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Fighting Groupthink at Universities

Question: In what ways can professorial “groupthink” be harmful?

Louis Menand:  Well, you want diversity in any intellectual organization.  I mean, that’s how good ideas arise.  They have to do battle with less-good ideas.  If, to the extent that everybody is accepting roughly the same paradigms for inquiry and there’s certain expectations about what counts as good result of your research, that’s not very good for diversity and it’s not very good for intellectual ferment, which is what you want to encourage.

I mean, universities are set up to get people to work together by having them disagree with each other.  So one of the difficulties with relative homogeneity of opinion among professors is—I happen to be of the same opinion as most professors, most professors are kind of liberal Democrats—it’s just that it discourages people from getting into the profession, which it’s very difficult to get into anyway, because they feel they’re going to be discriminated against or shunned or just not included in the conversation.  I don’t think that necessarily would be the case, but it’s discouraging to people.

Basically what you want in any profession—I would say the same thing if I were a lawyer or a doctor—is you want bright undergraduates to look at your profession as something they would be interested in getting into.  If the barriers to entry are really high and there seems to be some requirement that you tailor your views to fit the views of your colleagues, it’s going to discourage people from entering and they’ll go do something else that’s got a, you know, more reliable track to a career.

So I do worry a lot about the time it takes for people to get a PhD, about the difficulty of finding employment, about the difficulty of getting tenure, and generally about the perception that undergraduates have, that this is a very high-risk career to get started. And I don’t want people to feel that.  I want people to feel this is something that would be fun to do, and doable.

Question: How can universities become more ideologically diverse?

Louis Menand:  Well, I think, I mean, there are lots of, there are ways in which universities will never be a reflection of the general opinion of the public and they probably shouldn’t be.  It’s generally sort of sociologically observed that the better educated people are, the more liberal they tend to be, which would suggest that professors are going to be more liberal than the general public.  And I don’t think that you want to see universities in any way trying to have any kind of quota system about political views, or views in general.  You want the market to work in the way the market works.

But I think that one of the things that would make it a little bit more likely to get diversity into—I would just say to oxygenate the system that we’re working in—would be to make it a little easier to get a PhD.  Sometimes I think we should just give more PhD’s, but even if we didn’t get more PhD’s, if we just didn’t, if we didn’t make it 8 or 9 or 10 years to get a PhD, I think it would encourage people to enter who would otherwise find lots of reasons why it wasn’t a very wise thing to do.

The "Marketplace of Ideas" author suggests steps American colleges can take to become more ideologically diverse.

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A new hydrogel might be strong enough for knee replacements

Duke University researchers might have solved a half-century old problem.

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  • Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
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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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