Have you seen or heard the viral claim: “Having a husband adds 7 hours of housework per week for women?” It feels right—but is it? In this episode of Is This Legit?, I track down the source of this stat, dig into what the research actually says, and uncover why outdated data keeps going viral.

Along the way, we’ll talk about:

• The 2008 University of Michigan press release behind this claim (and why it’s not a study).
• What more recent research says about gender, marriage, and housework.
• How social media algorithms push misinformation.
• Why cuts to research funding are making it harder to get real answers.

If you’ve ever questioned where viral stats actually come from, wondered whether we’re using outdated data when better research exists, or just want to know the truth about who’s really doing the housework, this episode is for you.

Referenced:

• University of Michigan article
• 2023 American Time Use Survey Results
• 2024 Gender Equity Policy Institute Report
• 2013 PEW research report
• 2022 meta-analysis
• ABC news article

The internet is buzzing—ChatGPT’s Deep Research feature is here, and people are calling it a game-changer. Some even say it could replace researchers altogether. (Eek!)

But is it really that good? Or does it just look good?

In this episode, I put Deep Research to the test, running my own experiments on two widely shared statistics. What I found raised some serious questions about how AI gathers information, whether it can be trusted, and why looking "legit" doesn’t always mean being accurate.

If you’ve ever wondered whether AI can actually do research—or if it’s just like really good at Googling—this episode is for you.

In today’s episode, we’re diving into a mysterious and dramatic decision-making stat that’s been popping up everywhere lately.

But when you try to track it down, no one actually knows where it comes from. Every source just says it comes from various sources—or cites a source that points to… more unnamed sources, in an endless loop.

So what’s the truth?

We’ll break down the citation loop that keeps this number alive, expose the lack of a real source, and reveal how even major publications like Harvard Business Review, Forbes, and PBS repeated it without fact-checking.

Join me as I unpack what we know (and don’t know) about decision-making, how misinformation spreads even in places we should be able to trust, and why we need more good people in research to answer questions like this.

Referenced:

• 2015 - Roberts Wesleyan University Article
• 2016 - The Wall Street Journal
• 2018 - Psychology Today
• 2018 - National Library of Medicine
• 2021 - PBS
• 2022 - CNN Health
• 2023 - Harvard Business Review
• 2023 - Forbes
• Cornell University Study
• OREO Study
• Noom Study
• Microsoft Ad

In today’s episode, I’m tackling a viral health claim that sounds simple—but isn’t: that doing 10 squats every 45 minutes during an 8.5-hour period of sitting is better for blood sugar regulation than taking a 30-minute walk.

Is that what the research actually says? Not quite.

We’ll break down the study’s methodology, expose the grammatical ambiguity that helped this misinformation spread, and reveal how even AI initially misread the study.

Plus, you’ll learn why you should make reading the methods section of research your superpower, how bad science communication erodes public trust, and why representation in research matters more than you think.

Join me as I unpack what this study really found, challenge misleading claims, and share practical tips for spotting the next viral “science-backed” myth before it fools you.

Referenced:

• The Study
• The Video on Instagram
• The Tweet
• The Newsweek Article

In today’s episode, I’m tackling the bold, research-backed claim that AI produces lower carbon emissions for writing and drawing than humans. We’ll break down the study’s methodology, question its framing, and uncover the glaring omissions that make its conclusions feel more like a pro-AI pitch than neutral science. Plus, you’ll learn what Mark Twain has to do with all of this and why apples-to-oranges carbon calculations can skew the bigger picture.

Join me as I unpack the study’s findings, explore why bias in research matters, and share tips for critically evaluating the next viral “science-backed” claim you encounter.

Referenced:

• Scientific Reports article
• The Writer Magazine
• EPA’s Greenhouse Gas Equivalencies Calculator
• The Nature Conservancy’s footprint calculator

In today’s episode, I’m diving into the viral claim behind the triple nod, touted as a research backed hack for better communication. We’ll trace its evolution over the years, explore the research (or lack thereof) that backs it up, and unpack how ambiguous stats and missing citations can turn into misinformation. From precise percentages to vague references, we’ll see whether this popular nonverbal cue holds up to scrutiny.

Join me as I separate fact from fiction, explain why transparency in sharing “research” matters, and share tips for navigating the next viral stat you encounter.

Referenced:

• Mel Robbins Podcast
• YouTube video for the speaker’s organization
• The Carey Nieuwhof Leadership Podcast
• Time Magazine article
• LifeHacker
• Science of People

Perhaps you’ve seen the ads: a hot chocolate drink that promises to fix your sleep, boasting “93% of participants said it helped them get a better night’s rest.” But as a researcher who loves digging into the details, I had to ask: REALLY?

In today’s episode, I’m diving into the clinical study behind this claim from Beam’s Dream Powder. We’ll break down the who, what, when, where, and why of the research; explore the buzzwords like “randomized,” “double-blind,” and “placebo-controlled”; and unpack how the study design may not be as rigorous as it seems. From missing demographic details to potential placebo effects (hello, distinct flavors), we’ll see whether this magic hot chocolate truly lives up to its promise.

Join me as I separate fact from marketing spin, explain why transparency in research matters, and share tips for evaluating the next “scientifically proven” claim you see.

Clinical Trial Registry

Beam Blog