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'No' means 'not yet': How to survive professional disappointment

What do you do when "gatekeeper" bosses say no to your great ideas? You go back and pitch them again, says Beth Comstock, former Vice Chair of GE.

Beth Comstock: Yes, so “‘no’ equals ‘not yet’” is one of my kind of favorite mantras and a mental hack that was very helpful to me.

I think early in my career I—like many people—worked for a classic “gatekeeper” boss and he “had all the answers,” and the team got quite frustrated.

We thought we had a different way, different ideas to keep us contemporary and move forward, and he said no. I ended up leaving that job because I thought the gatekeeper was standing in my way. And what I came to realize is that gatekeepers exist everywhere. They’re probably even in our own head sometimes, where we just say we can’t do it.

And so out of that experience I realized there were a lot of ways I could have kept going back and trying a different approach with the gatekeeper. And I learned that with other gatekeepers and that “no” is “not yet”. So just because you hear no the first time, it doesn’t mean no is final.

And I can’t tell you how many people I’ve seen in the course of my career – I’m talking people just starting out which may be a little bit more understandable because you don’t know yet—all the way up to CEOs. When they hear no from whatever person they’re pitching an idea to they leave and you never see them again with that idea.

And you think well, you had all this passion. You had all this insight. Someone told you no and you just let it dissipate? It’s gone?

So to me I had to learn like “no” perhaps is an invitation. An invitation to come back again to try it. I had a three time rule that I would often use with different bosses I had where I felt like I needed at least three times to go back with the idea. What I learned is two things. One is I’m testing the idea myself: I’m trying to like put the right words together. Sometimes it’s just the words are wrong; The story is not there; I’m not being clear.

And I think if it’s the manager or someone is coming to you, you’re testing their passion for it. You’re testing how good an idea they think it is, because if somebody’s pitching you an idea but they’re not that excited about it you’re counting on them to go forward. So I think this idea of “no is not yet” is a resiliency test. It’s a way to say “how much do you care about that idea, how much do you want it to happen?” And it’s a sign of commitment to the idea.

Disappointment is an inevitable part of making change, of pushing for innovation and I think we have this fantasy that we buy in that you just pitch a brilliant idea, you’re just so fantastic, fantastically suited for it. You just go forth and the idea gets green-lit and off you go.

The reality is just because you’re well liked, your boss likes you, your team likes you, you’ve had a good track record doesn’t mean people are going to give you blind trust that the next idea is good. People want to know: what are you prepared to do to work for it? And I’ve found certainly in myself and in people I’ve worked with that often it’s those “try again” moments where you didn’t quite get off the right foot in pitching the idea or maybe you did a test of it and it didn’t work. And it’s when you come back and say, “I tried this and it didn’t work. Here, I’m disappointed. Here’s what I propose to do about it.” So I think a lot of this kind of resiliency building is a test of how do you deal with the disappointment? And I think disappointment is something you have to accept as part of the change-making process.

I have a little belief for myself that there’s a time to be disappointed. “I’m really sad that that idea didn’t get bought. In a sense I couldn’t sell it. People didn’t like, they didn’t understand what I was saying. Am I crazy? Do I not communicate? And I’m upset. I’m upset.”

And so I think you have to give yourself a little bit of time to kind of suck your thumb and say, “Ugh, I didn’t do as well as I wanted.” But then go, “Do I still believe in it? Is it still a good idea? How do I take that feedback? And now, I’ll go back and address some of those issues if they’re relevant.”

And use that disappointment as a bit again of that kind of push, a kick in the butt to get out there. So just because you have a good track record doesn’t mean you’re going to be successful the next time. And use that disappointment to be a bit of rocket fuel for yourself. Learn from it, but also say “Hey, do I still want to do this?” So that’s how I think about disappointment and kind of using it as resiliency.

What do you do when "gatekeeper" bosses say no to your great ideas? You go back and pitch them again, says Beth Comstock, former Vice Chair of GE. She learned that it doesn't matter how great your track record is - you can still hear a "no" to your proposal. But what's important is whether you have the passion and the resilience to get back out there and keep pursuing your idea until it's implemented.

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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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