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Accepted for/Published in: JMIR XR and Spatial Computing (JMXR)

Date Submitted: Jul 28, 2025
Date Accepted: Mar 17, 2026

The final, peer-reviewed published version of this preprint can be found here:

Augmented Reality–Assisted Training Tool for Mental Health Task-Sharers: Pilot Mixed Methods Usability Study

Ngiam LLV, Wozniak LP, Dinh-Le C, Seals AE, Ngo VK, Florez-Arango JF

Augmented Reality–Assisted Training Tool for Mental Health Task-Sharers: Pilot Mixed Methods Usability Study

JMIR XR Spatial Comput 2026;3:e80711

DOI: 10.2196/80711

Augmented Reality-Assisted Training Tool (ARATT) for Mental Health Task-Sharers: Pilot Mixed Methods Usability Study

  • Ling Li Vivian Ngiam; 
  • Lucas Piotr Wozniak; 
  • Catherine Dinh-Le; 
  • Ayanna Elon Seals; 
  • Victoria K. Ngo; 
  • Jose Fernando Florez-Arango

ABSTRACT

Background:

The growing global mental health (MH) burden, especially in under-resourced communities, calls for innovative, culturally responsive training approaches to expand care access and improve outcomes. Task-sharing, which shifts specific MH services to less specialized providers, has shown promise in addressing the shortage of trained professionals but is hindered by challenges in training and supervision. Traditional methods, such as role-playing and standardized patients, are resource-intensive and less scalable. Virtual simulations, including augmented reality (AR), present novel opportunities for immersive and interactive training. An AR-assisted training tool can enable culturally sensitive training while fostering empathy, communication skills, and confidence in handling nuanced MH scenarios. However, such a tool’s usability and effectiveness in MH task-sharing training remain underexplored.

Objective:

This pilot study aims to assess the usability of an (AR)-assisted MH task-sharing training tool that utilizes virtual patient (VP) simulation and evaluate its potential value in enhancing the current MH training landscape. Additionally, we propose design recommendations based on early prototype feedback for future related XR-assisted training tools.

Methods:

A five-step mixed-methods usability study assessed an AR-assisted mental health (MH) training tool. Five mental health trainee or workers first participated in the usability test, which consisted of a semi-structured pre-study interview, followed by an introduction to the study, user testing with a think-aloud protocol, and finally a post-study qualitative interview and quantitative questionnaire adapted from the Post-Study System Usability Questionnaire (PSSUQ). Qualitative data was analyzed by thematic analysis.

Results:

The AR simulation was overall positively received by participants and the proposed prototype showed promising usability with a PSSUQ score of 3.46 (SD 1.71), SYSUSE score of 3.46 (SD 1.77), INFOQUAL score of 3.76 (SD 1.73), and INTERQUAL score of 2.83 (SD 1.59). Its realism effectively fostered trainees’ empathy towards the VP, while increasing immersion and interaction quality. Despite some hardware limitations related to the headset and user discomfort that broke immersion, participants recognized the tool's potential and usefulness for training in various mental health scenarios. We proposed design recommendations based on the factors that contributed to the training’s realism. These include: 1) context, 2) structure of training, 3) VP's body language, voice, distance from the trainee, appearance, eye movements, and dialogue, and 3) technical considerations.

Conclusions:

This pilot study shows AR’s potential as a tool for training mental health workers and task-sharers, particularly in offering engaging, immersive, realistic, and empathetic communication practice. The initial AR prototype demonstrated usability and effectiveness in engaging trainees. Further research is needed to quantify its impact on learning outcomes, compare AR’s efficacy with that of traditional methods, and explore pathways for scalable implementation in diverse training contexts with larger sample sizes.


 Citation

Please cite as:

Ngiam LLV, Wozniak LP, Dinh-Le C, Seals AE, Ngo VK, Florez-Arango JF

Augmented Reality–Assisted Training Tool for Mental Health Task-Sharers: Pilot Mixed Methods Usability Study

JMIR XR Spatial Comput 2026;3:e80711

DOI: 10.2196/80711

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