DOI: 10.3886/e233682v1
title: Exploring Metro and Non-metro Differences in Satisfaction With Services and Community Participation Among Low-Income Personal Assistance Service Users

description: Personal assistance services (PAS) are supports provided by workers to assist disabled people with their activities of daily living. Access to in-home PAS allows people who need assistance with these activities to live in their own homes and communities, rather than moving to congregate living facilities. Because metro and non-metro areas differ in many ways, we explored the following research questions: (1) Are there differences between non-metro and metro PAS users?, (2) What factors are associated with satisfaction with services?, and (3) What factors are associated with satisfaction with community participation?. We randomly surveyed PAS consumers in five states about their experiences with PAS. To answer the first question, we compared metro or non-metro consumers using independent samples t-tests. We found few statistically significant differences between metro and non-metro respondents. To answer the second and third research questions, we conducted linear regressions predicting our dependent variables. In terms of satisfaction with services, our model explained very little of the variance, other than finding that being partnered or married was significantly, positively related to satisfaction with services. In predicting satisfaction with community participation, the model explained about a quarter of the variance, with having fewer disabilities and higher health status predicting more satisfaction. This research indicates that there are few differences between metro and non-metro low-income PAS consumers and that more research is needed to understand what factors are related to satisfaction with services and community participation in this population.<br>
description: <b>Demographic Variables:</b><br>1. Age:<br>Constructed as a continuous variable from the respondents' reported age.<br>2. Gender:<br>Constructed as a categorical variable (e.g., male, female, other).<br>3. Race/Ethnicity:<br>Constructed as categorical variables (e.g., White, Black or African American, Hispanic or Latino, etc.).<br>4. Education Level:<br>Constructed as a categorical variable (e.g., high school or less, some college, bachelor’s degree, etc.).<br>5. Employment Status:<br>Constructed as a categorical variable (e.g., employed, unemployed).<br>6. Household Income:<br>Constructed as an ordinal variable based on income ranges (e.g., below $20,000, $20,000-$39,999, etc.).<br>7. Receipt of Social Security Benefits:<br><br><br><b>Constructed as a binary variable (e.g., yes, no).</b><b>Attitude Toward EVV:</b><br>1. EVV Interference Concerns:<br>Constructed from the Likert-scale item measuring concern that EVV interferes with the consumer-caregiver relationship.<br>2. EVV as Fraud Prevention:<br>Constructed from the Likert-scale item measuring belief that EVV will reduce fraud in home care services.<br>3. EVV as Protective Measure:<br>Constructed from the Likert-scale item measuring belief that EVV will protect consumers and caregivers.<br>4. EVV Benefits:<br>Constructed from the Likert-scale item measuring belief that EVV will be beneficial overall.<br> <br><b> </b><b>Qualitative Themes (Coded Variables)</b><b>:</b><br>1. Consumer-Caregiver Relationship Impact:<br>Constructed from open-ended responses highlighting concerns that EVV might negatively impact the relationship between consumers and caregivers.<br>2. Hiring Difficulties Due to EVV:<br>Constructed from comments indicating that EVV complicates the process of hiring caregivers.<br>3. Limitations on Caregiver Time and Services:<br>Constructed from responses pointing out that EVV might limit the time caregivers can spend or the services they can provide.<br>4. Consumer Choice and Control Issues:<br>Constructed from comments that EVV reduces consumer autonomy, particularly in self-directed care models.<br>5. Logistical and Technical Challenges:<br>Constructed from responses mentioning difficulties with the technology and logistics of implementing EVV.<br>6. Unrecognized Unpaid Work:<br>Constructed from comments indicating that EVV does not account for unpaid work performed by caregivers.
description: Presence of Common Scales: Likert scale (1-5) for evaluating agreement with statements.
description: [1,200 randomly sampled PAS recipients. Stratified random sampling was used, with a focus on ensuring sufficient representation from both metro and nonmetro (rural) areas., 1,200 randomly sampled PAS recipients. Stratified random sampling was used, with a focus on ensuring sufficient representation from both metro and nonmetro (rural) areas.]
description: The population of interest includes adults with disabilities who receive Medicaid-funded personal assistance services (PAS) and reside in the United States, specifically in Alaska, Arizona, Montana, Texas, and Wisconsin.. Smallest Geographic Unit: Zip codes, categorized into metro and nonmetro areas based on Rural-Urban Continuum Codes (RUCCs).
description: mail questionnaire;