The implicit power motive predicts action selection
Publication year
2017Number of pages
11 p.
Source
Psychological Research, 81, 3, (2017), pp. 560-570ISSN
Publication type
Article / Letter to editor
Display more detailsDisplay less details
Organization
SW OZ BSI AO
Journal title
Psychological Research
Volume
vol. 81
Issue
iss. 3
Languages used
English (eng)
Page start
p. 560
Page end
p. 570
Subject
Work, Health and PerformanceAbstract
Previous research has indicated that implicit motives can reliably predict which behaviors people select or decide to perform. However, so far, the question of how these motives are able to predict this action selection process has received little attention. Based on ideomotor theory, we argue that implicit motives can predict action selection when an action has become associated with a motive-congruent (dis)incentive through repeated experiences with the action-outcome relationship. This idea was investigated by examining whether the implicit need for power (nPower) would come to predict action selection (i.e., choosing to press either of two buttons) when these actions had repeatedly resulted in motive-congruent (dis)incentives (i.e., submissive or dominant faces). Both Studies 1 and 2 indicated that participants became more likely to select the action predictive of the motive-congruent outcome as their history with the action-outcome relationship increased. Study 2 indicated that this effect stemmed from both an approach towards incentives and an avoidance of disincentives. These results indicate that implicit motives (particularly the power motive) can predict action selection as a result of learning which actions yield motive-congruent (dis)incentives. Our findings therefore offer a model of how implicit motives can come to predict which behaviors people select to perform.
This item appears in the following Collection(s)
- Academic publications [243399]
- Electronic publications [129932]
- Faculty of Social Sciences [29983]
- Open Access publications [104456]
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.