The Construct of State-Level Suspicion: A Model and Research Agenda for Automated and Information Technology (IT) Contexts

OBJECTIVE The objective was to review and integrate available research about the construct of state-level suspicion as it appears in social science literatures and apply the resulting findings to information technology (IT) contexts. BACKGROUND Although the human factors literature is replete with articles about trust (and distrust) in automation, there is little on the related, but distinct, construct of "suspicion" (in either automated or IT contexts). The construct of suspicion--its precise definition, theoretical correlates, and role in such applications--deserves further study. METHOD Literatures that consider suspicion are reviewed and integrated. Literatures include communication, psychology, human factors, management, marketing, information technology, and brain/neurology. We first develop a generic model of state-level suspicion. Research propositions are then derived within IT contexts. RESULTS Fundamental components of suspicion include (a) uncertainty, (b) increased cognitive processing (e.g., generation of alternative explanations for perceived discrepancies), and (c) perceptions of (mal)intent. State suspicion is defined as the simultaneous occurrence of these three components. Our analysis also suggests that trust inhibits suspicion, whereas distrust can be a catalyst of state-level suspicion. Based on a three-stage model of state-level suspicion, associated research propositions and questions are developed. These propositions and questions are intended to help guide future work on the measurement of suspicion (self-report and neurological), as well as the role of the construct of suspicion in models of decision making and detection of deception. CONCLUSION The study of suspicion, including its correlates, antecedents, and consequences, is important. We hope that the social sciences will benefit from our integrated definition and model of state suspicion. The research propositions regarding suspicion in IT contexts should motivate substantial research in human factors and related fields.