[en] Models and theories in behaviour change science are not in short supply, but they almost exclusively pertain to a particular facet of behaviour, such as automaticity or reasoned action, or to a single scale of observation such as individuals or communities. We present a highly generalisable conceptual model which is widely used in complex systems research from biology to physics, in an accessible form to behavioural scientists. The proposed model of attractor landscapes can be used to understand human behaviour change on different levels, from individuals to dyads, groups and societies. We use the model as a tool to present neglected ideas in contemporary behaviour change science, such as hysteresis and nonlinearity. The model of attractor landscapes can deepen understanding of well-known features of behaviour change (research), including short-livedness of intervention effects, problematicity of focusing on behavioural initiation while neglecting behavioural maintenance, continuum and stage models of behaviour change understood within a single accommodating framework, and the concept of resilience. We also demonstrate potential methods of analysis and outline avenues for future research.
Disciplines :
Sciences sociales & comportementales, psychologie: Multidisciplinaire, généralités & autres
Auteur, co-auteur :
Heino, Matti; Tampere University
PROVERBIO, Daniele ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Interventional Neuroscience
Marchand, Gwen; University of Nevada
Resnicow, Kenneth; University of Michigan
Hankonen, Nelli; Tampere University
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Attractor landscapes: a unifying conceptual model for understanding behaviour change across scales of observation
Date de publication/diffusion :
décembre 2022
Titre du périodique :
Health Psychology Review
ISSN :
1743-7199
eISSN :
1743-7202
Maison d'édition :
Routledge, Taylor & Francis Group, Royaume-Uni
Peer reviewed :
Peer reviewed vérifié par ORBi
Focus Area :
Physics and Materials Science
Projet FnR :
FNR10907093 - Critical Transitions In Complex Systems: From Theory To Applications, 2015 (01/11/2016-30/04/2023) - Jorge Gonçalves
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