N=1: Running an Experiment on Myself
Ask Better Questions. Respond Differently.
Do Hard Things. Believe. Have Fun.
There is no proof what I am doing for my MS will work. For me or for you.
That doesn't mean it won't work. Research proof is a slow, tricky thing to get. After $1 million of "proven" medical solutions didn't keep me out of a wheelchair, I decided that for me, the risk and cost of trying unproven things was acceptable.
MS is full of things that might happen. I might progress, I might not. A med might work. It might not.
I was curious what might happen if I did difficult, unproven things with a plausible mechanism for a long time. Things a doctor couldn't reasonably ask me to do. Things like diet, movement, and mindset work.
While I often follow the less-travelled health care road, I'm not smarter than my doctors or the researchers supporting them. They have a long list of insurance, medical proof, licensure, and other rules to follow. I'm just willing and able to work outside that box. If I get a bloody nose out of doing so, it's on me.
A physician can't reasonably ask a patient to sustain a demanding dietary protocol for nine years on the basis of plausible mechanism and mouse model data. A patient can reasonably refuse — and most will. I was willing to be the person who tried it anyway — not because I had proof it would work, but because I didn't have better options and I was willing to take the risk.
It helps that I have a research background — I was once bitten by an actual lab rat.
Most of my research was market and business research: running a research company, teaching research methods at the university level. Not medical, but a lot of the underlying structure transfers. That background has shaped how I think about the gap between what MS research can currently tell us and what I actually need to know to get better.
The gap is real, and it isn't anyone's fault.
I know large-scale MS research is expensive, slow, and structurally biased toward interventions that have funding behind them. Pharmaceutical companies can justify the cost of a clinical trial because there's a product at the end of it. Nobody is funding a ten-year study on whether broccoli and fermented foods move the needle on MS disability — not because it's a bad question, but because the money isn't there. Diet compliance is hard to track, individual variation is enormous, and the timeline for meaningful results in a progressive disease can stretch into years or decades. These aren't failures of science. They're the predictable constraints of how research actually gets done.
Definitive research also requires that nobody knows who is getting the experimental treatment and who isn't - not the doctor, not the patient. These "double-blind" research studies eliminate the possibility of "expectation bias" and "placebo effect" results. It turns out if someone believes a treatment will or won't work, they are usually right.
But the intiguing thing about placebos is they often work. I wanted to find out if the "placebo effect" wasn't a research bug, but a feature. If I believe a treatment will work and it does, that is all goodness for me. Belief is powerful medicine and I need all the help I can get. If the result is more mobility and less pain, I'm happy.
I am also willing to play MS like a game and have fun. I've already seen some pretty severe consequences. Five years in a wheelchair. Four months unable to speak. Extreme pain. Loss of career and marriage. After living through those things -- and still thriving -- they are far less scary than they once seemed. Eventually I started to feel like I had more to gain than lose. If I try and fail, at least I tried. If I had fun doing it, all the better.
That's the essence of what I call my N=1 research. I am the researcher and the research population putting the one into the N=1. I'm running the experiments on myself.
Ask better questions. Respond differently. Do hard things. Believe. Have fun.
I've been called a "mad scientist". I may also be the kid jumping off a bridge your mom warned you about. I'm willing to risk getting splattered on the rocks below.
The limitations of that are real and I don't pretend otherwise. I have no control group. I can't isolate which of the ten things I changed simultaneously actually drove the improvement — and honestly, I don't need to. My goal was never to produce generalizable proof. My goal was to get better. If I tried ten things and one of them worked, it doesn't matter that I can't identify which one. The result is the result.
What I can do is log it. Document what I did, when I did it, what changed, and what didn't. That makes me an anecdotal data point — which is a limited thing, but not a worthless one. If my path proves useful to someone else, they can cherry-pick what fits. If I end up as a cautionary tale, that's useful information too.
I hope it's useful info and fun to watch.
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