Observational studyAnnals of the Royal College of Surgeons of England2024
A survey of patient acceptability of the use of artificial intelligence in the diagnosis of paediatric fractures: an observational study.
Observational study in Annals of the Royal College of Surgeons of England, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Factors influencing AI acceptance in radiology: a systematic review across the radiology workflow.European radiology · 2026Pooled it
- Artificial Intelligence in Paediatric and Adolescent Fracture Detection: A Systematic Review and Meta-Analysis.Cureus · 2025Review
- Parental and carer views on the use of AI in imaging for children: a national survey.Insights into imaging · 2025Article
- Some artificial intelligence tools may currently be useful in orthopedic surgery and traumatology.World journal of orthopedics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThis study aimed to assess carer attitudes towards the use of artificial intelligence (AI) in management of fractures in paediatric patients. As fracture clinic services come under increasing pressure, innovative solutions are needed to combat rising demand. AI programs can be used to diagnosis fractures, but patient perceptions towards its use are uncertain.
methodsWe conducted a cross-sectional survey of carers of paediatric patients presenting to fracture clinic at a tertiary care centre, combining single-best-answer questions and Likert-type questions. We investigated patient perception of clinical review in the emergency department (ED), disruption to school to attend fracture clinic, and attitudes towards AI.
resultsOf the paediatric fracture patients participating in this study, 45% were seen within two hours, 29% were seen between two and four hours, and 26% were seen after four hours; 75% were seen by both a nurse and a doctor, 16% were seen only by a nurse and 9% only by a doctor. A total of 61% of children had to take time off school for their appointment and 59% of parents had to take time off. Of all respondents, 56% agreed that more research is needed to reduce waiting times, 76% preferred a nurse or doctor to review their child's radiograph, 64% were happy for an AI program to diagnose their child's fracture, and 82% were happy with an AI program being used as an adjunct to a clinician's diagnosis.
conclusionsCarer perceptions towards the use of AI in this setting are positive. However, they are not yet ready to relinquish human decision making to automated systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.