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
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Machine learning spots neural progenitors in adult human brains
But the finding has not settled the long-standing debate over the existence and extent of neurogenesis during adulthood, says Yale University neuroscientist Juan Arellano.

Machine learning spots neural progenitors in adult human brains
But the finding has not settled the long-standing debate over the existence and extent of neurogenesis during adulthood, says Yale University neuroscientist Juan Arellano.
Xiao-Jing Wang outlines the future of theoretical neuroscience
Wang discusses why he decided the time was right for a new theoretical neuroscience textbook and how bifurcation is a key missing concept in neuroscience explanations.
Xiao-Jing Wang outlines the future of theoretical neuroscience
Wang discusses why he decided the time was right for a new theoretical neuroscience textbook and how bifurcation is a key missing concept in neuroscience explanations.
Memory study sparks debate over statistical methods
Critics of a 2024 Nature paper suggest the authors failed to address the risk of false-positive findings. The authors argue more rigorous methods can result in missed leads.

Memory study sparks debate over statistical methods
Critics of a 2024 Nature paper suggest the authors failed to address the risk of false-positive findings. The authors argue more rigorous methods can result in missed leads.