A randomized trial of iPad distraction to reduce children’s pain and distress during intravenous cannulation in the paediatric emergency department
Bibliographic record
Abstract
OBJECTIVES: We compared the addition of iPad distraction to standard care, versus standard care alone, to manage the pain and distress of intravenous (IV) cannulation. METHODS: Eighty-five children aged 6 to 11 years requiring IV cannulation (without child life services present) were recruited for a randomized controlled trial from a paediatric emergency department. Primary outcomes were self-reported pain (Faces Pain Scale-Revised [FPS-R]) and distress (Observational Scale of Behavioral Distress-Revised [OSBD-R]), analyzed with two-sample t-tests, Mann-Whitney U-tests, and regression analysis. RESULTS: Forty-two children received iPad distraction and 43 standard care; forty (95%) and 35 (81%) received topical anesthesia, respectively (P=0.09). There was no significant difference in procedural pain using an iPad (median [interquartile range]: 2.0 [0.0, 6.0]) in addition to standard care (2.0 [2.0, 6.0]) (P=0.35). There was no significant change from baseline behavioural distress using an iPad (mean ± SD: 0.53 ± 1.19) in addition to standard care (0.43 ± 1.56) (P=0.44). Less total behavioural distress was associated with having prior emergency department visits (odds ratio [95% confidence interval]: -1.90 [-3.37, -0.43]) or being discharged home (-1.78 [-3.04, -0.52]); prior hospitalization was associated with greater distress (1.29 [0.09, 2.49]). Significantly more parents wished to have the same approach in the future in the iPad arm (41 of 41, 100%) compared to standard care (36 of 42, 86%) (P=0.03). CONCLUSIONS: iPad distraction during IV cannulation in school-aged children was not associated with less pain or distress than standard care alone. The effects of iPad distraction may have been blunted by topical anesthetic cream usage. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov: NCT02326623.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".