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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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Autism Self-Diagnosis Tools

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Autistic individuals are turning to self-diagnosis to explain their autism features, sometimes based on better awareness, sometimes based on what they see on social media. But how accurate are these autism diagnostic tools? They range anywhere from tik-tok videos all the way to a tool called the RAADS-R which has been described as a valid diagnostic measure. Unfortunately, as discussed by scientist Alexandra Sturm who looked closely at what this tool measures, it’s probably not a true diagnostic measure. However, diagnosis for adults is hard to obtain, Dr. Sturm provides suggestions on what to do if you are curious about an autism diagnosis and don’t know where to turn.

The RAADS can be found here: https://embrace-autism.com/raads-r/

https://www.tandfonline.com/doi/full/10.1080/09515089.2024.2327823

https://pubmed.ncbi.nlm.nih.gov/38305196/

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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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The importance of a childhood diagnosis

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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

https://journals.sagepub.com/doi/pdf/10.1177/13623613221086700?casa_token=Pt_EcbUzuDQAAAAA:_qVIXsQGRxWgoSOp4-kpLdohAr6CiB5lFYbhx8kK5omusM4rfHTjeyuzSLbxPh1OFftAc4j8BkuzCA

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9296439/

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How many people can be described as having “profound autism”?

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Quick answer: 26.7%. But what is “profound autism” and why is this label necessary? Have the rates of profound autism changed over time? How many do not have profound autism and are their needs different and how? Listen to this week’s ASF podcast and read the paper here: https://autismsciencefoundation.org/wp-content/uploads/2023/04/CDC-Profound-Autism-Statistics_ASF-Copy.pdf

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A potential biomarker to AID, not MAKE, a diagnosis

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The media has just called another biological marker a “diagnostic test”, when in this case, it was always intended to be an aid, not a test itself. It involves using baby hair strands to look a variation in metabolism of certain chemical elements across time. Remarkably, it showed similar results in autistic children in Japan, the US and Sweden. It’s not ready to be used as a diagnostic test, so what is it supposed to do? Listen to an interview with the inventor and researcher, Dr. Manish Arora from The Icahn School of Medicine at Mt. Sinai School here.

The full article (open access) can be found here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9740182/

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The true title should be: “A new open source screening tool to help detect autism”

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Many of the existing tools to identify autism cost money or are not specific for ASD, and they are hidden behind paywalls and are hard to obtain. A group of scientists led by Tom Frazer at John Caroll University put together a 39 questionnaire called the Autism Symptoms Dimensions Questionnaire to be filled out by parents of children. It’s free and open source! But that’s just the first step. The media got the intent wrong, yet again.

It should not replace a full diagnosis. Autism is complex, and even those with genetic forms of autism show heterogeneity in symptoms. They each need comprehensive evaluations. But this is a good start. Check it out here!!! It’s open source:

References below:

https://pubmed.ncbi.nlm.nih.gov/36670671/

https://onlinelibrary.wiley.com/doi/epdf/10.1111/dmcn.15497

https://pubmed.ncbi.nlm.nih.gov/36639821/