In the first 3 posts in this series, I described why N=1 experimentation is the only way to discover the right health and wellness program for your life, how to build individual experiments, and how to design an experimentation program over time. Thankfully, there are 2 major benefits from N=1 experimentation beyond accuracy and effectiveness, and I’m going to share those in this article: running experiments lower the resistance to change and lightens the cognitive load compared to just “making changes” in your life.

Sticking to Experiments is Easier

Lifestyle changes take effort, and before you make the change, you don’t know there will be a benefit. Your brain hasn’t gotten the dopamine hit from seeing the benefits and associated it with this new action. If you’re like the majority of people who’ve put in meaningful effort to things that haven't worked for their health, then there can be an emotional pull not to go through the stress of trying to change, especially because you might experience ‘failure’ again. Our egos don’t like to take a hit. Together, these subconscious mental processes lead many people to fail before crossing the starting line.

Thankfully, framing a new diet, sleep habit, or other change as an experiment makes starting it easier. An experiment has a set duration and doesn’t commit you to the change forever. This lowers the “activation energy” needed to give a shot to something that may not work. In my experience, most people feel like they can try almost anything for a week or two. You aren’t committing forever, and the idea of seeing if it works relieves some of the pressure if it doesn’t. You’re not necessarily the source of failure. Maybe it was the wrong fit for your body.

This also helps on the backend. If an intervention doesn’t work, then there’s no feeling bad about discarding it. It’s not giving up. If it does work, you have the positive feedback of the benefits and the subconscious perception of success to help give you a boost to keep it going.

Beyond just that specific change, using the N=1 experiment approach helps you keep up steam and make subsequent changes. When someone tries a diet and doesn’t see results, this often takes a lot of wind out of their sails. But, again, if the diet failed, rather than you failing, it’s much easier to try a new approach when you don’t feel the sting of personal failure. With this framing, even a failed intervention is a successful experiment: you found that the particular intervention isn’t the right one for you. And it’s much easier to build off of success.

Finally, running experiments can give people a frame to help protect against peer pressure. Especially with diet, exercise, and drinking less, other people will try to derail you, even if it’s coming from a subconscious place. “Come on - do you really need to eat a salad?” “Why are you being no fun?” There are many reasons people do this. Your change makes them feel bad for not doing it. What you’re trying didn’t work for them, so they don’t believe it will work for you. And on goes the list. Thankfully, in our work with clients at Fount, we’ve found that explaining what you’re doing as an experiment tends to dampen other peoples’ need to chime in on your choices with such fervor. This is especially true if the people around you see themselves as ‘into health’ or being at the cutting edge, since experimentation is an “advanced” way to approach changing your lifestyle. And once you are seeing the results, and ideally, they are too, then it’s harder for them to argue against it.

Experiments are Less Cognitively Demanding

Many people decide to make changes to their lifestyle in a moment of inspiration, whether they’re feeling especially motivated that day, heard a particularly exciting podcast, or got bad news from their doctor. But over the next couple of weeks or months, life intervenes. Work gets busy. Your relationships take priority, and it’s easy to revert to old habits or to lose track of whether you’re seeing benefits from the changes.

Amidst the hustle of everyday life, the predetermined, structured format of experiments can be a lifesaver. By outlining up-front the change you’re making, how often you’ll take actions, how long the experiment will run, and what you’re using to measure the outcome, it lightens the cognitive load in the subsequent weeks since you’ve already made these decisions. Most successful people take on more and more in their work and personal lives, so they are constantly running near capacity, so lightening cognitive load is critical to prevent overwhelm, which is a common path to failure for health and performance changes.

The experiment framework is also extremely helpful in reducing how much focus you need on progress and goals. If you decide ahead of time to keep track of how well you’re focusing or your energy levels, you are much more likely to do it. And keeping track in real time is much more effective than trying to think back across the last two weeks.  I regularly talk to clients who say they feel like the most recent interventions they’ve tried haven’t worked. But, when I ask about the goals they set at the beginning of the experiment, they’ve hit nearly all of them. Ask any coach: this is incredibly common, so it’s something we should ensure doesn’t derail our successes. Since you lay out the metrics to track success before the start of the experiment, it’s easier to take an objective look at the results, instead of how you feel about the change in a busy moment.

Finally, running experiments helps because it makes it easier to get rid of dead weight. While most of the health world is focused on recommending new interventions and new habits, one of the most effective things you can do is get rid of things that take time or energy, but aren’t serving you. By structuring your changes as experiments, you have clear metrics to say something didn’t work, so you can get rid of it and not waste your mental energy, time, or money.

Better And Easier

It’s rare that the most effective method is also the easier one. Moving from “making changes” to running experiments is one of those rare places. By investing a little time up front and leveraging the motivation in your moment of inspiration, you will make it much easier for yourself for the next weeks or months. Once you integrate the N=1 experimentation approach, I’m confident you’ll see these benefits in your own life.

In the previous post, I discussed designing individual n of 1 experiments. Here I am going to share the best approach to a broader program of experimentation, choosing which experiments to run and in what order, so it’s as easy as possible to stay motivated, keep making progress, and be efficient with time, money, and effort. At Fount, we call this optimal approach an “Experiment Journey.”

