PLoS ONE (Jan 2022)
Usability of augmented reality technology in tele-mentorship for managing clinical scenarios-A study protocol.
Abstract
BackgroundTele-mentorship is considered to offer a solution to training and providing professional assistance at a distance. Tele-mentoring is a method in which a mentor interactively guides a mentee at a different geographic location in real time using a technological communication device. During a healthcare procedure, tele-mentoring can support a medical expert, remote from the treatment site, to guide a less-experienced practitioner at a different geographic location. Augmented Reality (AR) technology has been incorporated in tele-mentoring systems in healthcare environments globally. However, evidence is absent about the usability of AR technology in tele-mentoring clinical healthcare professionals in managing clinical scenarios.AimThis study aims to evaluate the usability of Augmented Reality (AR) technology in tele-mentorship for managing clinical scenarios.MethodsThis study uses a quasi-experimental design. Four experienced health professionals and a minimum of twelve novice health practitioners will be recruited for the roles of mentors and mentees, respectively. In the experiment, each mentee wearing the AR headset performs a maximum of four different clinical scenarios in a simulated learning environment. A mentor who stays in a separate room and uses a laptop will provide the mentee remote instruction and guidance following the standard protocols for the treatment proposed for each scenario. The scenarios of Acute Coronary Syndrome, Acute Myocardial Infarction, Pneumonia Severe Reaction to Antibiotics, and Hypoglycaemic Emergency are selected, and the corresponding clinical management protocols developed. Outcome measures include the mentors and mentees' perception of the AR's usability, mentorship effectiveness, and the mentees' self-confidence and skill performance.EthicsThe protocol was approved by the Tasmania Health and Medical Human Research Ethics Committee (Project ID: 23343). The complete pre-registration of our study can be found at https://osf.io/q8c3u/.