Using confirmatory factor analyses and multiple indicators per construct, we examined a number of theoretically derived factor structures pertaining to numerous trust-relevant constructs (from 9 to12) across four institutional contexts (police, local governance, natural resources, state governance) and multiple participant-types (college students via an online survey, community residents as part of a city’s budget engagement activity, a random sample of rural landowners, and a national sample of adult Americans via an Amazon Mechanical Turk study). Across studies, a number of common findings emerged. First, the best fitting models in each study maintained separate factors for each trust-relevant construct. Furthermore, post hoc analyses involving addition of higher-order factors tended to fit better than collapsing of factors. Second, dispositional trust was easily distinguishable from the other trust-related constructs, and positive and negative constructs were often distinguishable. However, the items reflecting positive trust attitude constructs or positive trustworthiness perceptions showed low discriminant validity. Differences in findings between studies raise questions warranting further investigation in future research, including differences in correlations among latent constructs varying from very high (e.g., 12 inter-factor correlations above .9 in Study 2) to more moderate (e.g., only 3 correlations above .8 in Study 4). Further, the results from one study (Study 4) suggested that legitimacy, fairness, and voice were especially highly correlated and may form a single higher-order factor, but the other studies did not. Future research is needed to determine when and why different higher-order factor structures may emerge in different institutional contexts or with different samples.

The majority of trust research has focused on the benefits trust can have for individual actors, institutions, and organizations. This “optimistic bias” is particularly evident in work focused on institutional trust, where concepts such as procedural justice, shared values, and moral responsibility have gained prominence. But trust in institutions may not be exclusively good. We reveal implications for the “dark side” of institutional trust by reviewing relevant theories and empirical research that can contribute to a more holistic understanding. We frame our discussion by suggesting there may be a “Goldilocks principle” of institutional trust, where trust that is too low (typically the focus) or too high (not usually considered by trust researchers) may be problematic. The chapter focuses on the issue of too-high trust and processes through which such too-high trust might emerge. Specifically, excessive trust might result from external, internal, and intersecting external-internal processes. External processes refer to the actions institutions take that affect public trust, while internal processes refer to intrapersonal factors affecting a trustor’s level of trust. We describe how the beneficial psychological and behavioral outcomes of trust can be mitigated or circumvented through these processes and highlight the implications of a “darkest” side of trust when they intersect. We draw upon research on organizations and legal, governmental, and political systems to demonstrate the dark side of trust in different contexts. The conclusion outlines directions for future research and encourages researchers to consider the ethical nuances of studying how to increase institutional trust.

The purpose of this volume is to consider how trust research, particularly trust in institutions, might benefit from increased inter- or transdisciplinarity. In this introductory chapter, we first give some background on prior disciplinary, multidisciplinary, and interdisciplinary work relating to trust. Next, we describe how this many-disciplined volume on institutional trust emerged from the joint activities of the Nebraska Symposium on Motivation and a National Science Foundation-funded Workshop on institutional trust. This chapter describes some of the themes that emerged, while also providing an overview of the rest of the volume, which includes chapters that discuss conceptualizations, definitions, and measurement of trust; institutional trust across domains and contexts; and theoretical advances regarding the “dark” and “light” sides of institutional trust. Finally, we conclude with some thoughts about the future of and potential promises and pitfalls of trust as a focus of interdisciplinary study.

Examinations of trust have advanced steadily over the past several decades, yielding important insights within criminal justice, economics, environmental studies, management and industrial organization, psychology, political science, and sociology. Cross-disciplinary approaches to the study of trust, however, have been limited by differences in defining and measuring trust and in methodological approaches. In this chapter, we take the position that: 1) cross-disciplinary studies can be improved by recognizing trust as a multilevel phenomenon, and 2) context impacts the nature of trusting relations. We present an organizing framework for conceptualizing trust between trustees and trustors at person, group, and institution levels. The differences between these levels have theoretical implications for the study of trust and that might be used to justify distinctions in definitions and methodological approaches across settings. We highlight where the levels overlap and describe how this overlap has created confusion in the trust literature to date. Part of the overlap – and confusion – is the role of interpersonal trust at each level. We delineate when and how interpersonal trust is theoretically relevant to conceptualizing and measuring trust at each level and suggest that other trust-related constructs, such as perceived legitimacy, competence, and integrity, may be more important than interpersonal trust at some levels and in some contexts. Translating findings from trust research in one discipline to another and collaborating across disciplines may be facilitated if researchers ensure that their levels of conceptualization and measurement are aligned, and that models developed for a particular context are relevant in other, distinct contexts.