Start with Goals

The first thing you want to do when designing a new health and performance program or building on what you’re already doing is to solidly identify, or reassess, your goals. This may seem obvious, but I’ve seen many people skip over it or hurry through it. Starting with goals is key because if you don’t really care deep down about making an improvement, you are much less likely to sustain the time or effort required for progress. Goals are also critical to effectively prioritize experiments.

When I first started coaching, one of the things that surprised me was how often people find it challenging to describe their goals. This can happen for a wide range of reasons. They may feel intimidated. They may not be used to thinking about what they want. They may not be comfortable, deep down, asking for what they want. They may think they should only list things that they think are possible, even when they may not know what’s possible. There are many reasons, but I've found a relatively straightforward process you can use with friends, family, or with yourself.

The most effective question I’ve developed to get someone to describe their goals is, “If you had a magic wand and could change anything about your mind or body, what would it be?” Some will still respond very generally, saying, “I want to be healthier” or “I’m interested in longevity,” but without fail, if I suggest, “Tell me more…” and leave a long enough pause, they will start to get specific on areas of interest… although I may have to invite them to, “Tell me more…” several times.

If someone is having a lot of trouble, I will share the top 10 areas people request help in. It’s best not to start with this until you’ve explored what is top of mind for yourself because these may not be your particular goals, but if you need help, this list can be valuable. Also, if your first response is to think, “I want all of those,” you will need to put them in order of priority because if everything is a priority, nothing is really a priority.

Top Goals (not in any order):

1. Energy

2. Focus

3. Mood

4. Stress Management

5. Sleep

6. Gut health

7. Longevity/Healthspan

8. Fertility

9. Fat

10. Muscle

Through your goal setting process, whenever you have a very high-level goal (longevity; feeling better), try to at least add one or more moderately specific goals under that, since this is the level at which things start to become actionable (improving cardiovascular fitness; feeling more focused during the day). Of course, if you can get to very specific, measurable goals (running a 7-minute mile; staying in deep focus for 2 full hours Mondays, Wednesdays, and Fridays), that will help you track progress along the way.

Explore Your Options

The vast majority of people don’t spend all day thinking about health or performance. Between their busy job, family, and other demands, most people find it takes effort to stick to a new plan. You can’t do everything at once, and trying to do too many things amps up the likelihood of failure. To make it as easy as possible and to increase your odds of success, it’s key to start with things that matter to you more, where you are more likely to succeed, and that are easier to implement.  So, to figure you where to start, begin by asking yourself these questions to understand more about your goals and the interventions and experiments you are considering:

• What are my top goals? Starting with targets that matter a lot to you is important so you don’t write-off progress as trivial.

• What are you most excited about or motivated by? These may not always be the same goals you rank at the top, but excitement and motivation can carry you through as you run experiments. 

• Are there any goals where you think you can get relatively easy wins? Our brains learn very effectively. If we’re seeing success and our brains get the attendant dopamine hit, we’re more likely to keep going and be able to tackle harder challenges.

• What goal has relatively simple and easy to execute experiments you can run? The flip side of reward is stress. As stress goes up, our motivation to stick with something tends to decrease, so we are more likely to succeed with easier experiments.

• Is progress on any of the goals key to success with other goals? Are any of the goals blockers for progress in others? For example, if stress is off the charts and interfering with sleep, then progress towards stress goals may be required to improve sleep. If we ignore blockers, we won’t make progress.

As you’ll find, these don’t all line up. Sometimes the most important thing in your life is a big challenge, but some middle-of-the-pack goals have easy wins. We handle this through a concept we call “Experiment Cycles.”

Designing Experiment Cycles

Now that you have better insights into your goals and the experiments you’re considering, it’s time to design your next steps. Since you can’t do everything at once, the answer is to set up groups of experiments that give you the right mix of progress and impact. I’ve found that 2-week blocks of time with 2-4 experiments per “experiment cycle” works well for most people. It’s an amount of time where you can get the data you need for most experiments (diet changes may require longer), but not so long that it feels like you can’t keep it up. 2-4 experiments, depending on the intensity of each, gives you more than one chance of success, but you won’t be overwhelmed.

Here are considerations to consider when designing each experiment cycle:

1. No more than 1 demanding lifestyle change or experiment per cycle.

Even when you’re hyper motivated to make changes in your life, it’s best to consider that you’re in a marathon, not a sprint because sticking to changes will be key over time. So, to optimize the chance that you will be able to carry out the experiment successfully and then keep the change going if it works, keep to one major change at a time. More is rarely effective. Usually, it’s good to break down even one major change further to set yourself up for success.

For example, if you want to make changes to your diet, instead of a full overhaul, especially if you’d had trouble sticking to new plans before, you might decide to experiment with eating 1 gram of protein per pound of body weight for 2 weeks, or you might run an experiment on the effect of eating a certain amount of vegetables with every meal. In the long run, doing both of these things is probably great for you to keep muscle mass and lower inflammation, but doing one well is much better than failing at two. Only you know what your bandwidth for change is, and being realistic is highly valuable.

2. Add at least 1 “cool” experiment you’re excited about.

If this is all work and no fun, you’re much less likely to stick with it. When we work with clients, we always add at least one exciting experiment per experiment cycle. What each person finds exciting is different, but whether you’re jazzed about the latest Huberman or Attia podcast and want to try what they discussed or your friend is raving about a new supplement and you really want to try it, go with that, even if it’s not for your top goal. One of my favorites to use with my executive clients is to test the 3 supplements that seem to help focus most and see what helps someone drop into deep work:

• L-theanine can decrease stress levels, so if someone is hyperactivated mentally, this can be a big win.

