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
By
Spectrum
14 March 2023 | 5 min read
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
By
Kristin Sainani
28 February 2022 | 3 min read
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
By
Kristin Sainani
1 February 2022 | 4 min read
Explore more from The Transmitter
Links between tuberous sclerosis complex and autism, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 17 August.
Links between tuberous sclerosis complex and autism, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 17 August.
By
Jill Adams
18 August 2026 | 1 min read
The fun and flexibility of data science
Taylor Bolt spent his Ph.D. and postdoc digging through brain imaging data for clues to cognition. In industry, the datasets are different but the joy of answering questions with data remains.
The fun and flexibility of data science
Taylor Bolt spent his Ph.D. and postdoc digging through brain imaging data for clues to cognition. In industry, the datasets are different but the joy of answering questions with data remains.
By
Katie Moisse
18 August 2026 | 7 min read
Mind over metrics: How can we tell if two brains (or AI models) are alike?
The ability to record from large populations of neurons has triggered the development of myriad methods for comparing them. But we’re still grappling with how to convert measures of likeness into a better mechanistic understanding.
Mind over metrics: How can we tell if two brains (or AI models) are alike?
The ability to record from large populations of neurons has triggered the development of myriad methods for comparing them. But we’re still grappling with how to convert measures of likeness into a better mechanistic understanding.
By
Alex Williams
17 August 2026 | 7 min read