Community Interventions to Promote Mental Health and Social Equity.

PURPOSE OF REVIEW: We review recent community interventions to promote mental health and social equity. We define community interventions as those that involve multi-sector partnerships, emphasize community members as integral to the intervention, and/or deliver services in community settings. We examine literature in seven topic areas: collaborative care, early psychosis, school-based interventions, homelessness, criminal justice, global mental health, and mental health promotion/prevention. We adapt the social-ecological model for health promotion and provide a framework for understanding the actions of community interventions. RECENT FINDINGS: There are recent examples of effective interventions in each topic area. The majority of interventions focus on individual, family/interpersonal, and program/institutional social-ecological levels, with few intervening on whole communities or involving multiple non-healthcare sectors. Findings from many studies reinforce the interplay among mental health, interpersonal relationships, and social determinants of health. There is evidence for the effectiveness of community interventions for improving mental health and some social outcomes across social-ecological levels. Studies indicate the importance of ongoing resources and training to maintain long-term outcomes, explicit attention to ethics and processes to foster equitable partnerships, and policy reform to support sustainable healthcare-community collaborations.

Informing implementation and dissemination of a specialized primary care medical home for patients with serious mental illness: Clinician and administrator perspectives.

People with serious mental illness (SMI) have lower rates of use of preventative medical services and higher rates of mortality compared to the general population. Research shows that specialized primary care medical homes improve the health care of patients with SMI and are feasible to implement, safe, and more effective than usual care. However, specialized medical homes remain uncommon and model dissemination limited. As part of a controlled trial assessing an SMI-specialized medical home, we examined clinician and administrator perspectives regarding specialized versus mainstream primary care and identified ways to enhance the scale-up of a specialized primary care model for future dissemination. We conducted semistructured interviews with clinicians and administrators at three sites prior to the implementation of an SMI-specialized primary care medical home (n = 26) and at 1-year follow-up (n = 24); one site implemented the intervention, and two sites served as controls. Interviews captured service design features that affected the quality of care provided; contextual factors that supported or impeded medical home implementation; and knowledge, attitudes, and behaviors regarding the care of patients with SMI. Interviews were transcribed and coded. Clinicians and administrators described SMI-specialized primary care medical homes as advancing care coordination and outcomes for patients with SMI. Stakeholders identified elements of a specialized medical home that they viewed as superior to usual care, including having a holistic picture of patients' needs and greater care coordination. However, to enable scale-up, efforts are needed to increase staffing on care teams, develop robust clinician onboarding or training, and ensure close coordination with mental health care providers. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Stakeholder perspectives on sustainment of Housing First in a VA permanent supportive housing program.

OBJECTIVE: To evaluate the sustainment of Housing First (HF) implementation in a permanent supportive housing program for homeless-experienced veterans, 5 years after practice implementation. STUDY SETTING: From 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 DESIGN: Guided 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 COLLECTION: Fidelity 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 FINDINGS: Overall, 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. CONCLUSIONS: This 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.

Community Interventions to Promote Mental Health and Social Equity.

(Reprinted with permission from Current Psychiatry Reports (2020) 21: 35).

Resilience in homeless veterans: Clinical and cognitive correlates.

OBJECTIVE: Resilience is broadly defined as the ability to respond adaptively to challenges or adversity. It is unclear which clinical and cognitive factors are most closely related to resilience. Also, the dimensions that comprise resilience may differ among different groups, such as those who are homeless. The purpose of this study was to understand the relationships between resilience and clinical, cognitive, and functional variables among homeless veterans and to determine independent predictors of resilience. METHOD: One hundred homeless veterans completed measures of resilience, defeatist beliefs, negative symptoms, psychotic and mood symptoms, social and nonsocial cognition, and community functioning. We examined associations between resilience and clinical, cognitive, and functional measures. We performed regression analyses to determine independent contributions of the variables to resilience. RESULTS: Resilience was correlated with negative symptoms, defeatist beliefs, depression/anxiety symptoms, and social cognition. There were no significant correlations with nonsocial cognition or psychotic symptoms. Stepwise multiple linear regression showed that defeatist beliefs, motivational negative symptoms, expressive negative symptoms, and depression/anxiety symptoms made independent contributions. Resilience was correlated with community functioning in the domains of work, independent living, and social and family relationships. History of psychosis moderated the relationship between resilience and defeatist beliefs, which was stronger in those who had experienced psychosis. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: These findings suggest that resilience is an important construct to consider in homeless veterans, is related to other clinical factors such as defeatist beliefs and negative symptoms, and could be a valuable treatment target with the goal of improving functioning. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Social support and housing transitions among homeless adults with serious mental illness and substance use disorders.

