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PURPOSE: The population with serious mental illness has high risk for hospitalization or death due to unhealthy behaviors and inadequate medical care, though the level of risk varies substantially. Programs that integrate medical and psychiatric services improve outcomes but are challenging to implement and access is limited. It would be useful to know whether benefits are confined to patients with specific levels of risk. METHODS: In a population with serious mental illness and increased risk for hospitalization or death, a specialized medical home integrated services and improved treatment and outcomes. Treatment quality, chronic illness care, care experience, symptoms, and quality of life were assessed for a median of 385 days. Analyses examine whether improvements varied by baseline level of patient risk. RESULTS: Patients with greater risk were more likely to be older, more cognitively impaired, and have worse mental health. Integrated services increased appropriate screening for body mass index, lipids, and glucose, but increases did not differ significantly by level of risk. Integrated services also improved chronic illness care, care experience, mental health-related quality of life, and psychotic symptoms. There were also no significant differences by risk level. CONCLUSIONS: There were benefits from integration of primary care and psychiatric care at all levels of increased risk, including those with extremely high risk above the 95th percentile. When developing integrated care programs, patients should be considered at all levels of risk, not only those who are the healthiest.

Older adults with serious mental illness (SMI) have compromised physical function that could be improved with exercise; however, retention in exercise programs is a challenge. This study was a retrospective analysis of retention for the 150 older veterans with SMI that enrolled in Gerofit, a clinical exercise program offered in the Veterans Health Administration. Chi-square and t-tests were conducted to evaluate baseline differences between those that were and were not retained at six and 12 months. Retention was 33% and better health-related quality of life and endurance were related to retention. Future work is needed to improve exercise program retention in this population.

BackgroundThe COVID-19 pandemic increased disparities for communities burdened by structural barriers such as reduced affordable housing, with mental health consequences. Limited data are available on digital resources for public mental health prevention during the COVID-19 pandemic.ObjectiveThe study aim was to evaluate engagement in and impact of free digital resources on the Together for Wellness/Juntos por Nuestro Bienestar (T4W/Juntos) website during COVID-19 in California.MethodsA pilot evaluation of T4W/Juntos was performed, with partner agencies inviting providers, clients, and partners to visit the website and complete surveys at baseline (September 20, 2021, to April 4, 2022) and at 4-6-week follow-up (October 22, 2021, to May 17, 2022). Website use was assessed by three engagement items (ease of use, satisfaction, relevance), comfort in use, and use of six resource categories. Primary outcomes at follow-up were depression and anxiety (scores≥3 on Patient Health Questionnaire-2 item [PHQ2] and Generalized Anxiety Disorder-2 item [GAD2] scales). Secondary outcomes were post-pre differences in PHQ2 and GAD2 scores, and use of behavioral health hotlines and services the month before follow-up.ResultsOf 366 eligible participants, 315 (86.1%) completed baseline and 193 (61.3%) completed follow-up surveys. Of baseline participants, 72.6% identified as female, and 21.3% identified as lesbian, gay, bisexual, transgender, queer/questioning, and others (LGBTQ+). In terms of ethnicity, 44.0% identified as Hispanic, 17.8% as African American, 26.9% as non-Hispanic white, and 11.4% as other ethnicity. Overall, 32.7% had moderate anxiety or depression (GAD2/PHQ2≥3) at baseline. Predictors of baseline website engagement included being Hispanic versus other race/ethnicity (β=.27, 95% CI .10-.44; P=.002) and number of COVID-19-related behavior changes (β=.09, 95% CI .05-.13; P

The observation of genetic correlations between disparate human traits has been interpreted as evidence of widespread pleiotropy. Here, we introduce cross-trait assortative mating (xAM) as an alternative explanation. We observe that xAM affects many phenotypes and that phenotypic cross-mate correlation estimates are strongly associated with genetic correlation estimates (R2=74%). We demonstrate that existing xAM plausibly accounts for substantial fractions of genetic correlation estimates and that previously reported genetic correlation estimates between some pairs of psychiatric disorders are congruent with xAM alone. Finally, we provide evidence for a history of xAM at the genetic level using cross-trait even/odd chromosome polygenic score correlations. Together, our results demonstrate that previous reports have likely overestimated the true genetic similarity between many phenotypes.

