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Hand Washing Update

bathroom bottle clean container
Photo by Pixabay on Pexels.com

We looked at hand washing design research because conditions matter. People are influenced by their environment, often more than they realize. In that first post we highlighted to:

  • Turn off the water, to feel less rushed.
  • Make bosses (attending physicians) clean their hands.
  • Use incentives to reward (or penalize).
  • Put the hand-cleaning area adjacent to the need-hands-clean area.
  • Create a social expectation.

That research maps well to the EAST framework. To change behavior make things Easy, Attractive, Social, and Timely.

There are two updates since then.

First, The Behavioral Insights team researched which infographics communicated the best. Comparing seven ‘how to’ posters from around the world on 2,500 UK adults they found that “bright infographics with the step-by-step procedure prominently displayed without too much accompanying text” worked best to communicate good hand washing steps.

However, this was a ‘what I say’ question on a ‘what I do topic.’ Instead of hand washing it could have been a personal savings infographic about spending too much on a car. Sure, people will confirm they know the information but what would they do? It’s an encouraging start but more needs done.

Second, Google Search Trends for ‘hand wash’ negatively correlates with coronavirus cases. A few years ago, Google Trends predicted the flu rates ahead of the CDC but in following years erred enormously. Researchers suggested it was because people aren’t great at diagnosing the flu. How many times have you gone to WebMD AND had the thing. This bodes well for  the hand washing research, which stepped over that obstacle of unfamiliarity.

This focus on hand washing is timely but it’s also generalizable. It’s any verb. Investing. Driving. Loving. Parenting. All of these things are affected by the conditions they exist in.

Thank you for reading and supporting.

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Parlay Maths

A gambling parlay is a bet where two or more things have to happen. Will you have coffee and eggs for breakfast is less likely—thus longer odds and higher payout–than just betting on one or the other.

And people love betting parlays. The most popular Super Bowl bet is the coin toss, and Americans bet seven billion dollars (legally) on the game. 

And casinos love people betting parlays. According to UNLV, sports books earn five percent on bets, except for parlays. On those bets casinos take 30%.

Why do bettors do so poorly? It’s a little too much psychology and a little too little numeracy. Bettors, said Rufus Peabody, love to bet for things to happen. It’s easier to imagine one outcome than all outcomes. It’s why the ‘no safety’ bet almost always has positive EV. 

Bettors also don’t consider the numbers in the right light. Two independent seventy percent events only both occur half the time. Let’s run with that.

According to smart air filters, a t-shirt-mask will stop 70% of an airborne bacteria which is smaller than the coronavirus. That’s good. But what if we parlay masks?

If I wear a mask a t-shirt-mask and you wear a t-shirt mask we’ve reduced the viral load ten-fold. Thirty-percent of thirty-percent is .09. 

The same math that makes parlays good for Vegas and bad for gamblers is what makes masks good for all of us.

I wore mine to the store for the first time. It felt kinda foolish. But then I did the math.

UNLV explains the casino win percentage as “Win percentage, or win as a percentage of drop, AKA hold percentage, the percentage of money wagered that the casino kept.”

Peabody also tweeted about this: 

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Framing Employment

Framing is so important because it’s a way to get ‘free value’. Things well framed are perceived as well done—and perceived value is all there is.

I ran this one question poll on Mechanical Turk, Amazon’s data collection service, and Twitter to see how people perceive the same news. Each option describes the US labor market from mid-March to mid-April.

The question was, which one of these is the best (or least bad) way to describe what’s happened.

Over the last month..

The most important data isn’t that one section of the pie is larger than another but that there are sections of the pie. If  “135 million people remained employed” took the king’s share there would be nothing to figure out. In the many slices though we get many ideas.

Jason Zweig demonstrated this magnificently in a recent WSJ column. Imagine you’re of a certain age with a certain income and a certain promise of social security. It’s likely more than you realize. Zweig wrote:

The $2,000 a month that you and your spouse will each receive in the future has a present value of $772,235, according to OpenSocialSecurity.com.

That’s roughly what it would cost an insurance company to provide each of you with a guaranteed, inflation-adjusted $2,000 monthly payment for the rest of your lives (assuming you file for retirement benefits at age 70 and your spouse at 62).

