FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4283219618> ?p ?o ?g. }

• W4283219618 endingPage "e33368" @default.
• W4283219618 startingPage "e33368" @default.
• W4283219618 abstract "The emergence of Artificial Intelligence (AI) has been proven beneficial in several health care areas. Nevertheless, the uptake of AI in health care delivery remains poor. Despite the fact that the acceptance of AI-based technologies among medical professionals is a key barrier to their implementation, knowledge about what informs such attitudes is scarce.The aim of this study was to identify and examine factors that influence the acceptability of AI-based technologies among medical professionals.A survey was developed based on the Unified Theory of Acceptance and Use of Technology model, which was extended by adding the predictor variables perceived trust, anxiety and innovativeness, and the moderator profession. The web-based survey was completed by 67 medical professionals in the Netherlands. The data were analyzed by performing a multiple linear regression analysis followed by a moderating analysis using the Hayes PROCESS macro (SPSS; version 26.0, IBM Corp).Multiple linear regression showed that the model explained 75.4% of the variance in the acceptance of AI-powered care pathways (adjusted R2=0.754; F9,0=22.548; P<.001). The variables medical performance expectancy (β=.465; P<.001), effort expectancy (β=-.215; P=.005), perceived trust (β=.221; P=.007), nonmedical performance expectancy (β=.172; P=.08), facilitating conditions (β=-.160; P=.005), and professional identity (β=.156; P=.06) were identified as significant predictors of acceptance. Social influence of patients (β=.042; P=.63), anxiety (β=.021; P=.84), and innovativeness (β=.078; P=.30) were not identified as significant predictors. A moderating effect by gender was found between the relationship of facilitating conditions and acceptance (β=-.406; P=.09).Medical performance expectancy was the most significant predictor of AI-powered care pathway acceptance among medical professionals. Nonmedical performance expectancy, effort expectancy, perceived trust, and professional identity were also found to significantly influence the acceptance of AI-powered care pathways. These factors should be addressed for successful implementation of AI-powered care pathways in health care delivery. The study was limited to medical professionals in the Netherlands, where uptake of AI technologies is still in an early stage. Follow-up multinational studies should further explore the predictors of acceptance of AI-powered care pathways over time, in different geographies, and with bigger samples." @default.
• W4283219618 created "2022-06-22" @default.
• W4283219618 creator A5036422523 @default.
• W4283219618 creator A5056493412 @default.
• W4283219618 creator A5072225025 @default.
• W4283219618 creator A5072250112 @default.
• W4283219618 creator A5081779867 @default.
• W4283219618 date "2022-06-21" @default.
• W4283219618 modified "2023-09-26" @default.
• W4283219618 title "The Drivers of Acceptance of Artificial Intelligence–Powered Care Pathways Among Medical Professionals: Web-Based Survey Study" @default.
• W4283219618 cites W1708393801 @default.
• W4283219618 cites W1968206986 @default.
• W4283219618 cites W1996157629 @default.
• W4283219618 cites W2002562159 @default.
• W4283219618 cites W2005417104 @default.
• W4283219618 cites W2014192539 @default.
• W4283219618 cites W2022594136 @default.
• W4283219618 cites W2025642243 @default.
• W4283219618 cites W2072993835 @default.
• W4283219618 cites W2082223960 @default.
• W4283219618 cites W2100379340 @default.
• W4283219618 cites W2162061662 @default.
• W4283219618 cites W2163800176 @default.
• W4283219618 cites W2207476187 @default.
• W4283219618 cites W2289412484 @default.
• W4283219618 cites W2295340354 @default.
• W4283219618 cites W2577043885 @default.
• W4283219618 cites W2626812703 @default.
• W4283219618 cites W2757599011 @default.
• W4283219618 cites W2784868188 @default.
• W4283219618 cites W2899461901 @default.
• W4283219618 cites W2902461656 @default.
• W4283219618 cites W2916559661 @default.
• W4283219618 cites W2943207870 @default.
• W4283219618 cites W2947151330 @default.
• W4283219618 cites W2953532875 @default.
• W4283219618 cites W2968129296 @default.
• W4283219618 cites W2980098811 @default.
• W4283219618 cites W2981723284 @default.
• W4283219618 cites W2995109209 @default.
• W4283219618 cites W3000239480 @default.
• W4283219618 cites W3012810655 @default.
• W4283219618 cites W3043111161 @default.
• W4283219618 cites W3048871739 @default.
• W4283219618 cites W3143784018 @default.
• W4283219618 cites W4230859198 @default.
• W4283219618 doi "https://doi.org/10.2196/33368" @default.
• W4283219618 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35727614" @default.
• W4283219618 hasPublicationYear "2022" @default.
• W4283219618 type Work @default.
• W4283219618 citedByCount "1" @default.
• W4283219618 countsByYear W42832196182023 @default.
• W4283219618 crossrefType "journal-article" @default.
• W4283219618 hasAuthorship W4283219618A5036422523 @default.
• W4283219618 hasAuthorship W4283219618A5056493412 @default.
• W4283219618 hasAuthorship W4283219618A5072225025 @default.
• W4283219618 hasAuthorship W4283219618A5072250112 @default.
• W4283219618 hasAuthorship W4283219618A5081779867 @default.
• W4283219618 hasBestOaLocation W42832196181 @default.
• W4283219618 hasConcept C118552586 @default.
• W4283219618 hasConcept C119857082 @default.
• W4283219618 hasConcept C121955636 @default.
• W4283219618 hasConcept C138528620 @default.
• W4283219618 hasConcept C144133560 @default.
• W4283219618 hasConcept C15744967 @default.
• W4283219618 hasConcept C160735492 @default.
• W4283219618 hasConcept C162324750 @default.
• W4283219618 hasConcept C188353592 @default.
• W4283219618 hasConcept C196083921 @default.
• W4283219618 hasConcept C2780346085 @default.
• W4283219618 hasConcept C41008148 @default.
• W4283219618 hasConcept C50522688 @default.
• W4283219618 hasConcept C558461103 @default.
• W4283219618 hasConcept C71104824 @default.
• W4283219618 hasConcept C75630572 @default.
• W4283219618 hasConcept C77805123 @default.
• W4283219618 hasConcept C93225998 @default.
• W4283219618 hasConceptScore W4283219618C118552586 @default.
• W4283219618 hasConceptScore W4283219618C119857082 @default.
• W4283219618 hasConceptScore W4283219618C121955636 @default.
• W4283219618 hasConceptScore W4283219618C138528620 @default.
• W4283219618 hasConceptScore W4283219618C144133560 @default.
• W4283219618 hasConceptScore W4283219618C15744967 @default.
• W4283219618 hasConceptScore W4283219618C160735492 @default.
• W4283219618 hasConceptScore W4283219618C162324750 @default.
• W4283219618 hasConceptScore W4283219618C188353592 @default.
• W4283219618 hasConceptScore W4283219618C196083921 @default.
• W4283219618 hasConceptScore W4283219618C2780346085 @default.
• W4283219618 hasConceptScore W4283219618C41008148 @default.
• W4283219618 hasConceptScore W4283219618C50522688 @default.
• W4283219618 hasConceptScore W4283219618C558461103 @default.
• W4283219618 hasConceptScore W4283219618C71104824 @default.
• W4283219618 hasConceptScore W4283219618C75630572 @default.
• W4283219618 hasConceptScore W4283219618C77805123 @default.
• W4283219618 hasConceptScore W4283219618C93225998 @default.
• W4283219618 hasIssue "6" @default.
• W4283219618 hasLocation W42832196181 @default.
• W4283219618 hasLocation W42832196182 @default.

• next