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An update on why there are fewer autistic females compared to males

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This week, special podcast correspondent #MiaKotikovski summarizes new research on the increasing prevalence of autism, with a focus on females. While the number of diagnosed females is increasing faster than the number for males, females assigned at birth still are less likely to receive a diagnosis than males. Additional evidence points to females having more genetic mutations and lower cognitive ability, so the questions remain: Are there females with autism who are just not getting diagnosed despite having all the autism features? Why not? Does autism in females “look” the same as autism in males? What sets them apart? These articles are all featured in the year-end highlight of research, so this is the time to get a deep explanation of the latest in sex differences in #autism.

https://pubmed.ncbi.nlm.nih.gov/34563942

https://pubmed.ncbi.nlm.nih.gov/39334436

https://pubmed.ncbi.nlm.nih.gov/33966484

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Post-Pandemic Problems

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A few years after the start of the pandemic, and a couple of years into “recovery”, scientists are still disentangeling the effects of COVID-19 lockdowns and exposure. For example, is there an uptick in autism screen positives when pregnant mothers fell ill? Were there diagnostic disparities based on co-morbid conditions? Did autistic people feel better over time during the pandemic? This week’s #ASFpodcast explores these questions using new longitudinal data sets designed to better understand the long term impacts of the pandemic.

https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/39312236

https://onlinelibrary.wiley.com/doi/10.1111/jar.13300

https://pubmed.ncbi.nlm.nih.gov/39228920

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Culturally sensitive care with Mia Kotikovski

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On this week’s podcast, Mia Kotivkoski, founder of her own 5013c and recent graduate of Stony Brook University, reviews why understanding cultural and contextual factors influence not just an autism diagnosis but general health and outcomes of a broad group of people. They include immigrants, racial and ethnic differences, and socio-economic factors. What can be done? Listen to this week’s podcast to learn more.

https://www.aacap.org/App_Themes/AACAP/Docs/resource_centers/cultural_diversity/competency_curriculum%20_cap_training/cases_supporting_materials/clinics/Bernier-psychopathology_families_and_culture-autism.pdf

https://www.sciencedirect.com/science/article/pii/S1750946718300758?via%3Dihub

https://www.researchgate.net/publication/258193289_The_Impact_of_Culture_on_Autism_Diagnosis_and_Treatment_Considerations_for_Counselors_and_Other_Professionals

https://www.maactearly.org/uploads/9/2/2/3/9223642/considering_culture_facilitatorguide_final_102116.pdf

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7614360

https://www.scientificamerican.com/article/why-are-there-so-few-autism-specialists

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Machine Learning in Autism, Explained

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Thank you to Dennis Wall from Stanford University for explaining what Machine Learning is, how it’s related to Artificial Intelligence (today’s four buzz words) and how these new technologies are helping families get a diagnosis. He talks about the overall goals of these techniques, highlighting Cognoa’s CanvasDx to provide remote diagnoses to potentially reduce the waiting lists for families.

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Are new ICD-11 criteria for an autism diagnosis too vague?

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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. This week 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.

https://www.nature.com/articles/s41380-023-02354-y

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Waitlists for waitlists

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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.

Waitlist Crisis Report
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Juneteenth, 2023

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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.

https://pubmed.ncbi.nlm.nih.gov/36443922/

https://pubmed.ncbi.nlm.nih.gov/37196781/

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Can we solve the pandemic problems around diagnosis and intervention?

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This week’s #ASFpodcast highlights a few articles from the Journal of Autism and Developmental Disorders this week which examined the tolerability and efficacy of online diagnostic procedures and interventions, from the perspective of both parents and clinicians. They seem to work about the same, although there were some caveats. For many reasons, online and telehealth options are here to stay, and more needs to be done to improve their accuracy, acceptability, feasibility and effectiveness. These early studies are promising though, and lead the way to even more improvements to help make them a viable option for families in the future.

https://link.springer.com/article/10.1007/s10803-022-05435-z

https://link.springer.com/article/10.1007/s10803-022-05576-1

https://link.springer.com/article/10.1007/s10803-022-05554-7

https://link.springer.com/article/10.1007/s10803-022-05580-5https://link.springer.com/article/10.1007/s10803-022-05607-x

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Is autism a yes/no diagnosis?

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This week’s podcast highlights a paper from the IBIS (infant brain imaging study) that tracks infants from 6 months to 5 years of age to examine how ASD symptoms cluster together. These infants either have a diagnosis or they don’t, or they have something which doesn’t meet diagnostic threshold but is still impairing in some way. Ignoring the actual diagnosis, if the data is clustered together around how symptoms present, what happens? What does that mean for some of the longest standing research findings in ASD? For example, using this new approach which ignores and actual diagnosis, are more males are diagnosed than females? As it turns out, it equals out these ratios. What does this mean? Listen to this week’s podcast to hear directly from the first author, Catherine Burrows!

https://www.sciencedirect.com/science/article/abs/pii/S0006322322013130?casa_token=ZFZpvnUOIBkAAAAA:G667QIkX_Vd6JPeWvIPABo1FPrdNL_3IiW-ajy7xR2Nme_I4ztOEf2xJ4FyhGHTMgrb8Lqq6Og