Testing AREduX with HCPs and Caregivers of People Living with Dementia: A Work in Progress
Bibliographic record
Abstract
Given the lack of empathy training programs for healthcare providers (HCPs), our ongoing research is examining empathy and its role in caring for PLWD and as part of this research effort, recently introduced the Augmented Reality Education Experience (AREduX) virtual simulation prototype AREduX utilizes augmented reality to simulate the physical and cognitive symptoms of dementia, aiming to enhance empathy among HCPs and caregivers. Our ongoing research involves five phases, and this paper outlines the outcome of Phase 3: usability testing of the AREduX prototype with end users, including HCPs and caregivers of PLWD, to examine the functionality, clarity of content, ease of use, and user interface. We anticipate that AREduX will contribute significantly to the scientific understanding of empathy development, address knowledge gaps, and offer recommendations for implementing AR in experiential education for HCPs and PLWD caregivers.
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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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".