Effectiveness of an Edge AI-based Augmented Reality System for Hand Hygiene Training: a Multi-centre, Mixed-methods Cluster Randomised Controlled Trial
Effectiveness of an Edge AI-based Augmented Reality System for Hand Hygiene Training: a Multi-centre, Mixed-methods Cluster Randomised Controlled Trial
This multi-centre, mixed-methods cluster randomised controlled trial (cRCT) aims to evaluate the effectiveness of an edge artificial intelligence (AI)-based augmented reality (AR) training and assessment system for improving hand hygiene knowledge and practice across healthcare and educational settings. Hand hygiene remains one of the most effective measures to prevent healthcare-associated infections (HAIs), which cause substantial morbidity, mortality, and economic burden worldwide. Despite ongoing education efforts, conventional training methods-such as lectures and standard videos-often lack individualised feedback and interactivity, limiting behavioural improvement. The proposed AI-empowered AR system provides real-time assessment and personalised guidance, potentially transforming hand hygiene education into an adaptive, scalable, and evidence-driven learning experience.
The trial will be conducted at three centres: the Hong Kong Polytechnic University and the Chinese University of Hong Kong in Hong Kong SAR, and Tongji Hospital in Wuhan, China. Approximately 480 participants will be enrolled, including 240 undergraduate students in health-related disciplines and 240 healthcare professionals or supporting staff from hospitals. Cluster randomisation will be applied at the session level (6-25 participants per cluster). Randomisation will be performed by a statistician independent from recruitment, and allocation concealment will be maintained. The study will adopt a non-inferiority design, comparing the AI-based AR system against an existing validated educational program combining hand scanner feedback and instructional videos. Participants and assessors of handwashing quality will remain blinded to group allocation.
At baseline, participants will provide written informed consent and complete a standardized questionnaire assessing hand hygiene knowledge and practice. They will apply fluorescent powder to both hands and perform an initial handwashing attempt, recorded by an overhead camera. The percentage of fluorescent residue (measured by the Semmelweis Scanner™) will serve as an objective indicator of decontamination effectiveness, while trained infection prevention and control (IPC) experts will independently assess technique quality from anonymized video recordings. These evaluations will also be used as reference data for AI algorithm development.
In the intervention arm, participants will perform AI-based AR training sessions providing individualized feedback on handwashing performance. In the control arm, participants will receive feedback from the fluorescent scanner and watch a standard "seven-step" handwashing educational video. Following training, participants will repeat the handwashing procedure and post-intervention assessments, including fluorescent residue measurement and the same knowledge-practice questionnaire. The primary outcome is the improvement in decontamination effectiveness (reduction in fluorescent residue percentage between pre- and post-intervention). Secondary outcomes include correct performance of all seven handwashing steps, improvement in knowledge scores, and user satisfaction.
A qualitative component will complement the RCT to explore participants' experiences, attitudes, and perceived barriers toward AI-based AR hand hygiene training. A purposive subsample from both arms will be invited to participate in semi-structured interviews based on the Theoretical Domains Framework. Interviews will examine usability, motivation, learning experience, and perceived behavioral changes. Data will be audio-recorded, transcribed verbatim, and analyzed using thematic analysis with iterative coding to ensure credibility and consistency.
Ethical approval will be obtained from relevant institutional review boards. All participants will be informed of their rights, including voluntary participation and the ability to withdraw at any time without penalty. Potential risks are minimal, limited mainly to rare allergic reactions to fluorescent powder. All data, including video and image recordings, will be anonymised, stored securely, and deleted one year after project completion. No personally identifiable information will be collected.
This study will generate high-quality evidence on the feasibility and educational impact of integrating AI and AR technologies into hand hygiene training across academic and clinical settings. If proven effective, the system can be incorporated into health professional curricula and used at the point of care for real-time performance monitoring and auditing, contributing to sustainable infection prevention and control capacity building.
The importance of hand hygiene cannot be underestimated in both healthcare and community settings (Allegranzi et al., 2011; Mathur, 2011). The promotion of hand hygiene is the best practice in preventing health care-associated infection (WHO, 2009). It has been estimated that hand hygiene could reduce over 500 000 attributable deaths per year. It was found that the annual economic impact of health care-associated infection in the US was approximately US$6.5 billion in 2004 (WHO, 2009) and every US$1 spent on hand hygiene promotion could result in a US$23.7 benefit (Chen et al., 2011). Education plays a key role in setting a good practice base in hand hygiene.
