological intervention for

different mental challenges.

VR has been applied to train different mental

facets of sports performance. We identified that some

studies used VR technologies to support the affective

and cognitive components of mental training.

Regarding the affective dimension, VR

technologies have been used to lower soccer anxiety

levels by exposing users to simulated penalty kicks

(Harrison et al., 2021). Additionally, VR

interventions in stationary cycling have demonstrated

improvement in mood and reduction of tiredness

(Plante et al., 2003). Further, athletes feel more

motivated and less pressured during their training

(IJsselsteijn et al., 2004) and report increased

enjoyment (Mestre et al., 2011) using a virtual coach.

A positive effect on motivation has also been shown

in VR volleyball environments with emotionally

expressive virtual characters (Bai et al., 2021).

Elaborating on the cognitive dimension, VR

applications have shown potential in promoting

decision making in sports like basketball (Tsai et al.,

2019) and soccer (Wirth et al., 2021). They can also

support sprinters to improve their concentration

(Choiri et al., 2017) and help stationary cyclists to

ride at the prescribed speed by following the

instructions of a virtual coach (Mestre et al., 2011).

VR has also been used to analyze basketball tactics

(Cannavo et al., 2018) and to help rowers learn race

strategies to optimize energy use and enhance

performance (Hoffmann et al., 2014).

These research findings show that VR can address

both affective and cognitive components of sports,

but most studies have focused on either one

separately. We propose that a CBT-influenced VR

application can simultaneously target both aspects of

long-distance running. We also suggest that using a

CBT approach can provide an effective and

systematic way to initiate the development of VR

technology for potential mental training purposes.

3 SCOPE OF THIS STUDY

This article presents a study on the user experience

(UX) of a CBT-influenced VR application, exploring

its potential to integrate strategic and motivational

facets for long-distance races using an HMD without

physical running.

The research questions (RQs) of our study are:

• RQ1: How is the user experience characterized

within the VR application, as assessed through

usability metrics and subjective evaluations?

• RQ2: What are the main strengths and

drawbacks of the VR application as articulated by

individuals engaged in running activities?

• RQ3: To what extent is the VR application

feasible as a cognitive-behavioral tool for potential

use in mental preparation for running races?

• RQ4: What user profiles are most likely to

benefit from using this VR application?

3.1 VR-Application Description

We aimed to make the application effective by

following the conditions for VR exposure therapy that

Krijn et al. (Krijn et al., 2004) described: the virtual

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Figure 1: VR application flow diagram. Sequence of scenes.

environment should make users feel present, elicit

emotions, and induce cognitive changes generalizable

to real situations.

The VR application simulates typical racing

scenarios, aiming to instruct the running pace as the

main strategy, while a virtual coach avatar provides

strategic guidance, encouraging words, and

background audio plays to elicit emotion and

immersion for the user. As shown in Figure 1, the

CBT-influenced VR application takes the user

through six sequential scenes. These scenes are:

Settings: In this scene, the user can choose a preferred

initial pace for the competition, which is a crucial

strategic factor for any runner to know before starting

a race. The chosen pace will also set the speed of other

virtual characters in the subsequent scenes. The user

can select a pace from a list of values ranging from

2:30 to 6:30 min/km, with 0.10 min/km increments.

After selecting a pace, the user must press a virtual

button (start button) to proceed to the next scene.

Transition 1: This scene involves CBT techniques

such as behavioral activation and cognitive

restructuring. Here, the user is in a stadium setting,

where a female coach avatar gives a motivational

speech with strategic tips and encouragement. After

listening to the coach, the user must push a virtual

button to continue to the next scene. While the next

scene is loading, a sports-related inspirational quote

shows up on the screen. The goal of this scene is to

positively influence users’ motivation beforehand.

Start of the Race: It incorporates CBT techniques

such as imagery and cognitive restructuring. It depicts

the start of a road race based on a real competition

(see Figure 2). It plays the background sound of a

cheering crowd at a sporting event. The user is one of

the 41 virtual runners lined up at the starting line. The

starting gun signals the beginning of the race, and the

virtual characters sprint ahead. The user must use the

controllers to participate in the race. The thumb stick

determines the direction of the user’s motion, while

the buttons adjust the user’s pace. A speedometer in

the lower left side of the user view changes its reading

based on the user's pace. After completing about 300

m, which is one third of the route, the user listens to

the coach avatar giving a voice narration. The coach’

voice advises the user to avoid running fast and to

focus on keeping a steady pace. This part is

envisioned to target the strategy by instructing users

to avoid the common mistake of exhausting their

energy in the first stage of the race. The scene ends

when the user finishes the 1 km route, and the next

scene loads automatically.

Figure 2: User’s view of the "start of the race" scene.

Transition 2: It applies the behavioral activation

technique. In this scene, the user comes back to the

stadium. The coach avatar advises to stay calm and

confident for the next few kilometers of the race; it

also remarks that the user will soon overtake runners

who anxiously started too fast and are now exhausted.

After the coach’s speech, the user must press a virtual

button to advance to the following scene. The purpose

of this scene is to keep motivating the user by

explaining the outcome of applying the strategy at the

start of the race. A motivational quote for sports

appears on the screen as the subsequent scene loads.

