Negative and Positive Experiences During the COVID-19 Pandemic in Canadians With Developmental Disabilities: A One-Year Ontario-Based Survey.

PURPOSE: Understanding the experiences of people with developmental disabilities during the initial period of COVID-19 pandemic. METHODS: Individuals with developmental disabilities and their caregivers completed baseline and up to five follow-up online surveys using the CRISIS-AFAR measures, between July 2020 and September 2021. We used qualitative (thematic analysis) and quantitative (MANOVA) analytic methods. RESULTS: One hundred and eighteen participants (64 caregivers on individuals 6-62 years, 54 self-reporting individuals aged 17-55 years) completed baseline survey; 46 participants (23 caregivers, 23 self-reporting adults) completed ≥1 follow-up. Qualitative themes included uncertainty, and negative and positive influences on behaviours and routines, daily life and mental wellness. Those experiencing positive impacts did not stably perceive so longitudinally. CONCLUSIONS: Despite both negative and positive influences on individuals with developmental disabilities and their families, the prolonged pandemic had wide-ranging repercussions. Emergency preparedness planning should consider the disruptive effects of public health measures on routine and support for this vulnerable population.

Multivariate Association between Functional Connectivity Gradients and Cognition in Schizophrenia Spectrum Disorders.

BACKGROUND: Schizophrenia Spectrum Disorders (SSDs), which are characterized by social cognitive deficits, have been associated with dysconnectivity in "unimodal" (e.g., visual, auditory) and "multimodal" (e.g., default-mode and frontoparietal) cortical networks. However, little is known regarding how such dysconnectivity relates to social and non-social cognition, and how such brain-behavioral relationships associate with clinical outcomes of SSDs. METHODS: We analyzed cognitive (non-social and social) measures and resting-state functional magnetic resonance imaging data from the 'Social Processes Initiative in Neurobiology of the Schizophrenia(s) (SPINS)' study (247 stable participants with SSDs and 172 healthy controls, ages 18-55). We extracted gradients from parcellated connectomes and examined the association between the first 3 gradients and the cognitive measures using partial least squares correlation (PLSC). We then correlated the PLSC dimensions with functioning and symptoms in the SSDs group. RESULTS: The SSDs group showed significantly lower differentiation on all three gradients. The first PLSC dimension explained 68.53% (p<.001) of the covariance and showed a significant difference between SSDs and Controls (bootstrap p<.05). PLSC showed that all cognitive measures were associated with gradient scores of unimodal and multimodal networks (Gradient 1), auditory, sensorimotor, and visual networks (Gradient 2), and perceptual networks and striatum (Gradient 3), which were less differentiated in SSDs. Furthermore, the first dimension was positively correlated with negative symptoms and functioning in the SSDs group. CONCLUSIONS: These results suggest a potential role of lower differentiation of brain networks in cognitive and functional impairments in SSDs.

Task-based functional neural correlates of social cognition across autism and schizophrenia spectrum disorders.

BACKGROUND: Autism and schizophrenia spectrum disorders (SSDs) both feature atypical social cognition. Despite evidence for comparable group-level performance in lower-level emotion processing and higher-level mentalizing, limited research has examined the neural basis of social cognition across these conditions. Our goal was to compare the neural correlates of social cognition in autism, SSDs, and typically developing controls (TDCs). METHODS: Data came from two harmonized studies in individuals diagnosed with autism or SSDs and TDCs (aged 16-35 years), including behavioral social cognitive metrics and two functional magnetic resonance imaging (fMRI) tasks: a social mirroring Imitate/Observe (ImObs) task and the Empathic Accuracy (EA) task. Group-level comparisons, and transdiagnostic analyses incorporating social cognitive performance, were run using FSL's PALM for each task, covarying for age and sex (1000 permutations, thresholded at p < 0.05 FWE-corrected). Exploratory region of interest (ROI)-based analyses were also conducted. RESULTS: ImObs and EA analyses included 164 and 174 participants, respectively (autism N = 56/59, SSD N = 50/56, TDC N = 58/59). EA and both lower- and higher-level social cognition scores differed across groups. While canonical social cognitive networks were activated, no significant whole-brain or ROI-based group-level differences in neural correlates for either task were detected. Transdiagnostically, neural activity during the EA task, but not the ImObs task, was associated with lower- and higher-level social cognitive performance. LIMITATIONS: Despite attempting to match our groups on age, sex, and race, significant group differences remained. Power to detect regional brain differences is also influenced by sample size and multiple comparisons in whole-brain analyses. Our findings may not generalize to autism and SSD individuals with co-occurring intellectual disabilities. CONCLUSIONS: The lack of whole-brain and ROI-based group-level differences identified and the dimensional EA brain-behavior relationship observed across our sample suggest that the EA task may be well-suited to target engagement in novel intervention testing. Our results also emphasize the potential utility of cross-condition approaches to better understand social cognition across autism and SSDs.