The traditional training methods for hand hygiene include in-class lecture and practical, but they seldom receive individualised instructions and feedback due to limited manpower and facilities. Hence, there is an urgent need to design an automated and individualised training system. This proposed project aims to design and test an innovative education tool for hand hygiene, with the following specific objectives:
If demonstrated effective, this system can be integrated into the curriculum of students of health-related disciplines, healthcare professionals and supporting staff from hospitals as an e-learning approach. In future, this system can also be used at point-of-care for real-time monitoring and audit of healthcare workers in other healthcare settings. In addition to quantitative outcome measures, qualitative interviews will be conducted to explore students' learning experiences, attitudes, and perceived barriers regarding hand hygiene practice and the use of AI-based AR training tools.
Methods
Study design This is a mixed-methods study consisting of a multi-centre non-inferiority two-arm randomised controlled trial (RCT) and a qualitative component. The RCT will evaluate the effectiveness of the AI-based AR training system on students' knowledge and practice of hand hygiene, while the qualitative study will explore students' experiences, attitudes, and perceived barriers related to hand hygiene training through semi-structured interviews. There are three centres for this trial: the Hong Kong Polytechnic University, Chinese University of Hong Kong, and Tongji Hospital in Wuhan, China. We will recruit eligible undergraduates from two universities, and healthcare professionals/supporting staff from Tongji Hospital.
Subject recruitment We will recruit 480 undergraduate students from health-related disciplines from the Hong Kong Polytechnic University, and the Chinese University of Hong Kong (n=240); healthcare professionals and supporting staff in hospitals (n=240). Data collection will be conducted during September 2025 to December 2026. Participants will subscribe a time slot of training sessions (each session has up to 25 participants). All participants who attend the same session will be assigned to the same group by cluster randomisation. A statistician will assign the groups in advance by a random number generator. The participants will not be informed about their group before arriving the study sites.
We calculated the sample size for a cluster randomised controlled trial. We assume that the number of participants in each cluster ranges from 6 to 25, there will be approximately 10-30 clusters in each group. We also assume the standard deviation of subjects is 2.00, the intracluster correlation coefficient is 0.010, and the coefficient of variation of cluster sizes is 0.500 (Ahn et al. 2015). The total sample size of 480 can achieve >91% power to detect a difference between two group means (confidence interval -1.0 and 1.0) in a two-sided t-test with a significance level of 0.050.
Pre-intervention assessment During the site visit, the participants will be invited to sign a consent form first and fill in a questionnaire on knowledge and practice of hand hygiene (attached in Appendix 1).
Participants will need to put fluorescent powder on both of their hands and then perform hand washing using liquid soap without any instructions (1st HW attempt). The camera installed above the hand-wash basins will take videos of both hands (no face nor other parts of the body) during this procedure. After washing hands, participants will need to scan fluorescent powder remained on their hands in a hand scanner (The Semmelweis Scanner™). The recorded hand washing videos will be used to train the AI algorithms for automatic image processing and assessments. Two IPC experts will judge the quality of hand hygiene in these videos, which will be adopted as ground truth in image processing. The percentage of fluorescent gel residual on hands shown in the hand scanner will be used as an objective assessment for efficacy of hand washing in individual participants.
Interventions groups Group A (AI-based AR training system) Participants will use the AI-empowered AR training system to get individualised assessments of their hand wash performance. They will not be informed about the hand scanner results.
Group B (Hand scanner + Video training) Participants will use an existing education program that has been demonstrated effective in our previous study (unpublished). In brief, the participants will be informed about their hand scanner results during the first HW attempt. They will also watch a training video about the 7 steps of hand washing.
Post-intervention assessment The participants will take the second HW attempt by putting fluorescent powder on both of their hands again and then perform hand wash with videos recorded. After washing hands, participants will scan fluorescent powder remained on their hands again in a hand scanner.
Participants will also be asked to fill in a questionnaire on knowledge and practice of hand hygiene as part of post-intervention assessment.