Finish of the race: This scene incorporates CBT

techniques such as imagery, behavioral activation and

cognitive restructuring. In this scene, the user and

three virtual runner characters are nearing the finish

line on a street. The background sound consists of the

applause and cheers of a crowd, which gets louder as

the user approaches the end of the race. As the finish

line comes into view, the coach's voice reminds users

to swing their arms to increase their speed and

encourages them to give their best despite fatigue and

soreness. A motivational melody also starts playing

in the background. By doing all this, we aim to teach

strategy and boost motivation. The scene switches

automatically after the user crosses the finish line.

(a)

On-Your Marks, Ready? Exploring the User Experience of a VR Application for Runners with Cognitive-Behavioral Inﬂuences

333

Transition 3: It uses behavioral activation. This is the

last scene where the coach avatar acclaims the user

for exercising and encourages the user to succeed in

running a smart race. A celebratory melody plays in

the background to congratulate the user for finishing

the race. The user must then press a virtual button to

return to the first scene, marking the end of the mental

preparation.

With the VR-HMD's controllers, users could

interact with the virtual world in a first-person view.

Regarding the controllers’ buttons, the primary thumb

stick on the left controller enabled users to navigate

the virtual environment. By tilting their heads, they

could also adjust their direction of movement. To

adjust their speed, users pressed the B and A buttons

on the right controller, which respectively increased

or decreased it by 2 min/km each time.

Using the Unity game engine, we developed an

immersive VR application in English for the Oculus

Quest 2. We used CityGen3D editor to generate the

streets of the city for some VR scenes, created the

avatar's voice using a text-to-speech voice generator,

and applied Unity's built-in rendering pipeline to

create our VR-application. This VR application was

installed on the Oculus Quest 2 with a resolution of

1832 x 1920 pixels per eye, a refresh rate of 90 Hz,

and a field of view of 90 degrees. Participants used

the Oculus’s built-in headphones for audio.

To conclude this section, we would like to note

that we avoided involving the lower extremities in our

VR application, to prevent additional physical strain

on the runner’s legs beyond their regular training

before a competition.

4 METHODS

In this section, we explain how we proceeded to

identify key determinants of using VR technology

influenced by CBT and HMD to train strategy and

motivation for runners. All user tests were conducted

in accordance with our research project’s declaration

and obtained the approval of the ethical committee of

the authors’ institute.

4.1 Participants

This study included 25 participants (8 women, 17

men) who were regular or past runners who had

competed in a 3 km or longer race at least once. They

ranged in age between 21 and 57 years old (M = 37.1,

SD = 10.3) with a mean of 9.61 (SD = 8.45) years of

experience and a mean of 12.6 (SD = 18.3) running

races from 8 different countries. All participants

reported having English proficiency and were

voluntarily recruited through personal or third-party

verbal invitations, without regard to gender,

nationality, education, age, or running experience.

4.2 Procedure

Based on the participants’ locations, we conducted

our study in indoor and shady outdoor settings with

low noise levels to prevent distractions and potential

malfunctions with the HMD.

Before testing the CBT-influenced VR-

application, a researcher set the HMD’s virtual

boundaries for each participant. A researcher also

gave each participant written and verbal instructions

on how to use the VR application properly. The

researcher then adjusted the head strap of the HMD

to fit the participant's head size, and the participant

started using the VR application in a standing-up

position. Each single-test session lasted about 6-7

minutes per participant.

Upon testing the VR-application, participants were

asked to fill out a printed UX questionnaire. The

researcher took notes about the participants’ comments

and behaviors during the tests. Finally, the researchers

thanked people for their participation and gave them

more information about the study's purpose.

4.3 Apparatus and Material

We used the Oculus Quest 2 as the primary device for

this study. This is an affordable, widely available all-

in-one VR device with full motion freedom and a

high-resolution display.

To explore the user experience of our VR

application from a usability and a CBT-influenced

perspective, participants completed a paper UX

questionnaire. It was anonymous and consisted of 13

questions on a 10-point Likert scale and seven open-

ended questions in English. It was adapted from the

one developed for the Multimodal Learning Analytics

Grand Challenge (Worsley et al., 2015) and has been

validated and proven reliable in previous studies

(Romano et al., 2019; Schneider et al., 2019).

For reference in next sections, the questionnaire

Likert-scale items are represented as follows:

a) How likely would I be to use this VR application

in my free time?, b) How would I rate my experience

with this VR application?, c) Would I recommend this

VR application to a friend?, d) How motivated would

I be to use this VR application again?, e) Is the VR-

application fun to use?, f) I really felt like I was in a

race while using this VR application, g) I felt very

immersed in the VR scenarios while using the

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application, h) It is very important to feel immersed

in this type of (mental) training, i) A VR application

like this has the potential to help me improve my

tactic/strategy for a race, j) How important do I

perceive the execution of a good tactic/strategy

during a running race?, k) A VR application like this

has the potential to motivate me to push myself harder

to perform great in a race, l) I feel like I have learned

something while interacting with the VR application,

and m) A VR application like this has the potential to

train other elements of the mental aspects in a race.

4.4 Data Analysis

For comparison of all Likert scale ratings, data were

reported as means (M) and standard deviations (SD).