• Cocoa flavanols can decrease cortisol levels, while giving a boost in energy. If someone has stress, but also needs more energy, these can be quite beneficial.

• L-tyrosine is the amino acid our bodies use to make dopamine. Increasing dopamine levels can heighten our drive and goal direction, which can increase focus.

This experiment is also great because it can give you insight into whether your focus is affected more by over-activation of your brain, under-activation, or both. Find an experiment that’s cool to you, and go with it.

3. At least 1 experiment that will be simple to carry out

A key concept from psychology that I often return to with clients is, “Confidence does not proceed action. Action proceeds confidence.” Said in another way: wins stack up, and our brains learn from success. This means it’s critical to set yourself up for some easy wins, so ensure at least one of your experiments is simple. This ensures you gain momentum to take on more challenging experiments. Supplements are usually some of the easiest experiments to run, although people may have a hard time remembering to take them mid-day. In my experience, the easiest experiment to run is a supplement experiment when the client is scheduled to take them with breakfast, dinner, or pre-bed.

4. Ideally, at least 1 that has high likelihood of success

For the same reason, pick at least one experiment where you’re likely to get a win. All completed experiments, even ones where the intervention doesn’t work, are successful, but our brains prefer to see progress towards our goals. At the end of the experiment cycle, if nothing worked, you’re more likely to drift off and not keep going into the next experiment cycle, so this is a great strategy to ensure continued progress.

By considering all 4 of these factors, you can set yourself up for the best chance of success, both for this experiment cycle and moving on into the future. 

Combination Interventions

Before moving on, I want to discuss combo interventions briefly. Often, there are many interventions you can choose from to target a goal. For gut health, you might try meditation or breathwork to tamp down stress levels affecting your gut, a variety of supplements like curcumin, magnesium compounds, and quercetin, or an elimination diet, and the list goes on. 

So, do you take each of these separately, or do you combine 2 or more of them? This is really a judgment call, but here are the tradeoffs to consider:

Speed: If you combine multiple interventions together into an experiment, you will see the results faster than if you waited to run all of them separately.

Effect Size: If you try one intervention at a time, even if it helps, it may not have a large enough effect to notice as easily, so running more than one intervention at a time may help build up the effects to where you can see benefits.

Offsetting Effects: Unfortunately, there is a major potential drawback as well. One or more of the interventions you try may help, but one or more may also hurt you. This can cancel out the benefits of whatever was working, so you may write it off and lose a very valuable tool. Or, if one tool really helps, but another moderately hurts you, you may keep both not knowing you’re keeping something unhelpful in your plan. 

Insights: Just as you can lose a tool with this method, you can also miss insights. Not recognizing that a tool helped or hurt also can rob you of the insights that tell you what to try - or avoid - next. One way to mitigate this is to only combine tools working on the same physiological or psychological pathway. This doesn’t ensure there can’t be offsetting effects, but at least you won’t have 2 pathways working at cross purposes clouding where to go next.

So, if you have the time, it’s great to run experiments 1-by-1. You can also always try things together, find a combination that works, and then run the individual pieces separately later. Of course, that doesn’t help if offsetting effects lead to the combination with a great tool showing no benefits because it was canceled out.

Evaluation & Iteration

At the end of each cycle, the last step is to evaluate the results of each experiment. Based on the data you collected along the way, you should have a sense of whether the intervention helped in a meaningful way, hurt, or didn’t have a large effect. For interventions that helped, the experiment provides you with all the inputs you need to compare the magnitude of the benefits, the importance of the goal, and the time and resources required to keep it going to get a rough ROI for the intervention. This should give you a framework for comparing different interventions and help you decide whether to keep it or discard it. For people who like to see it in algorithmic terms, here is a notional calculation for ROI (which you wouldn’t actually put numbers into):

Beyond whether to keep the intervention, the results are also key to help guide you where to go next. Until you’ve hit the particular goal, If an intervention worked, you may consider experimenting with a bigger dose (which could be the amount of time you do breathwork or literally a larger dose of a supplement) or trying a tool that hits on the same physiological pathway, such as stress, inflammation, or hormone balance, as you now know that it is relevant to your goal. If an intervention didn’t work, you can also try a bigger dose, or you may want to try a different pathway. Then, it’s time to use the same rubric above for designing experiment cycle to take these insights and craft your next cycle.

I’ve been using this approach for years, as have our Fount clients, and I can tell you it works. Looking ahead, in the final installment in this series, I’m going to share ancillary benefits that come from running n of 1 experiments, beyond just accuracy and insight.

One thing you may feel is missing from this series on running n of 1 experiments is how to figure out which interventions to try. Over the next several months, I am going to share my framework for understanding the root of the challenges you may be facing and the top interventions for each of these underlying challenges, so stay tuned for more content soon.

Even if you last encountered experiments in high school science class, designing them to improve your health and performance is a relatively simple process. In the sections below, I lay out the step-by-step process we use at Fount for designing n of 1 experiments and discuss areas of nuance that can make them more effective. Following this process will help ensure you get the most out of the time, effort, and money you put into your health. If you want a cheat sheet version of this, you’ll find it near the bottom of the article.