Comparing the stability and reproducibility of brain-behavior relationships found using canonical correlation analysis and partial least squares within the ABCD sample.

Canonical correlation analysis (CCA) and partial least squares correlation (PLS) detect linear associations between two data matrices by computing latent variables (LVs) having maximal correlation (CCA) or covariance (PLS). This study compared the similarity and generalizability of CCA- and PLS-derived brain-behavior relationships. Data were accessed from the baseline Adolescent Brain Cognitive Development (ABCD) dataset (N > 9,000, 9-11 years). The brain matrix consisted of cortical thickness estimates from the Desikan-Killiany atlas. Two phenotypic scales were examined separately as the behavioral matrix; the Child Behavioral Checklist (CBCL) subscale scores and NIH Toolbox performance scores. Resampling methods were used to assess significance and generalizability of LVs. LV1 for the CBCL brain relationships was found to be significant, yet not consistently stable or reproducible, across CCA and PLS models (singular value: CCA = .13, PLS = .39, p < .001). LV1 for the NIH brain relationships showed similar relationships between CCA and PLS and was found to be stable and reproducible (singular value: CCA = .21, PLS = .43, p < .001). The current study suggests that stability and reproducibility of brain-behavior relationships identified by CCA and PLS are influenced by the statistical characteristics of the phenotypic measure used when applied to a large population-based pediatric sample.

Clinical neuroscience research is going through a translational crisis largely due to the challenges of producing meaningful and generalizable results. Two critical limitations within clinical neuroscience research are the use of univariate statistics and between-study methodological variation. Univariate statistics may not be sensitive enough to detect complex relationships between several variables, and methodological variation poses challenges to the generalizability of the results. We compared two widely used multivariate statistical approaches, canonical correlations analysis (CCA) and partial least squares correlation (PLS), to determine the generalizability and stability of their solutions. We show that the properties of the measures inputted into the analysis likely play a more substantial role in the generalizability and stability of results compared to the specific approach applied (i.e., CCA or PLS).

Transdiagnostic Neurobiology of Social Cognition and Individual Variability as Measured by Fractional Amplitude of Low-Frequency Fluctuation in Schizophrenia and Autism Spectrum Disorders.

Fractional amplitude of low-frequency fluctuation (fALFF) is a validated measure of resting-state spontaneous brain activity. Previous fALFF findings in autism and schizophrenia spectrum disorders (ASDs and SSDs) have been highly heterogeneous. We aimed to use fALFF in a large sample of typically developing control (TDC), ASD and SSD participants to explore group differences and relationships with inter-individual variability of fALFF maps and social cognition. fALFF from 495 participants (185 TDC, 68 ASD, and 242 SSD) was computed using functional magnetic resonance imaging as signal power within two frequency bands (i.e., slow-4 and slow-5), normalized by the power in the remaining frequency spectrum. Permutation analysis of linear models was employed to investigate the relationship of fALFF with diagnostic groups, higher-level social cognition, and lower-level social cognition. Each participant's average distance of fALFF map to all others was defined as a variability score, with higher scores indicating less typical maps. Lower fALFF in the visual and higher fALFF in the frontal regions were found in both SSD and ASD participants compared with TDCs. Limited differences were observed between ASD and SSD participants in the cuneus regions only. Associations between slow-4 fALFF and higher-level social cognitive scores across the whole sample were observed in the lateral occipitotemporal and temporoparietal junction. Individual variability within the ASD and SSD groups was also significantly higher compared with TDC. Similar patterns of fALFF and individual variability in ASD and SSD suggest some common neurobiological deficits across these related heterogeneous conditions.

A systematic review and meta-analysis of neuroimaging studies examining synaptic density in individuals with psychotic spectrum disorders.

