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Lessons Learned From a Five-year Study on Preventing Self-neglect Among At-risk Health Care Patients in Texas

Year: 2024
Type: conference-abstract
Abstract: This presentation focuses on lessons learned from a study on preventing self-neglect among healthcare patients that is currently featured as a Success on the Administration for Community Living’s Elder Justice webpage. Collaborators included researchers, a large healthcare system, and Adult Protective Services. We focused on preventing self-neglect by identifying older and disabled patients from 19 primary care clinics with risk factors for self-neglect such as depression and dementia. Clinics were randomized to intervention (patients received 4-months of case management) and control (usual care) conditions, and 477 randomly selected patients participated. The sample was predominantly Hispanic (68%) and low income (< $1,361). The lessons learned have important implications for practice, policy, and future research. For example, language mattered when recruiting study participants and the term ‘self-neglect’ needed to be softened. Despite paying $25-$35 for an interview, the response rate was approximately 30%, leading to timeline delays. Intervention group patients (285) who were interviewed at home had higher response rates than control patients (192) interviewed at the clinic/other settings. Thus, conducting home assessments for self-neglect and offering case management to at-risk patients was feasible. In general, at-risk patients were not self-neglecting but had a variety of needs (823 total needs) such as food insecurity and home modifications and needed service referrals (total 1,226 referrals). Needs were met 65% of the time. Barriers to service utilization included refusals. Discussion will focus on how the lessons learned can help research-practice collaborations prevent self-neglect among low-income, minority populations and prepare for challenges in the field.
Language: English
Subfield: Demography
Open Access status: gold
Estimated APC paid: $4,375
OpenAlex ID: W4405976461
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