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Gender and active travel: a qualitative data synthesis informed by machine learning.
Emily Haynes1, Judith Green2, Ruth Garside3
1European Centre for Environment & Human Health, University of Exeter Medical School, Truro, UK. e.c.haynes@exeter.ac.uk.
The International Journal of Behavioral Nutrition and Physical Activity
|December 23, 2019
Summary
This study used machine learning to analyze qualitative data on active travel, revealing gendered differences in commuting practices and safety perceptions. Findings can inform gender-sensitive policies for promoting physical activity.
Area of Science:
- Social Sciences
- Public Health
- Transportation Studies
Background:
- Population-level physical activity requires innovative approaches beyond individual behavior change.
- Social practice theory offers insights into active living but is often based on small-scale qualitative studies.
- Upscaling insights requires synthesizing data from multiple studies to identify broader patterns.
Purpose of the Study:
- To explore gendered patterns in active travel using pooled qualitative data.
- To apply machine learning techniques to large qualitative datasets for social science research.
- To identify differences in practices and discourses related to active travel between genders.
Main Methods:
- Pooled data from 280 transcripts across five UK qualitative research projects.
- Unsupervised topic modeling analysis using Leximancer text analytics software.
- Researcher-led interpretive analysis guided by social practice theory.
Main Results:
- Identified interrelated and relating practices in commuting, with gendered differences.
- Women's commutes were often multifunctional (e.g., school run, shopping).
- Men's commutes were more linear, with 'relating' practices (e.g., showering, relaxing).
- Gendered differences in discourse: women focused on subjective safety, men on external conditions.
- Machine learning identified differences in co-occurrence of practices and discourses between genders.
Conclusions:
- Machine learning application to qualitative data revealed significant gendered differences in active travel.
- Findings highlight the need for gender-sensitive strategies in promoting physical activity through travel.
- Results can inform future research and policy for inclusive active travel promotion.
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