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A Professor and His Blog

Question: How did you get started as a blogger?

Jay Rosen: Well, I’ve been interested in writing online for some time. I was an early participant in [Salon’s] Table Talk, which was, there are 4 on the section, in ’96, ‘97 because I just thought it was interesting that the readers could be published in the same space as the writers. That idea was intoxicating to me. And then I spent some time at Howard Rheingold’s site, Mindstorms, because I wanted to check out a different environment for writing online. But I didn’t know anything about blogging because both those sites were produced by people who [cut a new quote]. I didn’t really know about blogging until a student in one of my classes in 2002 told me about it. And he said, ‘Professor Rosen, this is really up your alley,” and he described his blog, which was an opinion blog. He was a conservative undergraduate at NYU, obviously a minority. But he found in his opinion blog a way to make connections and have a voice. Right? And he started telling me sort of how the blogging system worked, and I remember he said if you get a link from a big blog, you can get lots of readers. So I said, “Well, how many?” And he said, “Five, ten thousand,” and I found this staggering, because the leading quarterly journals in my scholarly field, if that, that kind of writer I was, I wanted to be, are, like, 3,000, 4,000 readers, right? And he’s already telling me that his opinion blog can get 5 or 10 overnight. So I didn’t really understand what a blog was, but I was very [interested in what] he was telling me, so he told me to go check out his blog in Instapundit.com. So I was very intrigued about what he had told me, and I started walking back to my office. By the time I got close to my office, I was closer to running, ‘cause I just had this sense that I wanted to know what it was. And I remember logging in and looking at Instapundit. I didn’t understand what it was because I was looking at the surface of the blog without understanding the [blogger’s sphere] behind it, but once I did, everything that I had been kind of wrestling with since Table Talk and Mindstorms, I realized it’s here. This is the thing. Self publishing is here. That’s a long revolution, self publishing. That’s a 300 year event, to the point where the capital required to be a publisher has gone down almost to zero. That’s a 300 year event, you know, like a 500 year flood? So media time, that’s like a thousand year flood. So, I took a year to study blogging, from 2002 to 2003, and the reasons I wanted to do it were about 5. The main one was I wanted to have my own magazine with no editor to help me, what a valid idea about the press and media was. I wanted to completely evade the existing editorial system, because frankly, it had kept me in a very limited state of expression for a long time. There’s only so much that I could say if I wanted to publish at Columbia Journalism a new article, if I wanted to write a op-ed for Los Angeles Times, which I did. And just the frustration with the limited range of terms and the very stunted [imaginary] of the press about itself is the main reason I wanted to have a blog which I conceived of as my own one person magazine, which is still my description of what PressThink is. So I wanted to go around the gate keepers, and I wanted to know what was happening in this field because I was pretty sure as soon as I understood the self publishing is here that was gonna have major consequences for professional journalism. So I wanted to know it. I also wanted to catch up to, as it were, where my students were, all right? And the student was a little bit ahead of the crowd, but he was definitely pointing me toward something that would connect me to my students. And I wanted a platform to address both professional journalists, who I have been talking to for a while in my earlier work, and this new class of potential journalists that I saw rising up. Also, I have a PhD. I did my dissertation on the whole idea of the public as this thing. [I’m] the receiving end of the press. That was what my research was about. So when I said this is a 300 year event, it comes out of that, because what blogging means is that the self publishing public is real. You know, A.J. Liebling said, “Freedom of the press belongs to those who owned one.” Well, what I said was, blogging means anyone can own one. That was exciting. That was something I had to be in on, and I knew, by the end of that afternoon, I would have to have a blog.

Recorded on: 08/19/2008

Jay Rosen talks about how we first started blogging.

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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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