BACKGROUND: There are unmet primary care needs among people with serious mental illness that might be improved with integrated care and medical care management. Many healthcare organizations have attempted to address this problem, but few interventions have been rigorously studied and found to be effective. OBJECTIVE: Study the implementation and effectiveness of a novel, specialized primary care medical home designed to improve the healthcare of patients with serious mental illness. DESIGN, SETTING, AND PARTICIPANTS: Clustered controlled trial for a median of 401 days. One Veterans Health Administration medical center was assigned to intervention and two were assigned to usual care (control). Thirty-nine clinicians and managers were included in the study, as well as 331 patients who met eligibility criteria. INTERVENTION: A specialized medical home with systematic patient engagement, proactive nurse panel management, a collaborative care psychiatrist, and a primary care physician providing care that included psychiatric treatment. MAIN MEASURES: Quality of care, chronic illness care and care experience, symptoms, and quality of life. KEY RESULTS: Sixty-five intervention patients (40%) moved all psychiatric care to the primary care team. No adverse events were attributable to the intervention. Compared with control, intervention patients had greater improvement over time in appropriate screening for body mass index, lipids, and glucose (χ2 = 6.9, 14.3, and 3.9; Ps

Effects estimated by genome-wide association studies (GWASs) include effects of alleles in an individual on that individual (direct genetic effects), indirect genetic effects (for example, effects of alleles in parents on offspring through the environment) and bias from confounding. Within-family genetic variation is random, enabling unbiased estimation of direct genetic effects when parents are genotyped. However, parental genotypes are often missing. We introduce a method that imputes missing parental genotypes and estimates direct genetic effects. Our method, implemented in the software package snipar (single-nucleotide imputation of parents), gives more precise estimates of direct genetic effects than existing approaches. Using 39,614 individuals from the UK Biobank with at least one genotyped sibling/parent, we estimate the correlation between direct genetic effects and effects from standard GWASs for nine phenotypes, including educational attainment (r = 0.739, standard error (s.e.) = 0.086) and cognitive ability (r = 0.490, s.e. = 0.086). Our results demonstrate substantial confounding bias in standard GWASs for some phenotypes.

BACKGROUND Serious mental illnesses (SMI) are common, disabling, and challenging to treat, requiring years of monitoring and treatment adjustments. Stress or reduced medication adherence can lead to rapid worsening of symptoms and behaviors. Illness exacerbations and relapses generally occur with little or no clinician awareness in real time, leaving limited opportunity to modify treatments. Previous research suggests that passive mobile sensing may be beneficial for individuals with SMI by helping them monitor mental health status, behaviors, and quickly detect worsening mental health for prompt assessment and intervention. However, there is too little research on its feasibility and acceptability in patients with SMI, and the extent to which passive data can predict changes in behaviors and symptoms. OBJECTIVE To study the feasibility, acceptability and safety of passive mobile sensing for tracking behaviors and symptoms of patients in treatment for SMI, as well as developing analytics that utilize passive data to predict changes in behaviors and symptoms. METHODS A mobile application (app) monitors and transmits passive mobile sensor and phone utilization data to track activity, sociability and sleep in patients with SMI. The study consists of a user-centered design phase and a mobile sensing phase. In the design phase, focus groups, interviews and in-lab usability testing inform further app development. In the mobile sensing phase, passive mobile sensing occurs with participants engaging in weekly assessments for up to nine months. Three and nine month interviews study the perceptions of passive mobile sensing and ease of app use. Clinician interviews before and after the mobile sensing phase study the usefulness and feasibility of app utilization in clinical care. Predictive analytic models are built, trained and selected, and make use of machine learning methods. Models use sensor and phone utilization data to predict behavioral changes and symptoms. RESULTS The study was funded in October 2020 and has received IRB approval. The user-centered design phase, consisting of focus groups, usability testing, and pre-intervention clinician interviews has been completed. Recruitment and enrollment for the mobile sensing phase are ongoing. CONCLUSIONS Findings may inform the development of passive sensing apps and self-tracking in patients with SMI, and integration into care to improve assessment, treatment, and patient outcomes. CLINICALTRIAL ClinicalTrials.gov NCT05023252; https://clinicaltrials.gov/ct2/show/NCT05023252

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.

