| Title |
Risk approximation in decision making: approximative numeric abilities predict advantageous decisions under objective risk
|
|---|---|
| Published in |
Cognitive Processing, January 2018
|
| DOI | 10.1007/s10339-018-0854-9 |
| Pubmed ID | |
| Authors |
Silke M. Mueller, Johannes Schiebener, Margarete Delazer, Matthias Brand |
| Abstract |
Many decision situations in everyday life involve mathematical considerations. In decisions under objective risk, i.e., when explicit numeric information is available, executive functions and abilities to handle exact numbers and ratios are predictors of objectively advantageous choices. Although still debated, exact numeric abilities, e.g., normative calculation skills, are assumed to be related to approximate number processing skills. The current study investigates the effects of approximative numeric abilities on decision making under objective risk. Participants (N = 153) performed a paradigm measuring number-comparison, quantity-estimation, risk-estimation, and decision-making skills on the basis of rapid dot comparisons. Additionally, a risky decision-making task with exact numeric information was administered, as well as tasks measuring executive functions and exact numeric abilities, e.g., mental calculation and ratio processing skills, were conducted. Approximative numeric abilities significantly predicted advantageous decision making, even beyond the effects of executive functions and exact numeric skills. Especially being able to make accurate risk estimations seemed to contribute to superior choices. We recommend approximation skills and approximate number processing to be subject of future investigations on decision making under risk. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 42 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 17% |
| Student > Bachelor | 7 | 17% |
| Student > Master | 5 | 12% |
| Researcher | 4 | 10% |
| Student > Doctoral Student | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 15 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 15 | 36% |
| Medicine and Dentistry | 3 | 7% |
| Nursing and Health Professions | 2 | 5% |
| Computer Science | 2 | 5% |
| Engineering | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 16 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 January 2018.
All research outputs
#18,584,192
of 23,018,998 outputs
Outputs from Cognitive Processing
#245
of 337 outputs
Outputs of similar age
#330,355
of 441,076 outputs
Outputs of similar age from Cognitive Processing
#3
of 4 outputs
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