Community‐based social interventions for people with severe mental illness: a systematic review and narrative synthesis of recent evidence

People living with severe mental illness (SMI) are one of the most marginalized groups in society. Interventions which aim to improve their social and economic participation are of crucial importance to clinicians, policy‐makers and people with SMI themselves. We conducted a systematic review of the literature on social interventions for people with SMI published since 2016 and collated our findings through narrative synthesis. We found an encouragingly large amount of research in this field, and 72 papers met our inclusion criteria. Over half reported on the effectiveness of interventions delivered at the service level (supported accommodation, education or employment), while the remainder targeted individuals directly (community participation, family interventions, peer‐led/supported interventions, social skills training). We identified good evidence for the Housing First model of supported accommodation, for the Individual Placement and Support model of supported employment, and for family psychoeducation, with the caveat that a range of models are nonetheless required to meet the varied housing, employment and family‐related needs of individuals. Our findings also highlighted the importance of contextual factors and the need to make local adaptations when “importing” interventions from elsewhere. We found that augmentation strategies to enhance the effectiveness of social interventions (particularly supported employment and social skills training) by addressing cognitive impairments did not lead to transferable “real life” skills despite improvements in cognitive function. We also identified an emerging evidence base for peer‐led/supported interventions, recovery colleges and other interventions to support community participation. We concluded that social interventions have considerable benefits but are arguably the most complex in the mental health field, and require multi‐level stakeholder commitment and investment for successful implementation.     

Physical healthcare of people with severe mental illness: everybody's business!

Aim People with severe mental illness are at higher risk of physical health problems. Guidelines recommend annual monitoring. An audit cycle was completed on individuals with severe mental illness under the care of an early interventions in psychosis (EIP) service to evaluate and improve physical health monitoring practice.Methods The number of patients who had undergone a physical health check in the previous year, and those having a record of it in their EIP notes, was examined. Interventions made between baseline audit and re-audit included improving awareness within the multidisciplinary EIP mental health team about the importance of physical health monitoring of people with severe mental illness and liaison with primary care health services.Results The number of patients undergoing at least one annual physical health check increased from 20% to 58%. Among patients who had undergone a physical health check at re-audit, a record of some or all the checks was available in the notes for 75% of patients.Clinical implications There is a need to improve awareness among mental health professionals about the importance of the physical health of people with severe mental illness and to make appropriate organisational changes.     

Temporal trends in associations between severe mental illness and risk of cardiovascular disease: A systematic review and meta-analysis

BackgroundSevere mental illness (SMI; schizophrenia, bipolar disorders (BDs), and other nonorganic psychoses) is associated with increased risk of cardiovascular disease (CVD) and CVD-related mortality. To date, no systematic review has investigated changes in population level CVD-related mortality over calendar time. It is unclear if this relationship has changed over time in higher-income countries with changing treatments.Methods and findingsTo address this gap, a systematic review was conducted, to assess the association between SMI and CVD including temporal change. Seven databases were searched (last: November 30, 2021) for cohort or case–control studies lasting ≥1 year, comparing frequency of CVD mortality or incidence in high-income countries between people with versus without SMI. No language restrictions were applied. Random effects meta-analyses were conducted to compute pooled hazard ratios (HRs) and rate ratios, pooled standardised mortality ratios (SMRs), pooled odds ratios (ORs), and pooled risk ratios (RRs) of CVD in those with versus without SMI. Temporal trends were explored by decade. Subgroup analyses by age, sex, setting, world region, and study quality (Newcastle–Ottawa scale (NOS) score) were conducted. The narrative synthesis included 108 studies, and the quantitative synthesis 59 mortality studies (with (≥1,841,356 cases and 29,321,409 controls) and 28 incidence studies (≥401,909 cases and 14,372,146 controls). The risk of CVD-related mortality for people with SMI was higher than controls across most comparisons, except for total CVD-related mortality for BD and cerebrovascular accident (CVA) for mixed SMI. Estimated risks were larger for schizophrenia than BD. Pooled results ranged from SMR = 1.55 (95% confidence interval (CI): 1.33 to 1.81, p < 0.001), for CVA in people with BD to HR/rate ratio = 2.40 (95% CI: 2.25 to 2.55, p < 0.001) for CVA in schizophrenia. For schizophrenia and BD, SMRs and pooled HRs/rate ratios for CHD and CVD mortality were larger in studies with outcomes occurring during the 1990s and 2000s than earlier decades (1980s: SMR = 1.14, 95% CI: 0.57 to 2.30, p = 0.71; 2000s: SMR = 2.59, 95% CI: 1.93 to 3.47, p < 0.001 for schizophrenia and CHD) and in studies including people with younger age. The incidence of CVA, CVD events, and heart failure in SMI was higher than controls. Estimated risks for schizophrenia ranged from HR/rate ratio 1.25 (95% CI: 1.04 to 1.51, p = 0.016) for total CVD events to rate ratio 3.82 (95% CI: 3.1 to 4.71, p < 0.001) for heart failure. Incidence of CHD was higher in BD versus controls. However, for schizophrenia, CHD was elevated in higher-quality studies only. The HR/rate ratios for CVA and CHD were larger in studies with outcomes occurring after the 1990s. Study limitations include the high risk of bias of some studies as they drew a comparison cohort from general population rates and the fact that it was difficult to exclude studies that had overlapping populations, although attempts were made to minimise this.ConclusionsIn this study, we found that SMI was associated with an approximate doubling in the rate ratio of CVD-related mortality, particularly since the 1990s, and in younger groups. SMI was also associated with increased incidence of CVA and CHD relative to control participants since the 1990s. More research is needed to clarify the association between SMI and CHD and ways to mitigate this risk.