BACKGROUND: Psychotic disorders have long been considered neurodevelopmental disorders where excessive synaptic pruning and cortical volume loss are central to disease pathology. We conducted a systematic review of the literature to identify neuroimaging studies specifically examining synaptic density across the psychosis spectrum. METHODS: PRISMA guidelines on reporting were followed. We systematically searched MEDLINE, Embase, APA PsycINFO, Web of Science and The Cochrane Library from inception to December 8, 2023, and included all original peer-reviewed articles or completed clinical neuroimaging studies of any modality measuring synaptic density in participants with a diagnosis of psychosis spectrum disorder as well as individuals with psychosis-risk states. The NIH quality assessment tool for observational cohort and cross-sectional studies was used for the risk of bias assessment. RESULTS: Five studies (k = 5) met inclusion criteria, comprising n = 128 adults (psychotic disorder; n = 61 and healthy volunteers; n = 67 and specifically measuring synaptic density via positron emission tomography (PET) imaging of the synaptic vesicle glycoprotein 2 A (SV2A). Three studies were included in our primary meta-analysis sharing the same outcome measure of SV2A binding, volume of distribution (VT). Regional SV2A VT was reduced in psychotic disorder participants in comparison to healthy volunteers, including the occipital lobe (Mean Difference (MD)= -2.17; 95% CI: -3.36 to -0.98; P < 0.001 ), temporal lobe (MD: -2.03; 95% CI: -3.19 to -0.88; P < 0.001 ), parietal lobe (MD:-1.61; 95% CI: -2.85 to -0.37; P = 0.01), anterior cingulate cortex (MD= -1.47; 95% CI: -2.45 to -0.49; P = 0.003), frontal cortex (MD: -1.16; 95% CI: -2.18 to -0.15; P = 0.02), amygdala (MD: -1.36; 95% CI: -2.20 to -0.52, p = 0.002), thalamus (MD:-1.46; 95% CI:-2.46 to -0.46, p = 0.004) and hippocampus (MD= -0.96; 95% CI: -1.59 to -0.33; P = 0.003). CONCLUSIONS: Preliminary studies provide in vivo evidence for reduced synaptic density in psychotic disorders. However, replication of findings in larger samples is required prior to definitive conclusions being drawn. PROSPERO: CRD42022359018.

Bifactor models of psychopathology using multi-informant and multi-instrument dimensional measures in the ABCD study.

Background: Due to limitations of categorical definitions of mental illness, there is a need for quantitative empirical investigations of the dimensional structure of psychopathology. Using exploratory bifactor methods, this study investigated a comprehensive and representative structure of psychopathology in children to better understand how psychotic-like experiences (PLEs), autism spectrum disorder (ASD) symptoms, impulsivity, and sensitivity to reward and punishment, may be integrated into extant general factor models of psychopathology. Methods: We used seven child-report and three parent-report instruments capturing diverse mental health symptoms in 11,185 children aged 9-10 from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study. We built on previous modeling frameworks by conducting both split sample and full sample factor analytic approaches that harnessed recent methodological advances in bifactor exploratory structural equation modeling (B-ESEM) to examine a wide range of psychopathology measures not previously integrated into a single analysis. Validity of psychopathology dimensions was examined by investigating associations with sex, age, cognition, imaging measures, and medical service usage. Results: All four factor analytic models showed excellent fit and similar structure within informant. PLEs loaded most highly onto a general psychopathology factor, suggesting that they may reflect non-specific risk for mental illness. ASD symptoms loaded separately from attention/hyperactivity symptoms. Symptoms of impulsivity and sensitivity to reward and punishment loaded onto specific factors, distinct from externalizing and internalizing factors. All identified factors were associated with clinically relevant risk factors, providing preliminary evidence for their construct validity. Conclusion: By integrating diverse child-report and parent-report psychopathology measures for children in the ABCD sample, we deliver data on the quantitative structure of psychopathology for an exceptionally large set of measurements and discuss implications for the field.

Utility of a virtual small group cognitive behaviour program for autistic children during the pandemic: evidence from a community-based implementation study.

