Jared M. Greenberg

Quality of Life: The Ultimate Outcome Measure of Interventions in Major Depressive Disorder

Background: Quality‐of‐life (QOL) assessment and improvement have recently been recognized as important components of health care, in general, and mental health care, in particular. Patients with major depressive disorder (MDD) have a significantly diminished QOL. Methods: Using a Medline search of relevant keywords for the past 26 years, this article reviews the empirical literature to provide information regarding QOL measurement, impairment, impact of comorbidity, and treatment effects in MDD. Results: Studies showed that QOL is greatly affected by depression. Severity of depression is also a major contributor to further reduction in QOL when depression is comorbid with other psychiatric and medical disorders. Treatment for MDD has been shown to improve QOL in the acute treatment phase, but QOL remains low compared to healthy controls even when symptoms are in remission following treatment. Conclusions: Patients with MDD suffer from poor QOL even after reduction of symptom severity. Clinicians should therefore include QOL assessment as an important part of treating depression. More research is needed to examine the factors contributing to poor QOL in MDD and to develop interventions to ameliorate it. Additionally, future treatment studies of MDD with or without comorbid disorders should track QOL as the ultimate outcome measure of treatment success.

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 individuals 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 (β=0.921 ± 0.194, z=4.76, p<2 × 10(-6)), by 2.84 at 9 months (β=1.045 ± 0.22, z=4.74, p<2.2 × 10(-6)), and by 4.1 at 12 months (β=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.

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.

Sex and Quality of Life

Sex is a key function of human beings. Its physical, emotional, psychological, and social aspects permeate into many parts of our lives. Therefore, it is a major contributor to “Quality of life” (QoL). This chapter covers defining and measuring sexual QoL, and then details sex and QoL in nonclinical populations covering a variety of demographic groups. A detailed review follows for QoL in clinical populations of medical/surgical, psychiatric disorders, and sexual disorders before and after treatment. The chapter concludes with a discussion of ways to enhance QoL by detailing interventions to improve QoL in general and in sex in particular.

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.

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.