Assessing depression recurrence, cognitive burden, and neurobiological homeostasis in late life: Design and rationale of the REMBRANDT Study.

Background: Late-life depression is characterized by disability, cognitive impairment and decline, and a high risk of recurrence following remission. Aside from past psychiatric history, prognostic neurobiological and clinical factors influencing recurrence risk are unclear. Moreover, it is unclear if cognitive impairment predisposes to recurrence, or whether recurrent episodes may accelerate brain aging and cognitive decline. The purpose of the REMBRANDT study (Recurrence markers, cognitive burden, and neurobiological homeostasis in late-life depression) is to better elucidate these relationships and identify phenotypic, cognitive, environmental, and neurobiological factors contributing to and predictive of depression recurrence. Methods: Across three sites, REMBRANDT will enroll 300 depressed elders who will receive antidepressant treatment. The goal is to enroll 210 remitted depressed participants and 75 participants with no mental health history into a two-year longitudinal phase focusing on depression recurrence. Participants are evaluated every 2 months with deeper assessments occurring every 8 months, including structural and functional neuroimaging, environmental stress assessments, deep symptom phenotyping, and two weeks of 'burst' ecological momentary assessments to elucidate variability in symptoms and cognitive performance. A broad neuropsychological test battery is completed at the beginning and end of the longitudinal study. Significance: REMBRANDT will improve our understanding of how alterations in neural circuits and cognition that persist during remission contribute to depression recurrence vulnerability. It will also elucidate how these processes may contribute to cognitive impairment and decline. This project will obtain deep phenotypic data that will help identify vulnerability and resilience factors that can help stratify individual clinical risk.

Predicting Age from White Matter Diffusivity with Residual Learning.

Imaging findings inconsistent with those expected at specific chronological age ranges may serve as early indicators of neurological disorders and increased mortality risk. Estimation of chronological age, and deviations from expected results, from structural magnetic resonance imaging (MRI) data has become an important proxy task for developing biomarkers that are sensitive to such deviations. Complementary to structural analysis, diffusion tensor imaging (DTI) has proven effective in identifying age-related microstructural changes within the brain white matter, thereby presenting itself as a promising additional modality for brain age prediction. Although early studies have sought to harness DTI's advantages for age estimation, there is no evidence that the success of this prediction is owed to the unique microstructural and diffusivity features that DTI provides, rather than the macrostructural features that are also available in DTI data. Therefore, we seek to develop white-matter-specific age estimation to capture deviations from normal white matter aging. Specifically, we deliberately disregard the macrostructural information when predicting age from DTI scalar images, using two distinct methods. The first method relies on extracting only microstructural features from regions of interest (ROIs). The second applies 3D residual neural networks (ResNets) to learn features directly from the images, which are non-linearly registered and warped to a template to minimize macrostructural variations. When tested on unseen data, the first method yields mean absolute error (MAE) of 6.11 ± 0.19 years for cognitively normal participants and MAE of 6.62 ± 0.30 years for cognitively impaired participants, while the second method achieves MAE of 4.69 ± 0.23 years for cognitively normal participants and MAE of 4.96 ± 0.28 years for cognitively impaired participants. We find that the ResNet model captures subtler, non-macrostructural features for brain age prediction.

Refining our Understanding of Anxiety in Autistic Youth: Examining the Role of Behavioral Inflexibility.

