Use recent gel nail:cancer headlines to discuss research design

Many of my students love a good manicure. Sometimes, they come in with full-on talons. The youth love manicures.

As such, the recent viral headlines about gel nail polish lamps and cancer matter to them.

Google search results, with over 52K hits for the search term gel nail cancer.

#scicomm

But what did the original research really study?

Headline reading: DNA damage and somatic mutations in mammalian cells after irradiation with a nail polish dryer

https://www.nature.com/articles/s41467-023-35876-8#Sec12

(CHECK OUT THIS GREAT RM IMAGE FROM THE ORIGINAL RESEARCH!!!)

This short NPR story by Rachel Treisman is a great summary. The NPR audio story is accompanied by a written report. In that report, Treisman succinctly summarizes the methodology:

A description of the methodology used in the gel nail study

https://www.npr.org/2023/01/26/1151332361/gel-nails-cancer-manicure-safe

1. Let's talk about science communication.

The NPR story is accurate science reporting. However, most of the headlines don't mention that a) some of the evidence came from mice cells, and they measured cell mutations but not cancer.

2. Let's talk about factorial ANOVA

The researchers used a 3 (cell types: human 1, human 2, and mouse cells) x 2 (exposure condition: acute vs chronic), outcome variables (cell death, mitochondrial damage, DNA damage).

3. Let's talk about repeated measure design.

In the acute condition, there were two sessions of 20 minutes, while in the chronic condition, the exposure occurred for days (again, see that fantastic image from the article!).

4. Let's talk about DVs

Some of the headlines say cancer, but the actual outcome measures cell death, DNA damage, and mitochondria damage.

5. Let's talk about using lab research to establish a basic premise

This wasn't a huge epidemiological study looking at actual cancer rates. It was nice, tidy lab research that used disembodied cells to study the first thing that must be established in the gel nail lamp:cancer argument. And that is the immediate effects of UV light on cells.

Ways to use funny meme scales in your stats classes

Have you ever heard of the theory that there are multiple people worldwide thinking about the same novel thing at the same time? It is the multiple discovery hypothesis of invention . Like, multiple great minds around the world were working on calculus at the same time. Well, I think a bunch of super-duper psychology professors were all thinking about scale memes and pedagogy at the same time. Clearly, this is just as impressive as calculus. Who were some of these great minds? 1) Dr. Molly Metz maintains a curated list of hilarious "How you doing?" scales. 2) Dr. Esther Lindenström posted about using these scales as student check-ins. 3) I was working on a blog post about using such scales to teach the basics of variables. So, I decided to create a post about three ways to use these scales in your stats classes: 1) Teaching the basics of variables. 2) Nominal vs. ordinal scales. 3) Daily check-in with your students. 1. Teach your students the basics...

Leo DiCaprio Romantic Age Gap Data: UPDATE

Does anyone else teach correlation and regression together at the end of the semester? Here is a treat for you: Updated data on Leonardo DiCaprio, his age, and his romantic partner's age when they started dating. A few years ago, there was a dust-up when a clever Redditor r/TrustLittleBrother realized that DiCaprio had never dated anyone over 25. I blogged about this when it happened. But the old data was from 2022. Inspired by this sleuthing, I created a wee data set, including up-to-date information on his current relationship with Vittoria Ceretti, so your students can suss out the patterns that exist in this data.

Tyler Vigen's Spurious Correlations

Tyler Vigen has has created a long list of easy-to-paste-into-a-powerpoint graphs that illustrate that correlation does not equal causation. For instance, while per capita consumption of cheese and number of people who die by become tangled in their bed sheets may have a strong relationship (r = 0.947091), no one is saying that cheese consumption leads to bed sheet-related death. Although, you could pose The Third Variable question to your students for some of these relationships). Property of Tyler Vigens, http://i.imgur.com/OfQYQW8.png Vigen has also provided a menu of frequently used variables (deaths by tripping, sunlight by state) to help you look for specific examples. This portion is interactive, as you and your students can generate your own graphs. Below, I generated a graph of marriage rates in Pennsylvania and consumption of high fructose corn syrup. Generated at http://www.tylervigen.com/

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