TY - JOUR
T1 - The construct of state-level suspicion
T2 - A model and research agenda for automated and information technology (IT) contexts
AU - Bobko, Philip
AU - Barelka, Alex J.
AU - Hirshfield, Leanne M.
N1 - Funding Information:
This material is based upon work supported by the U.S. Air Force Office of Scientific Research (AFOSR). Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the AFOSR. We thank the action editor, two reviewers, and Heather Odle-Dusseau for helpful comments on an earlier draft of this article.
PY - 2014/5
Y1 - 2014/5
N2 - 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.
AB - 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.
KW - distrust
KW - information technology
KW - state suspicion
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U2 - 10.1177/0018720813497052
DO - 10.1177/0018720813497052
M3 - Article
C2 - 24930171
AN - SCOPUS:84898981886
SN - 0018-7208
VL - 56
SP - 489
EP - 508
JO - Human Factors
JF - Human Factors
IS - 3
ER -