ObjectiveTo evaluate the sustainment of Housing First (HF) implementation in a permanent supportive housing program for homeless-experienced veterans, 5 years after practice implementation.Study settingFrom 2016 to 2017, primary data were collected from providers and veterans in the Department of Housing and Urban Development-VA Supportive Housing (HUD-VASH) program at Los Angeles.Study designGuided by the integrated sustainability framework, we performed a mixed-methods study to evaluate the sustainment of HF, an evidence-based practice implemented to improve housing outcomes. To assess sustainment, we measured fidelity to HF in six of seven HUD-VASH teams. These data were integrated with qualitative interviews with providers and veterans who described perceived sustainment to HF and contextual factors that supported or impeded sustainment.Data collectionFidelity to HF at 5 years after practice implementation, as a proxy for sustainment, was quantified via surveys with HUD-VASH teams. HUD-VASH providers (n = 51) and 31 veterans participated in semi-structured interviews. Team-based template analyses were used to develop an emergent understanding of stakeholder perspectives on HF sustainment.Principal findingsOverall, HUD-VASH teams reported HF sustainment. The lowest fidelity scores were found in the domains of client-to-staff ratios, frequency of client-provider contact, and time to housing. Qualitative findings indicated that outer contextual factors (e.g., housing scarcity) and organizational factors (e.g., staff turnover) impacted HF sustainment. Providers identified changes in leadership and unmet resource needs as impediments to practice sustainment. All stakeholders identified positively with the HF practice and believed that the approach benefited veterans.ConclusionsThis snapshot of HF sustainment demonstrates that this practice can be sustained over time. However, strong leadership, organizational resources, and community partnerships are needed. Adaptations to HF in response to outer contextual factors and organizational capacity may result in practice sustainment while allowing for flexibility in service provision.

BackgroundSerious mental illnesses (SMI) are common, disabling, and challenging to treat, requiring years of monitoring and treatment adjustments. Stress or reduced medication adherence can lead to rapid worsening of symptoms and behaviors. Illness exacerbations and relapses generally occur with little or no clinician awareness in real time, leaving limited opportunity to modify treatments. Previous research suggests that passive mobile sensing may be beneficial for individuals with SMI by helping them monitor mental health status and behaviors, and quickly detect worsening mental health for prompt assessment and intervention. However, there is too little research on its feasibility and acceptability and the extent to which passive data can predict changes in behaviors or symptoms.ObjectiveThe aim of this research is to study the feasibility, acceptability, and safety of passive mobile sensing for tracking behaviors and symptoms of patients in treatment for SMI, as well as developing analytics that use passive data to predict changes in behaviors and symptoms.MethodsA mobile app monitors and transmits passive mobile sensor and phone utilization data, which is used to track activity, sociability, and sleep in patients with SMI. The study consists of a user-centered design phase and a mobile sensing phase. In the design phase, focus groups, interviews, and usability testing inform further app development. In the mobile sensing phase, passive mobile sensing occurs with participants engaging in weekly assessments for 9 months. Three- and nine-month interviews study the perceptions of passive mobile sensing and ease of app use. Clinician interviews before and after the mobile sensing phase study the usefulness and feasibility of app utilization in clinical care. Predictive analytic models are built, trained, and selected, and make use of machine learning methods. Models use sensor and phone utilization data to predict behavioral changes and symptoms.ResultsThe study started in October 2020. It has received institutional review board approval. The user-centered design phase, consisting of focus groups, usability testing, and preintervention clinician interviews, was completed in June 2021. Recruitment and enrollment for the mobile sensing phase began in October 2021.ConclusionsFindings may inform the development of passive sensing apps and self-tracking in patients with SMI, and integration into care to improve assessment, treatment, and patient outcomes.Trial registrationClinicalTrials.gov NCT05023252; https://clinicaltrials.gov/ct2/show/NCT05023252.International registered report identifier (irrid)DERR1-10.2196/39010.

Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs' prediction accuracies, we constructed them using genome-wide association studies-some not previously published-from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the 'additive SNP factor'. Regressions in which the true regressor is this factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.

BackgroundClozapine clinics can facilitate greater access to clozapine, but there is a paucity of data on their structure in the US.MethodsA 23-item survey was administered to participants recruited from the SMI Adviser Clozapine Center of Excellence listserv to understand characteristics of clozapine clinics.ResultsClozapine clinics (N = 32) had a median caseload of 45 (IQR = 21-88) patients and utilized a median of 5 (IQR = 4-6) interdisciplinary roles. The most common roles included psychiatrists (100%), pharmacists (65.6%), nurses (65.6%), psychiatric nurse practitioners (53.1%), and case managers (53.1%). The majority of clinics outreached to patients who were overdue for labs (78.1%) and had access to on-site phlebotomy (62.5%). Less than half had on call services (46.9%).ConclusionsIn this first systematic description of clozapine clinics in the US, there was variation in the size, staffing, and services offered. These findings may serve as a window into configurations of clozapine teams.