Prior research has demonstrated that cognitive inflexibility is associated with anxiety in autistic individuals. Everyday patterns of behavioral inflexibility (e.g. observable inflexible behavior in the context of the need to change or adapt and that is manifested in real-world everyday settings) is common in autism and can be distinguished from performance on discrete cognitive tasks that tap flexible attention, learning, or decision-making. The purpose of this study was to extend this prior work on inflexibility in autism but with measures specifically developed with input from stakeholders (caregivers and clinicians) for autistic youth designed to measure everyday behavioral inflexibility (BI). We characterized anxiety in a large sample of autistic (N = 145) and non-autistic youth (N = 91), ages 3 to 17 years, using the Parent Rated Anxiety Scale for Autism Spectrum Disorder (PRAS-ASD). Further, we sought to understand how BI, measured via the Behavioral Inflexibility Scale (BIS), predicted anxiety compared to other variables known to increase anxiety in youth (chronological age, IQ, autism diagnosis, assigned sex at birth). Autistic youth had higher parent-related anxiety and BI compared to non-autistic youth. BI was the strongest predictor of anxiety scores, irrespective of diagnosis. Overall, our findings highlight the importance of BI to the understanding of anxiety in autistic youth.

Health Care Disparities Among Autistic LGBTQ+ People.

Background: Lesbian, gay, bisexual, transgender, or queer (LGBTQ+) people and disabled people experience disparities in access to health care compared with others. However, we have yet to understand how health care disparities may be further exacerbated at the intersection of disability and LGBTQ+ identity, particularly among autistic people. Objectives: The primary goals of this study were to (1) examine differences in unmet health care needs and health status between LGBTQ+ autistic people and straight/cisgender autistic people and (2) explore how state policies and demographics predict the unmet health care needs of the autistic LGBTQ+ people. Methods: We conducted a cross-sectional analysis using data from the 2019 National Survey on Health and Disability that included a subsample of autistic participants, with 62 LGBTQ+ adults and 58 straight/cisgender adults. To address our first study goal, we used an independent samples t-test, and to address our second study goal, we used Poisson regression. Results: The LGBTQ+ group reported significantly more days of poor physical and mental health, more co-occurring diagnoses, and more unmet health care needs than the straight/cisgender group. For LGBTQ+ people, protective state health care laws and a lower income resulted in significantly more health care needs being met. Conclusions: Findings from this study suggest that the intersection of an LGBTQ+ identity and autism is associated with greater disparities in physical and mental health as well as unmet health care needs; however, state policies prohibiting discrimination of LGBTQ+ people may act as a protective factor and result in fewer unmet health care needs. Future research should examine additional structural factors that may mitigate health inequities for autistic LGBTQ+ people.

Why is this an important issue?: More people in the autistic community identify as lesbian, gay, bisexual, transgender, or queer (LGBTQ+) as compared with the general population. Previous research described poorer health outcomes and issues in accessing health care for LGBTQ+ people. We need to understand how identifying as both autistic and LGBTQ+ is related to health outcomes and getting health care needs met. This is important information to improve future health care access and reduce health care issues. What was the purpose of this study?: We wanted to see whether there were differences between autistic/LGBTQ+ people and autistic/straight/cisgender people in accessing health care and health status. We also wanted to understand what factors contributed to unmet health care needs for autistic/LGBTQ+ people. What did the researchers do?: Our team used data from the second wave of the National Survey on Health and Disability (NSHD) fielded from October 2019 through January 2020. The NSHD sample included 2175 disabled participants, and 120 participants of the sample self-identified as autistic. We compared responses of autistic/LGBTQ+ people with autistic/straight/cisgender respondents. We compared these two groups on responses related to the number of good mental and physical health days, number of unmet health care needs, and number of additional diagnoses. We also looked at whether a person's income, location, race, or ethnicity, as well as whether state laws that supported LGBTQ+ health care related to the increased unmet health care needs of the LGBTQ+ group. What were the results of the study?: The results suggested that the autistic/LGBTQ+ group reported fewer good health days, more unmet health care needs, and more diagnoses. The authors also found that state-wide health care laws that protected LGBTQ+ people related to more health care needs being met. LGBTQ+ people with a lower income also had fewer unmet health care needs. What do these findings add to what was already known?: These findings are like other studies suggesting that identifying as autistic and LGBTQ+ results in more unmet health care needs and poorer health status. Our study adds to what is already known by exploring how other factors relate to the increased unmet health care needs among autistic/LGBTQ+ people. What are potential weaknesses in the study?: The NSHD subsample was small that may affect the study findings. Our sample also lacked diversity and primarily included White non-Hispanic/non-Latine participants, and those living in urban areas. The lack of diversity limits the generalizability of our findings. There are also many other factors (e.g., culture and provider knowledge) that may relate to unmet health care needs in autistic/LGBTQ+ people. Future research should investigate additional factors related to unmet health care needs. How will these findings help autistic adults now or in the future?: The findings are important because few research studies have focused on health care access among autistic/LGBTQ+ people in the United States. This study indicates the health care system is not supporting positive health outcomes and health care needs of autistic/LGBTQ+ adults. We need to continue to develop ways to support training of providers to reduce unmet health care needs and support better health outcomes.

