Acceptability of AI-applications in routine clinical care for children and adolescents: perspectives of parents and healthcare professionals
- 1Institute of Neurosciences and Medicine (Brain and Behavior, INM-7), Research Center Juelich, Juelich, Germany
Abstract
With the rapid advancement of artificial intelligence (AI) technologies, growing interest has emerged in its potential application in pediatric healthcare. Understanding the factors influencing AI acceptability among parents and clinical staff is an important prerequisite for facilitating its integration in clinical routine. To date, these factors have not been systematically assessed across different stakeholder groups. Here we investigated AI acceptability among parents (first cohort n = 198; second cohort: n = 79) and pediatric health care professionals (n = 33) across different disease, diagnosis or treatment scenarios. The effects of demographic variables and contextual predictors, such as data privacy, AI knowledge and perceived disease severity, on willingness to use AI were evaluated. More liberal data privacy was associated with reduced willingness to use AI (p < .001). A higher perceived disease severity was linked to higher willingness to use AI ({beta} = .10, p = .013) in the second parent group. When AI and clinicians recommendations conflicted, parents were more likely to choose AI over clinicians judgment in treatment compared to diagnosis scenarios. Healthcare professionals showed similar patterns but additionally weighted perceived disease severity when resolving disagreements. These findings highlight the importance of addressing stakeholder concerns regarding disease specific customization, accuracy, data privacy and accountability when introducing AI into pediatric healthcare settings.
HighlightsO_LIParents are more willing to use AI for conditions they perceive as more severe C_LIO_LIData sharing beyond institutional level significantly reduces willingness to use AI C_LIO_LIDigital literacy and previous medical knowledge facilitate tolerance for AI errors C_LIO_LIAI applications are preferred in treatment over diagnosis scenarios C_LIO_LIHuman judgements are prioritized over AI during inconsistent recommendations C_LI
Related
- Acceptability of Kangaroo Mother Care (KMC) in neonatal transport: a qualitative study on mothers' and healthcare professionals' perspectives on KMC transport in Ghana.
- Accessibility of essential medicines and vaccines among fisherfolk, artisanal miners and pastoralists in Mainland Tanzania: a qualitative study of barriers and strategies from the perspectives of healthcare professionals and community leaders.
- Professionals' perspectives on barriers to improving psychosocial care for adolescents with emotional and behavioural problems - a concept mapping case study.
- What is an ideal mHealth for post-discharge home care of CHD: perspectives from primary caregivers, healthcare professionals, and project technical consultants: a qualitative research study
- Qualitative Assessment of Access to Community Mental Health Centers from the Perspectives of Patients, Patient Relatives, and Healthcare Professionals
BibTeX
@misc{lin2026acceptability,
title = {{Acceptability of AI-applications in routine clinical care for children and adolescents: perspectives of parents and healthcare professionals}},
author = {F. Lin and A. C. Bischops and J.-L. Kerth and T. Meissner and T. Bruni and S. B. Eickhoff and B. Heinrichs and J. M. Lahnakoskia and J. Dukart},
howpublished = {medRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.10.26362703},
url = {https://www.medrxiv.org/content/10.64898/2026.09.10.26362703v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Acceptability of AI-applications in routine clinical care for children and adolescents: perspectives of parents and healthcare professionals
AU - F. Lin
AU - A. C. Bischops
AU - J.-L. Kerth
AU - T. Meissner
AU - T. Bruni
AU - S. B. Eickhoff
AU - B. Heinrichs
AU - J. M. Lahnakoskia
AU - J. Dukart
PY - 2026
DA - 2026/09/10
PB - medRxiv
DO - 10.64898/2026.09.10.26362703
UR - https://www.medrxiv.org/content/10.64898/2026.09.10.26362703v1
AB - With the rapid advancement of artificial intelligence (AI) technologies, growing interest has emerged in its potential application in pediatric healthcare. Understanding the factors influencing AI acceptability among parents and clinical staff is an important prerequisite for facilitating its integration in clinical routine. To date, these factors have not been systematically assessed across different stakeholder groups. Here we investigated AI acceptability among parents (first cohort n = 198; second cohort: n = 79) and pediatric health care professionals (n = 33) across different disease, diagnosis or treatment scenarios. The effects of demographic variables and contextual predictors, such as data privacy, AI knowledge and perceived disease severity, on willingness to use AI were evaluated. More liberal data privacy was associated with reduced willingness to use AI (p < .001). A higher perceived disease severity was linked to higher willingness to use AI ({beta} = .10, p = .013) in the second parent group. When AI and clinicians recommendations conflicted, parents were more likely to choose AI over clinicians judgment in treatment compared to diagnosis scenarios. Healthcare professionals showed similar patterns but additionally weighted perceived disease severity when resolving disagreements. These findings highlight the importance of addressing stakeholder concerns regarding disease specific customization, accuracy, data privacy and accountability when introducing AI into pediatric healthcare settings. HighlightsO_LIParents are more willing to use AI for conditions they perceive as more severe C_LIO_LIData sharing beyond institutional level significantly reduces willingness to use AI C_LIO_LIDigital literacy and previous medical knowledge facilitate tolerance for AI errors C_LIO_LIAI applications are preferred in treatment over diagnosis scenarios C_LIO_LIHuman judgements are prioritized over AI during inconsistent recommendations C_LI
ER -