Kristin Sainani is associate teaching professor of epidemiology and population health at Stanford University in California.
Kristin Sainani
Teaching professor
Stanford University
From this contributor
Journal Club: Meta-analysis oversells popular autism screen
The Modified Checklist for Autism in Toddlers (M-CHAT) accurately flags autistic toddlers, a new systematic review and meta-analysis suggests, contrary to past evidence that the tool’s validity varies depending on a child’s age and traits. Experts weigh in on the discrepancy.
Journal Club: Meta-analysis oversells popular autism screen
Flawed methods undermine study on undiagnosed autism and suicide
The researchers attempted to retroactively identify signs of autism in people who died by suicide, but their analysis is not convincing.
Flawed methods undermine study on undiagnosed autism and suicide
Study links screen time to autism, but problems abound
The paper relied on parent-reported data and adjusted for few potentially confounding variables.
Study links screen time to autism, but problems abound
Explore more from The Transmitter
Finding neuroheterogeneity’s sweet spot
Once thought to be detrimental to memory processing, neuronal diversity—at the right ‘Goldilocks’ dose—is a new boon to theoretical neuroscience.
Finding neuroheterogeneity’s sweet spot
Once thought to be detrimental to memory processing, neuronal diversity—at the right ‘Goldilocks’ dose—is a new boon to theoretical neuroscience.
COVID-19 and influenza effects in pregnancy; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 October.
COVID-19 and influenza effects in pregnancy; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 October.
What to do when traditional mechanistic approaches no longer work
Many complex behaviors have stubbornly resisted mechanistic explanations. Deciphering them will require new approaches—and perhaps a new concept of “understanding.”
What to do when traditional mechanistic approaches no longer work
Many complex behaviors have stubbornly resisted mechanistic explanations. Deciphering them will require new approaches—and perhaps a new concept of “understanding.”