So your expected Social Security payments are like a giant phantom annuity—a bundle of inflation-adjusted bonds you don’t own but whose income you have the right to receive. The same is true—usually without the ability to keep pace with inflation—if you are fortunate enough to have a defined-benefit pension plan.

Much of poker is played by the number. Professionals fold many more hands than they play because the numbers tell them that. But people don’t like to feel like automatons. They want action. When Annie Duke started teaching clients how to play poker she had to reframe how they saw the game.

Duke’s insight was to get her clients to choose to play by the numbers. She appealed to their meta side. They had to see the analytical next to the emotional and make a choice from those two options.

People are relative thinkers and many many decisions come down to framing one thing against another. It works for news, marketing, home purchases, dinner options, and dates. It works for everything.

 

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Colossal Comprehension

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This is the earth.

Part of our quarantine education was to get outside and make some scale drawings of our solar system.

We made our earth one roadway wide, about twenty feet in diameter and paced off two hundred yards and drew the moon. It was five feet wide. The ISS was seven inches from the earth’s surface.

It’s always challenging to consider the scale of the universe. It’s huge. It’s so huge that Mars was sixty miles away in our little universe.

Part-of-the-reason Einstein marveled about compound interest is because scale is really hard to understand. Once things scale up or down past the human perspective we just don’t quite get it. This came up on two recent podcasts.

First, Peter Attia spoke with his daughter about the coronavirus. It was an excellent, simple, good-for-kids episode. So how big (or little) is the virus?

“If were to cut one of your hairs, and you can barely see the edge when it’s cut, how many coronaviruses do you think we could line up on the tip of your hair when it’s cut?” Attia asked

A thousand viruses. That’s beyond the human scale of understanding.

One the other end of the spectrum, and closer to the solar system situation was Cade Massey’s longhorn lament.

“One of the things that frustrated me most when I to talk with people was them saying ‘Well, you’re not going to get this if you’re young.’ We knew the probabilities are steeply related to age but there’s still a probability for every age group. Throw millions of people at a small probability and you’ve got some sick people. We just aren’t good psychologically with these kinds of probabilities.” Cade Massey

The percentage for infection, hospitalization, and ventilation are remarkably small.

New York City houses eight million people and the metro area is home to twenty-one million. Projections note that only .27% will need beds, and only .063% will need ventilators.

Right now my sixth grade daughter is learning percentages as parts of the whole. She answers questions like; “If sixty percent of a class of twenty-four are boys, how many children are in the class?”

That’s good sixth grade math but it gets hard with large numbers. One-fourth of a percent is really small but eight million is really large. How does someone make sense of that? We probably just need to think slow, not fast.

 

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Numbing Numbers

On Epidemic, Ronald Klain talked about how long a shutdown may last.

“I’m asked this question when I’m on TV all the time, what’s the date, what’s the date? But this discussion about the date is the wrong discussion, the question is, what are the preconditions that we need to have in place before we can reopen large swaths of economic activity?”

That’s a harder question.

The CoVid19 situation is like a Sudoku board with very few numbers filled in. If that’s a nine this might be a four which makes that a two—shit that can’t work. There are so many interchangeable parts it’s easier to ask, ‘what’s the date?’

To get away from ‘what’s the date’ questions we can add one more small step, asking why.

‘Why’ gets us to answer.

For example, why is social distancing six feet? Is this a case like a power law where the bulk of the results come from one source? For example, when researchers looked at what size particles passed through what size fabrics, “0.02 micron Bacteriophage MS2 particles (5 times smaller than the coronavirus)“, a surgical mask stopped 89% of the particles, a vacuum bag 86%, and a cotton blend t-shirt stopped 70%. Not bad.

But when they doubled up, masks improved to stopping 89% and shirts to 71%. Small relative increases.

Is social distancing like that? Six feet is like wearing a mask made from a cotton shirt? Maybe not. The gas cloud research rather than aerosol or droplet research—the six feet origin work was done in the 1930’s—hints that viruses could travel twenty-seven feet in the air.

