Search

There is a dearth of research regarding adaptive functioning during the transition to adulthood in autism spectrum disorder (ASD). Profiles on the Vineland Adaptive Behavior Scales, Second Edition were examined by age and intellectual ability in 75 participants with ASD (16-58 years). Results extend previous reports of a cognitive advantage over adaptive functioning in children by demonstrating a similar pattern in an older sample. Daily living skills were a relative strength compared to communication and socialization in adults, but not adolescents. In general, highest subdomain scores were observed in writing skills and lowest scores were observed in interpersonal skills. Regardless of cognitive ability, all standard scores were well below average, indicating a need for lifelong intervention that targets adaptive functioning.

Schools regularly screen students for hearing and vision impairments because they present impediments to academic progress. For the same reason, schools should consider adding a universal screening for social challenges, which may also impede the learning process. This study reports on the development of the Social Challenges Screening Questionnaire (SCSQ), an efficient teacher-report screening questionnaire that identifies students with challenges who may benefit from a psychological evaluation. Further, the questionnaire may help identify students with Autism Spectrum Disorder who were previously undiagnosed. The SCSQ was administered to 549 general education students in the third and fourth grades. Internal consistency was 0.85. A smaller sample of students (n = 50) was selected for additional follow up assessment using the Social Responsiveness Questionnaire, Second Edition. Scores on the two instruments were strongly correlated (r = 0.87, p < 0.01), and sensitivity (0.94) and specificity (0.88) indicate the SCSQ can efficiently detect students with social challenges in need of a formal evaluation.

Profiles of performance on the Stanford Binet Intelligence Scales (SB5) and Vineland Adaptive Behavior Scales (VABS) were examined in 73 children and adolescents with autism spectrum disorder. SB5 cognitive profiles were observed to be similar between participants with and without early language delay, but different between participants with and without intellectual disability. With few exceptions, the distribution and cognitive profiles of participants with specific nonverbal IQ-verbal IQ and abbreviated IQ-full scale IQ discrepancy patterns paralleled previous reports. A cognitive functioning advantage over adaptive functioning was observed to be strongest in participants without intellectual disability and older participants. The previously reported VABS "autism profile" was not observed. Current findings clarify previous research and will inform the diagnostic process and treatment planning.

Uncertainty in the effective radiative forcing (ERF) of climate primarily arises from the unknown contribution of aerosols, which impact radiative fluxes directly and through modifying cloud properties. Climate model simulations with fixed sea surface temperatures but perturbed atmospheric aerosol loadings allow for an estimate of how strongly the planet's radiative energy budget has been perturbed by the increase in aerosols since pre-industrial times. The approximate partial radiative perturbation (APRP) technique further decomposes the contributions to the direct forcing due to aerosol scattering and absorption and to the indirect forcing due to aerosol-induced changes in cloud scattering, amount, and absorption, as well as the effects of aerosols on surface albedo. Here we evaluate previously published APRP-derived estimates of aerosol effective radiative forcings from these simulations conducted in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and find that they are biased as a result of two large coding errors that – in most cases – fortuitously compensate. The most notable exception is the direct radiative forcing from absorbing aerosols, which is more than 40 % larger averaged across CMIP6 models in the present study. Correcting these biases eliminates the residuals and leads to better agreement with benchmark estimates derived from double calls to the radiation code. The APRP method – when properly implemented – remains a highly accurate and efficient technique for diagnosing aerosol ERF in cases where double radiation calls are not available, and in all cases it provides quantification of the individual contributors to the ERF that are highly useful but not otherwise available. [ABSTRACT FROM AUTHOR]

The current study examined differences between parent report and diagnostician direct assessment of receptive language, expressive language, and fine motor abilities in toddlers with autism spectrum disorder (ASD) and other delays. Additionally, this study examined whether parent‐diagnostician consistency varied by child diagnosis and sex assigned at birth (SAB). Initial mixed analysis of variances (ANOVAs) were conducted using data from a sample of 646 toddlers to examine whether parent‐diagnostician consistency differed by child diagnosis. Matched samples (using child age, SAB, and nonverbal IQ) were then created within each diagnostic group and mixed ANOVAs were conducted to examine if consistency was similar in matched diagnostic subsamples and whether it differed by SAB. Findings from the full sample mostly replicated previous research that has documented consistency between parent report and direct observation regardless of child diagnosis. However, when examined in matched diagnostic subgroups, more nuanced patterns were observed. Parent report of receptive language was lower in ASD and ASD features subgroups and parent report of fine motor skills was lower than direct observation in the ASD, ASD features, and developmental delay groups. When examining the moderating effect of SAB, only expressive language was impacted for children in the ASD group. Results indicate the importance of considering child demographic characteristics and that child SAB may impact parent report and/or diagnostician perception of expressive language. Lay Summary: Research suggests parents are generally reliable reporters of child development. Little is known, however, about whether reliability of parent report differs by child sex. In this study we found that parents of children with autism rated their child's language comprehension abilities and fine motor skills differently than professional diagnosticians, and that consistency between parent‐report and direct‐observation by diagnosticians of expressive language varied by child sex. Our findings suggest child demographics/characteristics should be considered when examining parent report of language production. [ABSTRACT FROM AUTHOR]

