Functional assessment short test (FAST): Self-administration in outpatient mental health settings.

The Functional Assessment Short Test (FAST) is a clinician-administered assessment scale of psychosocial dysfunction across various domains typically impacted in individuals with bipolar disorder. The FAST is formally validated as a clinician-administered measure, but support for self-administration would allow its wider use. Therefore, this study aimed to determine whether the FAST could reliably serve as a self-report measure in individuals seeking mental health treatment. Participants completed both the self-report and clinician-administered versions of the FAST as part of their routine outpatient clinical care at the Bipolar Disorders Clinic at The University of Texas Health Austin (UTHA). We investigated correlations between self-report and clinician-administered FAST scores. There were significant positive correlations between self-report and clinician-administered scores in a diverse group of 84 individuals undergoing outpatient mental health treatment (Total FAST scores rS = 0.75; p < .001). These findings support using the FAST as a self-report scale, further increasing its utility to measure functional disability in mental health conditions such as bipolar disorder. Self-report application will increase the utility of the FAST in busy clinical workflows and, therefore, contribute to a more comprehensive clinical assessment of recovery and spur interventions that improve psychosocial functioning and quality of life.

Common Data Elements to Facilitate Sharing and Re-use of Participant-Level Data: Assessment of Psychiatric Comorbidity Across Brain Disorders.

The Ontario Brain Institute's "Brain-CODE" is a large-scale informatics platform designed to support the collection, storage and integration of diverse types of data across several brain disorders as a means to understand underlying causes of brain dysfunction and developing novel approaches to treatment. By providing access to aggregated datasets on participants with and without different brain disorders, Brain-CODE will facilitate analyses both within and across diseases and cover multiple brain disorders and a wide array of data, including clinical, neuroimaging, and molecular. To help achieve these goals, consensus methodology was used to identify a set of core demographic and clinical variables that should be routinely collected across all participating programs. Establishment of Common Data Elements within Brain-CODE is critical to enable a high degree of consistency in data collection across studies and thus optimize the ability of investigators to analyze pooled participant-level data within and across brain disorders. Results are also presented using selected common data elements pooled across three studies to better understand psychiatric comorbidity in neurological disease (Alzheimer's disease/amnesic mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia, and Parkinson's disease).

Quality assurance assessment of a specialized perinatal mental health clinic.

BACKGROUND: Mood and anxiety issues are the main mental health complaints of women during pregnancy and the postpartum period. Services targeting such women can reduce perinatal complications related to psychiatric difficulties. This quality assurance project aimed to examine changes in mood and anxiety symptoms in pregnant and postpartum women referred to the Women's Health Concerns Clinic (WHCC), a specialized outpatient women's mental health program. METHODS: We extracted patient characteristics and service utilization from electronic medical records of women referred between 2015 and 2016. We also extracted admission and discharge scores on the Edinburgh Postnatal Depression Scale (EPDS) and the Generalized Anxiety Disorder-7 (GAD-7) scale. RESULTS: Most patients accessed the WHCC during pregnancy (54%), had a diagnosis of major depressive disorder (54.9%), were prescribed a change in their medication or dose (61.9%), and accessed psychotherapy for perinatal anxiety (30.1%). There was a significant decrease in EPDS scores between admission and discharge (t(214) = 11.57; p = .000; effect size d = .86), as well as in GAD-7 scores (t(51) = 3.63; p = .001; effect size d = .61). A secondary analysis showed that patients with more severe depression and anxiety symptoms demonstrated even greater effect sizes. CONCLUSIONS: Changes in EPDS and GAD-7 scores indicate that the WHCC is effective in reducing mood and anxiety symptoms associated with the perinatal period. This project highlights the importance of quality assurance methods in evaluating the effectiveness of clinical services targeting perinatal mental health, in order to inform policy and funding strategies.

THE DEPRESSION INVENTORY DEVELOPMENT SCALE: Assessment of Psychometric Properties Using Classical and Modern Measurement Theory in a CAN-BIND Trial.

