Why Do People with Severe Mental Illness Have Poor Cardiovascular Health?-The Need for Implementing a Recovery-Based Self-Management Approach

Impact of the mental health reform in Israel on health care and mortality among people with severe mental illness

OBJECTIVE

Reports show disparities in the health care of people with severe mental illness (SMI). Yet, the moderating effect of mental health reforms on the health care disparities remain unexplored. The current study aimed to investigate the outcomes of the mental health reform in Israel on the use of health services among people with SMI.

METHOD

A case-control epidemiological study comparing the use of health services 3.5 years before and after the mental health reform for service users diagnosed with schizophrenia, schizoaffective disorder, and bipolar disorder. Data on health services included: blood cholesterol test (LDL), hemogalobin-A1C test, and visits to general practitioners (GPs) and specialists. Mortality was recorded.

RESULTS

Following the reform the number of visits to GPs was decreased among service users of the three SMI groups, as well as visits to specialists among service users with a schizoaffective or bipolar disorder. Following the reform service users of the three SMI groups showed no-change in the performance of LDL test. Complex findings were noted with regard to the performance of Hemoglobin-A1C test. Mortality rates were higher among service users with SMI and the relative risk were similar before and after the reform.

CONCLUSIONS

Users of the three SMI groups showed no benefits of the mental health reform in terms of use of health services. Improved health care can be attained by a closer collaboration between the primary physicians and community mental health services.

Stroke and suicide among people with severe mental illnesses

The associations between people with severe mental illnesses (SMI) and the risks of stroke, suicide, and death remain unclear. We examined healthcare service usage among adults with and without SMI and explored the risk of stroke, suicide, and death. We divided 18-80-year-old adults with SMI into catastrophic and non-catastrophic illness groups. These groups were subjected to a 1:5:5 propensity score matching with people without SMI. Data on demographic characteristics, economic factors, environmental factors, comorbid conditions, self-injury behavior, the number of outpatients and ED visits, and hospitalization were collected. The primary outcomes were risks of stroke, suicide, and death. We included 19,570 people with catastrophic SMI, 97,850 with non-catastrophic SMI, and 97,850 controls. Patients with SMI, especially those with catastrophic illnesses, had higher stroke risk, suicide, and death than those without SMI. People with SMI used health services more frequently than those without SMI. Patients with a history of hospitalization or ED access had a higher risk of stroke, suicide, and death. Our data indicate that special attention should be given to patients with SMI, particularly those with a history of healthcare service utilization, such as through more extended hospital stays with high-intensity interventions.

Measuring Engagement with Mental Health and Behavior Change Interventions: an Integrative Review of Methods and Instruments

BACKGROUND

Engagement is a complex construct consisting of behavioral, cognitive, and affective dimensions, making engagement a difficult construct to measure. This integrative review aims to (1) present a multidisciplinary overview of measurement methods that are currently used to measure engagement with adult mental health and behavior change interventions, delivered in-person, blended, or digitally, and (2) provide a set of recommendations and considerations for researchers wishing to study engagement.

METHODS

We used an integrative approach and identified original studies and reviews on engagement with mental health or behavior change interventions that were delivered in-person, digitally, or blended.

RESULTS

Forty articles were analyzed in this review. Common methods to assess engagement were through objective usage data, questionnaire-based data, and qualitative data, with objective usage data being used most frequently. Based on the synthesis of engagement measures, we advise researchers to (1) predefine the operationalization of engagement for their specific research context, (2) measure behavioral, cognitive, and affective dimensions of engagement in all cases, and (3) measure engagement over time.

CONCLUSIONS

Current literature shows a bias towards behavioral measures of engagement in research, as most studies measured engagement exclusively through objective usage data, without including cognitive and affective measures of engagement. We hope that our recommendations will help to reduce this bias and to steer engagement research towards an integrated approach.