Short report: The role of oral hypersensitivity in feeding behaviors of young autistic children.

LAY ABSTRACT: Feeding problems are common among autistic children and are linked to negative health consequences. Therefore, understanding feeding problems and factors that influence these behaviors is important for developing supports for children and families. While certain sensory processing patterns are commonly associated with feeding problems, less is known about the link between sensory processing and feeding behaviors in autism, as well as how parent behaviors and feelings during mealtime differ based on child sensory preferences. This research examined two groups of young autistic children who were reported to be picky eaters by their parents: those with and those without oral hypersensitivity. Children with oral hypersensitivity had more difficulty with food acceptance and their parents reported more negative feelings around feeding their child. However, the two groups of children (oral hypersensitive and not) did not differ in their medical/oral motor symptoms, mealtime behavior, or parent use of strategies at mealtimes. This research supports the need for personalized treatment strategies based on the child's sensory preferences to support both the child and parent in managing mealtimes.

Rapid detection of active pharmaceutical ingredients in drug products collected at an international mail facility by a satellite laboratory using a "toolkit" consisting of a handheld Raman spectrometer, portable mass spectrometer and portable FT-IR spectrometer.

A satellite laboratory "toolkit" consisting of a handheld Raman spectrometer, portable direct analysis in real-time mass spectrometer (DART-MS) and portable Fourier transform infrared (FT-IR) spectrometer was employed to examine 926 pharmaceutical, unknown and dietary supplement products collected at an international mail facility (IMF) for the presence of declared and undeclared active pharmaceutical ingredients (APIs) over the course of 68 working days. The toolkit successfully identified over 650 APIs, including over 200 unique APIs, using two or more devices. The performance of each individual device, and toolkit as a whole, were evaluated on all products and a subset of the products was forwarded to full-service laboratories for confirmatory analysis to determine false positive and false negative rates of the toolkit. The subset consisted of seven negative items (those not found to contain APIs using the toolkit) and 124 positive items (those found to contain at least one API using the toolkit). Overall, no false positives were detected in the negative items and only four false negatives and five false positives were detected in the positive items. Regarding the positive items, 119 of the 124 items were found to contain at least one API using at least two toolkit devices; each of these APIs were confirmed by a full-service laboratory. Furthermore, 90.2% of the APIs found by confirmatory laboratory analysis were detected by at least two toolkit devices. Based on these metrics and the fact that no false positives were detected by more than one device, it was concluded that when the toolkit detects and subsequently verifies/confirms an API using two or more devices, the results are as reliable as those generated by a full-service laboratory.

Perspective: The role of diversity advisory boards in autism research.

LAY ABSTRACT: This article argues that using groups of individuals that specifically focus on addressing issues with diversity in autism research and autism intervention development are key in ensuring that a greater amount of racial, ethnic, and gender diverse autistic individuals are included in the research and that the research is addressing the needs of these individuals and groups. We call these groups a diversity advisory board. A diversity advisory board will help improve diversity in autism research and intervention development by making sure that autism researchers (1) are intentional about addressing issues of diversity in their research and (2) are able to recruit a greater number of autistic individuals with diverse identities, and (3) by giving greater consideration to the context of diverse autistic individuals which will help autism-focused interventions work better in community settings. We give a short description of these arguments and ideas for how to form and use a diversity advisory board.

