Understanding active school travel through the Behavioural Ecological Model

Samuel Ginja, Bronia Arnott, Anil Namdeo, Elaine McColl

Research output: Contribution to journalArticle

8 Citations (Scopus)
200 Downloads (Pure)

Abstract

Active school travel (AST) is an important source of physical activity for children and a conceptual understanding of AST is necessary to inform promotion efforts. The aim of this article is to provide a conceptual analysis of AST. All currently identified AST formulations include intra-individual variables which are often recommended as intervention targets. However, existing literature lacks clarity on precisely how these intra-individual variables might shape specific AST interventions. Moreover, evaluative studies of AST interventions typically fail to specify an underpinning theory or model. To address this limitation, the Behavioural Ecological Model (BEM), not previously addressed in AST, is presented to guide this area of research. Based on specific examples, we draw attention to the role of potential antecedents and potential reinforcers of AST, as well as potential reinforcers of motorised travel. Antecedents and reinforcers may help to explain choices of school travel mode, and to inform and increase intervention options to promote AST. Consistent with the BEM, the provision of more immediate consequences, such as fun and material prizes, is an evidence-based strategy for increasing AST which is likely to be low-cost and easier to deliver than alternative interventions. This approach to the study of AST is expected to contribute to similar analyses in this and other areas of behaviour change research, and to a more useful discussion and treatment of theoretical and conceptual behavioural models.
Original languageEnglish
Pages (from-to)58-74
JournalHealth Psychology Review
Volume12
Issue number1
Early online date3 Nov 2017
DOIs
Publication statusPublished - 23 Nov 2017

Keywords

  • Travel behaviour
  • Theory
  • Models
  • Antecedents and reinforcers
  • contingencies

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