Objective: Many persons with serious mental illness (SMI) who have experienced homelessness struggle to sustain stable and independent housing. We know little about determinants of this population's housing status. This study aimed to identify person-level determinants of housing status among homeless-experienced veterans with SMI, focused primarily on cognition. Method: We administered cross-sectional surveys and detailed cognitive assessments on a convenience sample of homeless-experienced veterans with SMI (n = 90); we also reviewed these participants' medical records. We captured person-level potential predictors of housing status (demographics, cognition, diagnoses, symptoms, and service utilization) and 2 years of retrospective housing history. Participants' housing status was conceptualized as the setting (stable housing, other sheltered settings, and streets) they lived in for >50% of the past 2 years. We used the chi-square test and analysis of variance to determine how potential predictors differed by housing status. We used recursive partitioning to identify the combination of potential predictors and corresponding scores that best-differentiated participants by housing status. Results: No between-groups differences (p < .05) in cognition, symptoms, or other person-level factors were found among participants grouped by housing status. Recursive partitioning did not yield a stable model to predict housing status from the potential predictor variables. Conclusions and Implications for Practice: These data suggest that clinical interventions addressing studied person-level factors (e.g., cognitive rehabilitation) may not affect housing status for homeless-experienced veterans. As housing is highly influenced by social determinants of health, policies, and practices that affect contextual factors (e.g., affordable housing supply) may be more likely to improve housing status. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

[123I]FP-CIT SPECT has been valuable for distinguishing Parkinson disease (PD) from essential tremor. However, its performance for quantitative assessment of motor dysfunction has not been established. A virtual reality (VR) application was developed and compared with [123I]FP-CIT SPECT/CT for detection of severity of motor dysfunction. Forty-four patients (21 males, 23 females, age 64.5 ± 12.4) with abnormal [123I]FP-CIT SPECT/CT underwent assessment of bradykinesia, activities of daily living, and tremor with VR. Support vector machines (SVM) machine learning models were applied to VR and SPECT data. Receiver operating characteristic (ROC) analysis demonstrated greater area under the curve (AUC) for VR (0.8418, 95% CI 0.6071-0.9617) compared with brain SPECT (0.5357, 95% CI 0.3373-0.7357, p = 0.029) for detection of motor dysfunction. Logistic regression identified VR as an independent predictor of motor dysfunction (Odds Ratio 326.4, SE 2.17, p = 0.008). SVM for prediction of the Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) demonstrated greater R-squared of 0.713 (p = 0.008) for VR, compared with 0.0764 (p = 0.361) for brain SPECT. This study demonstrates that VR can be safely used in patients prior to [123I]FP-CIT SPECT imaging and may improve prediction of motor dysfunction. This test has the potential to provide a simple, objective, quantitative analysis of motor symptoms in PD patients.

ObjectiveInnovative approaches are needed for assessing treatment preferences of individuals with schizophrenia. Conjoint analysis methods may help to identify preferences, but the usability and validity of these methods for individuals with schizophrenia remain unclear. This study examined computerized conjoint analysis for persons with schizophrenia and whether preferences for weight management programs predict service use.MethodsA computerized, patient-facing conjoint analysis system was developed through iterative consultation with 35 individuals with schizophrenia enrolled at a community mental health clinic. An additional 35 overweight participants with schizophrenia then used the system to choose among psychosocial weight management programs varying in four attributes: location (community or clinic), delivery mode (Internet or in person), leader (clinician or layperson), and training mode (individual or group). A multilevel logit model with partial preference data determined contributions of each attribute to groupwide preferences. Associations were studied between preferences and use of a psychosocial weight management group.ResultsConjoint analysis system usability was rated highly. Groupwide preferences were significantly influenced by location (p

