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Record W4412394266 · doi:10.1097/hnp.0000000000000750

Effectiveness of Buzzy on Pain and Anxiety in Children and Adolescents Undergoing Needle Procedures

2025· article· en· W4412394266 on OpenAlexaff
Luigi Apuzzo, Francesco Burrai, Sonia Sellami, Elena Brioni, Valentina Micheluzzi

Bibliographic record

VenueHolistic Nursing Practice · 2025
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsMichel-Sarrazin
Fundersnot available
KeywordsVenipunctureAnxietyConfidence intervalMedicineRandomized controlled trialPhysical therapyStrictly standardized mean differenceAnesthesiaSurgeryInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

The use of cold vibration through the Buzzy device appears promising in reducing pain and anxiety levels in children and adolescents during needle-related procedures. This systematic review and meta-analysis summarizes and evaluates the evidence on this non-pharmacological treatment for pediatric patients undergoing venipuncture or injection procedures. A search was conducted across 6 databases in January 2025. Sixteen randomized controlled trials, involving a total of 1486 patients, were included. Cold vibration stimulation significantly reduced pain (Standard Mean Difference SMD -1.06, 95% confidence interval [-1.39, -0.72], P < .00001) and anxiety levels (SMD -1.60, 95% confidence interval [-2.70, -0.51], P = .004) compared to the control group. The judgment for the direction of the recommendation was rated "for" the Buzzy intervention, with the strength of the recommendation rated as "weak." The use of cold vibration through the Buzzy device may have beneficial effects in reducing anxiety and pain levels in children and adolescents undergoing needle procedures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.008
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.010
GPT teacher head0.322
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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