Core Elements

The key to designing effective experiments is to lay out what you’re going to test, how you’re going to do it practically, how you’re going to measure the results, and any safety considerations. This ensures you keep your approach consistent enough and track the data you need to have trustworthy results you can use to make decisions.

Intervention

The first step is to identify what you’re going to be testing, how to do it, and what you will need to run the experiment. You can ask these 3 questions:

What tool or technique do you want to test? Maybe a friend recently found a supplement helpful, you heard about getting sunlight exposure in the morning on the Huberman Lab podcast, or you’ve been doing research into what the best options are for optimizing focus.

How does it work? Regardless of the source, you want to ensure you know enough details to create an action plan. Sometimes, an intervention is as simple as getting sun exposure in the morning, but do you need to be outside? Can you get light through a window? Does it need to be open? You don’t want to spend a couple of weeks trying something only to discover you haven’t been doing it right and need to start again.

What resources do I need for this intervention? Some interventions may require media, like a guided meditation track, or things to buy, like glasses or supplements. Just as it’s important to know any nuances of using the tool, it’s key to understand if there are any in what you need to buy. For example, lots of people tell me they’ve already tried blue light blocking glasses to improve sleep. When I ask what color the lenses were, they often tell me they’re clear. This means that the lenses block less than 35% of blue light and won’t be very  effective in helping sleep at night (these are typically lenses for reducing eye strain). If someone intends to use blue light blockers to help sleep, they want to get lenses that block 99% or more of blue light, which means they will be orange or red.

Method

Once you’ve chosen the intervention and understand what you need for it, it’s time to lay out the details of how you’re going to put it into practice. This helps to ensure uniformity across the experiment, which is key to generating useful data. There are 3 key questions to answer here:

When will you use the tool or technique? Will you use it at a specific time of day or based on a trigger? For example, most people could take Vitamin B12 for a deficiency either at a set time in the morning or with breakfast because it doesn’t matter if you take it with food, just that you take it in the morning. However, if you’re using it to shift your circadian rhythm, you want to take it when you can get bright light exposure for the next 90 minutes to generate the strongest effects, so identifying the optimal time that also works for your schedule is key.

What dose will you use? For an action like wearing blue-light blocking glasses, the dose is how long you are going to wear them (for the 60 minutes before bed is a great starting point). For exercise, the dose might be the length of an exercise (running for 4 miles or 30 minutes) or the amount of sets, reps, and recovery time. For supplements, it’s typically how many milligrams you are taking. Especially when time’s involved, it’s important to start with a dose that doesn’t overwhelm you.

With what frequency will you use it? Are you going to be using the tool or technique daily, 4 days per week, only on weekdays, or at some other frequency? Some tools, like meditation, gain in effectiveness as you use them more, while it’s best not to use others too often or they will lose some of their benefits. For example, it’s best not to supplement daily with the amino acid L-tyrosine, which can increase dopamine levels to improve focus, because your body can become used to it over time, and it may lose its effect.

How long will you test the intervention? The longer you test the intervention, the more reliable the data will be because any one outlier day will affect the average less. Reaching the level of statistical significance used in scientific papers (p<0.05) might take a month or more, but most of us don’t need this level of certainty. Having a p value of less than 0.05 means that there is a greater than 95% chance the effects seen were due to the intervention, not random chance. I’m happy to make decisions, especially ones with small risks, if there’s a 70% or 80% chance that the effect is real, as opposed to a statistical anomaly. 

There’s also a cost to running long experiments. People are busy, and the longer it goes, the easier it is to drop off, forget to use the intervention, or for some other life event to intervene that can interfere with the data. So, find a nice balance. I recommend testing a new intervention for at least a week and ideally 2 weeks if you can. That seems to be a nice middle ground for most people, except for diet and exercise experiments which can take longer to show results.

When are you going to start the experiment? It’s critical to ensure you aren’t making other changes or running other experiments that may affect the data you’re collecting. You can run multiple experiments simultaneously if the impact of each is disparate, but otherwise you may want to run them at different times. For example, if you’re running a sleep experiment and it’s working, the better sleep may improve your focus, which could make it seem like a focus intervention is working.

Beyond other experiments, some key confounding factors are if you are traveling, sick, have a uniquely stressful time at work, are on vacation, or something else major is out of the ordinary. If one or more of these is planned or pops up during the intervention phase, you may want to remove those days from the data set, extend the data collection, or both, even if it’s annoying to extend the experiment.

Metrics

Tracking the results from the experiments is critical, but you also need to have a baseline to compare the results against. Ask yourself 2 questions to get your metrics right:

How are you going to measure the effects of the intervention? Different goals will call for different metrics, from lab testing to sleep and exercise wearables and self-report questions. While an objective measure like a lab test or wearable may feel like the most valuable, don’t underrate using how you feel as a marker. This is one of the key mistakes I see people make - there are very few interventions that make you feel consistently better over the course of a week or longer that aren’t good for you long term.Even for areas like sleep, how you feel in the morning and how you think you slept are often just as good or better than a wearable for assessing sleep quality. Of course, if you can combine objective and subjective metrics, that’s ideal. 

Regardless, the most important thing you can do is to use metrics that measure what you care about as directly as possible. I could use a cognitive psychology test to measure my sustained attention, but when evaluating new interventions for focus, I’m much more interested in how well I can get things done during the deep work blocks in my work schedule.