BackgroundTo improve mental health care access, the Veterans Health Administration (VA) implemented Primary Care-Mental Health Integration (PC-MHI) in clinics nationally. Primary care clinical leader satisfaction can inform model implementation and may be facilitated by collaborative care managers and technology supporting cross-specialty collaboration.Objective(1) To determine primary care clinical leaders' overall satisfaction with care from embedded mental health providers for a range of conditions and (2) to examine the association between overall satisfaction and two program features (care managers, technology).DesignCross-sectional organizational survey in one VA region (Southern California, Arizona, and New Mexico), 2018.ParticipantsSixty-nine physicians or other designated clinical leaders in each VA primary care clinic (94% response rate).Main measuresWe assessed primary care clinical leader satisfaction with embedded mental health care on four groups of conditions: target, non-target mental health, behavioral health, suicide risk management. They additionally responded about the availability of mental health care managers and the sufficiency of information technology (telemental health, e-consult, instant messaging). We examined relationships between satisfaction and the two program features using χ2 tests and multivariable regressions.Key resultsMost primary care clinical leaders were "very satisfied" with care for targeted anxiety (71%) and depression (69%), but not for other common conditions (37% alcohol misuse, 19% pain). Care manager availability was significantly associated with "very satisfied" responses for depression (p = .02) and anxiety care by embedded mental health providers (p = .02). Highly rated sufficiency of communication technology (only 19%) was associated with "very satisfied" responses to suicide risk management (p = .002).ConclusionsCare from embedded mental health providers for depression and anxiety was highly satisfactory, which may guide improvement among less satisfactory conditions (alcohol misuse, pain). Observed associations between overall satisfaction and collaborative care features may inform clinics on how to optimize staffing and technology based on priority conditions.

Adults with serious mental illness have high rates of obesity, with associated negative impacts on health-related quality of life. The present study utilized data from a randomized controlled trial (N = 276) to examine the effectiveness of in-person and online-delivered weight management interventions, compared to usual care, for improving health-related quality of life in this population. Participants completed quality of life assessments at baseline, 3 months, and 6 months. Mixed effects models examined group by time interactions. Compared to usual care, in-person MOVE was associated with improvements in loneliness (t = - 2.76, p = .006) and mental health related quality of life (t = 1.99, p = 0.048) at 6 months, and webMOVE was associated with improvements in weight-related self-esteem at 6 months (t = 2.23, p = .026) and mental health-related quality of life at 3 months (t = 2.17, p = 0.031) and 6 months (t = 2.38, p = .018). Web-based and in-person weight management led to improvements in health-related quality of life for adults with serious mental illness.ClinicalTrials.gov Identifier: NCT00983476.

In Veterans Health Administration's (VA) Primary Care-Mental Health Integration (PC-MHI) models, primary care providers, care managers, and mental health clinicians collaboratively provide depression care. Primary care patients, however, still lack timely, sufficient access to psychotherapy treatment. Adapting PC-MHI collaborative care to improve uptake of evidence-based computerized cognitive behavioral therapy (cCBT) may be a potential solution. Understanding primary care-based mental health clinician perspectives is crucial for facilitating adoption of cCBT as part of collaborative depression care. We examined PC-MHI mental health clinicians' perspectives on adapting collaborative care models to support cCBT for VA primary care patients. We conducted 16 semi-structured interviews with PC-MHI nurse care managers, licensed social workers, psychologists, and psychiatrists in one VA health-care system. Interviews were audio-recorded, transcribed, coded using the constant comparative method, and analyzed for overarching themes. Although cCBT awareness and knowledge were not widespread, participants were highly accepting of enhancing PC-MHI models with cCBT for depression treatment. Participants supported cCBT delivery by a PC-MHI care manager or clinician and saw it as an additional tool to engage patients, particularly younger Veterans, in mental health treatment. They commented that current VA PC-MHI models did not facilitate, and had barriers to, use of online and mobile treatments. If effectively implemented, however, respondents thought it had potential to increase the number of patients they could treat. There is widespread interest in modernizing health systems. VA PC-MHI mental health clinicians appear open to adapting collaborative care to increase uptake of cCBT to improve psychotherapy access.

