Degree

Doctor of Philosophy (PhD)

Department

Communication Studies

Document Type

Dissertation

Abstract

The current explanatory sequential mixed methods design study applied the statistical stigma results from part 1 to the interview schedule in part 2 to determine how the different types of stigma and social support impact enrollment on the Supplemental Nutrition Assistance Program (SNAP). Using data collected from Amazon’s Mechanical Turk engine, Louisiana SNAP participants, and the LSU research participation for part 1 of the study, four significant stigma variables were found to impact enrollment on SNAP: total stigma, past consequences from disclosing SNAP stigma, anticipated consequences from disclosing SNAP enrollment stigma, and concern for disclosing SNAP enrollment to a specific person stigma. Data from part 1 was applied to interview schedules, including questions about social support to 19 participants. Fourteen themes were found including judgment, embarrassment, feelings of failure, social support, race, satisfaction/dissatisfaction with SNAP, etc. Three stigma variables from part 1 were also found to impact enrollment in part 2—total stigma, anticipated consequences from disclosing SNAP enrollment, and Concern for disclosing SNAP enrollment to a specific person stigma. Findings suggest that stigmatizing experiences from SNAP enrollment impact both current and past enrolled participants but impact current enrollees more. Furthermore, less social support or negative support can lead to more feelings of judgment and shame indicating the powerful role that social support can have when dealing with the stigma from SNAP enrollment. The discussion chapter will describe and weave together the findings from parts 1 and 2 through the application of the theoretical foundations of the study, and report the most important implications from the findings.

Date

1-20-2021

Committee Chair

Pecchioni, Loretta

DOI

10.31390/gradschool_dissertations.5450

Available for download on Wednesday, January 19, 2028

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