The first part of the project aimed to identify strategies and techniques that people can use to self-manage their self-determined motivation, or to change behavior more generally. By pulling together existing taxonomies of behavior change techniques, and by conducting reviews of self-management strategies from sport, education and workplace psychology, we have developed a listing of self-enactable techniques. This listing (and toolkit), published in Nature Human Behaviour, will offer theorists as well as intervention developers clear definitions and examples of the agentic actions people can themselves take to change or self-manage motivation and behavior.
The second part of the project investigated the extents to which quality of work motivation fluctuates, and aimed to identify factors that predict significant changes in self-determined motivation. These could include changes in social context, work task, the use of self-management strategies and other variables such as sleep quality and stress. By using ecological momentary assessment (EMA) methods embedded in a smartphone app, this study allowed us to additionally test the primary relationships between self-determined motivation and psychological needs satisfaction proposed by self-determination theory using within-persons (as opposed to between-persons) data.
The final part of the project involves developing and evaluating an intervention that integrates the findings of the first two parts of the project. This study tests whether people can be helped to achieve and maintain an optimal motivational profile, wherein autonomous forms of motivation drive behavior more than (less adaptive) controlled forms of motivation.
Funding: Academy of Finland (grant no 295765), years 2016-20
Self-determined motivation for work and health: investigating fluctuations and identifying effective strategies for motivational self-management / Omaehtoinen motivaatio: Yksilöllisten motivaation hallintakeinojen koonti sekä työ- ja liikuntamotivaation ajallisen vaihtelun tutkimus
Project team:
University Researcher Keegan Knittle
Doctoral student Matti Heino
Research assistant Raisamiina Rimpelä
Previous staff: Franziska Ehbrecht, Marguerite Beattie, Minna Stenius
Principal investigator: Assistant professor Nelli Hankonen
Other collaborators: Jari Hakanen, Richard Ryan, Marylene Gagne, Wendy Hardeman, Martin Hagger, Marta Marques
Collaborators at TNO: Koen Hogenelst, Ferry Jagers, Tanja Krone, Roos Schelvis