OBJECTIVE: Mobile technologies, such as smartphones, can improve health services by delivering assessments and interventions that reach people in their daily lives. There is, however, disagreement regarding whether people with serious mental illness make meaningful use of mobile technology and whether interventions that rely on mobile technology should be tailored for this population. METHODS: At two clinics, 249 people with serious mental illness were interviewed regarding mobile phone use, and their cognitive functioning was assessed. RESULTS: Mobile phones were used by 86% of participants, including 60% who used a smartphone. Phones were used for messaging by 81%, Internet by 52%, e-mail by 46%, and applications by 45%. Individuals who were older, had a persistent psychotic disorder rather than bipolar disorder, received disability income, or had worse neurocognitive functioning were less likely to own a smartphone (χ2=52.7, p

ObjectiveMobile technologies, such as smartphones, can improve health services by delivering assessments and interventions that reach people in their daily lives. There is, however, disagreement regarding whether people with serious mental illness make meaningful use of mobile technology and whether interventions that rely on mobile technology should be tailored for this population.MethodsAt two clinics, 249 people with serious mental illness were interviewed regarding mobile phone use, and their cognitive functioning was assessed.ResultsMobile phones were used by 86% of participants, including 60% who used a smartphone. Phones were used for messaging by 81%, Internet by 52%, e-mail by 46%, and applications by 45%. Individuals who were older, had a persistent psychotic disorder rather than bipolar disorder, received disability income, or had worse neurocognitive functioning were less likely to own a smartphone (χ2=52.7, p

Anxiety disorders are the most common class of psychiatric problems affecting both children and adults. However, tools to effectively monitor and manage anxiety are lacking, and comparatively limited research has been applied to addressing the unique challenges around anxiety. Leveraging passive and unobtrusive data collection from smartphones could be a viable alternative to classical methods, allowing for real-time mental health surveillance and disease management. This paper presents eWellness, an experimental mobile application designed to track a full-suite of sensor and user-log data off an individual’s device in a continuous and passive manner. We report on an initial pilot study tracking ten people over the course of a month that showed a nearly 76% success rate at predicting daily anxiety and depression levels based solely on the passively monitored features.

OBJECTIVE: Examine preferences for family involvement in psychiatric care in a large, representative sample of veterans in treatment for schizophrenia. METHOD: Veterans with schizophrenia or schizoaffective disorder (N = 801) completed an assessment that included questions about demographic and clinical characteristics, status of family support, and preference for family involvement in their psychiatric care. Open-ended items were independently coded by two raters and categorized; Cohens kappa was calculated for each category. RESULTS: Among the 801 participants, 496 (61.9%) indicated that they had a family member who provided them with regular support; 304 (37.9%) had no family member who provided support; and 1 did not respond. Among the 304 without support, 272 (89.4%) had a living family member. Of the 496 participants who had a supportive family member, 135 (27.2%) wanted their family member involved in their care. Of the 272 participants who did not have a supportive family member, but had living family, 57 (21.0%) wanted their family involved. Barriers to involvement included concerns about privacy and burden. Preferred method of involvement included contact with the patients psychiatrist and education about the illness. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Preferences indicated by this large representative sample of individuals in care for schizophrenia indicate that a majority have supportive family and a substantial minority want family involved in their psychiatric care. Clinicians can address concerns about privacy and burden and deliver preferred services by phone or mail, overcoming anticipated barriers. Desire for family support groups was limited but present. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

ObjectiveThis study examines barriers to participation and retention in 2 modalities (web-based and in-person) of a weight-management intervention tailored for individuals with serious mental illness (SMI).MethodUsing a mixed-methods approach, we explored the barriers veterans with SMI face when participating in a web-based (WebMOVE) or in-person (MOVE-SMI) version of the same SMI-adapted MOVE weight-management program. Participants in the randomized controlled trial (n = 277) were recruited from specialty mental health clinics at a Veterans Affairs medical center. Barriers were analyzed across treatment condition and program attendance (engagement) at baseline and follow-up using a generalized lineal model. Post hoc analyses assessed whether changes in the trajectory of barriers over time were associated with engagement. A subsample of participants (n = 48) from the WebMOVE and MOVE-SMI treatment conditions completed a qualitative interview, and 2 coders used open coding to analyze the data.ResultsAlthough barriers specific to treatment modality existed, most barriers cut across intervention modality, including financial hardship, lack of reliable housing and transportation, comorbid physical and mental health issues, and competing demands on personal time. Results of post hoc analyses found the association between engagement and emotional and motivational factors to be statistically significant.ConclusionsThis study is the 1st to identify barriers in a web-based intervention for SMI. Similar barriers persisted across treatment modalities. Known barriers, particularly socioeconomic barriers, should be addressed to improve engagement and retention of individuals in weight-management interventions adapted for SMI, irrespective of modality. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

