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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: OBJECTIVE, METHODS, RESULTS. Meshes: Adult, Cognition Disorders, Comorbidity, Disability Evaluation, Female, Homeless Persons, Housing, Humans, Independent Living, Interpersonal Relations, Los Angeles, Male, Mental Disorders, Middle Aged, Neuropsychological Tests, Prognosis, Psychiatric Status Rating Scales, Psychometrics, Rehabilitation Centers, Risk Factors, Social Adjustment, Substance-Related Disorders, Treatment Outcome, Veterans.
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Do factors affecting exits from homelessness among persons with serious mental illness and substance use disorders? Context: We sought to understand the housing trajectories of homeless consumers with serious mental illness (SMI) and co-occurring substance use disorders (SUD) and to identify factors that best predicted achievement of independent housing. Using administrative data, we identified homeless persons with SMI and SUD admitted to a residential rehabilitation program from December 2008 to November 2011. Our primary outcome measure was independent housing status. On a random sample (N = 36), we assessed a range of potential predictors of housing outcomes, including symptoms, cognition, and social/community supports. We used the Residential Time-Line Follow-Back (TLFB) Inventory to gather housing histories since exiting rehabilitation and to identify housing outcomes. We used Recursive Partitioning (RP) to identify variables that best differentiated participants by these outcomes. We identified 3 housing trajectories: stable housing (n = 14), unstable housing (n = 15), and continuously engaged in housing services (n = 7). In RP analysis, 2 variables (Symbol Digit Modalities Test [SDMT], a neurocognitive speed of processing measure, and Behavior and Symptom Identification Scale [BASIS-24] Relationships subscale, which quantifies symptoms affecting relationships) were sufficient to capture information provided by 26 predictors to classify participants by housing outcome. Participants predicted to continuously engage in services had impaired processing speeds (SDMT score < 32.5). Among consumers with SDMT score ≥ 32.5, those predicted to achieve stable housing had fewer interpersonal symptoms (BASIS-24 Relationships subscale score < 0.81) than those predicted to have unstable housing. This model explains 57% of this sample's variability and 14% of this population's variability in housing outcomes.
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Because cognition and symptoms influencing relationships predicted housing outcomes for homeless adults with SMI and SUD, cognitive and social skills training may be useful for this population. Final Decision: yes