Psychometric Properties and Clinical Utility of CBCL and P-GBI Sleep Items in Children and Adolescents.

OBJECTIVE: Sleep is crucial to overall health, playing a complex role in a wide range of mental health concerns in children and adults. Nevertheless, clinicians may not routinely assess sleep problems due to lack of awareness or limitations such as cost or time. Scoring sleep-related items embedded on broader scales may help clinicians get more out of tools they are already using. The current study explores evidence of reliability, validity, and clinical utility of sleep-related items embedded on two caregiver-report tools: the Child Behavior Checklist (CBCL) and Parent General Behavior Inventory (P-GBI). METHOD: Youth aged 5-18 years and their parents were recruited from both an academic medical center (N = 759) and an urban community health center (N = 618). Caregivers completed the CBCL and P-GBI as part of a more comprehensive outpatient evaluation. Exploratory factor analyses, multi-group confirmatory factor analyses, and graded response models evaluated dimensionality, reliability, and invariance across samples. Correlations and receiver operating characteristic curve analyses probed associations with diagnostic and demographic variables. RESULTS: Two subscales emerged for each itemset. Across both samples, P-GBI sleep subscales were more reliable and consistent than CBCL sleep subscales, showed greater coverage of sleepiness and insomnia constructs, were better at discriminating individuals within a wider range of sleep complaints, and showed significant correlation with mood disorder diagnoses. CONCLUSIONS: The P-GBI sleep items provide a brief, reliable measure for assessing distinct dimensions of sleep complaints and detecting mood symptoms or diagnoses related to the youth's sleep functioning, making them a useful addition to clinical practice.

Development and Initial Validation of the in-Session Patient Affective Reactions Questionnaire (SPARQ) and the Rift In-Session Questionnaire (RISQ).

This article discusses the development and preliminary validation of a self-report inventory of the patient's perception of, and affective reaction to, their therapist during a psychotherapy session. First, we wrote a pool of 131 items, reviewed them based on subject matter experts' review, and then collected validation data from a clinical sample of adult patients in individual therapy (N = 701). We used exploratory factor analysis and item response theory graded response models to select items, confirmatory factor analysis (CFA) to test the factor structure, and k-fold cross-validation to verify model robustness. Multi-group CFA examined measurement invariance across patients with different diagnoses (unipolar depression, bipolar disorder, and neither of these). Three factors produced short scales retaining the strongest items. The in-Session Patient Affective Reactions Questionnaire (SPARQ) has a two-factor structure, yielding a four-item Negative affect scale and a four-item Positive affect scale. The Relationship In-Session Questionnaire (RISQ) is composed of four items from the third factor with dichotomized responses. Both scales showed excellent psychometric properties and evidence of metric invariance across the three diagnostic groups: unipolar depression, bipolar disorder, and neither of these. The SPARQ and the RISQ scale can be used in clinical or research settings, with particular value for capturing the patient's perspectives about their therapist and session-level emotional processes.

Comparing the factor structures and reliabilities of the EPDS and the PHQ-9 for screening antepartum and postpartum depression: a multigroup confirmatory factor analysis.

To evaluate and compare the factor structure and reliability of EPDS and PHQ in antepartum and postpartum samples. Parallel analysis and exploratory factor analysis were conducted to determine the structure of both scales in the entire sample as well as in the antepartum and postpartum groups. McDonald's omega statistics examined the utility of treating items as a single scale versus multiple factors. Multigroup confirmatory factor analysis (MCFA) was utilized to test the measurement invariance between the antepartum and postpartum groups. Two-factor models fit best for the EPDS in both the antepartum and postpartum groups; however, the most reliable score variance was attributable to a general factor for each scale. MCFA provided evidence of weak invariance across groups regarding factor loadings and partial invariance regarding item thresholds. PHQ-9 showed a two-factor model in the antepartum group; however, the same model did not fit well in the postpartum group. EPDS should be preferred to PHQ-9 for measuring depressive symptoms in peripartum populations. Both scales should be used as a single-factor scale. Caution is required when comparing the antepartum and postpartum scores.

Inter-Rater Reliability between Structured and Non-Structured Interviews Is Fair in Schizophrenia and Bipolar Disorders-A Systematic Review and Meta-Analysis.

