Patients' views on the implementation of artificial intelligence in radiology: development and validation of a standardized questionnaire

被引:89
作者
Ongena, Yfke P. [1 ]
Haan, Marieke [2 ]
Yakar, Derya [3 ]
Kwee, Thomas C. [3 ]
机构
[1] Univ Groningen, Ctr Language & Cognit, Oude Kijk Int Jatstr 26, NL-9700 AS Groningen, Netherlands
[2] Univ Groningen, Dept Sociol, Grote Rozenstr 31, NL-9712 TG Groningen, Netherlands
[3] Univ Groningen, Univ Med Ctr Groningen, Med Imaging Ctr, Dept Radiol, Groningen Hanzepl 1, NL-9713 GZ Groningen, Netherlands
关键词
Artificial intelligence; Surveys and questionnaires; Patients; Radiology; TECHNOLOGY; ACCEPTANCE;
D O I
10.1007/s00330-019-06486-0
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Objectives The patients' view on the implementation of artificial intelligence (AI) in radiology is still mainly unexplored territory. The aim of this article is to develop and validate a standardized patient questionnaire on the implementation of AI in radiology. Methods Six domains derived from a previous qualitative study were used to develop a questionnaire, and cognitive interviews were used as pretest method. One hundred fifty-five patients scheduled for CT, MRI, and/or conventional radiography filled out the questionnaire. To find underlying latent variables, we used exploratory factor analysis with principal axis factoring and oblique promax rotation. Internal consistency of the factors was measured with Cronbach's alpha and composite reliability. Results The exploratory factor analysis revealed five factors on AI in radiology: (1) distrust and accountability (overall, patients were moderately negative on this subject), (2) procedural knowledge (patients generally indicated the need for their active engagement), (3) personal interaction (overall, patients preferred personal interaction), (4) efficiency (overall, patients were ambiguous on this subject), and (5) being informed (overall, scores on these items were not outspoken within this factor). Internal consistency was good for three factors (1, 2, and 3), and acceptable for two (4 and 5). Conclusions This study yielded a viable questionnaire to measure acceptance among patients of the implementation of AI in radiology. Additional data collection with confirmatory factor analysis may provide further refinement of the scale.
引用
收藏
页码:1033 / 1040
页数:8
相关论文
共 23 条
[1]  
[Anonymous], SPSS SAS MATLAB R PR
[2]  
[Anonymous], 2015, Deep learning Nature, DOI [DOI 10.1038/NATURE14539, 10.1038/nature14539]
[3]  
[Anonymous], J THEOR APPL INF TEC
[4]  
[Anonymous], HLTH CARE TECHNOLOGY
[5]  
Callegaro M., 2015, Web survey methodology
[6]   SCREE TEST FOR NUMBER OF FACTORS [J].
CATTELL, RB .
MULTIVARIATE BEHAVIORAL RESEARCH, 1966, 1 (02) :245-276
[7]   Cronbach's Coefficient Alpha: Well Known but Poorly Understood [J].
Cho, Eunseong ;
Kim, Seonghoon .
ORGANIZATIONAL RESEARCH METHODS, 2015, 18 (02) :207-230
[8]   USER ACCEPTANCE OF COMPUTER-TECHNOLOGY - A COMPARISON OF 2 THEORETICAL-MODELS [J].
DAVIS, FD ;
BAGOZZI, RP ;
WARSHAW, PR .
MANAGEMENT SCIENCE, 1989, 35 (08) :982-1003
[9]  
Dillman D. A., 2014, Internet, phone, mail, and mixed-mode surveys: The tailored design method
[10]   Characterization of Patient Interest in Provider-Based Consumer Health Information Technology: Survey Study [J].
Featherall, Joseph ;
Lapin, Brittany ;
Chaitoff, Alexander ;
Havele, Sonia A. ;
Thompson, Nicolas ;
Katzan, Irene .
JOURNAL OF MEDICAL INTERNET RESEARCH, 2018, 20 (04)