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Segmenting children's active school travel behaviour: insights on caregivers' perceived risks and social norms.
- Source :
- Health Education (0965-4283); 2022, Vol. 122 Issue 4, p456-468, 13p
- Publication Year :
- 2022
-
Abstract
- Purpose: Active school travel (AST) programmes aim to change commuting behaviour to improve children's physical and mental health. However, very limited health education programmes for children use segmentation to create tailored solutions that understand the specific characteristics of each group of children and their caregivers in order to yield better results. The aim of this study is to use a statistical segmentation analysis (two-step cluster analysis) to gain insights on the examination of specific groups to design future health education interventions and campaigns that can improve children's health. Design/methodology/approach: Guided by the Ecological and Cognitive Active Commuting (ECAC) framework, a market segmentation analysis was performed. An online survey was designed to collect data from caregivers of children between 5 and 12 years attending school and responsible for taking the child to and/or from school in Victoria and Queensland, Australia. Using 3,082 responses collected from Australian caregivers of primary school children, a two-step cluster analysis was performed. Findings: Analysis revealed the most important variables for group formation were previous child walking behaviour, distance from school and caregiver income. Perceived risk of the physical environment was the most important psychographic segmentation variable for group formation, followed by social norms. Four distinct groups with different characteristics were identified from the analysis. Originality/value: This is the first study that applies the ECAC framework to perform market segmentation in the AST context. Results revealed four market segments that demand different tailored solutions. Findings shed light on how to better design AST interventions and campaigns to promote children's health using segmentation techniques. [ABSTRACT FROM AUTHOR]
- Subjects :
- HEALTH education
CAREGIVER attitudes
TRAVEL
MATHEMATICAL models
SOCIAL norms
ONE-way analysis of variance
CHILD behavior
ECOLOGY
SURVEYS
INCOME
RISK assessment
PSYCHOLOGY of caregivers
CHILDREN'S health
THEORY
CHI-squared test
WALKING
EMPLOYMENT
CLUSTER analysis (Statistics)
DATA analysis software
SCHOOL children
HEALTH promotion
Subjects
Details
- Language :
- English
- ISSN :
- 09654283
- Volume :
- 122
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Health Education (0965-4283)
- Publication Type :
- Academic Journal
- Accession number :
- 156419521
- Full Text :
- https://doi.org/10.1108/HE-09-2021-0120