Reporting on the Acceptance and Usability of a Virtual Reality Visual Rehabilitation Program in Pediatric Patients With Homonymous Hemianopia
Bibliographic record
Abstract
Background/Objectives: Visual field defects are common in patients with brain tumors. In children, early vision loss can lead to delayed development of motor, language, and social skills, limiting their independence and increasing the risk of depression or anxiety later in life. There is emerging evidence that audio-visual stimulation in the blind field is an effective rehabilitation technique for treating visual field loss. The purpose of this article is to report on feedback from participants in a pilot study that explored virtual reality (VR) as a home-based visual rehabilitation tool for treating hemianopia patients. Subjects/Methods: Ten pediatric patients with homonymous hemianopia (ages 10-17 years) were recruited for the study conducted through Toronto Western Hospital. Participants followed an audio-visual stimulation protocol from home over 4-6 weeks, training their visual perception through an head-mounted display Meta Quest 2 VR headset for 15 min, every other day. Participants completed visual assessments at baseline, postintervention, and at 1- and 6-month follow-ups. A semi-structured interview was conducted postintervention to collect feedback on the participant's experience with the device and the training protocol. Results: This article reports on the data collected through the exit interviews. All participants were able to complete the visual training protocol, and reported few technical difficulties using the system as well as few symptoms of cybersickness. Half of the participants perceived an improvement in their visual perception after completing the intervention. Participants were generally self-motivated to adhere to the therapy, but a common complaint was that the training became repetitive and they lost interest as the weeks progressed. Personalization or gamification of the intervention was recommended by participants for improving engagement.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".