Evidence map›Paper›PMID 38448378›Full record

ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2023

Development and evaluation of acceptance scale for artificial intelligence in digestive endoscopy by subjects.

Xiuyan Long, Haijun Deng, Zinan Zhang, Tao Liu, Xiaoyu Yu, Pan Gong, Li Tian

Abstract read
In one paragraph

Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xiuyan LongDepartment of Pediatrics, Third Xiangya Hospital, Central South University, Changsha 410013. 2070521987@qq.com.
Haijun DengSchool of Mathematics & Statistics, Guizhou University of Finance and Economics, Guiyang 550025.
Zinan ZhangDepartment of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050.
Tao LiuEight-Years Program of Clinical Medicine, Xiangya School of Medicine, Central South University, Changsha 410013.
Xiaoyu YuDepartment of Gastroenterology, Third Xiangya Hospital, Central South University, Changsha 410013, China.
Pan GongDepartment of Gastroenterology, Third Xiangya Hospital, Central South University, Changsha 410013, China.
Li TianDepartment of Gastroenterology, Third Xiangya Hospital, Central South University, Changsha 410013, China. tianlixy3@csu.edu.cn.

Funding

the Special Project for the Construction of Innovative Provinces in Hunan Province, China 2020SK2013
6 · The paper itself

Abstract

objectivesDigestive endoscopy is an important diagnostic and therapeutic tool for digestive system diseases. The artificial intelligence (AI)-assisted system in endoscopy (hereinafter referred to as AI in digestive endoscopy) has broad application prospects in the field of digestive endoscopy. The trust and acceptance of endoscopic subjects are the cornerstone of the research, application, and promotion of AI in digestive endoscopy. Currently, the tools for measuring the acceptance of AI in digestive endoscopy by subjects are limited at home and abroad. This study aims to develop a scale for measuring the acceptance of AI in digestive endoscopy by subjects, then to evaluate its reliability and validity.

methodsBy conducting literature research, an item pool and dimensions were constructed, and a preliminary scale was constructed using Delphi method. Through the first stage of the survey on the subjects, the reliability and validity of the scale were tested, and the revised scale was used for the second stage of survey on the subjects to further verify the structural validity of the scale.

resultsThe acceptance scale for AI in digestive endoscopy included 11 items in 3 dimensions: accuracy, ethics, benefit and willingness. In the first stage of the survey, 351 valid questionnaires were collected, and the Cronbach's α was 0.864. The correlation coefficient between the total score of the scale and the score of the test item was 0.636, and the Kaiser-Meyer-Olkin (KMO) value in exploratory factor analysis was 0.788. In the second stage of the survey, 335 valid questionnaires were collected, and in confirmatory factor analysis, the

conclusionsAcceptance scale for AI in digestive endoscopy by subjects developed in this study has good reliability and validity.

Indexed as

Artificial IntelligenceEndoscopy, GastrointestinalFactor Analysis, StatisticalHumansReproducibility of Resultsacceptanceartificial intelligence in digestive endoscopyscale

Identifiers

PMID38448378
PMCPMC10930752

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.