IntroductionSupported housing-which offers permanent, community-based housing and supportive services-effectively addresses homelessness. Yet, many persons with serious mental illness (SMI) struggle to retain housing in these programs. Social skills-which facilitate social interactions and instrumental tasks-predict premature exits from supported housing. Though social skills training effectively improves social skills and functioning for persons with SMI, this intervention is essentially absent from supported housing initiatives.MethodsThis study will use literature review, key informant interviews and an expert panel to adapt social skills training for supported housing, aiming to improve housing retention among SMI persons in these programs. In the Department of Housing and Urban Development-VA Supported Housing program (HUD-VASH) at VA Greater Los Angeles, we will conduct an effectiveness-implementation hybrid type I trial of the adapted intervention. Baseline and 6-month assessments (measuring social skills, mental health status, healthcare utilization, social networks, money management, and housing outcomes) will be conducted with intervention participants (n = 30) and a usual care control group (n = 20). We will use the generalized linear mixed model (GLMM) to compare change over 6 months between groups, capturing the intervention's effectiveness on factors strongly associated with housing retention. Qualitative data and surveys with staff, leadership, and participants will gather data on factors relevant to the intervention's future implementation in routine care.DiscussionFew effective psychosocial interventions for persons with SMI have been adapted or studied in supported housing initiatives. To our knowledge, this is the first study to adapt and study the effectiveness and implementation of social skills training in supported housing programs.

ObjectiveBy combining supportive services with independent housing, permanent supportive housing (PSH) programs effectively address homelessness. Yet, many persons with serious mental illness struggle to attain and retain housing in these programs. Social skills-which facilitate social interactions and instrumental tasks-predict premature exit from PSH. This project aimed to build consensus on a set of social skills that supports independent housing attainment and retention among homeless persons with serious mental illness, with a clinical focus on PSH programs.MethodsGuided by the RAND/University of California, Los Angeles, appropriateness method, the set of social skills was developed by using literature review; key informant interviews (N=12), a national consensus panel of experts in psychosocial rehabilitation and homelessness (N=11), and two focus groups with homeless persons with serious mental illness (N=17).ResultsThese methods identified 24 social skills in seven domains: finding and renting an apartment, using one's time well, getting closer to people, managing finances, avoiding problems with drugs and alcohol, solving interpersonal problems, and managing one's health. Expert panelists and focus group participants agreed that these social skills were feasible for inclusion in social skills training and could strongly affect housing outcomes in PSH settings.ConclusionsConsensus was reached about a set of social skills relevant to housing attainment and retention for persons with serious mental illness engaged in PSH. Next steps include modifying social skills training interventions to this skill set, making contextual modifications relevant to the setting and context of PSH, and studying the effectiveness and implementation of the adapted intervention in PSH.

People with serious mental illness have substantially worse health outcomes than people without mental illness. These patients use primary care less often and fail to receive needed preventive and chronic care. While a variety of care models have been implemented with the goal of improving care for these patients, few have been found to be effective. Young et al describes a specialty patient-centered medical home for patients with serious mental illness. In this model, the primary care provider manages the medical and mental health conditions of patients with stable psychiatric symptoms with assistance from a registered nurse and a consulting psychiatrist. The goal of this integrated model is to engage patients in preventive care by building a relationship with them in primary care and understanding both their medical and psychiatric needs. While this model may improve care and increase patient satisfaction, implementing this type of model may be challenging.

Few interventions train homeless consumers in housing-related independent living skills. To inform the development of such interventions for the Department of Veterans Affairs' Supported Housing consumers with serious mental illness, we examined these consumers' problem-solving skills and deficits. We performed semistructured interviews and cognitive tests with 20 consumers who retained housing for ≥1 year ("stayers") and 20 consumers who lost housing in