Qualitative Study In addition to the randomised controlled trial, a qualitative component will be conducted to explore participants' experiences, attitudes, and perceived barriers toward hand hygiene training (see Appendix 2). A purposive subsample of participants from both intervention and control groups will be invited to join semi-structured interviews guided by the Theoretical Domains Framework (Cane et al., 2012). The interviews will cover topics such as learning experience, motivation, usability, knowledge, skills, and social influences. All interviews will be audio-recorded and transcribed verbatim. Data will be analysed using thematic analysis, with initial codes generated inductively and then organised into broader categories and themes. Themes will be iteratively reviewed and refined to ensure credibility and consistency. Written informed consent will be obtained prior to participation, and confidentiality and voluntary participation will be strictly observed. Each participant will get a 100 HKD coupon. The sample coupon signature form can be found in Appendix 3.
Randomisation, allocation concealment, and blinding Participants will be randomly assigned to the intervention groups through a process of randomisation performed by a statistician who will not be involved in subject recruitment. The participants will be blinded. The RAs involved in subject recruitment and the IPC experts who judge the quality of hand hygiene will be blinded to the groupings. The RAs and student assistants involved in hand hygiene video recording at the study site will not be blinded because they will be giving instructions to the participants.
Ethical consideration
It is anticipated that the education program will not pose any physical or psychological harm to the participants. There is a very low chance of skin allergy to fluorescent powder. If a participant shows any sign of skin allergy, she or he will instantly stop the trail. The contact details of either the ethical or the research in-charge personnel are clearly written in the information sheet.
Explanation of the study will be given to participants who are interested in participating in the study. Participants will also be given the opportunity to ask our project personnel questions. Furthermore, the information sheet including the purpose of the study, confidentiality of the data, and rights of the participants, will also be provided to the participants. The contact details of either the ethical or the research in-charge personnel are clearly written in the information sheet. If they agree to participate in the study, they are required to sign the consent form. Their participation is on a voluntary basis; they have the right to withdraw from the study at any time if they want to without consequence.
All the collected data will be kept confidentially, and only the research personnel can access and handle the data. No personal information of the participants will be collected except the student ID number. For the qualitative component, participants will also be asked for consent to participate in interviews. All interview data will be anonymised and handled confidentially.
Confidentiality and Security
Data collection will be anonymous, only analysed for specified purposes and based on the consent or other legitimate basis laid down by law. No personal information will be linked to image/video data. All the image/video data will be deleted one year after the project is completed. The Project will not involve any activities or results raising security issues.
References
Allegranzi, B., Bagheri Nejad, S., Combescure, C., Graafmans, W., Attar, H., Donaldson, L., & Pittet, D. (2011). Burden of endemic health-care-associated infection in developing countries: systematic review and meta-analysis. Lancet, 377(9761), 228-241. https://doi.org/10.1016/S0140-6736(10)61458-4
Ahn, C., Heo, M., & Zhang, S. (2015). Sample Size Calculations for Clustered and Longitudinal Outcomes in Clinical Research. CRC Press. New York.
Chen, Y. C., Sheng, W. H., Wang, J. T., Chang, S. C., Lin, H. C., Tien, K. L., Hsu, L. Y., & Tsai, K. S. (2011). Effectiveness and limitations of hand hygiene promotion on decreasing healthcare-associated infections. PLoS One, 6(11), e27163. https://doi.org/10.1371/journal.pone.0027163
Mathur, P. (2011). Hand hygiene: back to the basics of infection control. Indian J Med Res, 134(5), 611-620. https://doi.org/10.4103/0971-5916.90985
WHO. (2009). In WHO Guidelines on Hand Hygiene in Health Care: First Global Patient Safety Challenge Clean Care Is Safer Care. https://www.ncbi.nlm.nih.gov/pubmed/23805438
Yang, L., Lu, Y., Cao, J., Huang, J., & Zhang, M. (2020). E-Tree Learning: A Novel Decentralized Model Learning Framework for Edge AI. IEEE Internet of Things Journal.
Cane, J., O'Connor, D., & Michie, S. (2012). Validation of the theoretical domains framework for use in behaviour change and implementation research. Implementation science, 7(1), 37.
Inclusion Criteria:
Exclusion Criteria:
l.yang@polyu.edu.hk+852 2766 6398
l.yang@polyu.edu.hk+852 2766 6398
chris.kclai@cuhk.edu.hk852-35051523