It’s hard to not recommend something other than ‘when we hear numbers we should ask why‘ but there’s so much ambiguity that’s all we can say with confidence. As for dealing with the here and now, here’s how to gamble with the coronavirus.

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Gambling with CoVid19

Bias warning, My wife and I can work from home, my kids kinda like homeschool (but really miss their friends) and I wiped down the groceries in the garage. 

It’s always helpful to ask, has someone faced my situation before? The answer is often yes. Rory Sutherland thrives at this.

On recent podcasts from Deep Dive (#249) and Wharton Moneyball (April 1, 2020) there were two very good steps to understanding anything with uncertainty.

Wharton Moneyball takes its name from Michael Lewis’s Moneyball. That book shed light on using advanced statistics to find other ways to win baseball games, that walking to first after a full count was actually better than hitting a single to first on the first pitched ball. Moneyball thinking has extended to new areas like basketball, movies, and Jeopardy.

On Wharton Moneyball, Adi Wyner spoke with Alan Salzberg who mentioned that he’s starting looking at CoVid19 deaths rather than cases. The former takes longer to materialize in number form but is better than the former which is mostly a product of testing. It’s trading a sampling error for a time lag.

“It was what we would generally call ‘garbage data’. A confirmed case  might me it was confirmed because someone came to the hospital and was already sick.” Alan Salzberg

Ok, good so far.

We need good data (walks instead of hits) but then Alan goes too far. The virus is mostly airborne and mostly won’t bother someone if it lands on a surface someone might touch and then finds a path into their body. That’s a lot of ifs. “Is that enough,” Salzberg wonders, “It stays for a little while, but in my mind I don’t think that should be a worry. I think you should wash your hands, and I’ve been doing that and I try not to touch my face a lot. But I think being ridiculously uptight about it is kind of crazy.”

Ok, that’s fine if we had better data.

But we don’t. Instead of six feet we might heed caution and stand at least twenty-seven feet apart. What’s the R0? How long is someone infected and asymptotic?

Ok, those are good questions.

There’s a lot of unknowns here and on Deep Dive, Matt (@PlusEVAnalytics) talked through what we can do when there are so many unknowns.

Think of Tom Brady’s 2020 over-under passing line of 4,256 passing yards, or 266 yards per game. His last four years totaled; 4057, 4355, 4577, and 3554. But with Tampa Bay he’s got better receivers. And he wants to prove to everyone that he’s still got it! And he wants to do it without Belichick!! Yeah!!!

But how much do those things count for? Like how much we know about CoVid19, we don’t know. Matt gives us a guide though. Do the things we don’t know make one outcome more likely? With age, ambiguity, competition, injury and so on, the unknown makes the under much more likely.

Matt credits much of this thinking to Taleb but the concept of sports and gambling make it clear. It seems like the unknown parts of the CoVid19 pandemic tilt the outcomes in favor of what’s much worse. Good data is a necessary start but ambiguity must be considered too.

Latest book: Idea Trails, 50 ideas from blogging the last four years.

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Quarantine Education

Shane Parrish asked, “What are some of the second and subsequent order consequences of covid-19 that you foresee with 80 percent confidence?”, how things would be different from the quarantine for CoVid19. It’s a good question to ask, if students participate in home school what else will change. A running list.

  • Better chronotype matching. Morning people get to do school in the morning, night owls at night. My oldest daughter gets two extra hours of sleep and goes to math class in her pajamas.
  • Better resources. We’ve taken drawing class from Mo Willems and learned about animals from the Cincinnati Zoo and Botanical Garden staff. My kids had great teachers but online they have access to the best ones.
  • Teaching young people. Though I haven’t seen much of this yet, it’s coming. Many instructors comment that they didn’t really understand something until they taught it. This can be true for kids at home too.
  • Learning technology tools. My younger daughter dictates her homework rather than typing it which she could do whereas in school she would use a pencil. If tools shape our thinking she’s thinking in new ways.
  • Plato’s cave and school. That same younger daughter needed help with answering why we have a leap day. That led to a talk about why we have the Georgian Calendar and not one that uses a leap week. Which also applies to why we do school-school and not home-school.
  • Asynchronous communications. If the future of work requires some asynchronous skill then this quarantine has been good practice.
  • Intrinsic motivations. My kids follow a program put forth by their school but this is mostly finished before lunch and they can move onto more enjoyable things. My guess is that a long-term homeschool arrangement would break the link between learning and school and create a hub where learning is connected to school, but many other things as well.

