Gender-Based Heat Map Images of Campus Walking Settings: A Reflection of Lived Experience.
Robert A ChaneyAlyssa BaerL Ida TovarPublished in: Violence and gender (2024)
Fear of crime can influence our view of and experience with the world around us. This can be problematic for individuals seeking physical activity, including from walk commuting. Prior work shows fear is especially evident among women, who report fear of rape and sexual abuse by men as a primary concern. We present the results of a cross-sectional survey ( n = 571) where participants were shown images from college campus ( n = 4 campuses) depicting different lighting (daytime, nighttime), and entrapment levels (high, low; i.e., able to easily escape if needed, with high entrapment being difficult and low being easy), and using the Qualtrics heat map tool, selected features that stood out to them most. Data were segregated by gender and analyzed to determine similarity of heat maps for the same base image. Heat map images were analyzed using canonical correlation ( Rc ) to determine the relationship between the two groups; dispersion testing to decipher spatial uniformity within the images; the Structural Similarity Index (SSIM) to characterize the nature of image patterns differences; and, the Breslow-Day Test to specify pattern locations within images. Several heat map images are also presented in the results. Overall, female and male participants appear to "see" different things when imagining walk-commuting (as seen by poor Rc values) and the nature of what they were looking at were different (as seen by poor SSIM values). Female participants tended to focus on areas outside the walking path, such as bushes and dark areas, whereas men's focus was on the path ahead [ χ 2 (1) = 4.29, p = 0.04]. Furthermore, women were more likely to select areas outside the walking path during high entrapment settings [ χ 2 (1) = 15.49, p < 0.001] and at nighttime [ χ 2 (1) = 4.98, p = 0.02]. Our study demonstrates point-of-view differences in female-male walking space assessments. Viewing walking safety through the lens of lived experience could be productive for holistic community walking safety.
Keyphrases
- deep learning
- convolutional neural network
- optical coherence tomography
- heat stress
- lower limb
- physical activity
- mental health
- artificial intelligence
- healthcare
- polycystic ovary syndrome
- high density
- body mass index
- obstructive sleep apnea
- middle aged
- pregnant women
- prefrontal cortex
- adipose tissue
- electronic health record
- insulin resistance