口腔初诊患者人工智能智慧问答系统使用体验量表的研制与心理测量学验证

刘睿夕; 匡碧芬; 杨依凡; 李宏; 赵娅琼; 冯云枝; 袁临天; 郭玥

doi:10.11817/j.issn.1672-7347.2026.260159

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口腔初诊患者人工智能智慧问答系统使用体验量表的研制与心理测量学验证
Development and psychometric validation of the User Experience Scale for Artificial Intelligence Question-Answering Systems among first-visit dental patients
中南大学学报(医学版) 中南大学学报(医学版) 2026年页码：1-12
作者机构：

中南大学湘雅二医院口腔医学中心，长沙 410011
作者简介：

刘睿夕，Email: Liurx211@163.com, ORCID: 0009-0007-0744-6784
匡碧芬，Email: zndxxyeyykbf@csu.edu.cn, ORCID: 0009-0006-1990-3789
郭玥，副研究员，Email: guoyue@csu.edu.cn, ORCID: 0000-0003-2403-2034
基金信息：

湖南省自然科学基金(2025JJ50687;2024JJ9209);中南大学中央高校基本科研业务(2024ZZTS0891┫。This work was supported by the Natural Science Foundation of Hunan Province ┣2025JJ50687;2024JJ9209);the Fundamental Research Funds for the Central Universities, Central South University(2024ZZTS0891);China.开放获取(Open access)：本文遵循知识共享许可协议，允许第三方用户按照署名-非商业性使用-禁止演绎4.0(CC BY-NC-ND 4.0┫的方式;在任何媒介以任何形式复制、传播本作品┣https://creativecommons.org/licenses/by-nc-nd/4.0/)
DOI：10.11817/j.issn.1672-7347.2026.260159
中图分类号：
CSTR：
收稿：2026-04-22，

网络首发：2026-07-31，
稿件说明：

刘睿夕, 匡碧芬, 杨依凡, 等. 口腔初诊患者人工智能智慧问答系统使用体验量表的研制与心理测量学验证[J/OL]. 中南大学学报(医学版), 2026,1-12.

LIU Ruixi, KUANG Bifen, YANG Yifan, et al. Development and psychometric validation of the User Experience Scale for Artificial Intelligence Question-Answering Systems among first-visit dental patients[J/OL]. Journal of Central South University. Medical Science, 2026, 1-12.
刘睿夕, 匡碧芬, 杨依凡, 等. 口腔初诊患者人工智能智慧问答系统使用体验量表的研制与心理测量学验证[J/OL]. 中南大学学报(医学版), 2026,1-12. DOI： 10.11817/j.issn.1672-7347.2026.260159.

LIU Ruixi, KUANG Bifen, YANG Yifan, et al. Development and psychometric validation of the User Experience Scale for Artificial Intelligence Question-Answering Systems among first-visit dental patients[J/OL]. Journal of Central South University. Medical Science, 2026, 1-12. DOI： 10.11817/j.issn.1672-7347.2026.260159.

摘要

目的

口腔健康是全身健康的重要组成部分，然而口腔初诊候诊场景下尚缺乏专用测评工具。本研究旨在通过系统研制并验证适用于中国口腔科初诊患者的人工智能问答系统使用体验量表(User Experience Scale for Artificial Intelligence Question-Answering Systems，UES-AIQA)，为口腔门诊人工智能(artificial intelligence，AI)服务质量评估提供标准化工具。

方法

通过文献分析与专家小组会议构建初始条目池，经2轮德尔菲专家函询完成条目筛选。采用方便抽样法选取305例口腔科初诊患者，第1批233例用于探索性因子分析(exploratory factor analysis，EFA)，第2批72例用于验证性因子分析(confirmatory factor analysis，CFA)，综合项目分析、因子分析及信度分析评价量表心理测量学属性。

结果

最终量表包含10个条目，呈单维度结构。各条目水平的内容效度指数(item-level content validity index，

-CVI)为0.900~1.000，量表水平的平均内容效度指数(scale-level content validity index/average，

-CVI/Ave)为0.980。平行分析与Kaiser准则均支持提取1个公因子，单因子累积方差贡献率为83.593%，各条目标准化因子载荷为0.879~0.937。CFA拟合结果显示卡方自由度比(ratio of chi-square to degrees of freedom，

)为3.190，比较拟合指数(comparative fit index，CFI)为0.929，Tucker-Lewis指数(Tucker-Lewis index，TLI)为0.900，标准化均方根残差(standardized root mean square residual，SRMR)为0.035，主要拟合指标均达到可接受标准；近似误差均方根(root mean square error of approximation，RMSEA)为0.174，偏高或因样本量较小(

=72)对该指标敏感所致；各条目标准化因子载荷为0.845~0.928。总量表克龙巴赫α系数为0.981，McDonald's ω系数为0.983，Spearman-Brown分半信度为0.970，重测组内相关系数(intra-class correlation coefficient，ICC)为0.830。

结论

UES-AIQA内容效度与信度达到心理测量学标准，结构效度部分指标达到可接受水平，可初步作为评估口腔科初诊患者AI智慧问答系统使用体验的标准化工具。现阶段样本来源及样本量较为有限，量表的结构稳定性与跨人群适用性仍需更大样本进一步验证。

Abstract

Objective

Oral health is an essential component of overall health; however

specific assessment tools for first-visit patients in dental outpatient waiting scenarios are currently lacking. This study aims to systematically develop and validate the User Experience Scale for Artificial Intelligence Question-Answering Systems (UES-AIQA) for Chinese first-visit dental patients

providing a standardized instrument for evaluating the service quality of artificial intelligence (AI)-based services in dental outpatient settings.

Methods

An initial item pool was developed through literature analysis and expert group discussions. Item selection was conducted through two rounds of Delphi expert consultation. A total of 305 first-visit dental patients were recruited using convenience sampling. The first sample of 233 participants was used for exploratory factor analysis (EFA)

and the second sample of 72 participants was used for confirmatory factor analysis (CFA). Psychometric properties of the scale were evaluated through item analysis

factor analysis

and reliability analysis.

Results

The final scale consisted of 10 items and demonstrated a unidimensional structure. The item-level content validity index (

-CVI) ranged from 0.900 to 1.000

and the average scale-level content validity index (

-CVI/Ave) was 0.980. Parallel analysis and the Kaiser criterion both supported the extraction of one common factor. The cumulative variance contribution rate of the single factor was 83.593%

and standardized factor loadings of all items ranged from 0.879 to 0.937. CFA showed that the ratio of chi-square to degrees of freedom (

) was 3.190

the comparative fit index (CFI) was 0.929

the Tucker-Lewis index (TLI) was 0.900

and the standardized root mean square residual (SRMR) was 0.035

with the major fit indices reaching acceptable levels. The root mean square error of approximation (RMSEA) was 0.174

which was relatively high and may have been influenced by the small sa

mples size (

=72)

as RMSEA is sensitive to sample size. Standardized factor loadings in the CFA model ranged from 0.845 to 0.928. The Cronbach's α coefficient of the total scale was 0.981

McDonald's ω coefficient was 0.983

Spearman-Brown split-half reliability coefficient was 0.970

and the test-retest intra-class correlation coefficient (ICC) was 0.830.

Conclusion

The UES-AIQA demonstrated satisfactory content validity and reliability according to psychometric standards

while several structural validity indicators reached acceptable levels. The scale may serve as a preliminary standardized tool for evaluating user experiences with AI question-answering systems among first-visit dental patients. Currently

the limited sample source and sample size remain constraints

and further validation with larger samples is required to confirm the structural stability and applicability of the scale across different populations.

关键词

Keywords

references

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