As an indicator of internal consistency reliability of

the items contributing to measure the same construct,

the Cronbach’s alpha was obtained. Its interpretation

followed the approach of George and Mallery

(George & Mallery, 2003), which is summarized as:

“_ > .9 – Excellent, _ > .8 – Good, _ > .7 – Acceptable,

_ > .6 – Questionable, _ > .5 – Poor, and _ < .5 –

Unacceptable”.

Furthermore, we used Pearson's correlation to

examine the strength and direction of the

relationships between the features that shape the

participants' opinions on the VR application

(independent variables) and their Likert-scale

responses. For this purpose, we calculated the

correlation coefficient (Pearson's r) and the p-value.

We reported the strength of the correlation using the

interpretation given by Dancey and Reidy (Dancey &

Reidy, 2007). For determining statistical significance,

we distinguish three cutoffs: p-value < 0.001, p-value

< 0.01, and p-value < 0.05.

Multiple linear regression models were used to

examine the effects of independent variables, and the

estimated marginal means for the categorical

predictors were calculated. All reported data was

statistically analyzed using Jamovi 2.4.5 software.

We applied a qualitative analysis of open-ended

responses by coding the data into emerging categories

and selecting the most frequent codes. Two

researchers independently performed the analysis and

compared their results.

5 RESULTS

Out of the 25 participants, eight reported having some

prior experience with VR technology. The results of

the Likert-scale questions, grouped by UX

questionnaire themes: user experience and support for

mental training, and constructs: acceptance,

immersion–presence (imagery component), race

strategy (cognitive restructuring and behavioral

activation component), motivation, and other mental

factors, are presented in Table 1. We ordered each

item in the groups by its mean in ascending order.

Table 1: Means (M) and Standard Deviations (SD) of the

Likert-scale items from the UX questionnaire.

Theme Construct

Likert-

scale

item

M SD

User

experience

Acceptance

5.40 2.29

6.20 1.73

6.32 2.61

6.76 2.35

7.52 2.20

Immersion –

presence

(Imagery)

6.56 2.58

6.72 2.30

7.44 1.76

Support

for mental

training

Race strategy

(Cognitive

restructuring

& behavioral

activation)

7.00 1.78

8.92 1.26

Motivation

6.80 1.87

Other mental

factors

6.36 1.78

7.28 1.99

an 1 Very awkward – 10 Very natural

1 Extremely bored – 10 Extremely motivated

ul 1 Very unlikely – 10 Very likely

da 1 Strongly disagree

–

10 Strongly agree

Participants rated the CBT-influenced VR

application positively for the acceptance construct (M

= 6.44, SD = 0.77 for aggregated values, Av) and the

immersion-presence construct (M = 6.9, SD = 0.47

for Av), signifying that they liked the VR application

and felt an acceptable degree of immersion (imagery)

in the virtual scenarios.

They also agreed that the VR application could

help them train the strategy (M = 7.96, SD = 1.36 for

Av) and other mental aspects of a running race (M =

6.82, SD = 0.65 for Av), and enhance their motivation

(M = 6.80, SD = 1.87). Moreover, they emphasized

the high importance of the strategic part during a race

(cognitive restructuring and behavioral activation).

We also conducted a correlation statistical

analysis to examine the relationship between the

Likert-scale responses from the UX questionnaire and

the independent variables: participants’ age, running

experience, and perceived importance of strategy

(Likert-scale item j). The analysis revealed some

noteworthy findings (see Table 2), which are

elaborated in the subsequent paragraphs.

On-Your Marks, Ready? Exploring the User Experience of a VR Application for Runners with Cognitive-Behavioral Inﬂuences

335

Table 2: Pearson’s correlation coefficients between the Likert-scale ratings from the UX questionnaire and the independent

variables: participants’ age, running experience, and perceived importance of strategy.

Theme Construct

Likert – scale

item

Age

Running

experience

Perceived importance

of strategy

User

experience

Acceptance

a -0.101 -0.124 0.374

b -0.157 -0.178 0.353

c -0.303 -0.226 0.568*

d -0.162 -0.183 0.502*

e -0.358 -0.174 0.483*

Immersion–presence

(Imagery)

f -0.198 -0.279 0.477*

g -0.211 -0.121 0.352

h -0.466* -0.205 0.621***

Support for

mental

training

Race strategy

(Cognitive restructuring &

ehavioral activation)

i -0.406* -0.239 0.709***

Motivation k -0.559** -0.465* 0.667***

Other mental factors

l -0.250 -0.170 0.536**

m -0.520** -0.458* 0.560**

*** p-value < 0.001, ** p-value < 0.01, * p-value < 0.05

Concerning the user experience theme and its:

• acceptance construct, the correlation analysis

indicated that participants who rated their strategy as

more important also had more positive attitudes and

experiences with the VR application. They were more

likely to use it again, recommend it to others, and

enjoy it.

• immersion-presence construct, the correlation

analysis showed that older runners tend to rate feeling

immersed for mental training as less important than

younger runners. In the same way, it was found that

the runners who rated their strategy as more important

also had higher ratings for the feeling in the race and

the importance of feeling immersed, and vice versa.

Speaking of the support for mental training theme

and its:

• race strategy construct, the correlation analysis

indicated that older runners tend to give lower scores

than younger runners on how much they think a VR

application can help them improve their race strategy.

