Psychosocial features of clinically relevant patient sub-groups with serious mental illness and comorbid diabetes

Abstract

Objective

Care for people with serious mental illness and diabetes is complicated by clinical heterogeneity. This cross-sectional analysis of 200 individuals comorbid for serious mental illness and diabetes explored differentiation of patient sub-groups characterized on selected dimensions within a biopsychosocial framework.

Methods

Relationships between self-efficacy, treatment expectation, social support and psychiatric symptom severity were first assessed via bivariate Spearman correlations among 200 individuals participating in a randomized trial who have diabetes and major depression, bipolar disorder, or schizophrenia. Next, latent profile analysis were conducted to determine underlying subgroups based on these variables. The resultant groups were compared on diabetes control, function, and symptoms.

Results

In the two sub-groups, group A was high on psychiatric symptoms, low on other psychosocial variables and had worse diabetes control. Group B was low on depression and high on other variables and had better diabetes control.

Conclusions

Symptom presentation, internal and external resources appear related to diabetes control in people comorbid for diabetes and serious mental illness. Care approaches need to go beyond standard education and consider biopsychosocial variables.

Introduction

Individuals with serious mental illness are particularly vulnerable to diabetes and related complications¹. As noted in a recent review, data on evidence-based care for these comorbid conditions is limited².

Psychosocial factors strongly associated with self-management of chronic health conditions, such as diabetes and serious mental illness, include social support, self-efficacy, and treatment outcome expectancies³. Self-efficacy is related to illness self-management activities including diet, exercise and smoking among the seriously mentally ill⁴, and is also an important factor for self-managing diabetes³. Social support helps maintain healthy behaviors in people with serious mental illness³. Outcome expectancies about whether a given treatment will result in positive outcomes, predict the likelihood of engagement in psychiatric and diabetes care⁵.

Psychiatric symptoms, including mood, are an important determinant of diabetes outcomes and a core dimension of self-management². A recent review emphasizes the contribution of depression to poor glycemic control, medical complications, poor outcomes and quality of life in diabetic patients. The specific relationship of mood and psychiatric symptom severity to diabetes management in people with more severe psychiatric illness is understudied.⁶

Psychiatric symptom severity, including mood, and self-efficacy have been studied in large trials², but other psychosocial factors associated with effective self -management are less well-understood. Given the limited information available on possible psychosocial correlates of illness status among patients comorbid for serious mental illness and diabetes, we conducted an exploratory statistical analysis to see if we could identify sub-groups of individuals with common symptom and psychosocial features. Based on the literature for chronic conditions in general, including mental illness and diabetes studied separately, we hypothesized that patterns of social support, self-efficacy, outcome expectancies, and mood could identify clinically relevant subgroups that differed on key psychiatric and diabetes-related factors. Understanding these inter-relationships may aid in the future selection of personalized treatment approaches.

Methods

This analysis used baseline data from 200 participants enrolled in a randomized controlled trial from November 21, 2011 through April 14, 2014, in a safety net setting, testing a novel self-management intervention vs. treatment as usual among seriously mentally ill patients comorbid for diabetes (1R01MH085665).

The inclusion criteria included having schizophrenia, schizoaffective disorder, bipolar disorder or major depression confirmed with the Mini-International Neuropsychiatric Interview (MINI)⁷, having type II diabetes and being ≥ 18 years of age.

Mean age of subjects was 52.7 +/− 9.5 years, with 64% women,53% African-Americans and 8% Hispanics.

Depression symptom severity was measured using the Montgomery Asberg Depression Rating Scale (MADRS)⁸. Global symptom severity was measured using the Brief Psychiatric Rating Scale (BPRS)⁹. The Global Assessment of Functioning scale (GAF) measured function. Social support was measured using the Multidimensional Scale of Perceived Social Support (MSPSS)¹⁰ which measures perception of social support systems and sources of social support. Perceived therapeutic efficacy for diabetes was measured utilizing the Perceived Therapeutic Efficacy Scale (PTES), which measures outcome expectancy related to treatments¹¹. Self-efficacy for diabetes was measured using the Perceived Diabetes Self-Management Scale (PDSMS)¹², a diabetes-specific adaptation of the Perceived Medical-Condition Self-Management Scale. The generic template from which the PDSMS was adapted can be modified for use with other chronic medical conditions. Self-efficacy for serious mental illness was measured with a modified template, the Perceived Mental Health Self-Management Scale (PMHSMS).

Diabetes control was evaluated with HbA1c which represents an average blood glucose level over the previous 3 months. The American Diabetes Association recommends that HbA1c be < 6.5%. Given the traditional focus in many standard diabetes education approaches, diabetes knowledge was assessed with the Brief Diabetes Knowledge Test¹³.

