Attractor landscapes: a unifying conceptual model for understanding behaviour change across scales of observation

Matti T.J. Heino, Daniele Proverbio, Gwen Marchand, Kenneth Resnicow, Nelli Hankonen

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)655-672
Number of pages18
JournalHealth Psychology Review
Volume17
Issue number4
DOIs
StatePublished - 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • Attractor landscape
  • behaviour change
  • complex systems
  • complexity
  • dynamics

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