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The predictive validity of implicit measures of self-determined motivation across health-related behaviours


David Keatley, Personality, Social Psychology, and Health Research Group, School of Psychology, University of Nottingham, University Park, Nottingham NG7 2RD, UK (e-mail:


Objective. Research on health-related behaviour has typically adopted deliberative models of motivation and explicit measures. However, growing support for implicit processes in motivation and health-related behaviour has caused a shift towards developing models that incorporate implicit and explicit processes.

Methods. The current research advances this area by comparing the predictive validity of a newly developed implicit measure of motivation from self-determination theory (SDT) with explicit measures of motivation for 20 health-related behaviours, in a sample of undergraduate students (N= 162). A dual systems model was developed to test whether implicit motivation provided unique prediction of behaviour.

Results. Structural equation models for each behaviour indicated some support for the role of implicit measures; explicit measures and intention provided more consistent, significant prediction across most behaviours.

Conclusions. This study provides some support for dual systems models, and offers an important contribution to understanding why some behaviours may be better predicted by either implicit or explicit measures. Future implications for implicit processes and SDT are outlined.

Statement of contribution

What is already known on this subject? 

Previous research has highlighted the unique effects of implicit processes on goal-directed behaviour. Several studies have supported the role of implicit processes in motivation.

What does this study add? 

The current study adds to the previous literature by investigating the role of implicit processes and self-determination theory. Furthermore, the current study uses a relatively novel implicit measure across a wide range of behaviours. Finally, the current study incorporates a dual-systems model to provide a conceptual understanding of the findings.