BACKGROUND: Autistic children often experience socioemotional difficulties relating to emotion regulation and mental health problems. Supports for autistic children involve the use of adapted interventions that target emotion regulation and social skills, alongside mental health symptoms. The Secret Agent Society Small Group (SAS: SG), an adapted cognitive behavioural program, has demonstrated efficacy through lab-delivered randomized control trials. However, research is still needed on its effectiveness when delivered by publicly funded, community-based autism providers under real-world ecologically valid conditions, especially within the context of a pandemic. The COVID-19 pandemic has disrupted access to community-based supports and services for autistic children, and programs have adapted their services to online platforms. However, questions remain about the feasibility and clinical utility of evidence-based interventions and services delivered virtually in community-based settings. METHODS: The 9-week SAS: SG program was delivered virtually by seven community-based autism service providers during 2020-2021. The program included the use of computer-based games, role-playing tasks, and home missions. Caregivers completed surveys at three timepoints: pre-, post-intervention, and after a 3-month follow-up session. Surveys assessed caregivers' perception of the program's acceptability and level of satisfaction, as well as their child's social and emotional regulation skills and related mental health challenges. RESULTS: A total of 77 caregivers (94% gender identity females; Mean = 42.1 years, SD = 6.5 years) and their children (79% gender identity males; Mean = 9.9 years, SD = 1.3 years) completed the SAS: SG program. Caregivers agreed that the program was acceptable (95%) and were highly satisfied (90%). Caregivers reported significant reduction in their child's emotion reactivity from pre- to post-intervention (-1.78 (95% CI, -3.20 to -0.29), p = 0.01, d = 0.36), that continued to decrease after the 3-month booster session (-1.75 (95% CI, -3.34 to -0.16), p = 0.02, d = 0.33). Similarly, improvements in anxiety symptoms were observed (3.05 (95% CI, 0.72 to 5.36), p = 0.006, d = 0.39). CONCLUSIONS: As online delivery of interventions for autistic children remains popular past the pandemic, our findings shed light on future considerations for community-based services, including therapists and agency leaders, on how best to tailor and optimally deliver virtually based programming. TRIAL REGISTRATION: This study has been registered with ISRCTN Registry (ISRCTN98068608) on 15/09/2023. The study was retroactively registered.

Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions.

Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.

Worldwide Prevalence and Disability From Mental Disorders Across Childhood and Adolescence: Evidence From the Global Burden of Disease Study.

Importance: The period from childhood to early adulthood involves increased susceptibility to the onset of mental disorders, with implications for policy making that may be better appreciated by disaggregated analyses of narrow age groups. Objective: To estimate the global prevalence and years lived with disability (YLDs) associated with mental disorders and substance use disorders (SUDs) across 4 age groups using data from the 2019 Global Burden of Disease (GBD) study. Design, Setting, and Participants: Data from the 2019 GBD study were used for analysis of mental disorders and SUDs. Results were stratified by age group (age 5 to 9, 10 to 14, 15 to 19, and 20 to 24 years) and sex. Data for the 2019 GBD study were collected up to 2018, and data were analyzed for this article from April 2022 to September 2023. Exposure: Age 5 to 9 years, 10 to 14 years, 15 to 19 years, and 20 to 24 years. Main Outcomes and Measures: Prevalence rates with 95% uncertainty intervals (95% UIs) and number of YLDs. Results: Globally in 2019, 293 million of 2516 million individuals aged 5 to 24 years had at least 1 mental disorder, and 31 million had an SUD. The mean prevalence was 11.63% for mental disorders and 1.22% for SUDs. For the narrower age groups, the prevalence of mental disorders was 6.80% (95% UI, 5.58-8.03) for those aged 5 to 9 years, 12.40% (95% UI, 10.62-14.59) for those aged 10 to 14 years, 13.96% (95% UI, 12.36-15.78) for those aged 15 to 19 years, and 13.63% (95% UI, 11.90-15.53) for those aged 20 to 24 years. The prevalence of each individual disorder also varied by age groups; sex-specific patterns varied to some extent by age. Mental disorders accounted for 31.14 million of 153.59 million YLDs (20.27% of YLDs from all causes). SUDs accounted for 4.30 million YLDs (2.80% of YLDs from all causes). Over the entire life course, 24.85% of all YLDs attributable to mental disorders were recorded before age 25 years. Conclusions and Relevance: An analytical framework that relies on stratified age groups should be adopted for examination of mental disorders and SUDs from childhood to early adulthood. Given the implications of the early onset and lifetime burden of mental disorders and SUDs, age-disaggregated data are essential for the understanding of vulnerability and effective prevention and intervention initiatives.

Disrupted Maturation of White Matter Microstructure After Concussion Is Associated With Internalizing Behavior Scores in Female Children.

