Premium
Decision Pattern Analysis as a General Framework for Studying Individual Differences in Decision Making
Author(s) -
Jackson Simon A.,
Kleitman Sabina,
Stankov Lazar,
Howie Pauline
Publication year - 2016
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.1887
Subject(s) - psychology , competence (human resources) , cognition , personality , metacognition , social psychology , cognitive psychology , neuroscience
This paper investigated decision pattern analysis (DPA) as a general and standard framework for studying individuals' consistent decision making behavior within and between contexts. DPA classifies decisions on the basis of judgement accuracy and the goal orientation of the decided‐upon action. Over repeated decisions, patterns of individuals' decision behavior are described by five variables: competence, optimality, recklessness, hesitancy and decisiveness. A fictitious medical decision making test and three standard cognitive ability tests (extended with confidence ratings and a ‘submit answer for marking’ decision) were used to investigate the psychometric properties of these DPA variables. Internal consistency of the decision patterns ranged from good to excellent. Convergent validity was assessed via cognitive abilities, metacognitive confidence and a control criterion imposed on confidence that determines the decision to be made: the point of sufficient certainty. Personality variables were included to assess discriminant validity. As hypothesised, cognitive abilities showed positive correlations with competence and optimality. High confidence, low points of sufficient certainty and a greater discrepancy between them were associated with higher decisiveness and recklessness, and lower hesitancy. Personality measures showed mixed and generally weak correlations with the DPA variables. These convergent and discriminant results also held after controlling for all variables in regression. The results provide preliminary psychometric support for DPA as a general framework of behavioral decision making. DPA has the potential to be exploited in many contexts for uses that, to date, have been unachievable in a psychometrically valid manner. Copyright © 2015 John Wiley & Sons, Ltd.