An Evaluation of Item Harmonization Strategies Between Assessment Tools of Psychopathology in Children and Adolescents.

Data aggregation in mental health is complicated by using different questionnaires, and little is known about the impact of item harmonization strategies on measurement precision. Therefore, we aimed to assess the impact of various item harmonization strategies for a target and proxy questionnaire using correlated and bifactor models. Data were obtained from the Brazilian High-Risk Study for Mental Conditions (BHRCS) and the Healthy Brain Network (HBN; N = 6,140, ages 5-22 years, 39.6% females). We tested six item-wise harmonization strategies and compared them based on several indices. The one-by-one (1:1) expert-based semantic item harmonization presented the best strategy as it was the only that resulted in scalar-invariant models for both samples and factor models. The between-questionnaires factor correlation, reliability, and factor score difference in using a proxy instead of a target measure improved little when all other harmonization strategies were compared with a completely at-random strategy. However, for bifactor models, between-questionnaire specific factor correlation increased from 0.05-0.19 (random item harmonization) to 0.43-0.60 (expert-based 1:1 semantic harmonization) in BHRCS and HBN samples, respectively. Therefore, item harmonization strategies are relevant for specific factors from bifactor models and had little impact on p-factors and first-order correlated factors when the child behavior checklist (CBCL) and strengths and difficulties questionnaire (SDQ) were harmonized.

Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium.

Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups-a 'lower brain volume' subgroup (SG1) and an 'higher striatal volume' subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium. Our prior MRI subgrouping models (671 participants; USA, Germany, and China) were applied to both FEP and HC. Participants were assigned into 1 of 4 categories: subgroup 1 (SG1), subgroup 2 (SG2), no subgroup membership ('None'), and mixed SG1 + SG2 subgroups ('Mixed'). Voxel-wise analyses characterized SG1 and SG2 subgroups. Supervised machine learning analyses characterized baseline and remission signatures related to SG1 and SG2 membership. The two dominant patterns of 'lower brain volume' in SG1 and 'higher striatal volume' (with otherwise normal neuromorphology) in SG2 were identified already at the first episode of psychosis. SG1 had a significantly higher proportion of FEP (32%) vs. HC (19%) than SG2 (FEP, 21%; HC, 23%). Clinical multivariate signatures separated the SG1 and SG2 subgroups (balanced accuracy = 64%; p < 0.0001), with SG2 showing higher education but also greater positive psychosis symptoms at first presentation, and an association with symptom remission at 1-year, 5-year, and when timepoints were combined. Neuromorphological subtypes of schizophrenia are already evident at illness onset, separated by distinct clinical presentations, and differentially associated with subsequent remission. These results suggest that the subgroups may be underlying risk phenotypes that could be targeted in future treatment trials and are critical to consider when interpreting neuroimaging literature.

Harmonizing bifactor models of psychopathology between distinct assessment instruments: Reliability, measurement invariance, and authenticity.

OBJECTIVES: Model configuration is important for mental health data harmonization. We provide a method to investigate the performance of different bifactor model configurations to harmonize different instruments. METHODS: We used data from six samples from the Reproducible Brain Charts initiative (N = 8,606, ages 5-22 years, 41.0% females). We harmonized items from two psychopathology instruments, Child Behavior Checklist (CBCL) and GOASSESS, based on semantic content. We estimated bifactor models using confirmatory factor analysis, and calculated their model fit, factor reliability, between-instrument invariance, and authenticity (i.e., the correlation and factor score difference between the harmonized and original models). RESULTS: Five out of 12 model configurations presented acceptable fit and were instrument-invariant. Correlations between the harmonized factor scores and the original full-item models were high for the p-factor (>0.89) and small to moderate (0.12-0.81) for the specific factors. 6.3%-50.9% of participants presented factor score differences between harmonized and original models higher than 0.5 z-score. CONCLUSIONS: The CBCL-GOASSESS harmonization indicates that few models provide reliable specific factors and are instrument-invariant. Moreover, authenticity was high for the p-factor and moderate for specific factors. Future studies can use this framework to examine the impact of harmonizing instruments in psychiatric research.

Response speed measurements on the psychomotor vigilance test: how precise is precise enough?