Data Analysis

The overall analysis explored potential differentiation of patient sub-groups characterized by their similarity on selected dimensions within a biopsychosocial framework utilizing depression, self-efficacy for serious mental illness and for diabetes, perceived therapeutic efficacy, and social support. We first assessed the relationships between self-efficacy, treatment expectation, social support and depression via bivariate Spearman correlations. Next, we conducted a multivariate latent profile analysis (LPA) to determine underlying subgroups based on these variables. LPA relates a set of observed continuous multivariate variables to a set of latent profiles (underlying subgroups) on a likelihood scale. The five scales were standardized to contribute equally to the analysis (i.e. similar ranges and variability). The subgroups identified by LPA are not known a priori, but rather are determined empirically. The single group model is first specified, which is then used as a comparison for models of increasing number of subgroups until the best-fitting model is identified. For each individual we estimate the probability of their membership in each subgroup. Individuals were then classified according to the subgroup for which they have the highest likelihood of membership, forming a categorical measure with a fixed number of profiles. We measured how well the model performed utilizing the entropy statistic. Sample means of the variables used in the LPA in each subgroup helped assign meaning to each latent class. Finally, we calculated whether these subgroups differenced on BPRS, GAF, HbA1c, diagnosis, and demographic factors utilizing t-tests and Chi Square.

Results

Depression symptom severity was significantly negatively correlated with all the psychosocial variables: self-efficacy for diabetes, r= −.32, p<.001; self-efficacy for serious mental illness, r=−49, p<.001; social support, r=−31, p<.001; and treatment expectancy, r=−.19, p<.02. The psychosocial variables were all significantly positively correlated with the exception of the positive correlation between treatment expectancies and social support which did not reach significance.

Latent profile analysis yielded two sub-groups based on the Lo-Mendell Rubin (LMR) Test¹⁴. The entropy for this latent profile analytic model was 0.883, denoting that model classified subjects relatively well. Group A (40% of the overall sample) is characterized by significantly higher levels of depression and significantly lower levels of self-efficacy for both diabetes mellitus and serious mental illness, perceived treatment efficacy, and social support (Table 1) compared to group B (59% of the overall sample).

Table 1.

Post-hoc Examination of Latent Profile Analysis Characterization of 2 Distinct Subgroups of Individuals with Serious Mental Illness and Comorbid Diabetes.

Variable	All individuals With serious mental illness-diabetes mellitus N= 200		Group A “Highly symptomatic, low resources” N= 81		Group B “Less symptomatic, more resources” N= 119		Statistic p-value
VARIABLES USED IN LATENT PROFILE ANALYSIS
MADRS	24.0 ± 9.1		31.0 ± 6.4		19.4 ± 7.6		<0.001
MSPSS	41.4 ± 10.2		35.0 ± 10.5		45.9 ± 7.1		<0.001
PDSMS	25.5 ± 6.9		21.8 ± 5.8		28.1 ± 5.4		<0.001
PHMHSMS	26.5 ± 6.5		21.3 ± 5.6		30.2 ± 4.1		<0.001
PTES	76.7 ± 16.8		69.3 ± 20.4		82.1 ± 11.1		<0.001
OTHER CLINICALLY RELEVANT VARIABLES
BPRS	40.0 ± 9.3		44.4 ± 8.7		37.1 ± 8.8		<0.001
GAF	51.6 ± 11.5		46.9 ± 8.7		54.8 ± 11.4		<0.001
HbA1c	8.2 ± 3.0		8.5 ± 2.6		7.6 ± 2.0		0.011
	N	%	N	%	N	%
Serious Mental Illness
Diagnosis							0.595
Schizophrenia	49	25	18	22	31	26
Bipolar Disorder	56	28	21	26	35	30
Major Depression	95	48	42	52	53	45

Mean ± standard deviation for continuous measures and number of subjects in each category for discrete measures with p-values reported from t-tests and chi-square tests where appropriate.

