Date of Graduation

Spring 5-15-2025

Document Type

Project

Degree Name

Doctor of Nursing Practice (DNP)

College/School

School of Nursing and Health Professions

Program

Psychiatric Mental Health Nurse Practitioner

First Advisor

Dr. Jo Loomis, DNP, FNP-C, CHSE, CLC, ANLC, NCMP, CNL

Second Advisor

Dr. Alicia Kletter, DNP, APRN, PMHNP-BC, FNP-BC

Abstract

Abstract

Background: Dependent adult children with severe mental illness (ASMI) living with aging parents have been an increasing population over decades due to lack of supportive housing and services in the community. ASMI living with aging parents is a high-risk group for housing instability and future homelessness. Local Problem: A limited amount of literature and data exist to determine the size and needs of the population of ASMI living with aging parents. A collaboration with University of San Francisco (USF) and non-profit, Solutions for Supportive Homes (S4SH) of San Mateo County (SMC) formed to disseminate information and quantify the “invisible population” of ASMI living with aging parents to encourage the need for increased services and supportive housing. Methods: Comprehensive literature review on target population, housing instability, homelessness, and social determinants of health documentation (SDoH) for public presentations and policy development. Interventions: Consolidation of current literature, knowledge, background, and available data to increase population awareness through presentations, pre/post surveys to establish basic needs/concerns assessment, and a policy brief presented to the county aimed at changing housing documentation practices. Results: Awareness of population and importance of SDoH related to ASMI living with aging parents was shown to increase, but population size could not be defined. A policy brief and presentation on the importance of documenting housing status to identify “invisible populations” was presented to the county and is being considered for adoption by SMC pending approval. Conclusion: Mandating the documentation of housing/household status in health records can help identify at-risk “invisible populations” to reduce and prevent homelessness in the county through data-driven, community planning.

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