BACKGROUND: Some children who experience concussions, particularly females, develop long-lasting emotional and behavioral problems. Establishing the potential contribution of preexisting behavioral problems and disrupted white matter maturation has been challenging due to a lack of preinjury data. METHODS: From the Adolescent Brain Cognitive Development cohort, 239 (90 female) children age 12.1 ± 0.6 years who experienced a concussion after study entry at 10.0 ± 0.6 years were compared to 6438 (3245 female) children without head injuries who were age 9.9 ± 0.6 years at baseline and 12.0 ± 0.6 years at follow-up. The Child Behavior Checklist was used to assess internalizing and externalizing behavior at study entry and follow-up. In the children with magnetic resonance imaging data available (concussion n = 134, comparison n = 3520), deep and superficial white matter was characterized by neurite density from restriction spectrum image modeling of diffusion magnetic resonance imaging. Longitudinal ComBat harmonization removed scanner effects. Linear regressions modeled 1) behavior problems at follow-up controlling for baseline behavior, 2) impact of concussion on white matter maturation, and 3) contribution of deviations in white matter maturation to postconcussion behavior problems. RESULTS: Only female children with concussion had higher internalizing behavior problem scores. The youngest children with concussion showed less change in superficial white matter neurite density over 2 years than children with no concussion. In females with concussion, less change in superficial white matter neurite density was correlated with increased internalizing behavior problem scores. CONCLUSIONS: Concussions in female children are associated with emotional problems beyond preinjury levels. Injury to superficial white matter may contribute to persistent internalizing behavior problems in females.

The Toronto Adolescent and Youth Cohort Study: Study Design and Early Data Related to Psychosis Spectrum Symptoms, Functioning, and Suicidality.

BACKGROUND: Psychosis spectrum symptoms (PSSs) occur in a sizable percentage of youth and are associated with poorer cognitive performance, poorer functioning, and suicidality (i.e., suicidal thoughts and behaviors). PSSs may occur more frequently in youths already experiencing another mental illness, but the antecedents are not well known. The Toronto Adolescent and Youth (TAY) Cohort Study aims to characterize developmental trajectories in youths with mental illness and understand associations with PSSs, functioning, and suicidality. METHODS: The TAY Cohort Study is a longitudinal cohort study that aims to assess 1500 youths (age 11-24 years) presenting to tertiary care. In this article, we describe the extensive diagnostic and clinical characterization of psychopathology, substance use, functioning, suicidality, and health service utilization in these youths, with follow-up every 6 months over 5 years, including early baseline data. RESULTS: A total of 417 participants were enrolled between May 4, 2021, and February 2, 2023. Participants met diagnostic criteria for an average of 3.5 psychiatric diagnoses, most frequently anxiety and depressive disorders. Forty-nine percent of participants met a pre-established threshold for PSSs and exhibited higher rates of functional impairment, internalizing and externalizing symptoms, and suicidality than participants without PSSs. CONCLUSIONS: Initial findings from the TAY Cohort Study demonstrate the feasibility of extensive clinical phenotyping in youths who are seeking help for mental health problems. PSS prevalence is much higher than in community-based studies. Our early data support the critical need to better understand longitudinal trajectories of clinical youth cohorts in relation to psychosis risk, functioning, and suicidality.

Neuroimaging and Biosample Collection in the Toronto Adolescent and Youth Cohort Study: Rationale, Methods, and Early Data.

BACKGROUND: The Toronto Adolescent and Youth (TAY) Cohort Study will characterize the neurobiological trajectories of psychosis spectrum symptoms, functioning, and suicidality (i.e., suicidal thoughts and behaviors) in youth seeking mental health care. Here, we present the neuroimaging and biosample component of the protocol. We also present feasibility and quality control metrics for the baseline sample collected thus far. METHODS: The current study includes youths (ages 11-24 years) who were referred to child and youth mental health services within a large tertiary care center in Toronto, Ontario, Canada, with target recruitment of 1500 participants. Participants were offered the opportunity to provide any or all of the following: 1) 1-hour magnetic resonance imaging (MRI) scan (electroencephalography if ineligible for or declined MRI), 2) blood sample for genomic and proteomic data (or saliva if blood collection was declined or not feasible) and urine sample, and 3) heart rate recording to assess respiratory sinus arrhythmia. RESULTS: Of the first 417 participants who consented to participate between May 4, 2021, and February 2, 2023, 412 agreed to participate in the imaging and biosample protocol. Of these, 334 completed imaging, 341 provided a biosample, 338 completed respiratory sinus arrhythmia, and 316 completed all 3. Following quality control, data usability was high (MRI: T1-weighted 99%, diffusion-weighted imaging 99%, arterial spin labeling 90%, resting-state functional MRI 95%, task functional MRI 90%; electroencephalography: 83%; respiratory sinus arrhythmia: 99%). CONCLUSIONS: The high consent rates, good completion rates, and high data usability reported here demonstrate the feasibility of collecting and using brain imaging and biosamples in a large clinical cohort of youths seeking mental health care.

Cognition and Educational Achievement in the Toronto Adolescent and Youth Cohort Study: Rationale, Methods, and Early Data.

