A significant challenge to measuring human-automation trust is the amount of construct proliferation, models, and questionnaires with highly variable validation. However, all agree that trust is a crucial element of technological acceptance, continued usage, fluency, and teamwork. Herein, we synthesize a consensus model for trust in human-automation interaction by performing a meta-analysis of validated and reliable trust survey instruments. To accomplish this objective, this work identifies the most frequently cited and best-validated human-automation and human-robot trust questionnaires, as well as the most well-established factors, which form the dimensions and antecedents of such trust. To reduce both confusion and construct proliferation, we provide a detailed mapping of terminology between questionnaires. Furthermore, we perform a meta-analysis of the regression models that emerged from those experiments which used multi-factorial survey instruments. Based on this meta-analysis, we demonstrate a convergent experimentally validated model of human-automation trust. This convergent model establishes an integrated framework for future research. It identifies the current boundaries of trust measurement and where further investigation is necessary. We close by discussing choosing and designing an appropriate trust survey instrument. By comparing, mapping, and analyzing well-constructed trust survey instruments, a consensus structure of trust in human-automation interaction is identified. Doing so discloses a more complete basis for measuring trust emerges that is widely applicable. It integrates the academic idea of trust with the colloquial, common-sense one. Given the increasingly recognized importance of trust, especially in human-automation interaction, this work leaves us better positioned to understand and measure it.

翻译：人机信任测量面临的一个重大挑战是构念扩散、模型繁多以及问卷验证水平参差不齐。然而，各方均认同信任是技术接受、持续使用、流畅交互和团队协作的关键要素。本文通过对经过验证且可靠的人机信任调查工具进行元分析，综合提出了人机交互中信任的共识模型。为实现这一目标，本研究识别了被引用最多且验证最佳的人机信任与人机信任问卷，以及构成此类信任维度与前置因素的最成熟因子。为减少概念混淆与构念扩散，我们提供了问卷间术语的详细映射。此外，我们对采用多因子调查工具的实验所涌现的回归模型进行了元分析。基于此元分析，我们论证了一个收敛且经实验验证的人机信任模型。该收敛模型为未来研究建立了整合框架，界定了当前信任测量的边界及需进一步探究的领域。本文最后讨论了如何选择与设计恰当的信任调查工具。通过比较、映射与分析结构良好的信任调查工具，确定了人机交互中信任的共识结构。此举揭示了更具普适性的信任测量基础，将学术层面的信任概念与日常实践中的常识性认知相融合。鉴于信任（尤其是人机交互中的信任）日益凸显的重要性，本研究使我们在理解与测量信任方面迈进了更扎实的一步。