What will you compare the experiment results against to see if the intervention worked? For experiments, we need a control to compare against the experimental data. For n of 1 experiments, since there is no separate control group of people, you need to provide the experiment and the control data yourself. This means you want to use a control ‘period of time’ when you did not use the intervention to compare against the time when you used it. The most straightforward approach is to collect a baseline data set. If you wear a sleep wearable, you may be collecting a baseline data set in the background, so you can use the week or weeks before starting the intervention for comparison. For something like energy or focus that you probably don’t track regularly, you will want to take a period of time before starting the intervention to ask yourself the same questions and collect the same data as you will be during the intervention phase. 

This is key: you want to collect the same data in the same way at the same time during the baseline phase as during the intervention phase, or you can add noise into your data that makes it harder to accurately discern how well the intervention worked. The baseline and intervention data sets don't have to be the same length, but just like the intervention phase, you need to ensure the baseline isn’t so short that an anomalous day can throw off the results. Similarly to the experimental phase, try to capture at least a week of data in the baseline phase and 2 weeks if you can, and consider extending the baseline phase and possibly throwing out some of the data if something out-of-the-ordinary pops up, like travel, being sick, or major stresses that don’t happen regularly. 

Red Flags

Most non-prescription interventions don’t have serious side effects, but it’s worth considering any potential risks during the design process. Ask these two questions to put smart guardrails in place:

Are there any safety considerations with this intervention? It’s smart to do some research into potential safety issues before using an intervention. This is tricky because many medical sources don’t understand how non-prescription interventions work, but looking at what a variety of sources across different fields say can be helpful to find commonalities. Doing this research, you may also occasionally find that this experiment is contraindicated for you. For example, people taking psychiatric medications should be careful or avoid taking certain supplements, like neurotransmitter precursors. If you’re not sure, talk to an open minded health professional to ensure you aren’t putting yourself at serious risk.

What symptoms will tell me to stop? If there are potentially serious side effects, lay out what your red lines are before starting. If you begin a new exercise program, and you’re experiencing serious joint pain, then it’s probably smart to stop. If your muscles are sore, but joints feel fine, that’s probably not a reason to stop. Except in serious cases, this is usually a judgment call. If your stomach is off, do you keep it up for another day or two to see if that goes away? If you have a mild headache, is it worth continuing? Setting out your own guidelines beforehand can help ensure you don’t keep things going past what’s smart.

Before closing, I’ll add a note on side effects and nutrition interventions. One of the very few times when interventions make people feel much better over long periods of time but may have hidden risks are when they elevate lipid levels and cardiovascular risk. We regularly see people run experiments that lead to fantastic results, less inflammation, less stress, more energy, better sleep — and a higher ApoB level, which is a strong predictor of heart disease risk (related to your LDL-C level, your “bad cholesterol”). Some scientists argue that ApoB levels aren’t a problem without the inflammation and oxidative stress of a poor diet, but the majority of the evidence still suggests that higher levels of ApoB are a driver of increased cardiovascular risk. So, especially with diet and also supplement interventions, I recommend doing baseline and post-experiment blood testing to see how changes are affecting your lipid levels.

Optional Additions

While the above areas are core to running effective experiments, there are two additional areas you may consider adding to get extra value from your experiments. 

Mechanisms of Action

For each intervention, it can be useful to understand the physiological or psychological mechanisms of action behind how it works. This is valuable because it can help ensure you’re selecting interventions that make sense for you and because it can set you up to notice “off-target” (or unintended) effects.

For example, returning to the amino acid L-tyrosine, if you know that the body uses it to make the neurotransmitter dopamine and that dopamine is involved in motivation, then you may be more likely to make the connection if you feel a stronger drive to work out on the days you take it. Alternately, if you know that dopamine is involved in reward signaling and addiction, you would also probably be more likely to tie the supplement to behavior changes like feeling even more glued to your phone than usual.

Tracking Off-Target Effects

While you may happen to notice off-target effects, especially if you understand the intervention well, you can also choose to track potentially related areas. While trying to track too many things is a risk because you can feel overwhelmed and stop tracking anything, intentionally collecting data on related factors can help you identify unexpected effects. I regularly track the results of experiments on my sleep, even if sleep isn’t the goal. Once, when I was running an experiment with a supplement for workout recovery, I noticed that I regularly had 15-20% more deep sleep when I used it late in the day. This led to a discovery that the supplement dramatically improves sleep for about 1/3 of people. While I did feel better the next day, I don’t think I would have noticed the effect had I not been tracking my sleep.

Cheat Sheet

Here is a distillation of the questions that will set you up for an effective n of 1 experiment.

Intervention

What tool or technique do you want to test? 

How does it work in practice? 

What resources do I need for it? 

Method

When will you use the tool or technique? 

What dose will you use? 

When and with what frequency will you use it? 

How long will you test the intervention for? 

When are you going to start the experiment? 

Metrics

How are you going to measure the effects of the intervention? 

What will you compare the experimental results against to see if the intervention worked? What period of time will you use as baseline data?

Red Flags

What safety considerations are there, if any, with this intervention?

What symptoms will tell you to stop? 

What It Looks Like in Practice

You don’t need to formally write up your experiments, but here is an example of all the information described above for an experiment. 