Additionally, the analysis suggested that the

participants who rated the VR application higher in

terms of its usefulness for their race strategy also

valued their race strategy more.

• motivation construct, the correlation analysis

revealed that older and more experienced runners

were less convinced that a VR application could help

them improve their motivation for race preparation

than younger and less experienced runners. The

correlation analysis also indicated that the runners

who valued their strategy more also rated the VR

application higher in terms of its motivational effect,

and vice versa.

• other mental factors construct, the correlation

analysis showed that older and more experienced

runners were less convinced that a VR application

could help them improve other mental aspects of their

race preparation than younger and less experienced

runners.

On the other hand, the correlation analysis

revealed that the runners who valued their strategy

more also rated the VR application higher in terms of

its usefulness for other mental elements, and vice

versa. Likewise, the correlation analysis indicated

that the runners who felt that they learned something

from the VR application also rated strategy higher in

terms of its importance, and vice versa.

We assessed the reliability of the acceptance and

immersion-presence constructs by calculating the

Cronbach's alpha coefficient for each construct based

on the mean of the items that composed it. The

acceptance construct had excellent internal

consistency (Cronbach's α = 0.925), and the

immersion-presence construct had good internal

consistency (Cronbach's α = 0.827).

Subsequently, we examined how the independent

variables (participants' age, running experience, and

perceived importance of strategy) influence

participants’ assessments of our four constructs

(acceptance, immersion-presence, race strategy, and

motivation). We applied multiple linear regression

models to analyze the effects of the independent

variables on each construct and estimated the

marginal means for the categorical predictors. The R2

values for each construct were: acceptance = 0.319,

immersion-presence = 0.322, race strategy = 0.524,

and motivation = 0.549.

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Table 3: Model coefficients of the constructs: acceptance, immersion-presence, race strategy, and motivation.

Theme

Construct Predictor Estimate

Standard

error

t p-value

Standard

estimate

User

experience

Acceptance

Interce

t -4.508 4.721 -0.955 0.350 -

e 0.056 0.053 1.054 0.304 0.295

Running

experience

-0.050 0.051 -0.973 0.342 -0.216

Perceived

importance of

strate

1.046 0.376 2.782 0.011 0.665

Immersion–presence

(Imagery)

Interce

t -2.503 4.599 -0.544 0.592 -

e 0.036 0.052 0.699 0.492 0.196

Running

erience

-0.046 0.050 -0.919 0.368 -0.203

Perceived

importance of

strate

0.952 0.366 2.600 0.017 0.620

Support for

mental

training

Race strategy

(Cognitive

restructuring &

behavioral activation)

Intercept -3.967 3.549 -1.118 0.276 -

Age 0.033 0.040 0.836 0.413 -0.168

Running

erience

-0.035 0.039 -0.907 0.375 0.795

Perceived

importance of

strateg

1.127 0.282 3.985 < .001 0.196

Motivation

Intercept -0.461 3.636 -0.127 0.900 -

e 0.001 0.041 0.033 0.974 0.007

Running

experience

-0.073 0.039 -1.852 0.078 -0.334

Perceived

importance of

strate

0.888 0.289 3.064 0.006 -

Our results (see Table 3) showed that only

perceived importance of strategy significantly

predicted the four constructs, while age and

experience did not significantly predict any.

The open-ended questions helped us identify the

upsides and downsides of the VR application and

suggested potential improvements. Participants gave

positive feedback on diverse aspects of the VR

application. 11 participants commented that they

learned to apply running pace during different stages

of a race. Two participants mentioned that they

learned something new about the running technique,

such as swinging their arms.

The background audio was another feature that

received high satisfaction from six participants, who

appreciated its motivational effects. The selection of

the virtual stages in a race was also approved by 11

participants, who enjoyed the diversity and realism of

the scenarios. Finally, seven participants found the

guidance and instructions helpful, and supportive.

Participants also reported some downsides to the

VR application. Three participants experienced

cybersickness symptoms like dizziness and eye strain,

but none felt the need to stop using the application.

Two participants who wore glasses expressed their

displeasure to wear them along with the HMD as it

made them feel uncomfortable. Some scenarios,

especially the "finish of the race" scene, were too

short for three participants, who complained about its

time duration. Three participants also reported initial

difficulties with the VR technology, needing more

time and instructions to adjust to the VR environment

and controls.

Additionally, participants also provided some

suggestions to enhance the VR application. 12

participants reported that to get a higher immersion,

it is necessary to incorporate physical movements that

mimic the running gait, such as swinging the arms or

lifting the knees. They believed that this would make

the VR experience more realistic and engaging. Six

participants recommended adding additional race

strategy scenarios, stages, and effects, such as

different terrains or weather conditions. Three

participants suggested finding alternatives to control

the speed in the VR application. They found the

current method of using a controller to be unnatural.

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Seven participants suggested improving the graphics,

indicating they were blurry.

More than half of the participants struggled to use

their VR hands to interact with the virtual elements at

the start of the test. For instance, one lady in her

sixties, who was excluded from the results, spent

about 15 minutes trying unsuccessfully. Six

participants exhibited boredom and asked the

researchers how long it would take to complete the

"start of the race" scene.

