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Related Concept Videos

Decision Making01:20

Decision Making

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
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Decision Making: Traditional Method01:14

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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
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Reason and Intuition01:37

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Avoidance-avoidance conflict refers to a psychological situation where a person must choose between two or more unpleasant alternatives. These conflicts are particularly stressful because neither option is desirable. This dilemma is often expressed in sayings like "caught between a rock and a hard place" or "between the devil and the deep blue sea." For instance, individuals who fear dental procedures may find themselves torn between enduring a painful toothache or facing the...
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Decision Making: P-value Method01:09

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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
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Cognitive Dissonance01:38

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Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
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Decisionmaking in practice: The dynamics of muddling through.

John M Flach1, Markus A Feufel2, Peter L Reynolds3

  • 1Department of Psychology, Wright State University, Dayton, OH, USA.

Applied Ergonomics
|May 16, 2017
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Summary
This summary is machine-generated.

Conventional decision models are open-loop, but real-world practice, like in healthcare, involves closed-loop, dynamic problem-solving. Adaptive, abductive reasoning, or "muddling through," better reflects this practical decision-making reality.

Keywords:
AbductionAdaptive controlDecisionmakingHeuristicJudgment

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Area of Science:

  • Decision-making science
  • Cognitive psychology
  • Healthcare management

Background:

  • Conventional decision models often assume independent, open-loop choices.
  • Real-world decision-making, particularly in fields like healthcare, is frequently a dynamic, closed-loop process.
  • Existing models may not accurately represent practical decision-making realities.

Purpose of the Study:

  • To present an alternative model for understanding decision-making.
  • To highlight discrepancies between theoretical models and practical application.
  • To propose a more realistic framework for decision-making in complex domains.

Main Methods:

  • Analysis of decision-making in practical work situations, including healthcare.
  • Comparison of conventional decision models with observed practices.
  • Conceptualization of decision-making as a closed-loop, dynamic problem-solving process.

Main Results:

  • Identified five key distinctions between conventional decision models and practical decision-making.
  • Proposed that abductive reasoning, characterized as adaptive "muddling through," aligns better with practice.
  • Demonstrated the limitations of normative rationality models in applied settings.

Conclusions:

  • Decision-making in practice, especially healthcare, is better understood as a dynamic, adaptive process.
  • Abductive reasoning and "muddling through" offer a more accurate framework than traditional models.
  • Future design efforts should focus on enhancing the "muddling through" process for greater functional insight, rather than enforcing normative rationality.