Effectiveness of the Use of Augmented Reality in Teaching the Management of Anaphylactic Shock at the Primary Care Level: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Augmented reality (AR) has benefits and feasibility in emergency medicine, especially in the clinical care of patients, in operating rooms and inpatient facilities, and in the education and training of emergency care providers, but current research on this topic is sparse. OBJECTIVE: The primary objective is to evaluate the short-term and long-term effectiveness of the use of AR in the treatment of patients with anaphylactic shock. The secondary objectives are to evaluate the safety in the treatment of patients with anaphylactic shock, evaluate the short-term and long-term effectiveness of stress management in this process, and determine the experiences and attitudes towards the use of AR in education. METHODS: The study will be conducted in 3 phases. In the first phase, we will develop and test the scenario for simulation of anaphylactic shock and the evaluation scale for assessing the effect of the intervention. In the second phase, a single-blinded, randomized controlled trial will be conducted. In the third phase, the use of AR in teaching the management of anaphylactic shock using focus groups will be evaluated qualitatively. All participants will participate in a 1-day training program consisting of a lecture on emergency care and anaphylactic shock as well as exercises in manual dexterity (aspiration, airway management, alternative airway management, artificial respiration, chest compressions, safe defibrillation, oxygen application, use of medication during emergency care). The test group will also focus on education about anaphylactic shock in AR (the intervention). The main outcome will be the evaluation of the participants' performance in coping with a simulated scenario of anaphylactic shock using a high-fidelity simulator (simulator with high levels of realism) and a standardized patient in an educational and clinical environment. The study will be conducted with primary care physicians. RESULTS: A scenario for the simulation with a high-fidelity simulator and standardized patient has already been developed. For the time being, we are developing an evaluation scale and starting to recruit participants. We plan to complete the recruitment of participants by the end of December 2020, start the randomized controlled trial in January 2021, and finish 1 year later. The first results are expected to be submitted for publication in 2021. CONCLUSIONS: This will be the first study to evaluate the effectiveness of the use of AR in medical teaching. Specifically, it will be based on a clinical case of anaphylactic shock at the primary care level. With our study, we also want to evaluate the translation of these educational results into clinical practice and assess their long-term impact. TRIAL REGISTRATION: ISRCTN Registry ISRCTN58047410; http://www.isrctn.com/ISRCTN58047410. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/22460.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.042 | 0.045 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.008 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.060 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".