One week down and we are doing well.

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Hand Washing Design

Update, April 25, 2020: The Behavioral Insights team researched which infographics communicated the best

John Gruber posted at Daring Fireball that when he washes his hands, he turns the water off and feels less rushed and more likely to wash for the CDC suggested twenty seconds. “It’s very clear to me after just two days that doing so makes it far more natural to spend more time actually sudsing your hands up. When you leave the water running, it subconsciously puts you in a bit of a rush, because you know you’re wasting water.” 

Rationally whether the water runs or not shouldn’t matter. The most important thing (mid-March 2020) is to kill the harmful viruses and bacteria people pick up during their (limited) social exposures. Though the chances are small, the consequences are the largest. However we aren’t rational and we don’t always wash our hands. 

At one teaching hospital, the best predictor of hand-washing was attending physicians. If they washed, the medical students followed. Multiple meta-analysis (meta-meta-analysis?) suggest the best option might be “multifaceted” nudges, educational materials, and bedside hand sanitizers. Another showed that performance reviews (personal wealth) and access to hand sanitizer (ease) had the strongest though-not-super-duper-strong effects. Incentives (personal health) also kept hand-washing levels high after the 2003 SARS outbreak.

What’s so interesting is that even though one path is clearly better, people need help following it. Hygiene is like diet or investments

This randomized control trial in India found a way to increase hand-washing 30X, even twelve months after the intervention. 

A study of 802 Kenyan households offers the model that makes the most sense to me for why people do anything. Those, “significant predictors of observed hand-washing behaviour: having the habit of hand-washing at particular junctures during the day, the motivated need for personal or household cleanliness, and a lack of cognitive concern about the cost of soap use.” 

Like finches, people are influenced by their environment. If we want to encourage actions like hand washing, social distancing, and factfullness we should design conditions that make those thing easy.

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Disagreeing in a Crisis

Recently on Twitter there’s been a trend of “it’s not that bad” tweets gong around. One said that half of Italy’s CoVid19 fatalities were people with three or more existing illness while people with no other illnesses existed in less than one-percent of deaths. Among the ‘maybe it’s not that bad’ list are Elon Musk, Phil Hellmuth, and Bill Gurley.

No one is saying doing nothing, but many are saying to look at the costs. Many are saying to think like economists. 

With hindsight we’ll see that someone had the right model from day one. It likely won’t be you or me. However we get to sharpen our thinking (skill) rather than be right (luck).

So, what might account for these experts in one domain to be right in this one too? 

  • Data. It could be that there’s so little good data that we face an elephant problem. The Italy statistics look like this. The China statistics look like this. One country sees a pandemic, one an outbreak. 
  • Uncertainty. Maybe I’m too confident in my projections of outcome distributions. It could be way better or way worse than I expect right now. 
  • Salience. It could be we’re all caught up against a ‘common enemy’ with nonstop news fanning the flames. 
  • Opportunity costs neglect. People tend to overemphasize the importance of what comes to mind and dismiss what else they could spend money or time on.
  • Stock data. The stock market thinks that immediate future earnings will be significantly less. Could this be a bad proxy? 
  • Outcome severity. Maybe there will be many more with ‘zero effects’ than ‘death/ruin’. If that’s the case then CoVid19 edges more towards “driving across the country” and away from “contracting Ebola.”
  • Existing immunity. The virus has already spread through many people and those that have survived are resistant to antibodies. The influence like illness data that’s coming out might suggest this. 

It could be that Musk, Gurley, and Hellmuth were wrong in their consideration of all the details. However the process of considering why is right. Our Phantom Tyler Cowen suggests we write out why the opposing side is correct. 

There’s a lot here about arguing well and the critics of that idea say that doing is so much more difficult than discussing it. In this crisis is an opportunity.

(I use luck in the Mauboussin sense of anything out of one’s control. For example, if this were a physics problem like ‘where will planet X by at time t we would have the answer for the CoVid19 pandemic).