BACKGROUND: Both cognition and educational achievement in youths are linked to psychosis risk. One major aim of the Toronto Adolescent and Youth (TAY) Cohort Study is to characterize how cognitive and educational achievement trajectories inform the course of psychosis spectrum symptoms (PSSs), functioning, and suicidality. Here, we describe the protocol for the cognitive and educational data and early baseline data. METHODS: The cognitive assessment design is consistent with youth population cohort studies, including the NIH Toolbox, Rey Auditory Verbal Learning Test, Wechsler Matrix Reasoning Task, and Little Man Task. Participants complete an educational achievement questionnaire, and report cards are requested. Completion rates, descriptive data, and differences across PSS status are reported for the first participants (N = 417) ages 11 to 24 years, who were recruited between May 4, 2021, and February 2, 2023. RESULTS: Nearly 84% of the sample completed cognitive testing, and 88.2% completed the educational questionnaire, whereas report cards were collected for only 40.3%. Modifications to workflows were implemented to improve data collection. Participants who met criteria for PSSs demonstrated lower performance than those who did not on numerous key cognitive indices (p < .05) and also had more academic/educational problems. CONCLUSIONS: Following youths longitudinally enabled trajectory mapping and prediction based on cognitive and educational performance in relation to PSSs in treatment-seeking youths. Youths with PSSs had lower cognitive performance and worse educational outcomes than youths without PSSs. Results show the feasibility of collecting data on cognitive and educational outcomes in a cohort of youths seeking treatment related to mental illness and substance use.

Self-Harm Events and Suicide Deaths Among Autistic Individuals in Ontario, Canada.

Importance: Reasons for elevated suicide risks among autistic people are unclear, with insufficient population-based research on sex-specific patterns to inform tailored prevention and intervention. Objectives: To examine sex-stratified rates of self-harm events and suicide death among autistic individuals compared with nonautistic individuals, as well as the associated sociodemographic and clinical risk factors. Design, Setting, and Participants: This population-based matched-cohort study using linked health administrative databases in Ontario, Canada included all individuals with physician-recorded autism diagnoses from April 1, 1988, to March 31, 2018, each matched on age and sex to 4 nonautistic individuals from the general population. Self-harm events resulting in emergency health care from April 1, 2005, to December 31, 2020, were examined for one cohort, and death by suicide and other causes from April 1, 1993, to December 31, 2018, were examined for another cohort. Statistical analyses were conducted between October 2021 and June 2023. Exposure: Physician-recorded autism diagnoses from 1988 to 2018 from health administrative databases. Main Outcomes and Measures: Autistic and nonautistic individuals who were sex stratified a priori were compared using Andersen-Gill recurrent event models on self-harm events, and cause-specific competing risk models on death by suicide or other causes. Neighborhood-level income and rurality indices, and individual-level broad diagnostic categories of intellectual disabilities, mood and anxiety disorders, schizophrenia spectrum disorders, substance use disorders, and personality disorders were covariates. Results: For self-harm events (cohort, 379 630 individuals; median age at maximum follow-up, 20 years [IQR, 15-28 years]; median age of first autism diagnosis claim for autistic individuals, 9 years [IQR, 4-15 years]; 19 800 autistic females, 56 126 autistic males 79 200 nonautistic females, and 224 504 nonautistic males), among both sexes, autism diagnoses had independent associations with self-harm events (females: relative rate, 1.83; 95% CI, 1.61-2.08; males: relative rate, 1.47; 95% CI, 1.28-1.69) after accounting for income, rurality, intellectual disabilities, and psychiatric diagnoses. For suicide death (cohort, 334 690 individuals; median age at maximum follow-up, 19 years [IQR, 14-27 years]; median age of first autism diagnosis claim for autistic individuals, 10 years [IQR, 5-16 years]; 17 982 autistic females, 48 956 autistic males, 71 928 nonautistic females, 195 824 nonautistic males), there was a significantly higher crude hazard ratio among autistic females (1.98; 95% CI, 1.11-3.56) and a nonsignificantly higher crude hazard ratio among autistic males (1.34; 95% CI, 0.99-1.82); the increased risks were associated with psychiatric diagnoses. Conclusions and Relevance: This cohort study suggests that autistic individuals experienced increased risks of self-harm events and suicide death. Psychiatric diagnoses were significantly associated with the increased risks among both sexes, especially for suicide death, and in partially sex-unique ways. Autism-tailored and autism-informed clinical and social support to reduce suicide risks should consider multifactorial mechanisms, with a particular focus on the prevention and timely treatment of psychiatric illnesses.

Premature white matter microstructure in female children with a history of concussion.