Influences of resting-state intrinsic functional brain connectivity on the antidepressant treatment response in late-life depression.

BACKGROUND: Late-life depression (LLD) is characterized by differences in resting state functional connectivity within and between intrinsic functional networks. This study examined whether clinical improvement to antidepressant medications is associated with pre-randomization functional connectivity in intrinsic brain networks. METHODS: Participants were 95 elders aged 60 years or older with major depressive disorder. After clinical assessments and baseline MRI, participants were randomized to escitalopram or placebo with a two-to-one allocation for 8 weeks. Non-remitting participants subsequently entered an 8-week trial of open-label bupropion. The main clinical outcome was depression severity measured by MADRS. Resting state functional connectivity was measured between a priori key seeds in the default mode (DMN), cognitive control, and limbic networks. RESULTS: In primary analyses of blinded data, lower post-treatment MADRS score was associated with higher resting connectivity between: (a) posterior cingulate cortex (PCC) and left medial prefrontal cortex; (b) PCC and subgenual anterior cingulate cortex (ACC); (c) right medial PFC and subgenual ACC; (d) right orbitofrontal cortex and left hippocampus. Lower post-treatment MADRS was further associated with lower connectivity between: (e) the right orbitofrontal cortex and left amygdala; and (f) left dorsolateral PFC and left dorsal ACC. Secondary analyses associated mood improvement on escitalopram with anterior DMN hub connectivity. Exploratory analyses of the bupropion open-label trial associated improvement with subgenual ACC, frontal, and amygdala connectivity. CONCLUSIONS: Response to antidepressants in LLD is related to connectivity in the DMN, cognitive control and limbic networks. Future work should focus on clinical markers of network connectivity informing prognosis. REGISTRATION: ClinicalTrials.gov NCT02332291.

Examining Sensitivity to Developmental Changes on the Behavioral Inflexibility Scale.

PURPOSE: The study objective was to determine if the validated Behavioral Inflexibility Scale (BIS) is sensitive to the detection of developmental changes in inflexibility in a sample of autistic children. METHODS: Parents of autistic children (n = 146, 3-17 years) completed the BIS at two time points, one year apart, to examine change. RESULTS: The findings indicate the BIS is sensitive to the detection of developmental changes and that child-level variables are not associated with those changes. Children's Time 1 BIS scores predicted children's severity on an independent outcome measure. Finally, a relationship between total services children were receiving and change in BIS scores over time was not found. CONCLUSION: The findings suggest the BIS is a reasonable candidate for consideration as an outcome measure.

Integrating the BIDS Neuroimaging Data Format and Workflow Optimization for Large-Scale Medical Image Analysis.

A robust medical image computing infrastructure must host massive multimodal archives, perform extensive analysis pipelines, and execute scalable job management. An emerging data format standard, the Brain Imaging Data Structure (BIDS), introduces complexities for interfacing with XNAT archives. Moreover, workflow integration is combinatorically problematic when matching large amount of processing to large datasets. Historically, workflow engines have been focused on refining workflows themselves instead of actual job generation. However, such an approach is incompatible with data centric architecture that hosts heterogeneous medical image computing. Distributed automation for XNAT toolkit (DAX) provides large-scale image storage and analysis pipelines with an optimized job management tool. Herein, we describe developments for DAX that allows for integration of XNAT and BIDS standards. We also improve DAX's efficiencies of diverse containerized workflows in a high-performance computing (HPC) environment. Briefly, we integrate YAML configuration processor scripts to abstract workflow data inputs, data outputs, commands, and job attributes. Finally, we propose an online database-driven mechanism for DAX to efficiently identify the most recent updated sessions, thereby improving job building efficiency on large projects. We refer the proposed overall DAX development in this work as DAX-1 (DAX version 1). To validate the effectiveness of the new features, we verified (1) the efficiency of converting XNAT data to BIDS format and the correctness of the conversion using a collection of BIDS standard containerized neuroimaging workflows, (2) how YAML-based processor simplified configuration setup via a sequence of application pipelines, and (3) the productivity of DAX-1 on generating actual HPC processing jobs compared with earlier DAX baseline method. The empirical results show that (1) DAX-1 converting XNAT data to BIDS has similar speed as accessing XNAT data only; (2) YAML can integrate to the DAX-1 with shallow learning curve for users, and (3) DAX-1 reduced the job/assessor generation latency by finding recent modified sessions. Herein, we present approaches for efficiently integrating XNAT and modern image formats with a scalable workflow engine for the large-scale dataset access and processing.

