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Clinical characteristics of individuals with serious mental illness and type 2 diabetes.

ABSTRACT: Data from 157 individuals with serious mental illness and comorbid diabetes enrolled in an ongoing treatment study were used to examine clinical correlates of diabetes control.Factors assessed included depressive symptoms (Montgomery-Åsberg Depression Rating Scale), global psychopathology severity (Brief Psychiatric Rating Scale), and glycosylated hemoglobin (HbA1c), a biomarker of diabetes control.Seventy-seven participants had depression, 40 had schizophrenia, and 40 had bipolar disorder. Most were moderately to severely depressed with poor diabetes control. No correlation between diagnosis and diabetes control was found after adjustment for gender, race, health literacy, diabetes duration, and diabetes knowledge. Greater depression severity and longer diabetes duration were related to poorer diabetes control. Lower severity of global psychopathology was related to poorer diabetes control, perhaps because of overall low levels of psychosis and mania.People with serious mental illness and diabetes face multiple challenges, which, along with severe depression, may impede diabetes self-management.

SUBMITTER: Sajatovic M

PROVIDER: S-EPMC4315335 | biostudies-other | 2015 Feb

REPOSITORIES: biostudies-other

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Clinical characteristics of individuals with serious mental illness and type 2 diabetes.

Sajatovic Martha M Gunzler Douglas D Einstadter Douglas D Thomas Charles C McCormick Richard A RA Perzynski Adam T AT Kanuch Stephanie S Cassidy Kristin A KA Dawson Neal V NV

Psychiatric services (Washington, D.C.) 20141117 2

<h4>Objective</h4>Data from 157 individuals with serious mental illness and comorbid diabetes enrolled in an ongoing treatment study were used to examine clinical correlates of diabetes control.<h4>Methods</h4>Factors assessed included depressive symptoms (Montgomery-Åsberg Depression Rating Scale), global psychopathology severity (Brief Psychiatric Rating Scale), and glycosylated hemoglobin (HbA1c), a biomarker of diabetes control.<h4>Results</h4>Seventy-seven participants had depression, 40 ha ...[more]

PMID: 25642615

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Project description:AimsPsychosocial rehabilitation (PSR) is at the core of psychiatric recovery. There is a paucity of evidence regarding how the needs and characteristics of patients guide clinical decisions to refer to PSR interventions. Here, we used explainable machine learning methods to determine how socio-demographic and clinical characteristics contribute to initial referrals to PSR interventions in patients with serious mental illness.MethodsData were extracted from the French network of rehabilitation centres, REHABase, collected between years 2016 and 2022 and analysed between February and September 2022. Participants presented with serious mental illnesses, including schizophrenia spectrum disorders, bipolar disorders, autism spectrum disorders, depressive disorders, anxiety disorders and personality disorders. Information from 37 socio-demographic and clinical variables was extracted at baseline and used as potential predictors. Several machine learning models were tested to predict initial referrals to four PSR interventions: cognitive behavioural therapy (CBT), cognitive remediation (CR), psychoeducation (PE) and vocational training (VT). Explanatory power of predictors was determined using the artificial intelligence-based SHAP (SHapley Additive exPlanations) method from the best performing algorithm.ResultsData from a total of 1146 patients were included (mean age, 33.2 years [range, 16-72 years]; 366 [39.2%] women). A random forest algorithm demonstrated the best predictive performance, with a moderate or average predictive accuracy [micro-averaged area under the receiver operating curve from 'external' cross-validation: 0.672]. SHAP dependence plots demonstrated insightful associations between socio-demographic and clinical predictors and referrals to PSR programmes. For instance, patients with psychotic disorders were more likely to be referred to PE and CR, while those with non-psychotic disorders were more likely to be referred to CBT and VT. Likewise, patients with social dysfunctions and lack of educational attainment were more likely to be referred to CR and VT, while those with better functioning and education were more likely to be referred to CBT and PE.ConclusionsA combination of socio-demographic and clinical features was not sufficient to accurately predict initial referrals to four PSR programmes among a French network of rehabilitation centres. Referrals to PSR interventions may also involve service- and clinician-level factors. Considering socio-demographic and clinical predictors revealed disparities in referrals with respect to diagnoses, current clinical and psychological issues, functioning and education.

Project description:BackgroundExperiences of homelessness and serious mental illness (SMI) negatively impact health and receipt of healthcare. Interventions that promote the use of primary care services for people with both SMI and homelessness may improve health outcomes, but this literature has not been evaluated systematically. This evidence map examines the breadth of literature to describe what intervention strategies have been studied for this population, elements of primary care integration with other services used, and the level of intervention complexity to highlight gaps for future intervention research and program development.MethodsWe followed an a priori protocol developed in collaboration with clinical stakeholders. We systematically searched the published literature to identify interventions for adults with homelessness who also had SMI. We excluded case reports, editorials, letters, and conference abstracts. Data abstraction methods followed standard practice. Data were categorized into intervention strategies and primary care integration strategies. Then we applied the Complexity Assessment Tool for Systematic Reviews (iCAT_SR) to characterize intervention complexity.ResultsTwenty-two articles met our inclusion criteria evaluating 15 unique interventions to promote engagement in primary care for adults with experiences of homelessness and SMI. Study designs varied widely from randomized controlled trials and cohort studies to single-site program evaluations. Intervention strategies varied across studies but primarily targeted patients directly (e.g., health education, evidence-based interactions such as motivational interviewing) with fewer strategies employed at the clinic (e.g., employee training, multidisciplinary teams) or system levels (e.g., data sharing). We identified elements of primary care integration, including referral strategies, co-location, and interdisciplinary care planning. Interventions displayed notable complexity around the number of intervention components, interaction between intervention components, and extent to which interventions were tailored to specific patient populations.DiscussionWe identified and categorized elements used in various combinations to address the primary care needs of individuals with experiences of homeless and SMI.

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Clinical characteristics of individuals with serious mental illness and type 2 diabetes.

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Clinical characteristics of individuals with serious mental illness and type 2 diabetes.

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