The effect of augmented reality on preoperative anxiety in children and adolescents: A randomized controlled trial
Bibliographic record
Abstract
BACKGROUND AND AIMS: Virtual reality has been shown to be an effective non-pharmacological intervention for reducing anxiety of pediatric patients. A newer immersive technology, that of augmented reality, offers some practical advantages over virtual reality, and also seems to show beneficial effects on anxiety. The main objective of this study was to determine whether augmented reality could reduce preoperative anxiety in pediatric patients undergoing elective day surgeries. A secondary outcome was to document the level of satisfaction from pediatric patients toward augmented reality intervention. METHODS: Children and adolescents aged between 5 and 17 years old scheduled for elective day surgery under general anesthesia were randomly divided into two groups. Patients in the control group received standard care, whereas patients in the augmented reality group were accompanied by two virtual characters who taught them relaxation techniques and provided emotional and informational support. Anxiety was measured at the time of admission and at the time of induction using the short version of the modified Yale Preoperative Anxiety Scale. RESULTS: The analysis included 37 pediatric patients in the augmented reality group and 64 in the control group. Anxiety scores were statistically significantly lower in the augmented reality group than those in the control group at the time of admission (median difference [95% CI]: 6.3 [0-10.4], p = .01), while no difference was observed between groups at the time of induction (median difference [95% CI]: -4.2 [-5.2-4.2], p = .58). Most patients in the augmented reality group wished to wear the glasses again and reported to be very satisfied with the intervention. CONCLUSION: To our knowledge, this study is the first large randomized controlled trial to provide empirical evidence of reduction in anxiety for children and adolescents using augmented reality prior to induction of general anesthesia.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".