Using Novel Implementation Tools for Evidence-based Intervention Delivery (UNITED) across public service systems for three evidence-based autism interventions in under-resourced communities: study protocol.

BACKGROUND: There are a growing number of evidence-based interventions (EBIs) for autistic individuals, but few are successfully implemented with fidelity in under-resourced communities and with families from traditionally disenfranchised groups. Implementation science offers tools to increase EBI use in communities, but most implementation strategies are designed specific to a single EBI. It is not feasible to develop a new implementation strategy each time a new EBI is introduced in the community. Therefore, to test the effectiveness and generalizability of implementation strategies we are developing and testing a multifaceted implementation strategy with three EBIs concurrently. The goal of this protocol paper is to describe the randomized field trial of an implementation strategy for use across autism EBIs, diverse settings and participants, with the goal of increasing rapid uptake of effective practices to reach our most vulnerable children. METHODS: We developed a multifaceted implementation strategy called Using Novel Implementation Tools for Evidence-based intervention Delivery (UNITED) to facilitate the implementation and sustainment of three EBIs in under-resourced settings. We will compare fidelity to, and effectiveness of, each intervention [Mind the Gap (MTG), Remaking Recess (RR), Self-Determined Learning Model of Instruction (SDLMI)] with and without UNITED in a randomized field trial. Randomization will be stratified using a minimization allocation method. We will train community practitioners using remote delivery of modules specific to the intervention, and active coaching via Zoom for at least 6 sessions and up to 12 as dictated by each EBI. Our primary outcome is fidelity to each EBI, and our secondary outcome is at the child or family level (family empowerment for MTG, child peer social engagement for RR, and adolescent self-determination for SDLMI, respectively). We will measure progress through the implementation phases using the Stages of Implementation Completion and cost-effectiveness of UNITED. DISCUSSION: The results of this study will provide rigorous data on the effectiveness and generalizability of one relatively light-touch implementation strategy in increasing use of autism EBIs and associated outcomes in diverse under resourced public service settings for underrepresented autistic youth. TRIAL REGISTRATION: Mind the Gap: Clinicaltrials.gov Identifier:  NCT04972825 (Date registered July 22, 2021); Remaking Recess: Clinicaltrials.gov Identifier:  NCT04972838 (Date registered July 22, 2021); Self-Determined Learning Model of Instruction: Clinicaltrials.gov Identifier:  NCT04972851 (Date registered July 22, 2021).

EPI susceptibility correction introduces significant differences far from local areas of high distortion.