OBJECTIVE: Research 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. METHOD: We 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. RESULTS: All 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 PRACTICE: Social 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

Emotional Well-Being and Public Health: Proposal for a Model National Initiative.

In 2011, the National Prevention, Health Promotion, and Public Health Council named mental and emotional well-being as 1 of 7 priority areas for the National Prevention Strategy. In this article, we discuss emotional well-being as a scientific concept and its relevance to public health. We review evidence that supports the association between emotional well-being and health. We propose a national emotional well-being initiative and describe its 6 components: systematic measurement of emotional well-being, identification of the drivers of emotional well-being, formation of partnerships with diverse stakeholders, implementation and dissemination of evidence-based interventions to promote emotional well-being and its drivers, development of public health messaging, and identification of and strategies to address disparities in emotional well-being and its drivers. Finally, we discuss ways in which a national emotional well-being initiative would complement current public health efforts and the potential challenges to such an initiative.

Community, Public Policy, and Recovery from Mental Illness: Emerging Research and Initiatives.

This commentary examines the roles that communities and public policies play in the definition and processes of recovery for adults with mental illness. Policy, clinical, and consumer definitions of recovery are reviewed, which highlight the importance of communities and policies for recovery. This commentary then presents a framework for the relationships between community-level factors, policies, and downstream mental health outcomes, focusing on macroeconomic, housing, and health care policies; adverse exposures such as crime victimization; and neighborhood characteristics such as social capital. Initiatives that address community contexts to improve mental health outcomes are currently under way. Common characteristics of such initiatives and select examples are discussed. This commentary concludes with a discussion of providers', consumers', and other stakeholders' roles in shaping policy reform and community change to facilitate recovery.

Does mental health influence weight loss in adults with prediabetes? Findings from the VA Diabetes Prevention Program.

OBJECTIVES: Mental illness may impact outcomes from structured behavioral weight loss interventions. This secondary analysis investigated the influence of mental health on weight loss among Veterans with prediabetes enrolled in either an in-person diabetes prevention program (DPP) or the usual care weight management program (MOVE!) designed to help patients achieve weight loss through changes in physical activity and diet. METHODS: Prediabetes was defined by Hemoglobin A1c between 5.7 and 6.4% or Fasting Plasma Glucose 100-125 mg/dL and no use of antiglycemic medications during the past six months. Veterans Health Administrative data were used to assign Veterans into one of three mental health diagnoses: severe mental illness (SMI), affective disorder (AD) without SMI, or No SMI/No AD. The influence of mental health on weight changes at 6 and 12 months was modeled using linear mixed-effects regression. RESULTS: On average, Veterans with prediabetes (n = 386) were 59 years old (SD = 10.0 years), with a BMI of 34.8 kg/m2 (SD = 5.3 kg/m2) and A1c of 6.0% (SD = 0.2%). The sample consisted of 12% (n = 47), 39% (n = 150), and 49% (n = 189) diagnosed with SMI, AD and No SMI/No AD, respectively. Across interventions, Veterans with SMI lost less weight than those with AD or No SMI/No AD. From baseline to 6 months, weight loss was significantly less for Veterans with SMI (1.53 kg) compared to Veterans with AD (3.85 kg) or No SMI/No AD (3.73 kg). This weight loss trend by mental health diagnosis continued from baseline to 12 months but was no longer statistically significant at 12 months. CONCLUSION: Weight loss was not clinically or statistically different among Veterans with prediabetes diagnosed with AD or No SMI/No AD. However, Veterans diagnosed with SMI exhibited less weight loss over 6 months than Veterans with AD or No SMI/No AD and though not statistically significant, the trend continued to 12 months, suggesting that SMI may influence weight loss outcomes.

