ArticleThe Journal of laryngology and otology2024
Understanding, experience and attitudes towards artificial intelligence technologies for clinical decision support in hearing health: a mixed-methods survey of healthcare professionals in the UK.
Article in The Journal of laryngology and otology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses 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
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Ethical concerns of AI in healthcare: A systematic review of qualitative studies.Nursing ethics · 2026Pooled it
- The implementation challenge of computerised clinical decision support systems for the detection of disease in primary care: systematic review and recommendations.Implementation science : IS · 2025Pooled it
- The Design-Driven Innovation Path of Human-Centered Artificial Intelligence in the Field of Healthcare: Theory, Practice, and Future Prospects.Healthcare (Basel, Switzerland) · 2026Review
- Hearing health professionals' attitudes and perceived skills toward artificial intelligence.BMC medical education · 2026Article
- Article
- Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
objectivesClinician acceptance influences technology adoption, but UK health professionals' attitudes towards artificial intelligence (AI) in hearing healthcare are unclear. This study aimed to address this knowledge gap.
methodsAn online survey, based on the Checklist for Reporting Results of Internet E-Surveys, was distributed to audiologists, ENT specialists and general practitioners. The survey collected quantitative and qualitative data on demographics and attitudes to AI in hearing healthcare.
resultsNinety-three participants (mean age 39 years, 56 per cent female) from three professional groups (21 audiologists, 24 ENT specialists and 48 general practitioners) responded. They acknowledged AI's benefits, emphasised the importance of the clinician-patient relationship, and stressed the need for proper training and ethical considerations to ensure successful AI integration in hearing healthcare.
conclusionThis study provides valuable insights into UK healthcare professionals' attitudes towards AI in hearing health and highlights the need for further research to address specific concerns and uncertainties surrounding AI integration in hearing healthcare.
Indexed as
Identifiers
What OpenQuestion holds
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.