Objective: The goal of the Depression Inventory Development (DID) project is to develop a comprehensive and psychometrically sound rating scale for major depressive disorder (MDD) that reflects current diagnostic criteria and conceptualizations of depression. We report here the evaluation of the current DID item bank using Classical Test Theory (CTT), Item Response Theory (IRT) and Rasch Measurement Theory (RMT). Methods: The present study was part of a larger multisite, open-label study conducted by the Canadian Biomarker Integration Network in Depression (ClinicalTrials.gov: NCT01655706). Trained raters administered the 32 DID items at each of two visits (MDD: baseline, n=211 and Week 8, n=177; healthy participants: baseline, n=112 and Week 8, n=104). The DID's "grid" structure operationalizes intensity and frequency of each item, with clear symptom definitions and a structured interview guide, with the current iteration assessing symptoms related to anhedonia, cognition, fatigue, general malaise, motivation, anxiety, negative thinking, pain, and appetite. Participants were also administered the Montgomery- Åsberg Depression Rating Scale (MADRS) and Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR) that allowed DID items to be evaluated against existing "benchmark" items. CTT was used to assess data quality/reliability (i.e., missing data, skewness, scoring frequency, internal consistency), IRT to assess individual item performance by modelling an item's ability to discriminate levels of depressive severity (as assessed by the MADRS), and RMT to assess how the items perform together as a scale to capture a range of depressive severity (item targeting). These analyses together provided empirical evidence to base decisions on which DID items to remove, modify, or advance. Results: Of the 32 DID items evaluated, eight items were identified by CTT as problematic, displaying low variability in the range of responses, floor effects, and/or skewness; and four items were identified by IRT to show poor discriminative properties that would limit their clinical utility. Five additional items were deemed to be redundant. The remaining 15 DID items all fit the Rasch model, with person and item difficulty estimates indicating satisfactory item targeting, with lower precision in participants with mild levels of depression. These 15 DID items also showed good internal consistency (alpha=0.95 and inter-item correlations ranging from r=0.49 to r=0.84) and all items were sensitive to change following antidepressant treatment (baseline vs. Week 8). RMT revealed problematic item targeting for the MADRS and QIDSSR, including an absence of MADRS items targeting participants with mild/moderate depression and an absence of QIDS-SR items targeting participants with mild or severe depression. Conclusion: The present study applied CTT, IRT, and RMT to assess the measurement properties of the DID items and identify those that should be advanced, modified, or removed. Of the 32 items evaluated, 15 items showed good measurement properties. These items (along with previously evaluated items) will provide the basis for validation of a penultimate DID scale assessing anhedonia, cognitive slowing, concentration, executive function, recent memory, drive, emotional fatigue, guilt, self-esteem, hopelessness, tension, rumination, irritability, reduced appetite, insomnia, sadness, worry, suicidality, and depressed mood. The strategies adopted by the DID process provide a framework for rating scale development and validation.

Prospective Assessment of Daily Patterns of Mood-Related Symptoms.

Background: The Mood Rhythm Instrument (MRI) is a new self-report questionnaire that aims to assess, the presence, and timing of daily patterns of mood-related symptoms. Here, we examined the reliability of the MRI against a prospective daily investigation over the course of 15 days. As a secondary aim, we examined whether the number of items with a perceived daily pattern correlated with severity of depressive symptoms and psychological well-being. Methods: Thirty-two participants recruited from the general population were asked to prospectively fill out a daily version of the MRI (MRI-d) for 15 days. On the 16th day, they filled out the MRI, the Beck Depression Inventory (BDI) and the World Health Organization 5-item well-being index (WHO-5). Results: The MRI showed high agreement with the MRI-d, which suggests that the MRI is a valid tool to assess daily patterns of mood symptoms. The number of mood symptoms perceived as having daily peaks correlated positively with BDI scores and negatively with WHO-5 scores. Conclusions: The MRI might be a valid tool to investigate the presence of daily patterns and the timing of mood-related factors.The MRI does not seem to be influenced by recall or recency biases. Future studies should test the usefulness of this new clinical instrument in individuals with mood disorders, as well as its ability to detect changes in the daily timing of mood symptoms before and after treatment.

Performance of the biological rhythms interview for assessment in neuropsychiatry: An item response theory and actigraphy analysis.

