Rose John, Reid Jason, Morton Lisa, Stomberg-Firestein Sasha, Miller Lisa
Spirituality Mind Body Institute & Clinical Psychology Program, Teachers College, Columbia University, New York, NY 10027, USA.
Behav Sci (Basel). 2025 Sep 1;15(9):1193. doi: 10.3390/bs15091193.
Trust in public institutions was challenged during the COVID-19 global pandemic, with widespread mistrust towards healthcare institutions as well as fellow public institutions. Concurrently, a new public institution or social tool, mass-market artificial intelligence (AI), more broadly emerged, which too may be a target of fluctuating public trust. Using national survey data from the United Kingdom's Centre for Data Ethics and Innovation (survey year: 2022, N = 4320; survey year: 2023, N = 4232), we explore the level of trust in civic institutions (healthcare, non-healthcare, and AI) during and immediately after the COVID-19 pandemic in the United Kingdom using a naturalistic quasi-experimental design. At both waves (2022 and 2023), principal component analysis and structural equation modeling over thirteen public institutions and AI variables confirmed three factors (or domains) of public trust: trust in healthcare institutions, trust in fellow civic institutions other than healthcare, and trust in AI. Measurement invariance testing of mean levels of public trust along each distinct component revealed that as compared with 2022, in 2023, (1) trust in healthcare institutions and in fellow civic institutions other than healthcare significantly increased and (2) trust in AI remained approximately level. Next, latent profile modeling revealed four levels of a common public trust profile, with all three domains of public trust being normatively closely associated. Taken together, these results suggest that a psychological stance of public trust, PT, may increase after a societal crisis.
在新冠疫情全球大流行期间,对公共机构的信任受到了挑战,人们对医疗机构以及其他公共机构普遍不信任。与此同时,一种新的公共机构或社交工具——大众市场人工智能(AI)更广泛地出现了,它也可能成为公众信任波动的对象。利用英国数据伦理与创新中心的全国调查数据(调查年份:2022年,N = 4320;调查年份:2023年,N = 4232),我们采用自然主义准实验设计,探讨了英国在新冠疫情期间及疫情刚结束后对公民机构(医疗、非医疗和人工智能)的信任程度。在两个调查阶段(2022年和2023年),对13个公共机构和人工智能变量进行主成分分析和结构方程建模,确认了公众信任的三个因素(或领域):对医疗机构的信任、对除医疗之外的其他公民机构的信任以及对人工智能的信任。对每个不同组成部分的公众信任平均水平进行测量不变性测试表明,与2022年相比,2023年,(1)对医疗机构和对除医疗之外的其他公民机构的信任显著增加,(2)对人工智能的信任基本保持不变。接下来,潜在剖面建模揭示了公众信任概况的四个水平,公众信任的所有三个领域在规范上密切相关。综上所述,这些结果表明,社会危机过后,公众信任的心理立场(PT)可能会增强。