Data · dataset · 2021
Software and results for: An agent-based model for simulating the impact of social norms on active commuting interventions
Listed in LSHTM Data Compass
Interventions to increase active commuting have been recommended as a method to increase population physical activity, but evidence is mixed.
Description
Social norms related to travel behaviour may influence the uptake of active commuting interventions but are rarely considered in the design and evaluation of interventions. In this study we develop an agent-based model that incorporates social norms related to travel behaviour and simulate the relative impact of four active commuting interventions.
A synthetic population of Waltham Forest, London, UK was generated using a microsimulation approach with data from the UK Census 2011 and UK HLS datasets. An agent-based model was created using this synthetic population which modelled how the actions of peers and neighbours, subculture, habit, weather, bicycle ownership, car ownership, environmental supportiveness, and congestion affect the decision to travel between four modes: walking, cycling, driving, and taking public transport.
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We examined four scenarios (and a control): car-free days; increasing environmental supportiveness for walking and cycling; decreasing environmental supportiveness for driving; increasing environmental supportiveness for walking and decreasing environmental supportiveness for driving. Compared to the control scenario, the car-free days scenario increased the odds of active commuting by 81.8% (OR 1.818; 95% CrI: [1.816 to 1.820]).
Increasing environmental supportiveness for walking and cycling had no effect (OR: 1.000; 95% CrI: [1.000 to 1.001]), as did decreasing environmental supportiveness for driving (OR: 1.000; 95% CrI: [0.999 to 1.001]), and increasing environmental supportiveness for walking and cycling while decreasing environmental supportiveness for driving (OR: 1.000; 95% CrI: [1.000 to 1.001]). These results provide support for car-free days as an intervention to ‘nudge’ people into active commuting.
However, why built environment interventions were less effective is unclear.
Links
Where it is published
- DOI doi.org/10.5281/zenodo.4916753 ↗
DOI / persistent id · from lshtm ac uk
Catalogue records · 1
- OAI-PMH record datacompass.lshtm.ac.uk/cgi/oai2?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3… ↗
metadata API · from lshtm ac uk
Topics
- From keywords
- Earth & Environmental Science · Humanities · Life Sciences · Medicine & Health · Social Science
- Inferred from text
- Sociology 71%
Related
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| LSHTM Data Compass | oai:datacompass.lshtm.ac.uk:2425 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4410 | enrichment · lshtm ac uk | taxonomy-embedding@1.0.0 | title+keywords+description (71%) |
| concepts[field].local:field:earth-environmental | mapping · lshtm ac uk | connector:lshtm_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · lshtm ac uk | connector:lshtm_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · lshtm ac uk | connector:lshtm_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · lshtm ac uk | connector:lshtm_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · lshtm ac uk | connector:lshtm_ac_uk@1.0.0 | |
| description | source · lshtm ac uk | connector:lshtm_ac_uk@1.0.0 | /metadata/dc/description |
| publication_date | source · lshtm ac uk | connector:lshtm_ac_uk@1.0.0 | |
| title | source · lshtm ac uk | connector:lshtm_ac_uk@1.0.0 | /metadata/dc/title |