Other six participants disregarded the avatar's

speech and kept pushing the button to augment their

speed. Approximately five participants looked up at

the sky or turned their heads to explore their

surroundings while virtually moving. Six participants

whose mother tongue was not English paid no

attention to the motivational quotes and the avatar's

speech during the test.

6 DISCUSSIONS

Regarding the user experience of our CBT-influenced

VR application (RQ1), overall, it received positive

ratings from the participants in terms of acceptance

and immersion. The mean scores of the items used to

evaluate these aspects were higher than six (on a 10-

point scale) for more than 80% of the time, indicating

that the participants had acceptable user experience.

Based on our results, we identified the main

perceived strengths and drawbacks of using our VR

application (RQ2). As distinguishable positive facets,

we found that participants enjoyed, engaged,

recognized and appreciated the virtual scenarios and

their background audio that simulated race stages.

This suggests that these scenarios contain relevant

and valuable features that can facilitate meaningful

learning experiences in virtual environments, as

supported by previous work (Dengel et al., 2022;

Vergara et al., 2019). Likewise, the presence of the

avatar coach and its guidance had a positive effect on

most participants’ perception (19 out of 25

participants), confirming its beneficial influence as

reported by prior studies (Eyck et al., 2006;

IJsselsteijn et al., 2006). Specifically, runners stated

learning to adjust their running pace according to the

coach avatar’s feedback, aligning with the research

findings on cycling (Mestre et al., 2011). Moreover,

the participants experienced relatively low levels of

cybersickness symptoms from the VR-application.

As visible drawbacks, we distinguished that some

participants faced challenges in getting accustomed to

and interacting with the VR application at the

beginning of the test. They claimed they needed more

time and guidance to adapt to the virtual environment

and its controls. These challenges could affect their

motivation and cause frustration. However, the use of

general user models based on people’s experience,

gender, or age could represent a viable alternative to

ease adaptation in virtual environments (Octavia et

al., 2011). On the other hand, although standing up

and using buttons or a joystick to control the VR

application have evoked some feelings and

perceptions related to running a race, participants

expected a more natural and intuitive way to mimic

real running gait for controlling speed and direction

in VR. Walking-based locomotion techniques

(Martinez et al., 2022) such as arm swinging, may be

adequate solutions for our application, as some

participants performed this movement involuntarily.

Furthermore, using a second language instead of the

native one may have caused some participants to

ignore the motivational quotes and the avatar's speech

in English, possibly due to the lack of language

switching skills. The incorporation of more languages

could mitigate this challenge.

Moreover, the application was perceived as a

promising VR-cognitive behavioral intervention that

can support mental preparation for running races

(RQ3). Our findings suggest that the VR application

has the potential to support elements such as race

strategy and motivation simultaneously.

Additionally, the runners gave a slightly higher rating

for strategy training than for motivation training. This

result is reflected in the open-ended questions, where

some runners mentioned: “I learned again to keep the

pace, mostly at the beginning of the race…”, “There

were good suggestions about pacing yourself …” and

“Slowing down in the beginning even if others

overtake you…”. However, other runners also

expressed boredom and commented: “I felt bored in

few minutes” and “It was realistic, but at same points

of the race, it was a bit boring”. To maintain

participants’ engagement, it would be advisable to

provide strategic instructions or motivational

speeches more frequently, as well as to monitor user

performance and give appropriate feedback regularly.

In addition, some participants orally expressed their

desire to interact with the virtual runners of the

application in an expressive manner. This finding is

consistent with the results of Bai et al (Bai et al.,

2021), who stated that virtual characters with emotion

expression in VR volleyball games can increase the

user’s emotional experience and engagement.

In terms of the type of users who have the

potential to benefit most from the VR application

(RQ4), results showed that the perceived importance

of the race strategy plays a key role in shaping the

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user's attitude, experience, motivation, learning

outcome, immersion, and usefulness of our CBT-

influenced VR application, regardless of their running

experience. Therefore, to get the most value out of our

VR-application, we recommend explaining to users

the relevance of a good race strategy, as pointed out

by Abbis and Laursen (Abbiss & Laursen, 2008).

The runners’ age variable can also modify the

user's importance of immersion and the usefulness of

the VR-application. Our results suggest that older

runners are less likely to value immersion for mental

training in VR than younger runners. This may be due

to different preferences or lower levels of experience

with VR. This finding aligns with previous research

(Syed-Abdul et al., 2019), which indicated that older

adults may face barriers or challenges in using VR,

such as lack of access, skills, or confidence, affecting

their perception of VR experiences.

This study has some limitations that should be

acknowledged. As a first limitation, we consulted

participants to explore whether our CBT-influenced

VR application could work, but we did not measure

its actual effectiveness. Nevertheless, studies like this

are good enough to provide a rough idea about the

functionality and impact on real users. Second, our

relatively small sample size (25 participants) may

affect the statistical reliability of our results.

Although a larger and more diverse sample would be

desirable to confirm and extend our findings, for

exploratory studies like ours, the number of

participants does not require many participants

(Nielsen & Landauer, 1993). Third, our study focused

only on strategy and motivation as the target mental

elements, but there are other cognitive (e.g., attention

and memory) and behavioral factors (e.g., confidence

and happiness) that may also affect an athlete's

performance. Finally, we used generic virtual

scenarios in our study that were suitable for any

runner, but they did not cater to or adapt to the

specific needs of each runner.

