Yin-Ling Irene Wong, Stephen R. Poulin
This study seeks to document patterns and reasons of leaving housing, and identify factors associated with different types of exits for a cohort of 452 residents with serious mental illness entering supported independent living (SIL) in Philadelphia, PA. The study cohort was tracked through an integrated administrative database comprised of information on basic demographic and clinical characteristics, length of stay, homeless shelter use, and publicly funded behavioral health services use. A convenience sample of 46 SIL leavers and their support staff provided data on scenarios of leaving. The findings of this study suggest that departure from SIL is not a unitary phenomenon, but involves plausibly unfavorable as well as favorable circumstances. Multivariate analysis based on administrative tracking data suggests demographic and clinical factors, housing setting, and service use factors to have effects on housing outcomes. Implications for the roles of program rules and resident–staff relationships play in affecting housing tenure. Implications for the development of permanent supportive housing for persons with serious mental illness are discussed.
@article{16708189-52cd-4eb7-b248-71f6b3db6367,
title={Tracking residential outcomes of support},
author={Yin-Ling Irene Wong and Stephen R. Poulin},
year={2026},
language={en}
}TY - JOUR TI - Tracking residential outcomes of support AU - Yin-Ling Irene Wong AU - Stephen R. Poulin PY - 2026 LA - en ER -
This paper addresses the challenge of assessing the feasibility of wind power plant projects at sites with insufficient or no local historic wind data
Important advances in electrochemical engineering technology over the last three decades have fostered the development of a lternative methods to alle
Increasing volumes of waste printed circuit boards from obsolete electronic equipment posed escalating environmental risks and resource losses due to