Intervention: L-Tyrosine for Focus

Method: Take 500 mg of L-tyrosine on an empty stomach 30 minutes before starting the most important deep work block of the day for 2 weeks on Monday, Tuesday, Thursday, and Friday. 

Metrics: Answer the following questions on a 1-5 scale

• Do you notice any difference trying to start high-focus work?

• Do you notice any difference in sustaining high focus work?

Collect baseline data Monday, Tuesday, Thursday, and Friday of the prior week.

Red Flags: Do not run this experiment without talking to your doctor if you are taking psychiatric medications or have a mental health disorder.

During the experiment, if you feel serious anxiety or get a bad headache, stop the experiment.  

Reasoning

Some people find it difficult to drop into deep work. One potential cause for this is that in most modern jobs, your brain gets dopamine hits when it switches from one task to another. Unfortunately, this teaches your brain to favor task switching and makes it harder to drop into and maintain focused work sessions. One approach that can aid this is boosting background dopamine levels, which can cause the brain to see the reward in the current task and enable sustained focus. The amino acid l-tyrosine is a precursor to dopamine and can help to increase background levels. Since dopamine can also be converted to adrenaline and noradrenaline, increasing dopamine levels has also been shown to improve stress resilience in some individuals. Conversely though, it may also accentuate the stress response, potentially causing deleterious effects.

Tracking Off Target Effects: Answer these questions daily

• Do you notice any difference in how you feel overall? 

• Do you feel calmer, more excited, and/or more stressed?

• Do you notice any differences in your energy levels?

• Do you notice any differences in how you’re reacting to what would normally be stressful events?

Conclusion

The approach I’ve laid out above will help to ensure you won’t waste your time when running n of 1 experiments. You will have everything setup to collect the data that will tell you whether an intervention works and if it fits into your life. In my next 2 posts, I’m going to describe some great ancillary benefits of running n of 1 experiments and how to design a more holistic program of experimentation, what we call an Experiment Journey at Fount, to give guidance on questions like which experiments you should run first and how many you should run at a time.

Our Society’s Current Approach is Broken

Our society keeps getting sicker. There’s something wrong with our food. Our lifestyles are poisoning us. The medical system is failing, and trust in it is faltering. Most doctors only get a few hours of training on the most important areas for health, like nutrition and sleep, in all of medical school. They don't have strong incentives outside of prescribing drugs, and they’re stuck with only 5 minutes to spend with you.

Meanwhile, the most appealing messages on health are crafted to sell products, not help you. The internet is full of influencers pushing one size fits all recommendations, short-term fixes that cause long-term problems, and unrealistic ‘must do’ lists. 1000s of supplements and devices claim that they’ll cure your ills and boost your performance.

If you recognize that our current system and most doctors and influencers aren’t incentivized or don’t have the skills to help you, how can you figure out what we should do?

Key Facets of a New Approach

First, we need to recognize that people really are different, so one-size-fits-all advice fails. With no apologies to the zealous influencers from vegan to carnivore and keto, none of these work for everyone; just because something worked for you doesn’t mean it’s right for the rest of us. I see each of these approaches help some people, hurt others, and change from helping to hurting over time for still others. The best approach will vary person to person and often over time.

Second, most of the data we get today is interesting, but ultimately not useful. If your sleep wearable says your deep and REM sleep were down last night, what should you do? If you didn’t intentionally change anything the day before or do something out of the norm, then there’s not much you can take from it about how to sleep better tomorrow. Often, wearables leave you with more questions than answers and ultimately just ‘neg’ you into feeling worse when you get a low score.

There are coaches and experts who can help work through these nuances, but the irony is that unless you’re an expert yourself, it’s difficult to tell who’s good. And even when you find the ‘good ones,’ their services are typically so sought after that they don’t have available appointments or charge rates that are inaccessible to all but the wealthiest clients. I know - I used to charge $10,000/month to work 1-on-1 with clients.

But reading studies will surely show the way, right? Probably not. Very few people have the time to go deep enough in the scientific literature to rationalize the contradictory findings, sniff out the poorly run studies, figure out what to do with mouse data, and identify when scientists are spouting highly technical, but incorrect conclusions. 

Even if you do have the time and enjoy it, would you want to run your life, your company, or your marriage based on the average results of 50 other people, companies, or couples? Probably not. You want to take into account the unique attributes, preferences, advantages, and disadvantages of your specific situation. So, while studies of 50 people who aren’t you may give a sense of whether a drug, a practice, or a diet is better than a placebo on average for those people, the results do not tell you if it will work for you, let alone if it’s the best option for your body, your goals, and your lifestyle. Meanwhile, some of those tools that ‘didn’t work’ in studies were spectacularly effective, but only for a subset of the group. If something only works for 15% of the group studied, even if it works spectacularly well, it will typically show no statistically significant benefit on average, but maybe you’re like the 15%!

Prescription: N of 1 Experiments are the Key

Thankfully, there is a way out of this morass: run experiments yourself, on yourself.

When researchers describe studies, they call the number of people in a study the “n” value. An n of 50 means 50 people participated in the study (sometimes also written n=50). When you run a study just on yourself, we call this an n of 1 (or n=1) experiment. And the beauty of running n of 1 experiments is that you’re no longer hoping a doctor knows what’s right, praying you’ve found the right influencer, or betting on the average results for other people. You’re discovering what works for your unique physiology and goals. 

