Projector-based virtual reality dome environment for procedural pain and anxiety in young children with burn injuries: a pilot study
Bibliographic record
Abstract
BACKGROUND: Virtual reality (VR) is a non-pharmacological method to distract from pain during painful procedures. However, it was never tested in young children with burn injuries undergoing wound care. AIM: We aimed to assess the feasibility and acceptability of the study process and the use of VR for procedural pain management. METHODS: From June 2016 to January 2017, we recruited children from 2 months to 10 years of age with burn injuries requiring a hydrotherapy session in a pediatric university teaching hospital in Montreal. Each child received the projector-based VR intervention in addition to the standard pharmacological treatment. Data on intervention and study feasibility and acceptability in addition to measures on pain (Face, Legs, Activity, Cry, Consolability scale), baseline (Modified Smith Scale) and procedural (Procedure Behavior Check List) anxiety, comfort (OCCEB-BECCO [behavioral observational scale of comfort level for child burn victims]), and sedation (Ramsay Sedation Scale) were collected before, during, and after the procedure. Data analyses included descriptive and non-parametric inferential statistics. RESULTS: We recruited 15 children with a mean age of 2.2±2.1 years and a mean total body surface area of 5% (±4). Mean pain score during the procedure was low (2.9/10, ±3), as was the discomfort level (2.9/10, ±2.8). Most children were cooperative, oriented, and calm. Assessing anxiety was not feasible with our sample of participants. The prototype did not interfere with the procedure and was considered useful for procedural pain management by most health care professionals. CONCLUSION: The projector-based VR is a feasible and acceptable intervention for procedural pain management in young children with burn injuries. A larger trial with a control group is required to assess its efficacy.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 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".