Amanda Lambert and co-workers study associations between severe mental illness and cardiovascular disease outcomes over time.     

Understanding and addressing religion among people with mental illness

This article reviews recent advances in the domain of psychiatry and religion that highlight the double‐edged capacity of religion to enhance or damage health and well‐being, particularly among psychiatric patients. A large body of research challenges stereotyped views of religion as merely a defense or passive way of coping, and indicates that many people look to religion as a vital resource which serves a variety of adaptive functions, such as self‐regulation, attachment, emotional comfort, meaning, and spirituality. There is, however, a darker side to religious life. Researchers and theorists have identified and begun to study problematic aspects of religiousness, including religiously‐based violence and religious struggles within oneself, with others, and with the divine. Religious problems can be understood as a by‐product of psychiatric illness (secondary), a source of psychiatric illness (primary), or both (complex). This growing body of knowledge underscores the need to attend more fully to the potentially constructive and destructive roles of religion in psychiatric diagnosis, assessment, and treatment. In fact, initial evaluative studies of the impact of spiritually integrated treatments among a range of psychiatric populations have shown promising results. The article concludes with a set of recommendations to advance future research and practice, including the need for additional psychiatric studies of people from diverse cultures and religious traditions.     

Utilization of the Behavior Change Wheel framework to develop a model to improve cardiometabolic screening for people with severe mental illness

Background

Individuals with severe mental illness (e.g., schizophrenia, bipolar disorder) die 10–25 years earlier than the general population, primarily from premature cardiovascular disease (CVD). Contributing factors are complex, but include systemic-related factors of poorly integrated primary care and mental health services. Although evidence-based models exist for integrating mental health care into primary care settings, the evidence base for integrating medical care into specialty mental health settings is limited. Such models are referred to as “reverse” integration. In this paper, we describe the application of an implementation science framework in designing a model to improve CVD outcomes for individuals with severe mental illness (SMI) who receive services in a community mental health setting.

Methods

Using principles from the theory of planned behavior, focus groups were conducted to understand stakeholder perspectives of barriers to CVD risk factor screening and treatment identify potential target behaviors. We then applied results to the overarching Behavior Change Wheel framework, a systematic and theory-driven approach that incorporates the COM-B model (capability, opportunity, motivation, and behavior), to build an intervention to improve CVD risk factor screening and treatment for people with SMI.

Results

Following a stepped approach from the Behavior Change Wheel framework, a model to deliver primary preventive care for people that use community mental health settings as their de facto health home was developed. The CRANIUM (cardiometabolic risk assessment and treatment through a novel integration model for underserved populations with mental illness) model focuses on engaging community psychiatrists to expand their scope of practice to become responsible for CVD risk, with significant clinical decision support.

Conclusion

The CRANIUM model was designed by integrating behavioral change theory and implementation theory. CRANIUM is feasible to implement, is highly acceptable to, and targets provider behavior change, and is replicable and efficient for helping to integrate primary preventive care services in community mental health settings. CRANIUM can be scaled up to increase CVD preventive care delivery and ultimately improve health outcomes among people with SMI served within a public mental health care system.

