Tele-mentoring using augmented reality technology in healthcare: A systematic review
Keywords:augmented reality (AR), mentoring, tele-mentoring, health professional education, systematic review
This systematic review aimed to identify how tele-mentoring systems that incorporate augmented reality (AR) technology are being used in healthcare environments. A total of 12 electronic bibliographic databases were searched using the terms “augmented reality”, “tele-mentoring” and “health”. The PRISMA checklist was used as a guide for reporting. The mixed method appraisal tool was used to assess the quality of the included experiments. The data were then analysed using a concept-centric approach and categorised primarily with regards to system performance and task performance measures. A total of 11 randomised controlled trials and 14 non-randomised designs were included for review. Both mentees and mentors assessed the system and task performance according to 25 categories. The feedback of mentees using AR tele-mentoring systems was generally positive. The majority of experiments revealed that the AR system was an effective tele-mentoring device overall and resulted in the effective performance of a procedure. Benefits included improvements in trainees’ confidence, task completion time and reductions in task errors and shifts in focus. However, the systems had limitations, including heaviness of the equipment, inconvenience, discomfort and distraction of wearing devices, limited battery life, the latency of video and audio signals and limited field of view.
Implications for practice or policy:
- Health practitioners can apply AR technology to receive and follow real-time annotated instructions verbally and visually from remote experts.
- Technical developers may consider improving AR devices in terms of lighter weight, larger field of view, more ergonomic design, more stable network connection and longer battery life.
- Further AR-related experiments may need to explore AR tele-mentoring systems’ utility across healthcare environments with larger samples, real patient populations in remote settings, cost-benefit analysis and impacts on short- and long-term patient outcomes.
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