We report on a study validating a scale to measure transportation disadvantage (TD) among individuals experiencing homelessness in a high-density suburban community in the southern US. Individuals experiencing homelessness represent some of the heaviest users of public transit in the US, perhaps due to their low rate of car ownership (just 15% in one community sample). Shelters often present community-level risks for TD, e.g., poor or nonexistent public transportation infrastructure, concentrated poverty, and locations distant from employment and resources. Few validated scales exist to measure TD, and even fewer have been tested with unstably housed individuals.
The study occurred in the largest municipality in the US that lacks a public bus system. Following IRB exemption, the authors administered surveys to clients (n=53; 45% female, 53% African American, mean age=44, SD, 13.01) at emergency shelters, domestic violence shelters, soup kitchens, and unsheltered locations during Spring 2018. The survey included a 9-item, 4-point likert scale developed to measure aspects of transportation disadvantage. Scale items covered transportation domains including costs, physical accessibility, and safety; higher scores indicating greater disadvantage. An additional survey question measured gaps in transportation services, and responses options were dichotomized as “none to moderate gap” or “large gap”. Data were analyzed in SPSS v. 24. Chronbach’s alpha was calculated for reliability purposes. Factor validity was assessed using an exploratory factor analysis (EFA) with an oblique rotated factor solution and maximum likelihood extraction method with visual analysis of scree plot and eigen values greater than 1. Criterion validity was assessed by testing the mean differences in the TD scale against perception of transportation service gaps.
Chronbach’s alpha for the nine items was .88. Nearly three quarters reported lack of access to reliable transportation; 85% reported transportation is a very big gap in services. The average transportation disadvantage score was 22.51 (SD= 8.56, ranging from 2, little disadvantage, to 36, great disadvantage). The EFA yielded a two-factor rotated solution (KMO=.776, Bartlett’s Test of Sphericity=346.029, p<.001). Factor one included six items addressing coverage of public transit, costs, and ability to locate transit when needed. Factor two included three items addressing physical accessibility and safety. Mean comparisons showed that those reporting greater perceived gaps in transportation services had higher mean TD scores (M=23.49, SD=8.45 vs. M=16.71, SD=7.48).
Findings show that the TD scale may demonstrate adequate psychometric properties for application with individuals experiencing homelessness. Reliability was within the acceptable range, the factor solution was unambiguous, and criterion validity resulted in logical relationships. Future research can build on the current study by expanding the sample size and geographic diversity thereby permitting confirmatory factor analyses that corroborate the EFA’s two-factor solution. Additionally, research should test the intersection of gender and race with transportation disadvantage as men and women and minority groups may show divergent travel patterns and needs. Overall, the fairly consistent reports of transportation disadvantage among individuals experiencing homelessness justify the need for research such as this effort to develop valid and reliable measures that will inform evidence-based funding and policy recommendations.