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Development, Reliability, and Structural Validity of the Scale for Knowledge, Attitude, and Practice in Ethics Implementation Among AI Researchers: Cross-Sectional Study

BACKGROUND: Medical artificial intelligence (AI) has significantly contributed to decision support for disease screening, diagnosis, and management. With the growing number of medical AI developments and applications, incorporating ethics is considered essential to avoiding harm and ensuring broad b...

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Autores principales: Zhang, Xiaobo, Gu, Ying, Yin, Jie, Zhang, Yuejie, Jin, Cheng, Wang, Weibing, Li, Albert Martin, Wang, Yingwen, Su, Ling, Xu, Hong, Ge, Xiaoling, Ye, Chengjie, Tang, Liangfeng, Shen, Bing, Fang, Jinwu, Wang, Daoyang, Feng, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636617/
https://www.ncbi.nlm.nih.gov/pubmed/37883175
http://dx.doi.org/10.2196/42202
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author Zhang, Xiaobo
Gu, Ying
Yin, Jie
Zhang, Yuejie
Jin, Cheng
Wang, Weibing
Li, Albert Martin
Wang, Yingwen
Su, Ling
Xu, Hong
Ge, Xiaoling
Ye, Chengjie
Tang, Liangfeng
Shen, Bing
Fang, Jinwu
Wang, Daoyang
Feng, Rui
author_facet Zhang, Xiaobo
Gu, Ying
Yin, Jie
Zhang, Yuejie
Jin, Cheng
Wang, Weibing
Li, Albert Martin
Wang, Yingwen
Su, Ling
Xu, Hong
Ge, Xiaoling
Ye, Chengjie
Tang, Liangfeng
Shen, Bing
Fang, Jinwu
Wang, Daoyang
Feng, Rui
author_sort Zhang, Xiaobo
collection PubMed
description BACKGROUND: Medical artificial intelligence (AI) has significantly contributed to decision support for disease screening, diagnosis, and management. With the growing number of medical AI developments and applications, incorporating ethics is considered essential to avoiding harm and ensuring broad benefits in the lifecycle of medical AI. One of the premises for effectively implementing ethics in Medical AI research necessitates researchers' comprehensive knowledge, enthusiastic attitude, and practical experience. However, there is currently a lack of an available instrument to measure these aspects. OBJECTIVE: The aim of this study was to develop a comprehensive scale for measuring the knowledge, attitude, and practice of ethics implementation among medical AI researchers, and to evaluate its measurement properties. METHODS: The construct of the Knowledge-Attitude-Practice in Ethics Implementation (KAP-EI) scale was based on the Knowledge-Attitude-Practice (KAP) model, and the evaluation of its measurement properties was in compliance with the COnsensus-based Standards for the selection of health status Measurement INstruments (COSMIN) reporting guidelines for studies on measurement instruments. The study was conducted in 2 phases. The first phase involved scale development through a systematic literature review, qualitative interviews, and item analysis based on a cross-sectional survey. The second phase involved evaluation of structural validity and reliability through another cross-sectional study. RESULTS: The KAP-EI scale had 3 dimensions including knowledge (10 items), attitude (6 items), and practice (7 items). The Cronbach α for the whole scale reached .934. Confirmatory factor analysis showed that the goodness-of-fit indices of the scale were satisfactory (χ(2)/df ratio:=2.338, comparative fit index=0.949, Tucker Lewis index=0.941, root-mean-square error of approximation=0.064, and standardized root-mean-square residual=0.052). CONCLUSIONS: The results show that the scale has good reliability and structural validity; hence, it could be considered an effective instrument. This is the first instrument developed for this purpose.