BackgroundPeople with serious mental illness (SMI) die many years prematurely, with rates of premature mortality two to three times greater than the general population. Most premature deaths are due to "natural causes," especially cardiovascular disease and cancer. Often, people with SMI are not well engaged in primary care treatment and do not receive high-value preventative and medical services. There have been numerous efforts to improve this care, and few controlled trials, with inconsistent results. While people with SMI often do poorly with usual primary care arrangements, research suggests that integrated care and medical care management may improve treatment and outcomes, and reduce treatment costs.MethodsThis hybrid implementation-effectiveness study is a prospective, cluster controlled trial of a medical home, the SMI Patient-Aligned Care Team (SMI PACT), to improve the healthcare of patients with SMI enrolled with the Veterans Health Administration. The SMI PACT team includes proactive medical nurse care management, and integrated mental health treatment through regular psychiatry consultation and a collaborative care model. Patients are recruited to receive primary care through SMI PACT based on having a serious mental illness that is manageable with treatment, and elevated risk for hospitalization or death. In a site-level prospective controlled trial, this project studies the effect, relative to usual care, of SMI PACT on provision of appropriate preventive and medical treatments, health-related quality of life, satisfaction with care, and medical and mental health treatment utilization and costs. Research includes mixed-methods formative evaluation of usual care and SMI PACT implementation to strengthen the intervention and assess barriers and facilitators. Investigators examine relationships among organizational context, intervention factors, and patient and clinician outcomes, and identify patient factors related to successful patient outcomes.DiscussionThis will be one of the first controlled trials of the implementation and effectiveness of a patient centered medical home for people with serious mental illness. It will provide information regarding the value of this strategy, and processes and tools for implementing this model in community healthcare settings.Trial registrationClinicalTrials.gov, NCT01668355 . Registered August 20, 2012.

Evidence-based practices effectively reduce weight in people with serious mental illness (SMI), yet participation is limited. Positive relationships between self-efficacy (SE), readiness to change (RtC), and subsequent participation in weight loss interventions have been demonstrated in the general population. The role of SE and RtC in predicting participation in individuals with SMI is explored. A total of 82 participants recruited from a county mental health clinic and a Veterans Affairs mental health clinic were randomly assigned to a weight management intervention or usual care. RtC and SE were assessed at baseline. Intervention participation rates were gathered. SE significantly correlated with intervention participation (p < 0.02). RtC did not predict significantly over and above SE. A linear combination of all measures was significantly related to participation (p < 0.05). To improve weight intervention participation by individuals with SMI, one direction may be to improve weight loss SE.

ObjectiveMany adults with serious mental illness are sedentary and experience significant medical illness burden. This study examined the effectiveness of online weight management with peer coaching (WebMOVE) for increasing general physical activity among adults with serious mental illness.MethodsUsing quantitative and qualitative data from a randomized controlled trial (N=276), this study compared WebMOVE, in-person weight management for adults with serious mental illness (MOVE SMI), and usual care. Participants completed assessments of general physical activity (baseline, three months, and six months) and a qualitative assessment (six months). Mixed-effects models examined group × time interactions on general physical activity.ResultsThere were significant differences between MOVE SMI and usual care for total physical activity at three (t=3.06, p=.002) and six (t=3.12, p=.002) months, walking at six months (t=1.99, p=.048), and moderate (t=2.12, p=.035) and vigorous (t=2.34, p=.020) physical activity at six months. There was a significant difference between WebMOVE and usual care for total physical activity at six months (t=2.02, p=.044) and a trend for a group difference in walking at six months (t=1.78, p=.076). These findings reflected a decline in physical activity among participants in usual care and an increase in physical activity among participants in MOVE SMI or WebMOVE.ConclusionsIn-person weight management counseling increased total physical activity and led to initiation of moderate and vigorous physical activity among adults with serious mental illness. Computerized weight management counseling with peer support led to more gradual increases in total physical activity.

ObjectiveResearch suggests that social supports are associated with housing retention among adults who have experienced homelessness. Yet, we know very little about the social support context in consumers find and retain housing. We examined the ways and identified the junctures in which consumers' skills and deficits in accessing and mobilizing social supports influenced their longitudinal housing status.MethodWe performed semi-structured qualitative interviews with VA Greater Los Angeles consumers (n = 19) with serious mental illness, substance use disorders, and a history of homelessness; interviews explored associations between longitudinal housing status (categorized as: stable, independent housing; sheltered housing, continually engaged in structured housing programs; and unstable housing) and social supports. We compared data from consumers in these 3 mutually exclusive categories.ResultsAll participants described social support as important for finding and maintaining housing. However, participants used formal (provider/case managers) and informal (family/friends) supports in different ways. Participants in stable housing relied on formal and informal supports to obtain/maintain housing. Participants in sheltered housing primarily used formal supports, for example, case management staff. Unstably housed participants used formal and informal supports, but some of these relationships were superficial or of negative valence. Interpersonal problems were prevalent across longitudinal housing status categories.Conclusions and implications for practiceSocial context, including patterns of formal and informal support, was associated with participants' longitudinal housing status. Within interventions to end homelessness, these findings suggest the value of future research to identify, tailor, and implement practices that can help consumers improve their social resources. (PsycINFO Database Record