Despite awareness that depression is common in autistic people, the mental health of minimally verbal (MV) autistic adults has received inadequate attention. Part of the problem is the lack of valid tools to assess depression in MV autistic adults. This study will investigate the utility and appropriateness of using surveys administered by a caregiver around depression and will gather information about behaviors that caregivers believe reflect low mood or depression. This project addresses a gap in mental health supports for MV autistic adults and will assist clinicians in determining which tools should be used for people with autism who show signs of depression but cannot verbally communicate their feelings.
Measuring Depression and Low Mood in Minimally-Verbal Autistic Adults: Establishing and Adapting Tools to Assess Emotional Well-Being
In the last version of the Diagnostic and Statistical Manual, the different subtypes of autism were folded into one label: autism spectrum disorder. A similar revision is being made around the International Classification of Diseases, the system the WHO uses across the world to describe autism and provide appropriate reimbursements for services and supports. In this version, the ICD-11, a combination of 300 different presentations of autism are described. A diagnosis can be made if 1 feature of social-communication and 1 feature of repetitive behaviors are documented, with an onset of any time in life. This is causing a lot of confusion in the community, because since the presentations are not specific to autism, it is difficult to provide an accurate diagnosis using the ICD-11. On this week’s podcast episode we talk to German psychiatrist Inge Kamp-Becker, MD, who outlines what the changes are, and how misdiagnosis can be made and what those consequences might be. Her summary is linked below.
Abstract
Emerging evidence suggests that the higher prevalence of autism in individuals who are assigned male than assigned female at birth results from both biological factors and identification biases. Autistic individuals who are assigned female at birth (AFAB) and those who are gender diverse experience health disparities and clinical inequity, including late or missed diagnosis and inadequate support. In this Viewpoint, an international panel of clinicians, scientists, and community members with lived experiences of autism reviewed the challenges in identifying autism in individuals who are AFAB and proposed clinical and research directions to promote the health, development, and wellbeing of autistic AFAB individuals. The recognition challenges stem from the interplay between cognitive differences and nuanced or different presentations of autism in some AFAB individuals; expectancy, gender-related, and autism-related biases held by clinicians; and social determinants. We recommend that professional development for clinicians be supported by health-care systems, professional societies, and governing bodies to improve equitable access to assessment and earlier identification of autism in AFAB individuals. Autistic AFAB individuals should receive tailored support in education, identity development, health care, and social and professional sense of belonging
Abstract
Background: Reporting retention data is critical to determining the soundness of a study’s conclusions (internal validity) and broader generalizability (external validity). Although selective attrition can lead to overestimates of effects, biased conclusions, or overly expansive generalizations, retention rates are not reported in many longitudinal studies.
Methods: We examined multiple child- and family-level factors potentially associated with retention in a longitudinal study of younger siblings of children with autism spectrum disorder (ASD; n = 304) or typical development (n = 163). The sample was followed from the first year of life to 36 months of age, for up to 7 visits.
Results: Of the 467 infant siblings who were consented and participated in at least one research visit, 397 (85.0%) were retained to study completion at 36 months. Retention rates did not differ by familial risk group (ASD-risk vs. Low-risk), sex, race, ethnicity, age at enrollment, number of children in the family, maternal employment, marital status, or parent concerns about the child at enrollment. A stepwise regression model identified 4 variables that, together, provided the most parsimonious predictive model of study retention: maternal education, maternal age at child’s birth, travel distance to the study site, and diagnostic outcome classification at the final study visit.
Conclusions: The retained and not-retained groups did not differ on most demographic and clinical variables, suggesting few threats to internal and external validity. The significantly higher rate of retention of children diagnosed with ASD (95%) than typically developing children (83%) may, however, present biases when studying recurrence risk. We conclude by describing engagement and tracking methods that can be used to maximize retention in longitudinal studies of children at risk of ASD.
Keywords: attrition; autism; external validity; internal validity; longitudinal study; retention.
A recent publication in the Lancet was dedicated to clinical recommendations to support autistic females at birth. Because more males than females are diagnosed with autism, their needs are often misunderstood, misinterpreted, or just ignored. Researchers, clinicians, scientists, parents and self-advocates from around the world joined together to identify those needs and propose solutions that can be implemented in everyday care. Listen to this week’s podcast episode to learn more, or read the article in its entirety at the link below.
Everyone who has looked for support for autism spectrum disorder is familiar with waitlists. Waitlists for evaluation, diagnosis, intervention, consultations and referrals. These waitlists prevent important opportunities for services and many groups developing technologies, policies, and approaches to reduce the waitlists or work around them. On this week’s podcast, we talk to Dr. Sharief Taraman from Cognoa to hear about their recent study on the scope of the problem on waitlists, what causes them, and how digital therapeutics may help them.
