So, what’s the deal with chiropractors?
Are they all just full of it?
Ian Kaplan is the COO of Hybrid Performance Method (Stefi Cohen’s training company) and soon to be doctor of chiropractic, and he’s also one of the most thoughtful and skeptical people in the fitness space.
In this conversation, Ian breaks down how he thinks about uncertainty and providing treatment options when a lot of the research shows that most things that we talk about in the fitness and rehab space – well – don’t actually work.
He also lays into some of the most common issues he sees with other chiros.
Check out the full episode with Ian to learn:
- Where most chiros go wrong – and why “evidence-based” has turned into a catch-all term
- Why pain doesn’t always have a linear relationship to tissue damage in the body – and how to think about pain and appropriate treatments in an uncertain world
- The nerdy way that Ian thinks about modeling his clinical decision-making and how it relates to artificial intelligence and information theory – and the future of pain science
Check out the episode at the links below. If you enjoyed the episode, the best way to support the show is to share with your friends, so send them a link.
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Check out more from Ian and Hybrid Performance Method here:
- Website: www.hybridperformancemethod.com
- Instagram: @kaplanfitness.hybrid | @hybridperformancemethod | @steficohen
- Podcast: Hybrid Unlimited
- [01:04] Ian’s beefs with the field of chiropractic – and what it means to be “evidence-based” in a field with so much uncertainty.
- [11:50] How should someone actually think about treatment given the inherent uncertainty in dealing with complex systems? How does Ian weigh the costs and benefits of a potential treatment?
- [18:46] Why are clinicians so easy to fool: regression toward the mean and threshold effects. And, how to give patients hope without lying to them.
- [25:46] Is it better to try to treat pain with targeted tissue interventions or is it better to focus on the brain?
- [33:31] The role of artificial intelligence in developing precision medicine models for treating pain patients
- [39:51] What are the barriers to effectively analyzing treatment data from chiropractors and physical therapists?
- [44:50] A brief summary of Bayesian inference and its value for treatments, pain science and making business decisions
- [56:56] How does Ian think about Bayesian inference as a unifying principle for weird stuff we see in pain science like placebo effects and extreme pain sensitivity
- [01:07:54] How to check out more from Ian
Links and Resources Mentioned
- What’s the Difference Between a “Straight” Chiropractor and a “Mixer”? from Gutierrez Chiropractic
- Sensitivity and specificity
- Threshold effect
- Opportunity cost
- Regression toward the mean
- Bean machine
- “Arthroscopic Partial Meniscectomy versus Sham Surgery for a Degenerative Meniscal Tear” from the New England Journal of Medicine
- “Null hypothesis significance testing: A short tutorial” from F1000 Research
- Confidence interval
- “Learn About Lookalike Audiences” from Facebook
- Introduction to Bayesian networks
- Information theory
- “The Bayesian brain: the role of uncertainty in neural coding and computation” from CellPress
- Frequentist probability
- “Frequentist And Bayesian Approaches In Statistics” from Probabilistic World
- “How to take the ‘outside view’” from McKinsey
- “The Book of Why: The New Science of Cause and Effect” by Judea Pearl
- Neural network
- “To Make Sense of the Present, Brains May Predict the Future” from Quanta Magazine
- Greg Lehman