Childhood concussion may interfere with neurodevelopment and influence cognition. Females are more likely to experience persistent symptoms after concussion, yet the sex-specific impact of concussion on brain microstructure in children is understudied. This study examined white matter and cortical microstructure, based on neurite density (ND) from diffusion-weighted MRI, in 9-to-10-year-old children in the Adolescent Brain Cognitive Development Study with (n = 336) and without (n = 7368) a history of concussion, and its relationship with cognitive performance. Multivariate regression was used to investigate relationships between ND and group, sex, and age in deep and superficial white matter, subcortical structures, and cortex. Partial least square correlation was performed to identify associations between ND and performance on NIH Toolbox tasks in children with concussion. All tissue types demonstrated higher ND with age, reflecting brain maturation. Group comparisons revealed higher ND in deep and superficial white matter in females with concussion. In female but not male children with concussion, there were significant associations between ND and performance on cognitive tests. These results demonstrate a greater long-term impact of childhood concussion on white matter microstructure in females compared to males that is associated with cognitive function. The increase in ND in females may reflect premature white matter maturation.

Systematic comparisons of different quality control approaches applied to three large pediatric neuroimaging datasets.

INTRODUCTION: Poor quality T1-weighted brain scans systematically affect the calculation of brain measures. Removing the influence of such scans requires identifying and excluding scans with noise and artefacts through a quality control (QC) procedure. While QC is critical for brain imaging analyses, it is not yet clear whether different QC approaches lead to the exclusion of the same participants. Further, the removal of poor-quality scans may unintentionally introduce a sampling bias by excluding the subset of participants who are younger and/or feature greater clinical impairment. This study had two aims: (1) examine whether different QC approaches applied to T1-weighted scans would exclude the same participants, and (2) examine how exclusion of poor-quality scans impacts specific demographic, clinical and brain measure characteristics between excluded and included participants in three large pediatric neuroimaging samples. METHODS: We used T1-weighted, resting-state fMRI, demographic and clinical data from the Province of Ontario Neurodevelopmental Disorders network (Aim 1: n = 553, Aim 2: n = 465), the Healthy Brain Network (Aim 1: n = 1051, Aim 2: n = 558), and the Philadelphia Neurodevelopmental Cohort (Aim 1: n = 1087; Aim 2: n = 619). Four different QC approaches were applied to T1-weighted MRI (visual QC, metric QC, automated QC, fMRI-derived QC). We used tetrachoric correlation and inter-rater reliability analyses to examine whether different QC approaches excluded the same participants. We examined differences in age, mental health symptoms, everyday/adaptive functioning, IQ and structural MRI-derived brain indices between participants that were included versus excluded following each QC approach. RESULTS: Dataset-specific findings revealed mixed results with respect to overlap of QC exclusion. However, in POND and HBN, we found a moderate level of overlap between visual and automated QC approaches (rtet=0.52-0.59). Implementation of QC excluded younger participants, and tended to exclude those with lower IQ, and lower everyday/adaptive functioning scores across several approaches in a dataset-specific manner. Across nearly all datasets and QC approaches examined, excluded participants had lower estimates of cortical thickness and subcortical volume, but this effect did not differ by QC approach. CONCLUSION: The results of this study provide insight into the influence of QC decisions on structural pediatric imaging analyses. While different QC approaches exclude different subsets of participants, the variation of influence of different QC approaches on clinical and brain metrics is minimal in large datasets. Overall, implementation of QC tends to exclude participants who are younger, and those who have more cognitive and functional impairment. Given that automated QC is standardized and can reduce between-study differences, the results of this study support the potential to use automated QC for large pediatric neuroimaging datasets.

Nabilone treatment for severe behavioral problems in adults with intellectual and developmental disabilities: Protocol for a phase I open-label clinical trial.

Severe behavioral problems (SBPs) are common contributors to morbidity and reduced quality of life for adults with intellectual and developmental disabilities (IDD) and their families. Current medications for SBPs show equivocal effectiveness and are associated with a high risk of side effects. New and safe treatments are urgently needed. While preliminary studies suggest that medical cannabinoids, particularly the synthetic cannabinoid nabilone, are plausible treatment options for SBPs in adults with IDD, data on the tolerability, safety and efficacy of nabilone in this population has never been investigated. Thus, we propose this first-ever Phase I pre-pilot open-label clinical trial to obtain preliminary data on the adherence, tolerability and safety profiles of nabilone in adults with IDD, and explore changes in SBPs pre- to post-treatment. We hypothesize that nabilone has favorable tolerability and safety profile for adults with IDD. The preliminary results will inform the next-stage pilot randomized controlled trials, followed by fully powered clinical trials eventually. This research helps fill the evidence gap in the use of cannabinoids in individuals with IDD to meet the needs of patients, families, and service providers.

