Behaviour Change Towards Cycling in 7 Case Study Cities. (June 2017)

• Record Type: Journal Article
• Authors: Boig, Ester Anaya; de Nazelle, Audrey; Götschi, Thomas; Gerike, Regine; Pierotti, Livia; Kahlmeier, Sonja; Cole-Hunter, Tom; Nieuwenhuijsen, Mark; Panis, Luc Int; Rojas-Rueda, David; Avila-Palencia, Ione
• Is Part Of: Journal of transport & health. Volume 5(2017)Supplement
• Page Start: S103
• Page End: S104
• Publication Date: 2017-06
• Subjects: Transportation -- Health aspects -- Periodicals; Transportation -- Periodicals; Public Health -- Periodicals; Noise, Transportation -- Periodicals; Air Pollutants -- Periodicals; 388
• DOI: 10.1016/j.jth.2017.05.263
• Languages: English
• ISSNs: 2214-1405

Abstract

Abstract : Background: In order to increase the levels of physical activity in urban population, it is essential to know how a behavioural change towards cycling as active mobility can be produced and what factors influence people in their choice to cycle. But few studies have done longitudinal analysis of behavioural changes in cycling in relation to their policy context. Methods: As part of the PASTA European project (Physical Activity through Sustainable Travel Approaches), a longitudinal survey in 7 European cities will provide the core data for the analysis. This survey was closed the 13th January 2017, after 2 years of data collection. The PASTA survey features specific questions designed to determine the attitudinal and behavioural profile of the participants. The conceptual framework used for the behavioural change assessment features an adaptation of the Transtheoretical Model of Behaviour Change and further developments, which describes five stages of change: Precontemplation, Contemplation, Preparation, Action and Maintenance. The sub-set of questions to determine the stage of change diagnosis are included in the initial (baseline) and final questionnaires, so that a "before" and "after" analysis can be undertaken. Other relevant psycho-social variables featured in the questionnaires will also be explored. The survey data is being complemented with background information including cycling policy and GIS data. Results: Our sample is 10, 557 participants across the seven cities (subject to further data cleaning). For this sample, a cross-city analysis of behavioural questions will be explored and compared for the initial (baseline) and final questionnaires. The baseline questionnaire has been already analysed and is showing a share of 23% of the sub-sampled participants (n=7, 580) in the Precontemplation stage, 7% in Contemplation, 18% in Preparation, 41% in Action and 11% in Maintenance. In this presentation, results will be shown from the complete dataset (that is including all questionnaires) detailed for each of the seven cities, which is being analysed at the moment. The results of the stage diagnosis will be crossed with several socio-demographic variables, such as income, age, education level and sex. As an example, mean age is 40.08 (13.04) years and 54% of the participants are female. Conclusions: Understanding the relative importance of the factors influencing mobility behaviour will help to determine the most promising policy avenues for the change towards cycling. This study puts together a unique mix of theories and methods in order to explore the bridges between behavioural change science and policy making.