Results 11 to 20 of about 97,401 (113)

Individual-level loss aversion in riskless and risky choices

Theory and Decision, 2022
Loss aversion can occur in riskless and risky choices. We present novel evidence on both in a non-student sample (660 randomly selected customers of a car manufacturer).
S. Gaechter, Eric J. Johnson, A. Herrmann   +2 more
semanticscholar   +1 more source

The extent of algorithm aversion in decision-making situations with varying gravity

PLoS ONE, 2023
Algorithms already carry out many tasks more reliably than human experts. Nevertheless, some subjects have an aversion towards algorithms. In some decision-making situations an error can have serious consequences, in others not.
I. Filiz, Jan René Judek, Marco Lorenz, Markus Spiwoks   +3 more
semanticscholar   +1 more source

GRADE Guidelines 34: Updated GRADE guidance for imprecision rating using a minimally contextualized approach.

Journal of Clinical Epidemiology, 2022
OBJECTIVE To provide updated guidance on when GRADE users should consider rating down more than one level for imprecision using a minimally contextualized approach.
L. Zeng, R. Brignardello-Petersen, M. Hultcrantz, R. Mustafa, M. Murad, A. Iorio, G. Traversy, E. Akl, Martin Mayer, H. Schünemann, G. Guyatt   +10 more
semanticscholar   +1 more source

GRADE Guidance article 35: Update on rating imprecision for assessing contextualized certainty of evidence and making decisions.

Journal of Clinical Epidemiology, 2022
INTRODUCTION GRADE guidance to rate the certainty domain of imprecision is presently not fully operationalized for rating down by two levels and when different or uncertainty in baseline risks are considered.
H. Schünemann, I. Neumann, M. Hultcrantz, R. Brignardello-Petersen, L. Zeng, M. H. Murad, A. Izcovich, G. P. Morgano, Tejan Baldeh, N. Santesso, Carlos Garcia Cuello, L. Mbuagbaw, G. Guyatt, W. Wiercioch, Thomas Piggott, H. de Beer, M. Vinceti, A. Mathioudakis, Martin Mayer, R. Mustafa, T. Filippini, A. Iorio, R. Nieuwlaat, M. Marcucci, P. A. Coello, S. Bonovas, D. Piovani, George Tomlinson, E. Akl   +28 more
semanticscholar   +1 more source

Factors affecting physicians’ intentions to communicate personalized prognostic information to cancer patients at the end of life: An experimental vignette study

Medical decision making, 2016
Purpose. To explore the effects of personalized prognostic information on physicians’ intentions to communicate prognosis to cancer patients at the end of life, and to identify factors that moderate these effects. Methods.
P. Han, N. Dieckmann, C. Holt, C. Gutheil, E. Peters   +4 more
semanticscholar   +1 more source

Responsible Precautions for Uncertain Environmental Risks

Journal of Benefit-Cost Analysis, 2019
Uncertain future risks pose cognitive and analytical challenges to household decision makers. Risks with uncertain probabilities, coupled with potentially severe outcomes pose problems for decision-making and are prone to overreactions.
W. Viscusi, Joel Huber, Jason Bell
semanticscholar   +1 more source

Decision-maker’s behavioral preferences modeling in fuzzy goal programming through linear-nonlinear membership functions

Results in Control and Optimization
A relevant extension of traditional goal programming (GP), fuzzy goal programming (FGP) can handle uncertainty and imprecision in multi-objective optimization problems.
Mohamed Sadok Cherif
doaj   +1 more source

Reward and aversion processing by input-defined parallel nucleus accumbens circuits in mice

Nature Communications, 2022
The nucleus accumbens (NAc) is critical in mediating reward seeking and is also involved in negative emotion processing, but the cellular and circuitry mechanisms underlying such opposing behaviors remain elusive.
Kuikui Zhou, Huan Xu, Shanshan Lu, Shaolei Jiang, Guoqiang Hou, Xiaofei Deng, Miao He, Yingjie Zhu   +7 more
semanticscholar   +1 more source

Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion

Organization science (Providence, R.I.), 2021
Past research offers mixed perspectives on whether domain experience helps or hurts algorithm-augmented worker performance. Reconciling these perspectives, we theorize that intermediate levels of domain experience are optimal for algorithm-augmented ...
R. Allen, P. Choudhury
semanticscholar   +1 more source

Who is the Expert? Reconciling Algorithm Aversion and Algorithm Appreciation in AI-Supported Decision Making

Proc. ACM Hum. Comput. Interact., 2021
The increased use of algorithms to support decision making raises questions about whether people prefer algorithmic or human input when making decisions.
Yoyo Tsung-Yu Hou, Malte F. Jung
semanticscholar   +1 more source