PURPOSE: In echo-planar diffusion-weighted imaging, correcting for susceptibility-induced artifacts typically requires acquiring pairs of images, known as blip-up blip-down acquisitions, to create an undistorted volume as a target to correct distortions that are often focal where regions with differences in magnetic susceptibility interface, such as the frontal and temporal areas. However, blip-up blip-down acquisitions are not always available, and distortion effects may not be specifically localized to such areas, with subtle effects potentially extending throughout the brain. Here, we apply a deep learning technique to generate an undistorted volume to correct susceptibility-induced artifacts and demonstrate implications for image fidelity and diffusion-based inference outside of areas where high focal distortion is present. METHODS: To demonstrate differences due to susceptibility artifact correction, uncorrected baseline images were compared to identical images where correction was performed using an undistorted target volume produced by the deep learning tool "PreQual". Widespread geometric distortion was assessed visually by referencing diffusion-weighted images to T1-weighted images. Tract-based spatial statistics (TBSS) were utilized to perform whole brain analysis of fractional anisotropy (FA) values to assess differences between subject groups (depressed vs. non-depressed) via permutation-based, voxel-wise testing. Multivariate regression models were then used to contrast TBSS results between corrected and non-corrected diffusion images. RESULTS: Susceptibility artifact correction resulted in visible, widespread improvement in image fidelity when referenced to T1-weighted images. TBSS results were dependent on susceptibility artifact correction with correction resulting in widespread structural alterations of the mean FA skeleton, changes in skeletal FA, and additional positive tests of significance of regression coefficients in subsequent regression models. CONCLUSION: Our results indicated that EPI distortion effects are not purely focal, and that reducing distortion can result in significant differences in the interpretation of diffusion data, even in areas remote from high distortion.

Brief report: replication of the psychometric characteristics of the behavioral inflexibility scale in an independent sample.

The Behavioral Inflexibility Scale (BIS) is a recently developed measure of behavioral inflexibility, defined as rigid patterns of behavior that contrast with the need to be flexible when the situation calls for it. In this study, we sought to replicate previous findings on the psychometric properties of the BIS in a community sample. Data for this study were collected using in-person assessments of 163 autistic and 95 non-autistic children ages 3-17 and included the BIS, measures of social-communication ability and repetitive behaviors, and an assessment of cognitive ability. Our findings replicate the psychometric properties of the BIS, indicating that the measure is a valid measure of behavioral inflexibility in ASD.

Exploring Growth in Expressive Communication of Infants and Toddlers With Autism Spectrum Disorder.

One of the earliest indicators of autism spectrum disorder (ASD) is delay in language and social communication. Despite consensus on the benefits of earlier diagnosis and intervention, our understanding of the language growth of children with ASD during the first years of life remains limited. Therefore, this study compared communication growth patterns of infants and toddlers with ASD to growth benchmarks of a standardized language assessment. We conducted a retrospective analysis of growth on the Early Communication Indicator (ECI) of 23 infants and toddlers who received an ASD diagnosis in the future. At 42 months of age, children with ASD had significantly lower rates of gestures, single words, and multiple words, but significantly higher rates of nonword vocalizations. Children with ASD had significantly slower growth of single and multiple words, but their rate of vocalization growth was significantly greater than benchmark. Although more research is needed with larger samples, because the ECI was designed for practitioners to monitor children's response to intervention over time, these findings show promise for the ECI's use as a progress monitoring measure for young children with ASD. Limitations and the need for future research are discussed.

A culturally grounded autism parent training program with Black parents.

LAY ABSTRACT: Parent training programs have been well-studied in Autism Spectrum Disorders and shown to increase a parent's feeling of empowerment, advocacy skills, and treatment enrollment for their child. The majority of parent training interventions have been developed without considering the unique needs of under-represented communities, such as the Black community. Black children with autism are not only misdiagnosed or not diagnosed at all, but are not accessing services equally compared to their White peers. There is an urgent need for culturally adapted interventions in order to decrease the disparity gap. The Color of Autism Foundation developed and ran a parent training program for Black parents of children with autism. The program was grounded in two key features: (1) creating a circle of support for parents to connect and heal from ongoing and historical racial trauma and (2) using parents of Black children with autism as the main facilitators. We believe this increased parent's ability to engage in the educational aspects of the training. Overall, parents reported high levels of satisfaction with the training were highly engaged (attended an average of five of six sessions) and reported high levels of empowerment. Parents also reported continued mistrust in the medical and research community and a need for more Black providers. Further work should examine the relationship of the parent and provider in autism treatment and study the impact of circles of healing for Black families.