     

Associations between social jetlag and mental health in young people: A systematic review

ABSTRACT

Adolescence and early adulthood (collectively categorized as “young people”) is a transitional period associated with a number of key physiological, social and psychological changes. Sleep difficulties, notable in this age group, may adversely affect physical and mental health. Of interest is the impact of the natural shift in young people towards a more evening-type sleep pattern (chronotype), whilst social constraints encourage early waking to fit with school/work timings. This leads to a misalignment in sleep timing between weekdays and weekends, known as social jetlag, which may contribute to emerging mental health difficulties seen during this age group. A systematic literature review was undertaken to investigate the association between social jetlag and mental health outcomes.

Systematic searching of electronic databases (The Cochrane Library; PsycINFO; CINAHL; Scopus; and PubMed), grey literature and review of reference lists identified seven studies which assessed associations between social jetlag and mental health outcomes in young people. Quality appraisal was completed using the Appraisal Tool for Cross-Sectional Studies.

Findings appeared equivocal; however significant associations were revealed with social jetlag associated with clinical depression and seasonal depression, in female participants and high latitude regions. Quality of included studies was moderate (10–13 criteria met). A lack of homogeneity between study methodologies precluded the conduct of a meta-analysis.

The ambiguous results found may result from confounding factors including non-comparable methods of measuring social jetlag and mental health both in this age group and the selected studies. Future research should address a lack of homogeneity through the development of an interdisciplinary core outcome set, and agreement on a standardized measure and calculation for social jetlag.     

Clustering of physical health multimorbidity in people with severe mental illness: An accumulated prevalence analysis of United Kingdom primary care data

BackgroundPeople with severe mental illness (SMI) have higher rates of a range of physical health conditions, yet little is known regarding the clustering of physical health conditions in this population. We aimed to investigate the prevalence and clustering of chronic physical health conditions in people with SMI, compared to people without SMI.Methods and findingsWe performed a cohort-nested accumulated prevalence study, using primary care data from the Clinical Practice Research Datalink (CPRD), which holds details of 39 million patients in the United Kingdom. We identified 68,783 adults with a primary care diagnosis of SMI (schizophrenia, bipolar disorder, or other psychoses) from 2000 to 2018, matched up to 1:4 to 274,684 patients without an SMI diagnosis, on age, sex, primary care practice, and year of registration at the practice. Patients had a median of 28.85 (IQR: 19.10 to 41.37) years of primary care observations. Patients with SMI had higher prevalence of smoking (27.65% versus 46.08%), obesity (24.91% versus 38.09%), alcohol misuse (3.66% versus 13.47%), and drug misuse (2.08% versus 12.84%) than comparators. We defined 24 physical health conditions derived from the Elixhauser and Charlson comorbidity indices and used logistic regression to investigate individual conditions and multimorbidity. We controlled for age, sex, region, and ethnicity and then additionally for health risk factors: smoking status, alcohol misuse, drug misuse, and body mass index (BMI). We defined multimorbidity clusters using multiple correspondence analysis (MCA) and K-means cluster analysis and described them based on the observed/expected ratio. Patients with SMI had higher odds of 19 of 24 conditions and a higher prevalence of multimorbidity (odds ratio (OR): 1.84; 95% confidence interval [CI]: 1.80 to 1.88, p < 0.001) compared to those without SMI, particularly in younger age groups (males aged 30 to 39: OR: 2.49; 95% CI: 2.27 to 2.73; p < 0.001; females aged 18 to 30: OR: 2.69; 95% CI: 2.36 to 3.07; p < 0.001). Adjusting for health risk factors reduced the OR of all conditions. We identified 7 multimorbidity clusters in those with SMI and 7 in those without SMI. A total of 4 clusters were common to those with and without SMI; while 1, heart disease, appeared as one cluster in those with SMI and 3 distinct clusters in comparators; and 2 small clusters were unique to the SMI cohort. Limitations to this study include missing data, which may have led to residual confounding, and an inability to investigate the temporal associations between SMI and physical health conditions.ConclusionsIn this study, we observed that physical health conditions cluster similarly in people with and without SMI, although patients with SMI had higher burden of multimorbidity, particularly in younger age groups. While interventions aimed at the general population may also be appropriate for those with SMI, there is a need for interventions aimed at better management of younger-age multimorbidity, and preventative measures focusing on diseases of younger age, and reduction of health risk factors.

In an observational analysis of primary care data from the UK, Naomi Launders and colleagues study the prevalence and clustering of physical health conditions and multimorbidity in individuals with severe mental illnesses.