Assessment of anxiety in children with neurodevelopment disorders: Rasch analysis of the Spence Children's Anxiety Scale.

Anxiety is common in neurodevelopmental disorders (NDD). The parent version of the Spence Children's Anxiety Scale (SCAS-P) is a widely used measure to assess anxiety across a broad range of childhood populations. However, assessment of the measurement properties of the SCAS-P in NDDs have been limited. The present study aimed to assess the psychometric properties of the SCAS-P in children with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) using Rasch Measurement Theory. Data from the Province of Ontario Neurodevelopmental Disorders Network Registry were used in the analysis. Children (ages 6-13 years old) with a primary diagnosis of ADHD (n=146) or ASD (n=104) were administered the SCAS-P. Rasch Measurement Theory was used to assess measurement properties of the SCAS-P, including unidimensionality and item-level fit, category ordering, item targeting, person separation index and reliability and differential item functioning. The SCAS-P fit well to the Rasch model in both ADHD and ASD, including unidimensionality, satisfactory category ordering and goodness-of-fit. However, item-person measures showed poor precision at lower levels of anxiety. Some items showed differential item functioning, including items within the obsessive-compulsive, panic/agoraphobia and physical injury fears domains, suggesting that the presentation of anxiety may differ between ADHD and ASD. Overall, the results generally support the use of the SCAS-P to screen and monitor anxiety symptoms in children with ADHD and ASD. Future studies would benefit from examination of more severely anxious NDD cohort, including those with clinically diagnosed anxiety.

Rasch analyses of the Quick Inventory of Depressive Symptomatology Self-Report in neurodegenerative and major depressive disorders.

Background: Symptoms of depression are present in neurodegenerative disorders (ND). It is important that depression-related symptoms be adequately screened and monitored in persons living with ND. The Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) is a widely-used self-report measure to assess and monitor depressive severity across different patient populations. However, the measurement properties of the QIDS-SR have not been assessed in ND. Aim: To use Rasch Measurement Theory to assess the measurement properties of the Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) in ND and in comparison to major depressive disorder (MDD). Methods: De-identified data from the Ontario Neurodegenerative Disease Research Initiative (NCT04104373) and Canadian Biomarker Integration Network in Depression (NCT01655706) were used in the analyses. Five hundred and twenty participants with ND (Alzheimer's disease or mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia and Parkinson's disease) and 117 participants with major depressive disorder (MDD) were administered the QIDS-SR. Rasch Measurement Theory was used to assess measurement properties of the QIDS-SR, including unidimensionality and item-level fit, category ordering, item targeting, person separation index and reliability and differential item functioning. Results: The QIDS-SR fit well to the Rasch model in ND and MDD, including unidimensionality, satisfactory category ordering and goodness-of-fit. Item-person measures (Wright maps) showed gaps in item difficulties, suggesting poor precision for persons falling between those severity levels. Differences between mean person and item measures in the ND cohort logits suggest that QIDS-SR items target more severe depression than experienced by the ND cohort. Some items showed differential item functioning between cohorts. Conclusion: The present study supports the use of the QIDS-SR in MDD and suggest that the QIDS-SR can be also used to screen for depressive symptoms in persons with ND. However, gaps in item targeting were noted that suggests that the QIDS-SR cannot differentiate participants falling within certain severity levels. Future studies would benefit from examination in a more severely depressed ND cohort, including those with diagnosed clinical depression.

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).

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.

3alpha-reduced neuroactive steroids and their precursors during pregnancy and the postpartum period.

Allopregnanolone (ALLO) and pregnanolone (PREG), the 3alpha-reduced metabolites of progesterone (PROG), are potent modulators of gamma-aminobutyric acid type A receptors that may function as endogenous anxiolytics. They are purported to be involved in the etiology or expression of clinical depression. In the present study we quantified ALLO and PREG, as well as PROG, 5alpha-dihydroprogesterone (5alpha-DHP), 5beta-dihydroprogesterone (5beta-DHP), epiallopregnanolone and pregnenolone (PREGNEN), in plasma from healthy women at five time points during pregnancy and the postpartum period. Analysis was by gas chromatography/electron capture - negative chemical ionization - mass spectrometry. Neuroactive steroids increased significantly from 10 to 36 weeks of pregnancy, except for 5beta-DHP and PREGNEN which did not change significantly. PROG was the most abundant steroid throughout pregnancy, followed by 5alpha-DHP and ALLO. Metabolite to precursor ratios differed depending on the enzyme and substrate: the turnover of PROG to 5alpha-DHP (catalyzed by 5alpha-reductase) was stable while the conversion of PROG to 5beta-DHP (catalyzed by 5beta-reductase) decreased later in pregnancy. 3alpha-Hydroxysteroid oxidoreductase-mediated turnover of 5alpha- and 5beta-DHP to their metabolites ALLO and PREG, respectively, rose during pregnancy, but the turnover of 5alpha-DHP to ALLO dropped at the late prenatal visit. At 6 weeks postpartum all steroids were significantly reduced compared with late prenatal values, with 5alpha-DHP being the most abundant postpartum steroid. These results provide the basis for further study of neuroactive steroids in psychiatric conditions of pregnancy and the postpartum period.