7 CONCLUSIONS

We presented a formative study on the user

experience of a VR application that targets mental

factors in endurance sports such as running. Results

from our study show the feasibility of using such an

application for targeting mental elements such as race

strategy and motivation simultaneously from the

perspective of runners with race experience. The

results and methods in this study may serve as a

guideline for researchers and developers to create

CBT-influenced VR tools for potential mental

training in the field of sports psychology, aimed at

enhancing athletes’ performance.

The CBT-influenced VR application appeals

more to the participants who have a high interest in

strategy as a key factor in their mental preparation.

The application may not be as attractive for

participants who do not value strategy as much or

have other preferences or goals. The user experience

in CBT-influenced VR applications may vary by

participants’ age, as different age groups have

different perspectives and expectations on the VR

technology.

For future work, we suggest exploring the

incorporation of meaningful or recognizable music in

the design of an CBT-influenced VR application, as

it has been demonstrated to improve athletes’

performance by increasing their motivation and

enjoyment (Ballmann et al., 2021). Similarly, we

recommend the integration of multisensory sources

(visual, audio, and tactile), as they may regulate the

cognitive load and enhance the user experience by

increasing immersion and presence with vibrotactile

stimuli (Marucci et al., 2021). In that sense, runners

can get mentally prepared through VR-cognitive-

behavioral training, which complements the physical

and technical aspects, and run their best possible race

with confidence.

REFERENCES

Abbiss, C. R., & Laursen, P. B. (2008). Describing and

Understanding Pacing Strategies during Athletic

Competition. Sports Medicine, 38(3), 239–252.

https://doi.org/10.2165/00007256-200838030-00004

Ahir, K., Govani, K., Gajera, R., & Shah, M. (2020).

Application on Virtual Reality for Enhanced Education

Learning, Military Training and Sports. Augmented

Human Research, 5(1), 7. https://doi.org/10.1007/s411

33-019-0025-2

Bai, Z., Yao, N., Mishra, N., Chen, H., Wang, H., &

Magnenat Thalmann, N. (2021). Enhancing Emotional

Experience by Building Emotional Virtual Characters

in VR Volleyball Games. Computer Animation and

Virtual Worlds, 32(3–4). https://doi.org/10.1002/cav.20

Ballmann, C. G., McCullum, M. J., Rogers, R. R., Marshall,

M. R., & Williams, T. D. (2021). Effects of Preferred

vs. Nonpreferred Music on Resistance Exercise

Performance. Journal of Strength and Conditioning

Research, 35(6), 1650–1655. https://doi.org/10.1519/

JSC.0000000000002981

Blackwell, S. E. (2021). Mental Imagery in the Science and

Practice of Cognitive Behaviour Therapy: Past, Present,

and Future Perspectives. International Journal of

On-Your Marks, Ready? Exploring the User Experience of a VR Application for Runners with Cognitive-Behavioral Inﬂuences

339

Cognitive Therapy, 14(1), 160–181. https://doi.org/

10.1007/s41811-021-00102-0

Boucher, V. G., Pelaez, S., Parent, A.-A., Plouffe, J., &

Comtois, A. S. (2020). Momentum During a Running

Competition: A Sequential Explanatory Mixed-

Methods Study. International Journal of Exercise

Science, 13(5), 615–632.

Cannavo, A., Musto, M., Prattico, F. G., Raho, F., &

Lamberti, F. (2018). A participative system for tactics

analysis in sport training based on immersive virtual

reality. 4th Workshop on Everyday Virtual Reality

(WEVR 2018)–25th IEEE Conference on Virtual

Reality and 3D User Interfaces (IEEE VR 2018), 1–4.

Cardenas Hernandez, F. P., Schneider, J., Di Mitri, D.,

Jivet, I., & Drachsler, H. (2024). Beyond hard workout:

A multimodal framework for personalised running

training with immersive technologies. British Journal

of Educational Technology. https://doi.org/10.1111/

bjet.13445

Choiri, M. M., Basuki, A., Bagus, A. Y., Sukaridhoto, S.,

& Jannah, M. (2017). Design and development virtual

reality athletic — Virtual imagery to train sprinter’s

concentration. 2017 International Electronics

Symposium on Knowledge Creation and Intelligent

Computing (IES-KCIC), 161–166. https://doi.org/10.11

09/KCIC.2017.8228580

Dancey, C., & Reidy, J. (2007). Statistics without Maths for

Psychology. Pearson Education.

Dengel, A., Buchner, J., Mulders, M., & Pirker, J. (2022).

Levels of Immersive Teaching and Learning:

Influences of Challenges in the Everyday Classroom. In

Immersive Education (pp. 107–122). Springer

International Publishing. https://doi.org/10.1007/978-

3-031-18138-2_7

DeSena, D., Miner, K., Tischler, S., & Rimer, J. (2024).

Cognitive-Behavioral Therapy (CBT) Group Program

for Depression: Adult Patient Manual. In University of

Michigan. Michigan Medicine, Department of

Psychiatry. https://psych.med.umich.edu/anxiety-

program/pdf/Depression-101.pdf

Eyck, A., Geerlings, K., Karimova, D., Meerbeek, B.,

Wang, L., IJsselsteijn, W., de Kort, Y., Roersma, M., &

Westerink, J. (2006). Effect of a Virtual Coach on

Athletes’ Motivation (Persuasive Technology.