Roadblocks and detours on pathways to a clinical diagnosis of autism for girls and women: A qualitative secondary analysis.

BACKGROUND: Autism is not always considered for girls and women until later along their clinical diagnostic pathways. Misdiagnosis or late diagnosis can pose significant disadvantages with respect to accessing timely health and autism-related services and supports. Understanding what contributes to roadblocks and detours along clinical pathways to an autism diagnosis can shed light on missed opportunities for earlier recognition. OBJECTIVE: Our objective was to examine what contributed to roadblocks, detours, and missed opportunities for earlier recognition and clinical diagnosis of autism for girls and women. DESIGN: We conducted a qualitative secondary analysis using data from a Canadian primary study that examined the health and healthcare experiences of autistic girls and women through interviews and focus groups. METHODS: Transcript data of 22 girls and women clinically diagnosed with autism and 15 parents were analysed, drawing on reflexive thematic analysis procedures. Techniques included coding data both inductively based on descriptions of roadblocks and detours and deductively based on conceptualizations of sex and gender. Patterns of ideas were categorized into themes and the 'story' of each theme was refined through writing and discussing analytic memos, reflecting on sex and gender assumptions, and creating a visual map of clinical pathways. RESULTS: Contributing factors to roadblocks, detours, and missed opportunities for earlier recognition and diagnosis were categorized as follows: (1) age of pre-diagnosis 'red flags' and 'signals'; (2) 'non-autism' mental health diagnoses first; (3) narrow understandings of autism based on male stereotypes; and (4) unavailable and unaffordable diagnostic services. CONCLUSION: Professionals providing developmental, mental health, educational, and/or employment supports can be more attuned to nuanced autism presentations. Research in collaboration with autistic girls and women and their childhood caregivers can help to identify examples of nuanced autistic features and how context plays a role in how these are experienced and navigated.

Comparing the stability and reproducibility of brain-behaviour relationships found using Canonical Correlation Analysis and Partial Least Squares within the ABCD Sample.

Introduction: Canonical Correlation Analysis (CCA) and Partial Least Squares Correlation (PLS) detect associations between two data matrices based on computing a linear combination between the two matrices (called latent variables; LVs). These LVs maximize correlation (CCA) and covariance (PLS). These different maximization criteria may render one approach more stable and reproducible than the other when working with brain and behavioural data at the population-level. This study compared the LVs which emerged from CCA and PLS analyses of brain-behaviour relationships from the Adolescent Brain Cognitive Development (ABCD) dataset and examined their stability and reproducibility. Methods: Structural T1-weighted imaging and behavioural data were accessed from the baseline Adolescent Brain Cognitive Development dataset (N > 9000, ages = 9-11 years). The brain matrix consisted of cortical thickness estimates in different cortical regions. The behavioural matrix consisted of 11 subscale scores from the parent-reported Child Behavioral Checklist (CBCL) or 7 cognitive performance measures from the NIH Toolbox. CCA and PLS models were separately applied to the brain-CBCL analysis and brain-cognition analysis. A permutation test was used to assess whether identified LVs were statistically significant. A series of resampling statistical methods were used to assess stability and reproducibility of the LVs. Results: When examining the relationship between cortical thickness and CBCL scores, the first LV was found to be significant across both CCA and PLS models (singular value: CCA = .13, PLS = .39, p < .001). LV1 from the CCA model found that covariation of CBCL scores was linked to covariation of cortical thickness. LV1 from the PLS model identified decreased cortical thickness linked to lower CBCL scores. There was limited evidence of stability or reproducibility of LV1 for both CCA and PLS. When examining the relationship between cortical thickness and cognitive performance, there were 6 significant LVs for both CCA and PLS (p < .01). The first LV showed similar relationships between CCA and PLS and was found to be stable and reproducible (singular value: CCA = .21, PLS = .43, p < .001). Conclusion: CCA and PLS identify different brain-behaviour relationships with limited stability and reproducibility when examining the relationship between cortical thickness and parent-reported behavioural measures. However, both methods identified relatively similar brain-behaviour relationships that were stable and reproducible when examining the relationship between cortical thickness and cognitive performance. The results of the current study suggest that stability and reproducibility of brain-behaviour relationships identified by CCA and PLS are influenced by characteristics of the analyzed sample and the included behavioural measurements when applied to a large pediatric dataset.