This approach also turns all the wearables and other testing from a novelty into something extremely useful. If you have a structured experiment, then you do know what you changed and can use your sleep wearable to assess whether you had more Deep and REM sleep this week than last. That’s now useful data.

At the same time, you are no longer stuck if you can’t find a great coach. You can test each recommendation or program, whether you hear about it from a coach or an influencer and see if it works for you. If you find someone that’s consistently recommending winners, you can start to put more trust in them, while still evaluating their next recommendations. It’s “trust, but verify” at its finest.

N of 1 experiments also help us find not only what works physiologically, but what works for our lives. If you put in the effort and still can’t fit something into your life, then it’s probably not right for you. Even the most precise physiological fit for your body doesn’t help if you don’t do it, and since there are rarely quick fixes, we need things that we can stick with for the long term.

With results on how effective an intervention is for your body and your lifestyle, you have the data to decide whether the cost-benefit ratio is favorable for you. Something takes a lot of time and effort, but only a minimal benefit? Probably not worth it. Simple, but you feel much better? Probably worth it, and you can make an educated decision about the ‘in-betweens.’ For all these reasons, n of 1 experiments are the most important health technology — and the path forward when the system around us is terminally broken.

Thankfully, n of 1 experiments are also easier to design and run than many people think. In my next several posts, I’ll cover how to structure optimal n of 1 experiments, the additional benefits they bring beyond being the most accurate and effective way to discover what works for you, and how to design a series of experiments to develop a comprehensive health and performance program tailored to you.

Welcome to the rejuvenated Fount Blog. We’ll be sending out regular content and welcome any comments, requests, or suggestions via blog@fount.bio. Follow me to learn more on Twitter at @andrewherrbio

Source: New England Journal of Medicine

5 Strategies to Thrive during the Holidays

1. The Veggie Defense

Vegetables combine anti-inflammatory polyphenols, natural fiber, and take up space in your stomach. Eat ½ a plate of them before you dive in for the heavier food and dessert, and you will tend to eat less, and the polyphenols and fiber will mitigate the other potentially pro-inflammatory ingredients' effects on your blood vessels and gut microbiome.

2. Fiber Pregame

Taking 3 grams of psyllium husk fiber 30 minutes before your meal can also take up space in your stomach and feed the good bacteria in your microbiome, mitigating the inflammatory effects. You can use this up to twice a day - make sure to mix the fiber with a large glass of water though! You can get psyllium husk fiber at any drug store. Just look for a version without a lot of additives.

3. Speaking of Water

Water can also take up room in your gut, and drinking a lot has the double benefit of helping you dilute and flush out some of the high levels of salt that tend to show up in holiday foods, which decreases the effects on blood pressure. Shoot for 3-4 liters (96-128 oz) of water per day total, and consider drinking half a liter (16 oz) before the big meal!

4. Pregame, with a Workout

When you work out, you use up some of your body’s carbohydrate reserves, make your muscles more readily take up carbohydrates and sugar, and turn down your immune system. This makes your body better able to take in, store, and use up the carbs you eat, while decreasing the inflammatory effects of huge, rich meals. Try 30+ minutes of cardio exercise before the big meal, and if you want to really take advantage, add some weightlifting as well. The carbs and sugar will cause your body to release insulin, which will actually increase your muscle gains from the lift!

5. The Mind-Body Connection

The holidays can also present unique stresses. If that’s the case for you, consider a 10-20 minute meditation before the time that’s most likely to challenge you. Not only will this lower your stress hormone levels and stress reactivity, but it will also set you up for being better able to handle big meals, since stress hormones negatively affect our metabolism and digestion! Get a double benefit by doing a walking meditation, so you get some movement in as well. Walking meditations can also be easier for some people since you don’t have to sit still. Here’s a quick 10-minute guided versionyou can check out.

From all of us on the Fount Team, we wish you a Happy Thanksgiving! Hopefully, these tools can help you feel great throughout the holidays!

If you’re new to Fount, this article is an introduction to how we think about the health and performance world today and what we’re doing to improve it. You can learn more about the company on our website at www.fount.bio and on social at @FountBio, @AndrewHerrBio, and @TheClayMethod.

Diagnosis

Our society keeps getting sicker. There’s something wrong with our food. Our lifestyles are poisoning us. The medical system is failing, and trust in it is faltering. People just want to know what to eat, take, and do to live, feel, and perform like they want, but they don’t know where to turn. 

Most doctors only get a few hours of training on the most important areas for health, like nutrition and sleep, in all of medical school. They don't have strong incentives outside of prescribing drugs, and they’re stuck with only 5 minutes to spend with you. So, it’s no surprise that they push drugs or give you 10-second advice so generic it's useless. Even they hate what medicine has become!

Meanwhile, the most appealing messages on health are crafted to sell products, not help people. The internet is full of one size fits all recommendations, short-term fixes that cause long-term problems, and unrealistic ‘must do’ lists. 1000s of supplements and devices claim that they’ll cure your ills and boost your performance.

When we look at the state of society, it’s clear that the current products, information, and tools are not working. Why?

First, people really are different, so one-size-fits-all advice fails. With no apologies to the zealous influencers from vegan to carnivore and keto, none of these work for everyone; just because something worked for you doesn’t mean it is right for rest of us. I see each of these approaches help some people, hurt others, and change from helping to hurting over time for still others. The best approach will vary person to person and over time for each person. 

