People will believe what they want to believe.

This is one of the things I’ve learned about people this year.

[[okay, so this is isn’t the funny or happy story I promised, whoops!]]

In the hospital, if a patient even hints at needing that Dilaudid (“you know, that one med that starts with a D”), they’re automatically questioned to having drug seeking behavior. This is a subconscious action that I will admit to being guilty of despite my disdain of such reflexive thinking. Obviously Dilaudid helps the pain, it’s a strong opioid medication. There are not many people who wouldn’t feel relief. But asking for this, doesn’t make everyone a drug seeker.

The reason, I think, for such automatic judgment is two-fold.

  1. We’re busy and need algorithmic thinking. It helps streamline, simplify, and organize.
  2. We’ve all either been personally taken advantage of by drug-seekers before or heard nasty stories of this happening and would rather not be burned.

Many consequences go along with such labeling. Following providers may become even more judgmental, less attentive and less empathetic. To make matters worse, there’s an ongoing “opioid crisis” which assigns the blame to physicians who prescribe them. In reality, real people have real pain and it’s not always treatable with alternatives. Avoiding opioids like the plague can lead to under-treatment of pain and ultimately result in more harm than good.

Patients with sickle cell disease are a prime example of people who get judged despite having legitimate physiologic reasons for pain. Often times, they have been admitted many times since childhood for “pain crises” and as adults are tolerant to regular doses requiring uncomfortably large doses of opioids. On the other hand, those of us who have worked in poor socioeconomic areas also know that sometimes these patients (or their family members) abuse their access to opioid medications. (Think, The Wire) Clearly, its complicated and not always easy to trust patients to be honest but I still insist that we shouldn’t let a few bad experiences generalize the way we treat everyone who needs pain medication. But we’re busy! We don’t have time to re-evaluate every single person and situation. And this is how generalizations get made and never changed.

This backwards thinking is not only true of how we sometimes judge patients but also how we judge one another.

I think this applies to other fields as well, but residency being my first real work experience, I’ve noticed this now. People seem to hand out and acquire reputations in the work environment rather quickly. One person imposes a reputation unto another and word spreads like wild fire. Now everyone believes a person is a certain way because that’s what they have heard. Is it possible for people to change from the way they were on day #1? Of course it is! And of course they do! Then why does the initial reputation continue to follow people around? Simply because it’s easy. Why not just perpetuate a reputation and find ways to fit each person into an outdated mold? It’s like when I stopped wearing my retainers but still tried to put them on a year later after my teeth moved around. That hurt. People will view one another the way they want to view one another, the way they’ve been told to view one another. But that hurts too if an inappropriately made judgment leads to disrespect and demoralizing criticism! Unfortunately, we don’t have control over how others think. Not unless you’re a real-life mentalist. We just have to work hard and seek validation from within rather than from others’ evaluations. This means we can’t take things personally. Ideally.

We recently had a speaker at Grand Rounds who also touched on the idea that people have unwavering opinions but from the larger perspective of research and scientific discovery. He challenged the importance we place on the “p-value.” Who arbitrarily set the p-value at 5%? And why must we throw away valuable data and information just because the overall result is deemed insignificant if the p-value is greater than 5%? For those of us who have not taken a statistics class in a while, the p-value determines the chance that a result is achieved by luck rather than reality. If a study shows a finding with a p-value greater than 5%, then that is considered to be a very high chance that the results are obtained by pure luck and the results are considered invalid. The whole research study is thrown away including all of the money, effort and potentially valuable information obtained.

Apparently, people will also throw away results with a sufficient p-value if they don’t believe it. For example, this speaker told us about a valid study that demonstrated that certain medicines that bind metal ions may be protective against heart disease. Before this study, these medicines were largely considered to be voo-doo. Now, this study had just validated the voo-doo! The cardiology community was polarized. How in the world could this voo-doo truly be true? The study was well-designed, followed modern day standards and the results had acceptable p-values! Still many cardiologistis chose to reject these specific results mainly because they didn’t want to believe them. Again, there is no p-value that would be good enough for a closed mind. There is no such thing as logic or objective data that can dissuade someone when they want to believe something.

Obviously, it is not possible to re-evaluate every single thing we’re told and to confirm every belief, result or label for ourselves. Sometimes, we just have to trust what people tell us. Whether p-values should or should not continue to determine how we accept results in science is a discussion for another time. For now, my only hope is that we value one another enough to re-assess and re-evaluate a judgment made by someone else or a prior experience. Hopefully, we stop being lazy and approach one another with an open mind to avoid generalizations. These kind of judgments can have harmful and real consequences. If we stick to algorithmic thinking then what differentiates us from a computer? We owe one another more than that.

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