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spelling pubmed-106366172023-11-11 Development, Reliability, and Structural Validity of the Scale for Knowledge, Attitude, and Practice in Ethics Implementation Among AI Researchers: Cross-Sectional Study Zhang, Xiaobo Gu, Ying Yin, Jie Zhang, Yuejie Jin, Cheng Wang, Weibing Li, Albert Martin Wang, Yingwen Su, Ling Xu, Hong Ge, Xiaoling Ye, Chengjie Tang, Liangfeng Shen, Bing Fang, Jinwu Wang, Daoyang Feng, Rui JMIR Form Res Original Paper BACKGROUND: Medical artificial intelligence (AI) has significantly contributed to decision support for disease screening, diagnosis, and management. With the growing number of medical AI developments and applications, incorporating ethics is considered essential to avoiding harm and ensuring broad benefits in the lifecycle of medical AI. One of the premises for effectively implementing ethics in Medical AI research necessitates researchers' comprehensive knowledge, enthusiastic attitude, and practical experience. However, there is currently a lack of an available instrument to measure these aspects. OBJECTIVE: The aim of this study was to develop a comprehensive scale for measuring the knowledge, attitude, and practice of ethics implementation among medical AI researchers, and to evaluate its measurement properties. METHODS: The construct of the Knowledge-Attitude-Practice in Ethics Implementation (KAP-EI) scale was based on the Knowledge-Attitude-Practice (KAP) model, and the evaluation of its measurement properties was in compliance with the COnsensus-based Standards for the selection of health status Measurement INstruments (COSMIN) reporting guidelines for studies on measurement instruments. The study was conducted in 2 phases. The first phase involved scale development through a systematic literature review, qualitative interviews, and item analysis based on a cross-sectional survey. The second phase involved evaluation of structural validity and reliability through another cross-sectional study. RESULTS: The KAP-EI scale had 3 dimensions including knowledge (10 items), attitude (6 items), and practice (7 items). The Cronbach α for the whole scale reached .934. Confirmatory factor analysis showed that the goodness-of-fit indices of the scale were satisfactory (χ(2)/df ratio:=2.338, comparative fit index=0.949, Tucker Lewis index=0.941, root-mean-square error of approximation=0.064, and standardized root-mean-square residual=0.052). CONCLUSIONS: The results show that the scale has good reliability and structural validity; hence, it could be considered an effective instrument. This is the first instrument developed for this purpose. JMIR Publications 2023-10-26 /pmc/articles/PMC10636617/ /pubmed/37883175 http://dx.doi.org/10.2196/42202 Text en ©Xiaobo Zhang, Ying Gu, Jie Yin, Yuejie Zhang, Cheng Jin, Weibing Wang, Albert Martin Li, Yingwen Wang, Ling Su, Hong Xu, Xiaoling Ge, Chengjie Ye, Liangfeng Tang, Bing Shen, Jinwu Fang, Daoyang Wang, Rui Feng. Originally published in JMIR Formative Research (https://formative.jmir.org), 26.10.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Zhang, Xiaobo
Gu, Ying
Yin, Jie
Zhang, Yuejie
Jin, Cheng
Wang, Weibing
Li, Albert Martin
Wang, Yingwen
Su, Ling
Xu, Hong
Ge, Xiaoling
Ye, Chengjie
Tang, Liangfeng
Shen, Bing
Fang, Jinwu
Wang, Daoyang
Feng, Rui
Development, Reliability, and Structural Validity of the Scale for Knowledge, Attitude, and Practice in Ethics Implementation Among AI Researchers: Cross-Sectional Study
title Development, Reliability, and Structural Validity of the Scale for Knowledge, Attitude, and Practice in Ethics Implementation Among AI Researchers: Cross-Sectional Study
title_full Development, Reliability, and Structural Validity of the Scale for Knowledge, Attitude, and Practice in Ethics Implementation Among AI Researchers: Cross-Sectional Study
title_fullStr Development, Reliability, and Structural Validity of the Scale for Knowledge, Attitude, and Practice in Ethics Implementation Among AI Researchers: Cross-Sectional Study
title_full_unstemmed Development, Reliability, and Structural Validity of the Scale for Knowledge, Attitude, and Practice in Ethics Implementation Among AI Researchers: Cross-Sectional Study
title_short Development, Reliability, and Structural Validity of the Scale for Knowledge, Attitude, and Practice in Ethics Implementation Among AI Researchers: Cross-Sectional Study
title_sort development, reliability, and structural validity of the scale for knowledge, attitude, and practice in ethics implementation among ai researchers: cross-sectional study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636617/
https://www.ncbi.nlm.nih.gov/pubmed/37883175
http://dx.doi.org/10.2196/42202
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