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Using Guilt to Save Energy

Question: How can we teach people to save energy?

Dan Ariely: Energy. So, let's rewind the clock for a second and think about what happened when the gas prices reached $4.00. It was incredible. It was amazing how concerned people were. In fact, I was on a radio show with somebody who bought an Escalade, you know, a Cadillac Escalade, one of these huge cars -- eight month earlier. He bought this car when the price of gasoline was $3.20, and he was back at the dealership when the price hit $4.00 to trade it in. And he bought it for $74,000, they were offering $35,000, or something like that.

Now, this is a huge loss that he was going to -- now, on that day, everybody was afraid of big cars and everybody wanted to turn them back, and nobody wanted to buy them. It was the worst time from a supply and demand perspective to sell a gas guzzler. And I said "Wait. Don't do it. It's the wrong thing." How many years will you have to drive from a financial perspective, how many years will you have to drive with this to justify it? Now, it's true that the price of gasoline increased by 80 cents since you bought the car, but it was very expensive when you bought it, and you decided to buy it. Now, just to be clear, I don't want people to drive gas guzzlers and so on, but this guy was going to lose a tremendous amount of money, not to mention he was going to buy a new car for this.

The question was, why were people so concerned? Now, I went back home and I looked at my personal finances and I discovered that the way that gasoline prices affected my personal life in terms of how much I was spending a year on it was really quite marginal compared to how much my healthcare cost has increased, but nobody seems to care. Nobody seems to be shouting over this. And even the gas, even energy prices at home, gas and electricity have gone up dramatically, but it was the pump that go people so up roared. Now why?

I think there are two reasons, one is that we all have this ideology of gas should cost $1.00 per gallon from whenever in the past. And the second thing is we see it all the time, do you even know how much a kilowatt hour is costing you? It's hard to tell because we don't see it. But you stand next to the pump, you fill it up, there's nothing else to do and you're watching these number go up.

So, two things are happening. You know how much it costs and you buy multiple units every time. Imagine the same thing would happen to bread. Last year when there was the oil crises, bread increased dramatically, my bakery basically had to put out a sign that said, "I'm sorry, but the price of wheat has increased more than 200% recently." But when we buy bread, we don't really remember how much it cost last time and we don't buy 12 loaves or 15 loaves at a time.

So, what is the lesson from this about energy consumption. I think it's about saliency. That energy consumption when something is salient is going to be very painful to us; guilt invoking and we are going to try to do things to overcome it. Energy consumption that is hidden and we don't see is not going to matter so much. So, now the question is, what do we do with electricity at home? How do we get people to think more carefully?

Now, you can imagine you can use the same metaphor. You can imagine you can get people a gauge in their home that shows them every moment how much energy they're using. You can imagine that when they are using another instrument at home, it shows them how much they could have used and how much they are using right now and how much the difference is costing them, or even worse, would cost them at retirement with compound interest.

So, linking these financial element to energy consumption I think has a huge role if you think about a display instrument that could teach us about what we are using, how much it costs us, how much it is saving, and therefore change our decisions. So, do you know how much money you would save if you changed your light bulb to compact florescent light bubs? How much would you save if you decreased your temperature of your house in the winter by one degree, or increase it by one degree? We just don't know these numbers, but I think displays could make it a memorable change in terms of attention, and also help us translate it in terms of concrete ways on what you can get.

Look, if you keep on doing this this way, you could get two days in the Bahamas next time you go on vacation.

Recorded on November 18, 2009

Behavioral Psychologist Dan Ariely has some ideas on how to get us to reduce our carbon footprints.

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Predicting PTSD symptoms becomes possible with a new test

An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.

Image source: camillo jimenez/Unsplash
Technology & Innovation
  • 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
  • Early treatment is available but there's been no way to tell who needs it.
  • Using clinical data already being collected, machine learning can identify who's at risk.

The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.

In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.

That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.

70 data points and machine learning

nurse wrapping patient's arm

Image source: Creators Collective/Unsplash

Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:

"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."

The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.

Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."

Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.

Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.

On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.

Going forward

person leaning their head on another's shoulder

Image source: Külli Kittus/Unsplash

Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."

"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.

The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.

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