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- W2332079078 abstract "Objective: We used meta-analysis to assess research concerning human trust in automation to understand the foundation upon which future autonomous systems can be built. Background: Trust is increasingly important in the growing need for synergistic human–machine teaming. Thus, we expand on our previous meta-analytic foundation in the field of human–robot interaction to include all of automation interaction. Method: We used meta-analysis to assess trust in automation. Thirty studies provided 164 pairwise effect sizes, and 16 studies provided 63 correlational effect sizes. Results: The overall effect size of all factors on trust development was ḡ = +0.48, and the correlational effect was [Formula: see text] = +0.34, each of which represented medium effects. Moderator effects were observed for the human-related ( ḡ = +0.49; [Formula: see text] = +0.16) and automation-related ( ḡ = +0.53; [Formula: see text] = +0.41) factors. Moderator effects specific to environmental factors proved insufficient in number to calculate at this time. Conclusion: Findings provide a quantitative representation of factors influencing the development of trust in automation as well as identify additional areas of needed empirical research. Application: This work has important implications to the enhancement of current and future human–automation interaction, especially in high-risk or extreme performance environments." @default.
- W2332079078 created "2016-06-24" @default.
- W2332079078 creator A5005165657 @default.
- W2332079078 creator A5007652754 @default.
- W2332079078 creator A5029052652 @default.
- W2332079078 creator A5046204847 @default.
- W2332079078 date "2016-03-22" @default.
- W2332079078 modified "2023-10-16" @default.
- W2332079078 title "A Meta-Analysis of Factors Influencing the Development of Trust in Automation" @default.
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