Use of Virtual Reality in the Reduction of Pain After the Administration of Vaccines Among Children in Primary Care Centers: Protocol for a Randomized Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Pain and anxiety caused by vaccination and other medical procedures in childhood can result in discomfort for both patients and their parents. Virtual reality (VR) is a technology that is capable of entertaining and distracting the user. Among its many applications, we find the improvement of pain management and the reduction of anxiety in patients undergoing medical interventions. OBJECTIVE: We aim to publish the protocol of a clinical trial for the reduction of pain and anxiety after the administration of 2 vaccines in children aged 3 to 6 years. METHODS: We will conduct a randomized, parallel, controlled clinical trial with 2 assigned groups. The intervention group will wear VR goggles during the administration of 2 vaccines, while the control group will receive standard care from a primary care center for the procedure. Randomization will be carried out by using the RandomizedR computer system-a randomization tool of the R Studio program. This trial will be an open or unblinded trial; both the subjects and the investigators will know the assigned treatment groups. Due to the nature of the VR intervention, it will be impossible to blind the patients, caregivers, or observers. However, a blind third-party assessment will be carried out. The study population will include children aged 3 to 6 years who are included in the patient registry and cared for in a primary care center of the region of Central Catalonia. They will receive the following vaccines during the Well-Child checkup: the triple viral+varicella vaccine at 3 years of age and the hepatitis A+diphtheria-tetanus-pertussis vaccine at 6 years of age. RESULTS: The study is scheduled to begin in January 2022 and is scheduled to end in January 2023, which is when the statistical analysis will begin. As of March 2022, a total of 23 children have been recruited, of which 13 have used VR during the vaccination process. In addition, all of the guardians have found that VR helps to reduce pain during vaccination. CONCLUSIONS: VR can be a useful tool in pediatric procedures that generate pain and anxiety. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/35910.
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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 | 0.040 | 0.039 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.060 | 0.010 |
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".