Research suggests that toddlers with no language delay (NLD) should have better outcomes than those with language delay (LD). However, the predictive utility of language milestones relative to co-varying factors such as age at diagnosis, IQ, and ASD symptomatology is unclear. This study compared school-aged children with ASD and NLD (n = 59) to a well-matched group with ASD and LD (n = 59). The LD group was diagnosed at younger ages and their historical ASD symptoms were more severe than the NLD group. The groups were similar in current ASD symptoms and adaptive functioning at school age. Language milestones were correlated with adaptive functioning, but IQ and social symptoms of ASD were stronger predictors of functioning at school age. Therefore, language milestones may not be the best indicators of prognosis for children who are diagnosed after toddlerhood., Author(s): Anthony Goodwin [sup.1] , Nicole L. Matthews [sup.1] , Christopher J. Smith [sup.1] Author Affiliations: (1) grid.430554.3Southwest Autism Research and Resource Center, 300 North 18th Street, 85006, Phoenix, AZ, [...]

Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC), including 60 the first global stocktake under the Paris Agreement that will conclude at COP28 in December 2023. Evidence-based decision making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5-10 years, creating potential for an information gap between report cycles. We base this update on the assessment methods used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report, updating the monitoring datasets and to produce updated estimates for key climate indicators including emissions, greenhouse gas concentrations, radiative forcing, surface temperature changes, the Earth's energy imbalance, warming attributed to human activities, the remaining carbon budget and estimates of global temperature extremes. The purpose of this effort, grounded in an open data, open science approach, is to make annually updated reliable global climate indicators 70 available in the public domain (https://doi.org/10.5281/zenodo.7883758, Smith et al., 2023). As they are traceable and consistent with IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that human induced warming reached 1.14 [0.9 to 1.4] °C over the 2013-2022 period and 1.26 [1.0 to 1.6] C in 2022. Human induced warming is increasing at an unprecedented rate of over 0.2 °C per decade. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 57 ± 5.6 GtCO2e over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there are signs that emission levels are starting to stabilise, and we can hope that a continued series of these annual updates might track a real-world change of direction for the climate over this critical decade. [ABSTRACT FROM AUTHOR]

Uncertainty in the effective radiative forcing (ERF) of climate primarily arises from the unknown contribution of aerosols, which impact radiative fluxes directly and through modifying cloud properties. Climate model simulations with fixed sea surface temperatures but perturbed atmospheric aerosol loadings allow for an estimate of how strongly the planet's radiative energy budget has been perturbed by the increase in aerosols since pre-industrial times. The approximate partial radiative perturbation (APRP) technique further decomposes the contributions to the direct forcing from aerosol scattering and absorption, and to the indirect forcing from aerosol-induced changes in cloud scattering, amount, and absorption, as well as the effects of aerosols on surface albedo. Here we evaluate previously published APRP-derived estimates of aerosol effective radiative forcings from these simulations and find that they are slightly biased as a result of large but compensating errors. These biases are largest for the aerosol direct effect owing to underestimated aerosol absorption. Correcting these biases eliminates the residuals and leads to better agreement with ground-truth estimates derived from double-calls to the radiation code. The APRP method - when properly implemented - remains a highly accurate and efficient technique for diagnosing aerosol ERF in cases where double radiation calls are not available, and in all cases it provides quantification of the individual contributors to the ERF that are highly useful but not otherwise available. [ABSTRACT FROM AUTHOR]

The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood and diversity in climate model experiments persists as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article synthesizes current challenges and emphasizes opportunities for advancing our understanding of climate change and model diversity. The perspective of this article is based on expert views from three multi-model intercomparison projects (MIPs) - the Precipitation Driver Response MIP (PDRMIP), the Aerosol and Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specialisms across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation-response paradigm through multi-model ensembles of Earth System Models of varying complexity. It specifically facilitated contributions to the research field through sharing knowledge on best practices for the design of model diagnostics and experimental strategies across MIP boundaries, e.g., for estimating effective radiative forcing. We discuss the challenges of gaining insights from highly complex models that have specific biases and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible, and machine learning approaches for faster and better sub-grid scale parameterizations where they are needed. Both would improve our ability to adopt a smart experimental design with an optimal tradeoff between resolution, complexity and simulation length. Future experiments can be evaluated and improved with sophisticated methods that leverage multiple observational datasets, and thereby, help to advance the understanding of climate change and its impacts. [ABSTRACT FROM AUTHOR]