Virtual Reality distraction during pediatric medical procedures
Bibliographic record
Abstract
Pediatric medical interventions are often associated with high levels of anticipatory fear and anxiety and procedural pain. Management of procedure-related distress commonly includes the use of distraction techniques which aim to divert attention away from the procedure and focus attention on an activity or task (Piira et al., 2002; Vessey et al., 1994). Distraction techniques can be provided in many forms (e.g. conversation, books, movies, computer games) which range from passive to active interventions. It has been suggested that the more active/interactive and interesting a distraction technique, the greater the potential for distraction, but this suggestion remains to be adequately tested (Dahlquist et al., 2002; MacLaren & Cohen, 2005; Mason et al., 1999). Virtual reality (VR) has become popular through the entertainment industries and the technology has only recently been applied in simulated and remote surgical techniques, rehabilitation and health applications. While research exploring the therapeutic use of VR as a distraction intervention for children and adults is sparse (Gold et al., 2005), theoretically this intervention has the potential to be an effective form of management for distress associated with medical procedures.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".