Open AccessExploring healthcare professionals’ perceptions of artificial intelligence: Piloting the Shinners Artificial Intelligence Perception tool
Author(s) -
Lucy Shinners,
Sandra Grace,
Stuart Smith,
Alexandre Stephens,
Christina Aggar
Publication year - 2022
Publication title -
digital health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.595
H-Index - 8
ISSN - 2055-2076
DOI - 10.1177/20552076221078110
Subject(s) - exploratory factor analysis , workforce , perception , health care , preparedness , psychology , variance (accounting) , health professionals , applied psychology , applications of artificial intelligence , exploratory research , medical education , scale (ratio) , nursing , knowledge management , medicine , computer science , psychometrics , artificial intelligence , clinical psychology , management , political science , business , physics , accounting , quantum mechanics , neuroscience , sociology , anthropology , law , economics
Objective There is an urgent need to prepare the healthcare workforce for the implementation of artificial intelligence (AI) into the healthcare setting. Insights into workforce perception of AI could identify potential challenges that an organisation may face when implementing this new technology. The aim of this study was to psychometrically evaluate and pilot the Shinners Artificial Intelligence Perception (SHAIP) questionnaire that is designed to explore healthcare professionals’ perceptions of AI. Instrument validation was achieved through a cross-sectional study of healthcare professionals ( n = 252) from a regional health district in Australia.Methods and Results Exploratory factor analysis was conducted and analysis yielded a two-factor solution consisting of 10 items and explained 51.7% of the total variance. Factor one represented perceptions of ‘ Professional impact of AI’ (α = .832) and Factor two represented ‘ Preparedness for AI’ (α = .632). An analysis of variance indicated that ‘use of AI’ had a significant effect on healthcare professionals’ perceptions of both factors. ‘Discipline’ had a significant effect on Allied Health professionals’ perception of Factor one and low mean scale score across all disciplines suggests that all disciplines perceive that they are not prepared for AI.Conclusions The results of this study provide preliminary support for the SHAIP tool and a two-factor solution that measures healthcare professionals’ perceptions of AI. Further testing is needed to establish the reliability or re-modelling of Factor 2 and the overall performance of the SHAIP tool as a global instrument.