STUDY OBJECTIVES: The psychomotor vigilance test (PVT) is frequently used to measure behavioral alertness in sleep research on various software and hardware platforms. In contrast to many other cognitive tests, PVT response time (RT) shifts of a few milliseconds can be meaningful. It is, therefore, important to use calibrated systems, but calibration standards are currently missing. This study investigated the influence of system latency bias and its variability on two frequently used PVT performance metrics, attentional lapses (RTs ≥500 ms) and response speed, in sleep-deprived and alert participants. METHODS: PVT data from one acute total (N = 31 participants) and one chronic partial (N = 43 participants) sleep deprivation protocol were the basis for simulations in which response bias (±15 ms) and its variability (0-50 ms) were systematically varied and transgressions of predefined thresholds (i.e. ±1 for lapses, ±0.1/s for response speed) recorded. RESULTS: Both increasing bias and its variability caused deviations from true scores that were higher for the number of lapses in sleep-deprived participants and for response speed in alert participants. Threshold transgressions were typically rare (i.e. <5%) if system latency bias was less than ±5 ms and its standard deviation was ≤10 ms. CONCLUSIONS: A bias of ±5 ms with a standard deviation of ≤10 ms could be considered maximally allowable margins for calibrating PVT systems for timing accuracy. Future studies should report the average system latency and its standard deviation in addition to adhering to published standards for administering and analyzing the PVT.

Distinct and shared contributions of diagnosis and symptom domains to cognitive performance in severe mental illness in the Paisa population: a case-control study.

BACKGROUND: Severe mental illness diagnoses have overlapping symptomatology and shared genetic risk, motivating cross-diagnostic investigations of disease-relevant quantitative measures. We analysed relationships between neurocognitive performance, symptom domains, and diagnoses in a large sample of people with severe mental illness not ascertained for a specific diagnosis (cases), and people without mental illness (controls) from a single, homogeneous population. METHODS: In this case-control study, cases with severe mental illness were ascertained through electronic medical records at Clínica San Juan de Dios de Manizales (Manizales, Caldas, Colombia) and the Hospital Universitario San Vicente Fundación (Medellín, Antioquía, Colombia). Participants were assessed for speed and accuracy using the Penn Computerized Neurocognitive Battery (CNB). Cases had structured interview-based diagnoses of schizophrenia, bipolar 1, bipolar 2, or major depressive disorder. Linear mixed models, using CNB tests as repeated measures, modelled neurocognition as a function of diagnosis, sex, and all interactions. Follow-up analyses in cases included symptom factor scores obtained from exploratory factor analysis of symptom data as main effects. FINDINGS: Between Oct 1, 2017, and Nov 1, 2019, 2406 participants (1689 cases [schizophrenia n=160; bipolar 1 disorder n=519; bipolar 2 disorder n=204; and major depressive disorder n=806] and 717 controls; mean age 39 years (SD 14); and 1533 female) were assessed. Participants with bipolar 1 disorder and schizophrenia had similar impairments in accuracy and speed across cognitive domains. Participants with bipolar 2 disorder and major depressive disorder performed similarly to controls, with subtle deficits in executive and social cognition. A three-factor model (psychosis, mania, and depression) best represented symptom data. Controlling for diagnosis, premorbid IQ, and disease severity, high lifetime psychosis scores were associated with reduced accuracy and speed across cognitive domains, whereas high depression scores were associated with increased social cognition accuracy. INTERPRETATION: Cross-diagnostic investigations showed that neurocognitive function in severe mental illness is characterised by two distinct profiles (bipolar 1 disorder and schizophrenia, and bipolar 2 disorder and major depressive disorder), and is associated with specific symptom domains. These results suggest the utility of this design for elucidating severe mental illness causes and trajectories. FUNDING: US National Institute of Mental Health.

Draft Whole-Genome Sequence of a Novel Chryseobacterium viscerum Strain Isolated from Fresh Water at Dripping Springs, New Mexico.

We sequenced the genome of a bacterial species recently isolated from fresh water at Dripping Springs, NM, and identified it as Chryseobacterium viscerum This species had previously been isolated only from dead or diseased fish. This report shows that C. viscerum can be found in nature as a free-living species not associated with diseased fish.

Repeated Administration Effects on Psychomotor Vigilance Test Performance.

