TY  - JOUR
PY  - 2022//
TI  - Modeling responses to alarm systems: a drift diffusion model approach
JO  - Proceedings of the Human Factors and Ergonomic Society annual meeting
A1  - Rieger, Tobias
A1  - Koob, Valentin
A1  - Parnassa, Tomer
A1  - Manzey, Dietrich
A1  - Meyer, Joachim
SP  - 711
EP  - 715
VL  - 66
IS  - 1
N2  - In numerous applications, alarm systems play an important role, supporting human decision-making. So far, however, little research dealt with the cognitive mechanisms that are at play in alarm-supported decision-making. In the present study, we aim to disentangle underlying cognitive mechanisms by using drift diffusion modeling. The results showed that going beyond standard approaches of analyzing alarm-system supported binary decision tasks can reveal results unlikely to be captured otherwise. That is, the analyses revealed that the alarm system?s output biased the decision-making process, requiring less evidence to be sampled for agreeing with the system than for disagreeing with the system. Moreover, evidence was accumulated faster on correct than on incorrect alarm system recommendations. Thus, the present results point to promising directions for gaining a more fine-grained picture of automation supported decision making.<p />  <p>Language: en</p>
LA  - en
SN  - 2169-5067
UR  - http://dx.doi.org/10.1177/1071181322661389
ID  - ref1
ER  -