Case study
Project
VR framework for
Anxiety
Industry
Virtual Reality
Role
UX Researcher
& Designer
Contributions
Job interviews are crucial in achieving employment opportunities, yet they often trigger high levels of anxiety and stress, particularly in individuals with the fear of facing criticism. Study highlights the importance of practice in reducing anxiety and improving interview performance. Virtual reality (VR) offers an innovative approach to simulate realistic environments, enabling users to practice and improve their skills in a safe and controlled setting.
Despite the potential of VR in training, current solutions often lack personalisation, interactive feedback, and engaging elements that keep users motivated. Many individuals with interview anxiety struggle with eye contact, focus, and confidence during interviews. Existing VR tools are either cost-prohibitive or lack the immersive quality needed to replicate real-life challenges.
This research aims to explore how interview anxiety affects fresh graduates from diverse regional backgrounds who experience anxiety about criticism among criticising audiences. Specifically, it examines how immersive technology and an avatar-based interaction framework could be utilised as therapeutic tools to reduce anxiety in facing interviews and boost confidence, with a focus on overcoming barriers such as fear of criticism, underestimating skills, and language-related nervousness.
Preliminary study: Participants completed a pre-test questionnaire to assess their anxiety levels, followed by consent collection.
Prototype Interaction:
Mock Interviews: Participants interacted with an AI-generated animated avatar interviewer, focusing on making eye contact using the cursor and responding to questions using keyboard controls.
Character Building and Feedback: After each question, participants received performance-based rewards in the form of virtual Lego parts, which could be used to create and build characters, promoting engagement and reinforcing learning.
Post-Test: Participants provided feedback through a post-test questionnaire, which evaluated eye contact practice, feedback acceptance, usability, and overall experience.
Eye Contact Practice: Participants rated the experience using Likert scale (Quantitative), Qualitative feedbacks collected on “impact on overcoming anxiety” and improvements.
Accepting Negative Criticism: Participants rated the delivery of criticism, visualisations using Likert scale (Quantitative), Feedbacks collected on “gamification” and areas for improvements. (Qualitative)
System Usability: Participants rated the prototype usability, accessibility of controls using Likert scale (Quantitative), Qualitative feedbacks collected on “issues encountered and challenges faced” during the practice.
Overall engagement: Participants rated the “confident about handling job interviews” using Likert scale (Quantitative), recommendation for changes participants like to be added or improved in the VR version of this tool (Quantitative).
Practice of making eye contact by hovering the eye area showed a positive result with a mean value higher than three (M = 3.59, SD = 0.82).
Effectiveness of the framework on overcoming anxiety about maintaining eye contact during interviews.
The responses indicated a moderately positive outcome, with a mean score of 3.62 (SD = 1.15).
Participants believed this exercise could help them build the habit of maintaining eye contact during interviews.
The responses had a significantly higher favourable result, with a mean score of 3.97 (SD = 1.02).
User Satisfaction Evaluation Questionnaire (USEQ) score
To evaluate the overall success of the framework, the User Satisfaction Evaluation Questionnaire (USEQ) score was calculated by summing the mean values of the key categories:
USEQ score = 3.73 + 3.48 + 3.41 + 3.76 + 3.72 = 18.1 / 25
Participants believed this exercise could help them build the habit of maintaining eye contact during interviews.
The responses had a significantly higher favourable result, with a mean score of 3.97 (SD = 1.02).
Eye contact practice:
Future updates should test the framework in a VR environment with features like real-time focus tracking & measuring the time, customizable virtual faces to make the practice more realistic.
Feedback delivery:
Participants emphasized the importance of feedback delivery mechanisms incorporating real-time voice and visual tools, and progress-tracking options for an effective experience.
Immersiveness:
Participants prioritising realism, interactivity, and customisation in the next iteration of the VR application. Key suggestions included implementing advanced technologies like eye trackers and AI for adaptive interactions for effective training experience.
The study successfully explored how effective is a VR based framework and user satisfaction on mitigating interview anxiety.
Future Design Recomondations
The avatar based framework incorporated with the gamified feedback system has the potential to guide to design a VR environment to mitigate interview anxiety, as the result showing the positive results of eye contact practice and feedback delivering systems
Planning for limited resources and budget requires prioritising essential features and being flexible with the available tools.
When working with unfamiliar technology, using simpler, more accessible platforms can help move the project forward, even if compromises are needed.
Ensuring technical compatibility and user familiarity with tools is crucial for the success of user testing, especially for remote participants.
Real-time feedback and dynamic AI capabilities require more advanced development skills, and it's essential to set realistic expectations given the project's scope.
The participant selection was based on a survey assessing job interview anxiety, and participants self-identified as anxious individuals.
The quality of the Figma prototype was impacted by limited time and budget, using free assets for avatars and voiceovers, resulting in less natural interactions.
The quality of the Figma prototype was impacted by limited time and budget, using free assets for avatars and voiceovers, resulting in less natural interactions.
The character-building feedback feature was based on Marvel characters and Lego blocks, but some participants were unsatisfied with the limited options available.
The project planned to incorporate AI for interview question generation and real-time feedback, but the Figma prototype had preset questions, limiting interaction and feedback capabilities.
The eye tracking feature was not included due to sensor requirements, and the cursor-based method was used instead.
The study was conducted towards the end of the year with a mix of in-person and online participants, and faced the challenges with Figma tool usage and internet connectivity, and low level of monitoring.