Health care professionals’ and parents’ perspectives on the use of AI for pain monitoring in the neonatal intensive care unit: multisite qualitative study
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Abstract
BACKGROUND: The use of artificial intelligence (AI) for pain assessment has the potential to address historical challenges in infant pain assessment. There is a dearth of information on the perceived benefits and barriers to the implementation of AI for neonatal pain monitoring in the neonatal intensive care unit (NICU) from the perspective of health care professionals (HCPs) and parents. This qualitative analysis provides novel data obtained from 2 large tertiary care hospitals in Canada and the United Kingdom. OBJECTIVE: The aim of the study is to explore the perspectives of HCPs and parents regarding the use of AI for pain assessment in the NICU. METHODS: In total, 20 HCPs and 20 parents of preterm infants were recruited and consented to participate from February 2020 to October 2022 in interviews asking about AI use for pain assessment in the NICU, potential benefits of the technology, and potential barriers to use. RESULTS: The 40 participants included 20 HCPs (17 women and 3 men) with an average of 19.4 (SD 10.69) years of experience in the NICU and 20 parents (mean age 34.4, SD 5.42 years) of preterm infants who were on average 43 (SD 30.34) days old. Six themes from the perspective of HCPs were identified: regular use of technology in the NICU, concerns with regard to AI integration, the potential to improve patient care, requirements for implementation, AI as a tool for pain assessment, and ethical considerations. Seven parent themes included the potential for improved care, increased parental distress, support for parents regarding AI, the impact on parent engagement, the importance of human care, requirements for integration, and the desire for choice in its use. A consistent theme was the importance of AI as a tool to inform clinical decision-making and not replace it. CONCLUSIONS: HCPs and parents expressed generally positive sentiments about the potential use of AI for pain assessment in the NICU, with HCPs highlighting important ethical considerations. This study identifies critical methodological and ethical perspectives from key stakeholders that should be noted by any team considering the creation and implementation of AI for pain monitoring in the NICU.
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Racine et al. (42) assessed AI for pain monitoring in neonatal intensive care units (NICUs); the AI-assisted systems enhanced the accuracy and consistency of pain assessments, enabling more effective pain management strategies for preterm infants.
“Racine et al. (42) assessed AI for pain monitoring in neonatal intensive care units (NICUs). The AI-assisted systems enhanced the accuracy and consistency of pain assessments, enabling more effective pain management strategies for preterm infants.”
From Artificial intelligence in nursing: an integrative review of clinical and operational impacts (2025) · cites this paper as [42]
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Artificial intelligence in nursing: an integrative review of clinical and operational impacts
Hassanein, S., El Arab, R. A., Abdrbo, A., Abu-Mahfouz, M. S., Gaballah, M. K. F., Seweid, M. M., Almari, M., & Alzghoul, H. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1552372 · Cited by 134 · see citing works
- Authors
- Racine, N., Chow, C., Hamwi, L., Bucsea, O., Cheng, C., Du, H., Fabrizi, L., Jasim, S., Johannsson, L., Jones, L., Laudiano-Dray, M. P., Meek, J., Mistry, N., Shah, V., Stedman, I., Wang, X., & Riddell, R. P.
- Affiliations
- University of Ottawa (CA)
- York University (CA)
- Mount Sinai Hospital (CA)
- University College London (GB)
- University College Hospital (GB)
- Corresponding author
- Racine, Nicole
- ORCID
- Venue
- JMIR AI
- Publisher
- JMIR Publications Inc.
- Published
- 2024-02-09
- Volume
- 3
- Pages
- e51535
- ISSN
- 2817-1705 (ISSN-L)
- PMC
- PMC11041412
- OpenAlex
- W4389858138
- Cited by
- 19
- References
- 42
- Citations by year
- 2026: 7 · 2025: 10 · 2024: 2
- FWCI
- 7.00
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- JMIR AI (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion, cc-by)
- Funders
- University of Ottawa
- Canadian Institutes of Health Research
- Medical Research Council (MR/S003207/1)
- Topics
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pediatric Pain Management Techniques
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Ethics and Legal Issues in Pediatric Healthcare
- Keywords
- artificial intelligence, neonatal pain assessment, neonatal intensive care unit, preterm infants, healthcare professionals' perspectives, parents' perspectives, implementation barriers, ethical considerations, clinical decision-making, parental distress, parental involvement, human care
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