Families living on welfare in low-income impoverished neighborhoods encounter multiple barriers that need mitigating before seeking work to reach self-sufficiency. Many welfare recipients' self-sufficiency barriers are unnoticeable to caseworkers due to lack of data sharing to assess clients' needs through information technology processes. The purpose of this exploratory descriptive phenomenological qualitative study was to understand welfare recipients' viewpoints on socioeconomic barriers to living self-sufficiently and gain perspectives from human services caseworkers and technical resources on data sharing issues that impact recipients' ability to live independently from government assistance. Data collection and observational field notes resulted from in-depth interviews of 11 participants to capture welfare recipients' lived experience on human services barriers to achieve self-sufficiency, as well as, caseworker and technical resources views on welfare systems data sharing issues. The analysis of semistructured interviews revealed that welfare systems data sharing is an enhancement needed to help caseworkers identify and mitigate welfare recipients' self-sufficiency barriers. The common assessment framework model provided a contextual view to exploring research questions to elicit participants' perceptions of data sharing in welfare systems processes. The data analysis showed that the lack of data sharing impacts caseworkers' ability to assist recipients with self-sufficiency barriers. Results indicated the need for caseworkers to use data sharing to understand client's socioeconomic barriers and to make effective decisions to lead them to self-sufficiency. The impact on positive social change is using automated data sharing to identify and mitigate recipients' barriers to self-sufficiency.
| Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-7354 |
| Date | 01 January 2018 |
| Creators | Nichols, Valenta Eunice |
| Publisher | ScholarWorks |
| Source Sets | Walden University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Walden Dissertations and Doctoral Studies |
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