PERSUASIVE 2006., Ed.; pp. 158–161). Springer.

https://doi.org/10.1007/11755494_22

Farley, O. R. L., Spencer, K., & Baudinet, L. (2019). Virtual

reality in sports coaching, skill acquisition and

application to surfing: A review. Journal of Human

Sport and Exercise, 15(3). https://doi.org/10.14198/

jhse.2020.153.06

George, D., & Mallery, P. (2003). SPSS for Windows step

by step: A simple guide and reference 11.0 Update (4th

ed.). Boston: Allyn & Bacon.

Gréhaigne, J.-F., Godbout, P., & Bouthier, D. (1999). The

Foundations of Tactics and Strategy in Team Sports.

Journal of Teaching in Physical Education, 18(2), 159–

174. https://doi.org/10.1123/jtpe.18.2.159

Gustafsson, H., Lundqvist, C., & Tod, D. (2017). Cognitive

behavioral intervention in sport psychology: A case

illustration of the exposure method with an elite athlete.

Journal of Sport Psychology in Action,

8(3), 152–162.

https://doi.org/10.1080/21520704.2016.1235649

Hammer, C., & Podlog, L. (2016). Motivation and

Marathon Running. In Marathon Running: Physiology,

Psychology, Nutrition and Training Aspects (pp. 107–

124). Springer International Publishing. https://doi.org/

10.1007/978-3-319-29728-6_6

Hanton, S., Wadey, R., & Mellalieu, S. D. (2008).

Advanced Psychological Strategies and Anxiety

Responses in Sport. The Sport Psychologist, 22(4),

472–490. https://doi.org/10.1123/tsp.22.4.472

Harrison, K., Potts, E., King, A. C., & Braun-Trocchio, R.

(2021). The Effectiveness of Virtual Reality on Anxiety

and Performance in Female Soccer Players. Sports,

9(12), 167. https://doi.org/10.3390/sports9120167

Hoffmann, C. P., Filippeschi, A., Ruffaldi, E., & Bardy, B.

G. (2014). Energy management using virtual reality

improves 2000-m rowing performance. Journal of

Sports Sciences, 32(6), 501–509. https://doi.org/

10.1080/02640414.2013.835435

IJsselsteijn, W. A., Kort, Y. A. W. de, Westerink, J., Jager,

M. de, & Bonants, R. (2006). Virtual Fitness:

Stimulating Exercise Behavior through Media

Technology. Presence: Teleoperators and Virtual

Environments, 15(6), 688–698. https://doi.org/10.1162/

pres.15.6.688

IJsselsteijn, W., de Kort, Y., Westerink, J., de Jager, M., &

Bonants, R. (2004). Fun and Sports: Enhancing the

Home Fitness Experience (pp. 46–56).

https://doi.org/10.1007/978-3-540-28643-1_8

Kilduff, G. J. (2014). Driven to Win. Social Psychological

and Personality Science, 5(8), 944–952.

https://doi.org/10.1177/1948550614539770

Kim, Y. M., Rhiu, I., & Yun, M. H. (2020). A Systematic

Review of a Virtual Reality System from the

Perspective of User Experience. International Journal

of Human–Computer Interaction, 36(10), 893–910.

https://doi.org/10.1080/10447318.2019.1699746

Krijn, M., Emmelkamp, P. M. G., Olafsson, R. P., &

Biemond, R. (2004). Virtual reality exposure therapy of

anxiety disorders: A review. Clinical Psychology

Review, 24(3), 259–281. https://doi.org/10.1016/j.cpr.2

004.04.001

Martinez, E. S., Wu, A. S., & McMahan, R. P. (2022).

Research Trends in Virtual Reality Locomotion

Techniques. 2022 IEEE Conference on Virtual Reality

and 3D User Interfaces (VR), 270–280.

https://doi.org/10.1109/VR51125.2022.00046

Marucci, M., Di Flumeri, G., Borghini, G., Sciaraffa, N.,

Scandola, M., Pavone, E. F., Babiloni, F., Betti, V., &

Aricò, P. (2021). The impact of multisensory

integration and perceptual load in virtual reality settings

on performance, workload and presence. Scientific

Reports, 11(1), 4831. https://doi.org/10.1038/s41598-

021-84196-8

McCormick, A., Meijen, C., Anstiss, P. A., & Jones, H. S.

(2019). Self-regulation in endurance sports: theory,

research, and practice. International Review of Sport

CSEDU 2025 - 17th International Conference on Computer Supported Education

340

and Exercise Psychology, 12(1), 235–264.

https://doi.org/10.1080/1750984X.2018.1469161

Mestre, D. R., Ewald, M., & Maiano, C. (2011). Virtual

Reality and Exercise: Behavioral and Psychological

Effects of Visual Feedback. Studies in Health

Technology and Informatics 2011, 167, 122–127.

Nielsen, J., & Landauer, T. K. (1993). A mathematical

model of the finding of usability problems. Proceedings

of the SIGCHI Conference on Human Factors in

Computing Systems - CHI ’93, 206–213.

https://doi.org/10.1145/169059.169166

Octavia, J. R., Raymaekers, C., & Coninx, K. (2011).