Patterns in reporting and participant inclusion related to race and ethnicity in autism intervention literature: Data from a large-scale systematic review of evidence-based practices.

LAY ABSTRACT: Researchers who study autism-related interventions do a poor job reporting data related to the race and ethnicity of autistic individuals who participate in their studies, and of those who do report these data, the participants are overwhelmingly White. This is problematic for many reasons, as we know little about how interventions are meeting the needs of culturally and linguistically diverse populations, and we assume that interventions are effective for all when they have been developed and validated primarily with and for White children. This study examined the reporting patterns of autism intervention researchers whose work was included in a large-scale systematic review of the intervention literature published between 1990 and 2017. We found that only 25% of studies (out of 1,013 included in the review) included data related to the race and ethnicity of their participants, with minimal change in reporting patterns across the years. In studies with reported data, White participants had the highest rate of participation, with a large gap between the next highest rates of participation among Hispanic/Latino, Black, and Asian participants. Other race and ethnicity groups had very low representation. This study includes additional analyses which examine how the reporting patterns and the inclusion of racially and ethnically diverse participants varies across study types, interventions, and outcome areas. Reporting this data is merely a starting point to begin to address the many disparities in autism-related healthcare, education, and research practices, and this article includes broader implications and next steps to ensure the field becomes more equitable and inclusive.

Measuring the Functional Impact of Behavioral Inflexibility in Children with Autism Using the Behavioral Inflexibility Scale: Clinical Interview (BIS-CI).

For individuals with autism spectrum disorder (ASD), behavioral inflexibility can affect multiple domains of functioning and family life. The objective of this study was to develop and validate a clinical interview version of the Behavioral Inflexibility Scale. Trained interviewers conducted interviews with parents of 144 children with ASD and 70 typically developing children (ages: 3-17 years). Using exploratory factor analysis, the Behavioral Inflexibility Scale-Clinical Interview (BIS-CI) was found to be unidimensional. Reliability data indicated the measure was internally consistent (α = 0.80), achieved excellent inter-rater reliability (ICC = 0.97) and test-retest reliability (ICC = 0.87). These findings demonstrate that the BIS-CI is a reliable and valid measure to determine the functional impact of behavioral inflexibility.

Biases, Barriers, and Possible Solutions: Steps Towards Addressing Autism Researchers Under-Engagement with Racially, Ethnically, and Socioeconomically Diverse Communities.

Autistic individuals who are also people of color or from lower socioeconomic strata are historically underrepresented in research. Lack of representation in autism research has contributed to health and healthcare disparities. Reducing these disparities will require culturally competent research that is relevant to under-resourced communities as well as collecting large nationally representative samples, or samples in which traditionally disenfranchised groups are over-represented. To achieve these goals, a diverse group of culturally competent researchers must partner with and gain the trust of communities to identify and eliminate barriers to participating in research. We suggest community-academic partnerships as one promising approach that results in high-quality research built on cultural competency, respect, and shared decision making.

Evaluating the Feasibility of The NIH Toolbox Cognition Battery for Autistic Children and Adolescents.

This study evaluates the feasibility of the NIH Toolbox Cognition Battery (NIH-TCB) for use in autism spectrum disorder (ASD). 116 autistic children and adolescents and 80 typically developing (TD) controls, ages 3-17 years, completed four NIH-TCB tasks related to inhibitory control, cognitive flexibility, processing speed, and episodic memory. While the majority of autistic and TD children completed all four tasks, autistic children experienced greater difficulties with task completion. Across autistic and TD children, performance on NIH-TCB tasks was highly dependent on IQ, but significant performance differences related to ASD diagnosis were found for two of four tasks. These findings highlight the potential strengths and limitations of the NIH-TCB for use with autistic children.