The use of extended reality (XR) in patient education: A critical perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective: Extended reality (XR) has emerged as an innovative educational modality that offers the potential for the creation of more interactive and engaging forms of patient education experiences and products. The purpose of this article is to describe the field of XR technologies and review its potential through a critical lens as well as its possible adoption as a mainstream technology for providing patient education in the future. Method: A review of the literature was undertaken to summarise the emerging evidence concerning the effectiveness of XR as a patient education modality. The findings of several reviews are summarised and a critical discussion of potential issues and challenges in the adoption and use of XR among particular marginalised populations are explored. Results: The emerging evidence suggests that different forms of XR technology applications have the potential to create immersive and engaging patient education experiences that can lead to enhanced patient satisfaction, positive educational outcomes and reduced patient anxiety. Nonetheless, there have been calls for greater consideration of how patient characteristics, including socioeconomic status, gender, cultural and generational differences, influence the learning effects of virtual reality educational applications, as well as its adoption and implementation for patient education purposes. Conclusion: The evidence surrounding the effectiveness of XR in patient education is growing; however, various factors could influence the successful adoption and implementation of XR in different patient populations who have traditionally experienced challenges with digital health literacy. The paper offers some recommendations for enhancing the evidence base and potential approaches to advance the design and evaluation of XR applications in patient education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it