Adaptation in virtual environments: conceptual

framework and user models. Multimedia Tools and

Applications, 54(1), 121–142. https://doi.org/10.1007/

s11042-010-0525-z

Opriş, D., Pintea, S., García-Palacios, A., Botella, C.,

Szamosközi, Ş., & David, D. (2012). Virtual reality

exposure therapy in anxiety disorders: a quantitative

meta-analysis. Depression and Anxiety, 29(2), 85–93.

https://doi.org/10.1002/da.20910

Plante, T. G., Frazier, S., Tittle, A., Babula M., Ferlic, E.,

& Riggs, E. (2003). Does virtual reality enhance the

psychological benefits of exercise? Journal of Human

Movement Studies., 485–507.

Roberts, G. C., Nerstad, C. G. L., & Lemyre, P. N. (2018).

Motivation in Sport and Performance. In Oxford

Research Encyclopedia of Psychology. Oxford

University Press. https://doi.org/10.1093/acrefore/97

80190236557.013.150

Romano, G., Schneider, J., & Drachsler, H. (2019).

Dancing Salsa with Machines—Filling the Gap of

Dancing Learning Solutions. Sensors, 19(17), 3661.

https://doi.org/10.3390/s19173661

Rupprecht, P. M., & Matkin, G. S. (2012). Finishing the

Race: Exploring the Meaning of Marathons for Women

Who Run Multiple Races. Journal of Leisure Research,

44(3), 308–331. https://doi.org/10.1080/00222216.201

2.11950267

Schneider, Romano, & Drachsler. (2019). Beyond

Reality—Extending a Presentation Trainer with an

Immersive VR Module. Sensors, 19(16), 3457.

https://doi.org/10.3390/s19163457

Scurati, G. W., Bertoni, M., Graziosi, S., & Ferrise, F.

(2021). Exploring the Use of Virtual Reality to Support

Environmentally Sustainable Behavior: A Framework

to Design Experiences. Sustainability, 13(2), 943.

https://doi.org/10.3390/su13020943

Syed-Abdul, S., Malwade, S., Nursetyo, A. A., Sood, M.,

Bhatia, M., Barsasella, D., Liu, M. F., Chang, C.-C.,

Srinivasan, K., M., R., & Li, Y.-C. J. (2019). Virtual

reality among the elderly: a usefulness and acceptance

study from Taiwan. BMC Geriatrics, 19(1), 223.

https://doi.org/10.1186/s12877-019-1218-8

Thiel, C., Foster, C., Banzer, W., & De Koning, J. (2012).

Pacing in Olympic track races: Competitive tactics

versus best performance strategy. Journal of Sports

Sciences, 30(11), 1107–1115. https://doi.org/10.1080/

02640414.2012.701759

Tsai, W.-L., Su, L., Ko, T.-Y., Yang, C.-T., & Hu, M.-C.

(2019). Improve the Decision-making Skill of

Basketball Players by an Action-aware VR Training

System. 2019 IEEE Conference on Virtual Reality and

3D User Interfaces (VR), 1193–1194. https://doi.org/

10.1109/VR.2019.8798309

van Loenen, I., Scholten, W., Muntingh, A., Smit, J., &

Batelaan, N. (2022). The Effectiveness of Virtual

Reality Exposure–Based Cognitive Behavioral Therapy

for Severe Anxiety Disorders, Obsessive-Compulsive

Disorder, and Posttraumatic Stress Disorder: Meta-

analysis. Journal of Medical Internet Research, 24(2),

e26736. https://doi.org/10.2196/26736

Vergara, D., Extremera, J., Rubio, M. P., & Dávila, L. P.

(2019). Meaningful Learning Through Virtual Reality

Learning Environments: A Case Study in Materials

Engineering. Applied Sciences, 9(21), 4625.

https://doi.org/10.3390/app9214625

Whelan, J. P., Mahoney, M. J., & Meyers, A. W. (1991).

Performance enhancement in sport: A cognitive

behavioral domain. Behavior Therapy, 22(3), 307–327.

https://doi.org/10.1016/S0005-7894(05)80369-7

Wirth, M., Kohl, S., Gradl, S., Farlock, R., Roth, D., &

Eskofier, B. M. (2021). Assessing Visual Exploratory

Activity of Athletes in Virtual Reality Using Head

Motion Characteristics. Sensors, 21(11), 3728.

https://doi.org/10.3390/s21113728

Worsley, M., Chiluiza, K., Grafsgaard, J. F., & Ochoa, X.

(2015). 2015 Multimodal Learning and Analytics

Grand Challenge. Proceedings of the 2015 ACM on

International Conference on Multimodal Interaction,

525–529. https://doi.org/10.1145/2818346.2829995

Wu, J., Sun, Y., Zhang, G., Zhou, Z., & Ren, Z. (2021).

Virtual Reality-Assisted Cognitive Behavioral Therapy

for Anxiety Disorders: A Systematic Review and Meta-

Analysis. Frontiers in Psychiatry, 12. https://doi.org/

10.3389/fpsyt.2021.575094

On-Your Marks, Ready? Exploring the User Experience of a VR Application for Runners with Cognitive-Behavioral Inﬂuences

341