We aimed to find agreement between diagnoses obtained through standardized (SDI) and non-standardized diagnostic interviews (NSDI) for schizophrenia and Bipolar Affective Disorder (BD). METHODS: A systematic review with meta-analysis was conducted. Publications from 2007 to 2020 comparing SDI and NSDI diagnoses in adults without neurological disorders were screened in MEDLINE, ISI Web of Science, and SCOPUS, following PROSPERO registration CRD42020187157, PRISMA guidelines, and quality assessment using QUADAS-2. RESULTS: From 54231 entries, 22 studies were analyzed, and 13 were included in the final meta-analysis of kappa agreement using a mixed-effects meta-regression model. A mean kappa of 0.41 (Fair agreement, 95% CI: 0.34 to 0.47) but high heterogeneity (Î2 = 92%) were calculated. Gender, mean age, NSDI setting (Inpatient vs. Outpatient; University vs. Non-university), and SDI informant (Self vs. Professional) were tested as predictors in meta-regression. Only SDI informant was relevant for the explanatory model, leaving 79% unexplained heterogeneity. Egger's test did not indicate significant bias, and QUADAS-2 resulted in "average" data quality. CONCLUSIONS: Most studies using SDIs do not report the original sample size, only the SDI-diagnosed patients. Kappa comparison resulted in high heterogeneity, which may reflect the influence of non-systematic bias in diagnostic processes. Although results were highly heterogeneous, we measured a fair agreement kappa between SDI and NSDI, implying clinicians might operate in scenarios not equivalent to psychiatry trials, where samples are filtered, and there may be more emphasis on maintaining reliability. The present study received no funding.

Finding a Needed Diagnostic Home for Children with Impulsive Aggression.

Aggressive behavior is one of the most common reasons for referrals of youth to mental health treatment. While there are multiple publications describing different types of aggression in children, it remains challenging for clinicians to diagnose and treat aggressive youth, especially those with impulsively aggressive behaviors. The reason for this dilemma is that currently several psychiatric diagnoses include only some of the common symptoms of aggression in their criteria. However, no single diagnosis or diagnostic specifier adequately captures youth with impulsive aggression (IA). Here we review select current diagnostic categories, including behavior and mood disorders, and suggest that they do not provide an adequate description of youth with IA. We also specifically focus on the construct of IA as a distinct entity from other diagnoses and propose a set of initial, provisional diagnostic criteria based on the available evidence that describes youth with IA to use for future evaluation.

Developing Empirical Latent Profiles of Impulsive Aggression and Mood in Youths across Three Outpatient Samples.

OBJECTIVE: Aggression with impulsivity and reactivity (AIR) may distinguish a subset of youth from those with attention problems, rule-breaking behavior, or mood disorders, potentially with differential treatment response. Yet, DSM-5 and ICD-10 do not include an AIR diagnosis. Thus, we empirically grouped youths into profiles based on AIR, manic, depressive, rule-breaking, and self-harm behaviors; examined which profiles replicated across three samples; and characterized profile sets on demographic and clinical features. METHOD: After harmonizing data from three samples (n = 679, n = 392, n = 634), Latent Profile Analysis (LPA) assigned youth to profiles based on caregiver-reported measures of AIR, manic, depressive, rule-breaking, and self-harm behaviors. Profiles from each sample were grouped into sets based on profile similarity. Analyses tested differences in diagnoses, sex, and race, age, functioning, and mood severity. RESULTS: Eight-profile solutions fit best. Seven profiles replicated across samples: high AIR and self-harm, lower depressive and manic scores; high AIR, manic symptoms, and self-harm; high depression symptoms; three smaller sets with high manic and depressive symptoms and moderate AIR; and two high rates of bipolar diagnoses and family bipolar history. Two sets were high on both AIR and mood symptoms, were the most impaired, and had the highest comorbidity. CONCLUSIONS: Analyses support an empirical definition of AIR, separate from mood disorders. Profile sets distinguished by level of AIR and mood symptoms differed in demographic and diagnostic characteristics as well as functioning. Importantly, a set emerged with high AIR but low mood indicators and with high rates of ADHD and ODD, but not mood disorder.