BACKGROUND: Biological rhythm disturbances are widely associated with the pathophysiology of mood disorders. The Biological Rhythms Interview for Assessment in Neuropsychiatry (BRIAN) is a self-report that indexes rhythm disturbance in sleep, activity, social and eating patterns. The aim of this study was to perform an Item Response Theory (IRT) analysis of the BRIAN and investigate its associations with objective sleep and rhythm disturbance measures. METHODS: 103 subjects (31 bipolar, 32 major depression and 40 healthy volunteers) wore an actiwatch for fifteen days, and completed a first morning urine sample and the BRIAN on day 15. IRT analysis assessed individual BRIAN items and their relationship to total score. Individual actiwatch records were processed to produce a sequence of transitions between rest/activity, and a likelihood of transitioning between states was calculated to investigate sleep-wake dynamics. Cosinor analysis produced daily activity rhythms (DARs). Spearman correlations were used to assess the association between sleep/DAR variables and the BRIAN. RESULTS: IRT analyses showed that 11 of 18 BRIAN items displayed a high level of discrimination between item options across a range of BRIAN total scores. Total BRIAN score correlated with wake after sleep onset, total activity count during sleep, and urinary 6-sulphatoxymelatonin. BRIAN Activity domain correlated with the daytime transition probability from rest to activity. LIMITATIONS: The sample size may have been underpowered for the graded-response model employed in IRT. The study lacked an objective comparison for BRIAN eating and social domain. CONCLUSION: The present study reveals the BRIAN displays promising external validity compared to objective parameters of circadian rhythmicity.

The Depression Inventory Development Workgroup: A Collaborative, Empirically Driven Initiative to Develop a New Assessment Tool for Major Depressive Disorder.

The Depression Inventory Development project is an initiative of the International Society for CNS Drug Development whose goal is to develop a comprehensive and psychometrically sound measurement tool to be utilized as a primary endpoint in clinical trials for major depressive disorder. Using an iterative process between field testing and psychometric analysis and drawing upon expertise of international researchers in depression, the Depression Inventory Development team has established an empirically driven and collaborative protocol for the creation of items to assess symptoms in major depressive disorder. Depression-relevant symptom clusters were identified based on expert clinical and patient input. In addition, as an aid for symptom identification and item construction, the psychometric properties of existing clinical scales (assessing depression and related indications) were evaluated using blinded datasets from pharmaceutical antidepressant drug trials. A series of field tests in patients with major depressive disorder provided the team with data to inform the iterative process of scale development. We report here an overview of the Depression Inventory Development initiative, including results of the third iteration of items assessing symptoms related to anhedonia, cognition, fatigue, general malaise, motivation, anxiety, negative thinking, pain and appetite. The strategies adopted from the Depression Inventory Development program, as an empirically driven and collaborative process for scale development, have provided the foundation to develop and validate measurement tools in other therapeutic areas as well.

Depression in women: windows of vulnerability and new insights into the link between estrogen and serotonin.

OBJECTIVE: The purpose of this commentary is to provide an update on the research in both preclinical and clinical models regarding the cross-talk between estrogen and various serotonin molecular markers and the possible implications this may have on female-related mood disorders. CONCLUSIONS: Animal and human studies provide strong and consistent evidence suggesting that estrogen is able to regulate the serotonin pathway at various levels. The general trend that emerges is that estrogen administration increases serotonin availability by altering mRNA and protein levels of various serotonin markers and by decreasing serotonin breakdown. These effects may have direct implications on female mood disorders such as premenstrual disorders and depression during pregnancy, postpartum, and during the menopausal transition.

Challenges and opportunities to manage depression during the menopausal transition and beyond.

Women are at a higher risk than men of developing depression and anxiety and such increased risk might be particularly associated with reproductive cycle events. Recent evidence suggests that the transition to menopause may constitute a window of vulnerability for some women for the development of new onset and recurrent depression. Several biological and environmental factors seem to be independent predictors or modulating factors for the occurrence of depression in menopausal women; they include the presence and severity of hot flushes, sleep disturbances, history of severe premenstrual syndrome or postpartum blues, stressful life events, history of depression, socioeconomic status, and use of hormones and psychotropic agents. The regulation of monoaminergic systems by ovarian hormones might explain, at least in part, the emergence of depressive symptoms and/or anxiety in biologically predisposed subpopulations. The use of transdermal estradiol, as well as serotonergic and noradrenergic antidepressants, is an efficacious strategy in the treatment of depression and vasomotor symptoms in symptomatic women in midlife. In this review, the authors discuss the existing evidence of a greater risk for the development of depression during the menopausal transition and the putative underlying mechanisms contributing to this window of vulnerability. Hormonal and nonhormonal treatment strategies for depression and anxiety in this particular population are critically examined, although more tailored treatment options are still needed.