Study Objectives: The Psychomotor Vigilance Test (PVT) is reported to be free of practice effects that can otherwise confound the effects of sleep loss and circadian misalignment on performance. This differentiates the PVT from more complex cognitive tests. To the best of our knowledge, no study has systematically investigated practice effects on the PVT across multiple outcome domains, depending on administration interval, and in ecologically more valid settings. Methods: We administered a validated 3-minute PVT (PVT-B) 16 times in 45 participants (23 male, mean ± SD age 32.6 ± 7.3 years, range 25-54 years) with administration intervals of ≥10 days, ≤5 days, or 4 times per day. We investigated linear and logarithmic trends across repeated administrations in 10 PVT-B outcome variables. Results: The fastest 10% of response times (RT; plin = .0002), minimum RT (plog = .0010), and the slowest 10% of reciprocal RT (plog = .0124) increased while false starts (plog = 0.0050) decreased with repeated administration, collectively decreasing RT variability (plog = .0010) across administrations. However, the observed absolute changes were small (e.g., -0.03 false starts per administration, linear fit) and are probably irrelevant in practice. Test administration interval did not modify the effects of repeated administration on PVT-B performance (all p > .13 for interaction). Importantly, mean and median RT, response speed, and lapses, which are among the most frequently used PVT outcomes, did not change systematically with repeated administration. Conclusions: PVT-B showed stable performance across repeated administrations. Combined with its high sensitivity, this corroborates the status of the PVT as the de facto gold standard measure of the neurobehavioral effects of sleep loss and circadian misalignment.

Attention Deficit Hyperactivity Disorder Symptoms and Psychosis in 22q11.2 Deletion Syndrome.

OBJECTIVE: 22q11.2 Deletion Syndrome (22q11.2DS) is associated with increased risk for schizophrenia in adulthood while Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent diagnosis in childhood. Inattention symptoms are pronounced in 22q11.2DS and given that attentional impairment is a core feature of schizophrenia, inattention symptoms may reflect underlying ADHD, psychosis, or both. We investigate whether inattention is associated with psychosis in 22q11.2DS and in other groups at risk for psychosis but without the deletion (ND) (idiopathic clinical risk and first degree family members of individuals with schizophrenia). METHODS: One hundred thirty-seven individuals with 22q11.2DS (mean age: 14.0), 84 ND individuals with subthreshold psychosis (mean age: 16.9) and 31 ND individuals with family history of psychosis (mean age: 17.0) were included in the study. Psychopathology was assessed using research diagnostic assessments. RESULTS: ADHD total symptoms were associated with overall levels of subthreshold psychosis symptoms in 22q11.2DS (ß = .8, P = .04). Inattention symptoms were specifically associated with positive (ß = .5, P = .004), negative (ß = .5, P = .03), and disorganized (ß = .5, P < .001) symptoms, while hyperactivity-impulsivity symptoms were associated with disorganized symptoms (ß = .5, P = .01). The prevalence of ADHD inattention symptoms was higher in 22q11.2DS with subthreshold psychosis compared to ND individuals with subthreshold psychosis (P < .001), even when adjusting for cognitive impairment and overall psychopathology. The pattern was similar when comparing individuals with 22q11.2DS and ND individuals with family history of psychosis. CONCLUSIONS: This is the first study to examine the associations between ADHD symptoms and psychosis in 22q11.2DS. Our findings support a potentially important role of ADHD inattention symptoms in psychosis in 22q11.2DS.

Subthreshold psychotic symptoms in 22q11.2 deletion syndrome.

OBJECTIVE: Chromosome 22q11.2 deletion syndrome (22q11DS) confers 25% risk for psychosis and is an invaluable window for understanding the neurobiological substrate of psychosis risk. The Structured Interview for Prodromal Syndromes (SIPS) is well validated in nondeleted populations for detecting clinical risk but has only recently been applied to 22q11DS. We assessed the largest 22q11DS cohort to date and report on SIPS implementation and symptoms elicited. METHOD: The SIPS, including its 19 subscales, was administered to 157 individuals with 22q11DS aged 8 to 25 years. Youth and caregiver interviews were conducted and rated separately, then compared for agreement. Implementation of the SIPS in 22q11DS was challenging because of the prevalence of developmental delay and comorbid conditions. However, by explaining questions and eliciting examples, we were able to help youths and caregivers understand and respond appropriately. Consensus ratings were formulated and analyzed with itemwise and factor analysis. RESULTS: Subthreshold symptoms were common, with 85% of individuals endorsing 1 or more. The most commonly rated items were ideational richness (47%) and trouble with focus and attention (44%). Factor analysis revealed a 3-factor solution with positive, negative, and disorganized components. Youth-caregiver comparisons suggested that youths report greater symptoms of perceptual abnormalities, suspiciousness, trouble with emotional expression, and bizarre thinking. Caregivers reported more impaired tolerance to normal stress, poor hygiene, and inattention. CONCLUSION: The SIPS was adapted for 22q11DS through comprehensive and semi-structured administration methods, yielding a high prevalence of subthreshold psychotic symptoms. The significance and predictive validity of these symptoms require future longitudinal analysis.