Incorporating multidimensional patient-reported outcomes of symptom severity, functioning, and quality of life in the Individual Burden of Illness Index for Depression to measure treatment impact and recovery in MDD.

CONTEXT: The National Institute of Mental Health Affective Disorders Workgroup identified the assessment of an individual's burden of illness as an important need. The Individual Burden of Illness Index for Depression (IBI-D) metric was developed to meet this need. OBJECTIVE: To assess the use of the IBI-D for multidimensional assessment of treatment efficacy for depressed patients. DESIGN, SETTING, AND PATIENTS: Complete data on depressive symptom severity, functioning, and quality of life (QOL) from depressed patients (N = 2280) at entry and exit of level 1 of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study (12-week citalopram treatment) were used as the basis for calculating IBI-D and self-rating scale changes. RESULTS: Principal component analysis of patient responses at the end of level 1 of STAR*D yielded a single principal component, IBI-D, with a nearly identical eigenvector to that previously reported. While changes in symptom severity (Quick Inventory of Depressive Symptomatology-Self Report) accounted for only 50% of the variance in changes in QOL (Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form) and 47% of the variance in changes in functioning (Work and Social Adjustment Scale), changes in IBI-D captured 83% of the variance in changes in QOL and 80% in functioning, while also capturing 79% of the variance in change in symptom severity (Quick Inventory of Depressive Symptomatology-Self Report). Most importantly, the changes in IBI-D of the 36.6% of remitters who had abnormal QOL and/or functioning (mean [SD], 2.98 [0.35]) were significantly less than the changes in IBI-D of those who reported normal QOL and functioning (IBI-D = 1.97; t = 32.6; P < 10(-8)) with an effect size of a Cohen d of 2.58. In contrast, differences in symptom severity, while significant, had a Cohen d of only 0.78. CONCLUSIONS: Remission in depressed patients, as defined by a reduction in symptom severity, does not denote normal QOL or functioning. By incorporating multidimensional patient-reported outcomes, the IBI-D provides a single measure that adequately captures the full burden of illness in depression both prior to and following treatment; therefore, it offers a more accurate metric of recovery. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00021528.

Predicting relapse in major depressive disorder using patient-reported outcomes of depressive symptom severity, functioning, and quality of life in the Individual Burden of Illness Index for Depression (IBI-D).

BACKGROUND: Patients with Major Depressive Disorder (MDD) often experience unexpected relapses, despite achieving remission. This study examines the utility of a single multidimensional measure that captures variance in patient-reported Depressive Symptom Severity, Functioning, and Quality of Life (QOL), in predicting MDD relapse. METHODS: Complete data from remitted patients at the completion of 12 weeks of citalopram in the STAR*D study were used to calculate the Individual Burden of Illness index for Depression (IBI-D), and predict subsequent relapse at six (n=956), nine (n=778), and twelve months (n=479) using generalized linear models. RESULTS: Depressive Symptom Severity, Functioning, and QOL were all predictors of subsequent relapse. Using Akaike information criteria (AIC), the IBI-D provided a good model for relapse even when Depressive Symptom Severity, Functioning, and QOL were combined in a single model. Specifically, an increase of one in the IBI-D increased the odds ratio of relapse by 2.5 at 6 months (ß=0.921 ± 0.194, z=4.76, p<2 × 10(-6)), by 2.84 at 9 months (ß=1.045 ± 0.22, z=4.74, p<2.2 × 10(-6)), and by 4.1 at 12 months (ß=1.41 ± 0.29, z=4.79, p<1.7 × 10(-6)). LIMITATIONS: Self-report poses a risk to measurement precision. Using highly valid and reliable measures could mitigate this risk. The IBI-D requires time and effort for filling out the scales and index calculation. Technological solutions could help ease these burdens. The sample suffered from attrition. Separate analysis of dropouts would be helpful. CONCLUSIONS: Incorporating patient-reported outcomes of Functioning and QOL in addition to Depressive Symptom Severity in the IBI-D is useful in assessing the full burden of illness and in adequately predicting relapse, in MDD.