Can biomarkers that measure things like visual social attention be a good proxy for an in person behavioral diagnosis? Why would this be important? This week’s podcast explores two new studies the the Journal of the American Medical Association that show a simple device called EarliPoint can be used to shorten the wait times to receive a diagnostic evaluation. Currently autism can be diagnosed at 18 months but most families do not get into an appointment until 4-5 years of age. That can change. Families were able to easily complete it, it predicted things like not just a diagnosis but behavioral features and cognitive ability. It’s been deployed in 6 speciality centers, been approved by the FDA, and hopefully coming to a clinic near you soon.
Objectives: Autism spectrum disorder (autism) is a heterogeneous condition that poses challenges in describing the needs of individuals with autism and making prognoses about future outcomes. We applied a newly proposed definition of profound autism to surveillance data to estimate the percentage of children with autism who have profound autism and describe their sociodemographic and clinical characteristics.
Methods: We analyzed population-based surveillance data from the Autism and Developmental Disabilities Monitoring Network for 20 135 children aged 8 years with autism during 2000-2016. Children were classified as having profound autism if they were nonverbal, were minimally verbal, or had an intelligence quotient <50.
Results: The percentage of 8-year-old children with profound autism among those with autism was 26.7%. Compared with children with non-profound autism, children with profound autism were more likely to be female, from racial and ethnic minority groups, of low socioeconomic status, born preterm or with low birth weight; have self-injurious behaviors; have seizure disorders; and have lower adaptive scores. In 2016, the prevalence of profound autism was 4.6 per 1000 8-year-olds. The prevalence ratio (PR) of profound autism was higher among non-Hispanic Asian/Native Hawaiian/Other Pacific Islander (PR = 1.55; 95 CI, 1.38-1.73), non-Hispanic Black (PR = 1.76; 95% CI, 1.67-1.86), and Hispanic (PR = 1.50; 95% CI, 0.88-1.26) children than among non-Hispanic White children.
Conclusions: As the population of children with autism continues to change, describing and quantifying the population with profound autism is important for planning. Policies and programs could consider the needs of people with profound autism across the life span to ensure their needs are met.
Keywords: autism; public health; surveillance.
Best practice for the assessment of autism spectrum disorder (ASD) symptom severity relies on clinician ratings of the Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2), but the association of these ratings with objective measures of children’s social gaze and smiling is unknown. Sixty-six preschool-age children (49 boys, M = 39.97 months, SD = 10.58) with suspected ASD (61 confirmed ASD) were administered the ADOS-2 and provided social affect calibrated severity scores (SA CSS). Children’s social gaze and smiling during the ADOS-2, captured with a camera contained in eyeglasses worn by the examiner and parent, were obtained via a computer vision processing pipeline. Children who gazed more at their parents (p = .04) and whose gaze at their parents involved more smiling (p = .02) received lower social affect severity scores, indicating fewer social affect symptoms, adjusted R2 = .15, p = .003.
Keywords: Autism diagnostic observation schedule; Autism spectrum disorder; Objective measurement; Smiling; Social gaze.
Two recent papers suggest that a childhood diagnosis of ASD is important for adulthood quality of life and well being. But another one points out that it isn’t the only thing, or even the primary factor, involved in improved quality of life and well-being as autistic adults age. There are others, like comorbid mental health problems, demographic factors like gender and current age. These studies were conducted by autistic researchers and did an amazing thing – one tried to replicate the other. The media got the point of these findings wrong (shocker) so today’s #ASFpodcast explains what they mean.
https://journals.sagepub.com/doi/pdf/10.1177/13623613231173056
The disparity in diagnosis between Black kids and white kids is narrowing, but not by luck or coincidence. Based on previous research, clinicians are altering their professional training and their outreach to make sure more Black families are diagnosed and receive interventions. On today’s podcast, we highlight a recent study that focused on different ways to lower the age of diagnosis and improve access to early intervention in Black families. This intervention improved cognitive outcomes in Black kids.
Last week in Stockholm, Sweden, 2200 researchers and scientists working to understand and help those on the spectrum, met to share their most recent findings and exchange ideas. What were the main takeaways as ASF saw them? In our latest podcast episode, we cover why some autistic people don’t want genetics to be studied, how to better engage families with IDD and who are non-speaking, females, adults, international studies and yes, diversity. The program book was released a day before the meeting and can be found here: https://cdn.ymaws.com/www.autism-insar.org/resource/resmgr/docs/annualmeeting/insar2023_program_book.pdf