MADRS = Montgomery Asberg Depression Rating Scale, possible scores range from 0 – 60, with higher scores indicating more severe depression

MSPSS= Multidimensional Scale of Perceived Social Support, possible scores range from 1 – 84, with higher scores indicating greater perceived social support

PDSMS= Perceived Diabetes Self-Management Scale, possible scores range from 8 – 40, with higher scores indicating greater perceived diabetes self-management confidence

PMHSMS= Perceived Mental Health Self-Management Scale, possible scores range from 8 – 40, with higher scores indicating greater perceived mental health self-management confidence

PTES= Perceived Therapeutic Efficacy Scale, possible scores range from 0 – 100, with higher scores indicating higher confidence

BPRS= Brief Psychiatric Rating Scale, possible scores range from 18 – 126, with higher scores indicating more severity

GAF= Global Assessment of Functioning, possible scores range from 1 – 100, with higher scores indicating better functioning

HbA1c= glycosylated hemoglobin

Table 1 also presents the group means on clinically relevant variables not used in forming the groups. Group A was significantly higher on psychiatric symptoms, significantly higher on HgbA1c (worse control of diabetes) and significantly lower on global functioning. The groups did not differ significantly on age, race, gender, body mass index, psychiatric diagnosis, or on diabetes knowledge.

Discussion

Self-management for patients comorbid for serious mental illness and diabetes is complex and includes a variety of elements such as taking medications reliably and on-time, as well as challenging life-style commitments. Heterogeneity among the seriously mentally ill makes it unlikely that a “one-size fits all” approach will be optimal in meeting diverse patient needs. Additionally, resource constraints in real-world treatment settings make it impractical to implement labor-intensive interventions for every patient comorbid for serious mental illness and diabetes. There has been limited research on how best to approach medically complex seriously mentally ill patients and match right treatments to the right individuals.

This analysis using variables that have been independently demonstrated to be related to care engagement for seriously mentally ill patients supported the presence of two conceptually distinct subgroups. In clinical terms, group A can be conceptualized as having higher depression and lower internal and external resources in contrast to group B which can be conceptualized as having less depression and more resources. Group A, with the most severe depression, had the least confidence that they could manage both their psychiatric illness and diabetes, had the lowest expectations for treatment, and the lowest perceived social support. This group scored significantly worse on measures of psychiatric symptom severity, general functioning and diabetes control than the other group.

Clinical implications of these findings suggest that the higher symptom/lower resource group might require more focused and intensive effort to improve self-management. Limitations in social networks, and their need for empowerment and self-confidence may make them the best candidates for personalized interventions such as peer specialists, care navigators and home outreach. The consistency of their more severe psychiatric symptoms may also indicate a need for more aggressive use of psychiatric therapies for depression.

The group with the lowest depression severity displayed relatively high self-efficacy for both mental illness and diabetes, had a relatively optimistic outlook on outcomes of treatment, and reported stronger social support. They also had relatively better control of their diabetes. They may be good candidates for less intensive self-management interventions. Examples could include computer-based programs or care that is only incrementally different from standard diabetes education. Given their relatively strong levels of social support, involving members of the patient’s support network could enhance their relatively strong psychological processes.

While other studies have often measured both depression and self-efficacy, this study is unique in including additional psychosocial variables which have been shown in other populations and in limited studies, to be relevant to outcomes in the seriously mentally ill. The relationships among the symptoms, health status and internal and external supports in individuals with serious mental illness and diabetes, underscores the importance of enhancing support with peer counselors or other individuals who can help address unique concerns and help meet ongoing challenges.

The magnitude of mean mood score differences between the groups is notable. Using reports which have suggested a MADRS total score of 31 as a cutoff between severe and moderate depression¹⁵ and a MADRS cutoff of 20–24 between mild and moderate depression, the group A MADRS mean fell in the severe range, and the group B mean in the mild range. While study assessments included very gross measurement of psychiatric drugs, we did not have information on drug dosages or previous drug treatments or on psychotherapeutic treatments that may have been tried in the past.

Interestingly, psychiatric diagnosis did not appear to be related to characteristics that described these two sub-groups. The distribution of diagnoses among the sub-groups suggests that underlying psychosocial mechanisms appear independent of diagnosis. Additionally, diabetes knowledge was not different between the two groups. This suggests that psychiatric symptom severity and the constellation of psychosocial factors included in the group formation may offer additional opportunities to improve diabetes control in addition to standard diabetes knowledge enhancement approaches.

This study has a number of limitations, including single site enrollment, limited data on past and current pharmacological and behavioral treatments, and that research samples may not entirely represent “real-world” populations. Strengths of the analysis include the confirmed diagnoses, and enrollment in a safety-net primary care setting where many high-risk medically complex individuals with serious mental illness receive care.

In conclusion, the limited studies that have been conducted on seriously mentally ill patients with chronic medical conditions, including diabetes, suggest that psychiatric symptom severity, including depression and self-efficacy are modifiable². Social support networks can also be expanded, and outcome expectancy have been shown to be changeable. Consideration of all of these factors can potentially personalize care tailored to specific challenges and strengths among patients comorbid for serious mental illness and diabetes and may inform treatment approaches that can advance care for this vulnerable group of individuals.