Second, despite this, most influencers stick to one size fits all because the best sales tactic is to become a guru and tell your followers that you have found the answer! This is much easier than being nuanced. It’s also difficult to convey enough nuance through short-form content to give your followers tools to figure it out themselves. And even if they could convey it, most influencers don’t have this knowledge themselves, so it’s no surprise that most of the health content we consume isn’t very helpful!

And third, most of the data we have today, at least in the way we receive it, is interesting, but ultimately not useful. If your sleep wearable says your deep and REM sleep were down last night, what should you do? If you didn’t intentionally change anything the day before or do something out of the norm, then there’s not much you can take from it about how to sleep better tomorrow. Often, wearables leave you with more questions than answers and ultimately just ‘neg’ people into feeling worse than they really are when they get a low score.

There are coaches and experts who can help work through these nuances, but the irony is that unless you’re an expert yourself, it’s difficult to tell who’s a charlatan. And even when you find the ‘good ones,’ their services are typically so sought after that they don’t have available appointments or charge rates that are inaccessible to all but the wealthiest clients.

But reading studies will surely show the way, right? Probably not. Very few people have the time to go deep enough in the scientific literature to handle the contradictory findings, sniff out the poorly run studies, figure out what to do with mouse data, and identify when scientists are spouting highly technical, but incorrect conclusions. 

Even if you do have the time and enjoy it, would you want to run your life, your company, or your marriage based on the average results of 50 other people, companies, or couples? Probably not. You want to take into account the unique attributes, preferences, advantages, and disadvantages of your specific situation. So, while studies of 50 people who aren’t you may give a sense of whether a drug, a practice, or a diet is better than a placebo on average for those people, the results do not tell you if it will work for you, let alone if it’s the best option for your body, your goals, and your lifestyle. Meanwhile, some of those tools that ‘didn’t work’ in studies were spectacularly effective, but only for a subset of the group. If something only works for 15% of the group studied, even if it works spectacularly well, it will typically show a negative result on average, but maybe you’re like the 15%!

Prescription

Thankfully, there is a way out of this morass: run experiments yourself, on yourself.

When researchers describe studies, they call the number of people in a study the “n” value. N=50 means 50 people participated in the study. When you run a study just on yourself, we call this an n=1 experiment. And the beauty of running n=1 experiments is that you’re no longer hoping a doctor knows what’s right, praying you’ve found the right influencer, or betting on the average results for other people. You’re seeing what works for you.

Today this is difficult to do today because it’s hard to know what to try at all and especially what to try first. It’s also inconvenient to run and track the results of experiments, but thankfully, these are solvable with curated knowledge and technology.

Validated protocols are the first piece. We’ve spent the last 4 years working 1-on-1 with clients to understand what goals people truly care about and assess protocols to find the ones people can run without disrupting their lives and that help a meaningful proportion of people. Based on this work, we have a curated repository of 100s of “high-ROI” protocols across nutrition, supplements, meditation, breathwork, sleep, light, temperature, exercise, recovery, and mindset, each with all the information you need to run it. No individual protocol works for everyone, but each protocol we validate has a good enough chance it will work if targeted properly, with a large enough benefit when it does, that the amount of effort required to run the experiment is worth it. And somewhere within our repository of protocols are the ones that will help you.

Targeting is the second piece. People need to know which protocols to run first and where to go from there, or many will get discouraged and derailed. We’ve gathered data to understand what protocols are most likely to work for you based on whatever data you bring, whether it’s blood work, wearables, interviews, self-report data, or all of these. There is a lot more work to do in this area, but we can already give you a great place to start and help you know where to go from there. And the beauty of better targeting experiments is that you get results faster. Most people talk about the benefits of personalized health in terms of better outcomes, but faster may be more important. People are busy and have limited attention spans, especially for things that don’t work. If we can help them see progress faster, this has huge implications for compliance and long-term benefits.

The third piece is making it easier to run, track, and analyze n=1 experiments. We have built a system that makes running experiments as easy as interacting with your task list or schedule. We’ve tied this directly into a system designed to collect data, ranging from sleep wearables to the weather outside to how you’re feeling, in as effortless and simple a way as possible, and the analysis layer is automated and easy to understand.

Thankfully, all three parts of this are right around the corner in the new Fount app and services we’re getting ready to launch. We’ve purpose-built it all to make it easy to run n=1 experiments, collect and analyze data, and to know where to go next, so you can feel better quickly.

Building an Operating System

N=1 experimentation based on well targeted, validated protocols with simple data collection and analysis is the cornerstone of an operating system to optimize longevity and performance. This is the vision for what we’re building at Fount. And it’s not just our team working towards this. Our customers are helping build it with us: their experiments are helping to train the algorithms that will make this operating system increasingly scalable, so millions of people can finally get access to real answers about what will help, quickly, without expensive coaches. We want everyone who can afford a couple of streaming services to have access to what currently requires an expert coach and thousands of dollars a month.

Our mission at Fount is to amplify human potential so people can build a better future for themselves, their families, their communities, and the world. Building the operating system to democratize n=1 experimentation is the path to get there. We’re early in the journey, but our path forward is clear. Thank you for joining us in our quest.

// Thanks to Clayton Kim for comments & suggestions.