DOI: 10.3886/e214941
title: Evaluating MTurk as a recruitment tool for rural people with disabilities

description: <b>Background:</b> Recruitment of people with disabilities often occurs through disability organizations, advocacy groups, service providers, and patient registries. Recruitment that relies exclusively on established relationships can produce samples that may miss important information. The MTurk online marketplace offers a convenient option for recruitment. <b>Objective:</b> The paper compares samples recruited through (1) conventional and (2) MTurk methods to better understand how these samples contrast with one another and with national estimates of people with disabilities. <b>Methods:</b> In 2019, researchers recruited 1374 participants through conventional methods and 758 through MTurk to complete the National Survey on Health and Disability (NSHD). We analyzed sample differences between recruitment groups with t-tests, Chi-square, and logistic regression. <b>Results:</b> With the exception of race/ethnicity, the conventional and MTurk samples were significantly different on several dimensions including age, gender, education level, marital status, children living at home, and sexual orientation. The MTurk sample was overrepresented in lower income brackets. A significantly higher percentage of the conventional sample received SSI, SSDI, or both, compared to the MTurk sample (36.2% vs 12.8%) and had significantly higher rates of insurance coverage. Comparisons with American Community Survey data show that the conventional and MTurk samples aligned more closely with the general population of people with disabilities on different characteristics. Conclusions: MTurk is a viable complement to conventional recruitment methods, but it should not be a replacement. A combination of strategies builds a more robust dataset that allows for more varied examination of issues relevant to people with disabilities.
description: Response Rates: NA<br><br>
description: Presence of Common Scales: <b>Socio-Demographic Variables:</b><br>Age: Measured in years.<br>Gender: Categorical (e.g., male, female, other).<br>Education: Categorical (e.g., high school, some college, college graduate).<br>Marital Status: Categorical (e.g., single, married, divorced).<br>Children at Home: Categorical (yes/no).<br>Sexual Orientation: Categorical (e.g., heterosexual, lesbian, bisexual, gay, asexual, other). <br><b>Economic Indicators</b><b>:</b><br>Income: Measured as a percentage of the Federal Poverty Level (FPL).<br>Employment Status: Categorical (e.g., full-time, part-time, not employed).<br>Receipt of SSI/SSDI: Categorical (yes/no). <br><b>Health Indicators</b><b>:</b><br>Overall Health: 5-point Likert scale (1 = poor, 5 = excellent).<br>Days of Poor Physical Health: Number of days in the past 30 days.<br>Days of Poor Mental Health: Number of days in the past 30 days. <b><br>Disability Measures</b><b>:</b><br>Primary Disability Type: Categorical (e.g., mental illness/psychiatric, physical, chronic illness/disease, intellectual/developmental, sensory, neurological).<br>Any Disability: Based on open-ended responses and categorized into primary and secondary groups.<br>ACS Functional Limitations: Six questions assessing functional limitations (e.g., hearing, seeing, concentrating, walking, bathing, doing errands).<br><b>Rural and Urban Classification</b><b>:</b><br>Based on the Office of Management and Budget (OMB) rural-urban classification scheme.<br>County and Zip Code Information: Used to classify respondents into metropolitan, micropolitan, or noncore categories.
description: 2132 respondents
description: US adults aged 18-64 who identify as having one or more disabilities. Smallest Geographic Unit: United States
description: face-to-face interview; other; web-based survey; <b>NSHD (National Survey on Health and Disability)(first and second wave)</b><b>: </b>Primary data collected for the study, focusing on the experiences of adults with disabilities.<br><b>OMB (Office of Management and Budget)</b><b>:</b> Data used for rural-urban classification based on the OMB’s classification scheme.<br><b>ACS (American Community Survey)</b><b>:</b> Data from the ACS-6, a set of questions used to measure disability prevalence based on functional limitations.