Literature DB >> 25917611

The Role of Trust as a Mediator Between System Characteristics and Response Behaviors.

Eric T Chancey1, James P Bliss2, Alexandra B Proaps2, Poornima Madhavan3.   

Abstract

OBJECTIVE: The purpose of the current work was to clarify how subjective trust determines response behavior when interacting with a signaling system.
BACKGROUND: In multiple theoretical frameworks, trust is acknowledged as a prime mediator between system error characteristics and automation dependence. Some researchers have operationally defined trust as the behavior exhibited. Other researchers have suggested that although trust may guide operator responses, trust does not completely determine the behavior.
METHOD: Forty-four participants interacted with a primary flight simulation task and a secondary signaling system task. The signaling system varied in reliability (90%, 60%) and error bias (false alarm, miss prone). Trust was measured halfway through the experimental session to address the criterion of temporal precedence in determining the effect of trust on behavior.
RESULTS: Analyses indicated that trust partially mediated the relationship between reliability and agreement rate. Trust did not mediate the relationship between reliability and reaction time. Trust also did not mediate the relationships between error bias and reaction time or agreement rate. Analyses of variance generally supported specific behavioral and trust hypotheses, indicating that the paradigm employed produced similar effects on response behaviors and subjective estimates of trust observed in other studies.
CONCLUSION: These results indicate that strong assumptions of trust acting as the prime mediator between system error characteristics and response behaviors should be viewed with caution. APPLICATION: Practitioners should consider assessing factors other than trust to determine potential operator response behaviors, which may be more predictive.
© 2015, Human Factors and Ergonomics Society.

Entities:  

Keywords:  human–automation interaction; reliability issues; trust in automation; warning compliance; warning systems

Mesh:

Year:  2015        PMID: 25917611     DOI: 10.1177/0018720815582261

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  5 in total

Review 1.  Trust in Robots: Challenges and Opportunities.

Authors:  Bing Cai Kok; Harold Soh
Journal:  Curr Robot Rep       Date:  2020-09-03

2.  CX-ToM: Counterfactual explanations with theory-of-mind for enhancing human trust in image recognition models.

Authors:  Arjun R Akula; Keze Wang; Changsong Liu; Sari Saba-Sadiya; Hongjing Lu; Sinisa Todorovic; Joyce Chai; Song-Chun Zhu
Journal:  iScience       Date:  2021-12-11

Review 3.  From Trust in Automation to Decision Neuroscience: Applying Cognitive Neuroscience Methods to Understand and Improve Interaction Decisions Involved in Human Automation Interaction.

Authors:  Kim Drnec; Amar R Marathe; Jamie R Lukos; Jason S Metcalfe
Journal:  Front Hum Neurosci       Date:  2016-06-30       Impact factor: 3.169

4.  Approaching the Discriminatory Work Environment as Stressor: The Protective Role of Job Satisfaction on Health.

Authors:  Donatella Di Marco; Rocio López-Cabrera; Alicia Arenas; Gabriele Giorgi; Giulio Arcangeli; Nicola Mucci
Journal:  Front Psychol       Date:  2016-08-30

5.  The effects of personality and locus of control on trust in humans versus artificial intelligence.

Authors:  Navya Nishith Sharan; Daniela Maria Romano
Journal:  Heliyon       Date:  2020-08-28
  5 in total

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