Study: Subclinical Doses of Lithium Have Plenty of Effects

Drugs have effects. Take more of a drug, and you’ll get more and bigger effects. They call this a dose-response relationship — take some dose, get some response. Benadryl makes you drowsy, mercury gives you hallucinations, cyanide kills you. 

But these effects only kick in above certain doses. At very low doses, the drug has no effects. This always has to be true, because at zero dose, the drug can’t have any effects. 

Then at some dose, the effect starts kicking in. Sometimes this means you start feeling it a little and it gets stronger over time. Other times, it means the response rate increases, and more people start feeling the effect as they take bigger doses.

At some point, the effect is as strong as it can possibly get and it doesn’t get any stronger. Everyone who is going to have a reaction is getting the strongest effect they can get.

Dose-response relationships can be described with dose-response curves, like this one: 

Often these curves make the most sense on a log scale (probably because this is bounded exponential growth; it’s exponential but eventually everyone who is going to have the effect already has it), so for this exercise, we’ll be portraying the x-axis on a log scale. This may not be true for all drugs, but it’s a reasonable starting place.

Lithium is a metal that is also a drug that sometimes causes weight gain. But no one really knows what the dose-response curve for weight gain on lithium looks like. Weight gain is clearly a side effect of clinical doses of lithium (about 50-300 mg of elemental lithium a day), at least for some people. But almost no one has studied lithium doses below 50 mg a day, so we don’t know at what point this weight gain effect starts kicking in.

The dose-response curve could look like this, where weight gain doesn’t show up until you hit therapeutic doses of 100 mg/day and more:

The y-axis is 0 to 40 lbs, this is arbitrary, graphs are for illustration purposes, not real data, etc.

Or it could look like this, where effects kick in starting at subclinical doses of as low as 1 mg/day:

Or it could even look like this, where weight gain starts at trace doses of less than 1 mg/day, and once you’re getting 10 mg/day, you’re maxed out:

The curve could be spread out, with gradual effects increasing across all plausible doses:

Or it could be incredibly abrupt, where weight gain happens suddenly once you’ve passed a certain threshold: 

There’s also good reason to believe the dose-response curve will be different for different people. The response may be different in terms of the shape of the curve, when the effects kick in, and when they max out. 

By ancient tradition, we will call our example patients “Alice” and “Bob”. In this hypothetical, Bob starts seeing weight gain as he approaches 1 mg/day and has already gained almost 40 lbs at 10 mg/day, but Alice doesn’t get the same effects until noticeably higher doses: 

It might also be different in terms of the maximum effect. In this next example, not only does Alice not start gaining weight until 10 mg/kg, she caps out her weight gain at just over 20 lbs, while Bob gains 40 lbs on a similar dose:

Psychiatric doses of lithium are in the 50-300 mg range (elemental), and some people think this means that weight gain must happen in this range. But this may not be the case. 

First of all, there’s plenty of evidence suggesting that the psychiatric effects of lithium kick in at trace doses of less than 1 mg/day. The effects may not be very strong at trace doses, but you can still pick them out in a population-level analysis. In fact, there’s a whole dang literature finding that rates of dementia, suicide, homicide, and other “behavioral outcomes” are associated with trace lithium levels in drinking water. This suggests that some effects kick in at very small doses.

But regardless of whether or not trace amounts of lithium lower the suicide rate, the fact is that lithium has several different effects, and there’s no reason those effects can’t kick in at different doses. It might look something like this:

In this case the y-axis is in percent, not lbs, since you can’t have pounds brain fog.

(To be clear, all these curves are completely made up for the purposes of illustration.)

This should probably be our default assumption. Most drugs have multiple effects, and different effects often kick in at different doses. For example, alcohol is a drug that makes you talkative at low doses and makes you puke your guts out at high doses.

(Your mileage may vary. Adam Mastroianni, who reviewed this piece, says, “Not me, I puke a tiny amount at tiny doses, increasing to a massive amount of puke at large doses.”) 

dose-response figure showing different effects

In fact, we know that lithium has effects that kick in at different doses, because therapeutic effects tend to kick in well before patients die from lithium toxicity, and death is also an effect.

It’s true that some people don’t gain weight at all, even on clinical doses of more than 1000 mg/day. But this might just mean that in their case, the dose-response curve for weight gain is above the dose-response curve for toxicity/death. You can’t get there without dying, so we never see it. (And for some people, the mechanism by which lithium causes weight gain probably just doesn’t work at all.)

In any case, we have almost no information about what the curves might look like for lithium, because there’s very little research on doses below the low end of the clinical range (around 50 mg/day). There’s that literature on trace doses in drinking water which we mentioned above, and there’s one RCT from the ‘90s finding that trace doses of lithium made violent offenders friendlier and happier — but as far as we know, there’s never been any formal study on doses in the range of 1-50 mg/day. If anyone has studied weight gain on lithium doses below 50 mg/day, we’ve certainly never seen it.

So let’s see what we can do to figure out anything at all about the dose-response curve for the weight gain effects of lithium — and, maybe more interesting, the effects of lithium in general. Do any of these curves start showing up at subclinical doses?

Nootropics Survey

One thing that’s interesting, in terms of our bigger “is lithium exposure causing the obesity epidemic?” question, is that most of the side effects of lithium are non-specific — if you feel nauseous and tired, it could be lithium exposure, but it could equally be a million other things. That makes it hard to tell if symptoms of lithium exposure have increased over the past 50 years, since no one has been tracking brain fog rates since 1970. If the rate of increased thirst has dectupled, we might not even know (unless…).  

But one thing people do track is hypothyroidism. Clinical doses of lithium, at least, can lead to hypothyroidism, and even mild thyroid dysfunction is linked to changes in body weight. And while the evidence isn’t anywhere near conclusive, some studies suggest that the rate of hypothyroidism has increased — see for example this popular press article, this analysis of hypothyroidism in the UK, and this study of a population in Scotland. Since clinical doses can cause thyroid problems, increasing rates of hypothyroidism make it slightly more plausible that trace lithium exposure (which has clearly increased) has subclinical effects.

Some of the effects we’re going to study — like fatigue, depression, and muscle weakness — are also symptoms of hypothyroidism. These are also nonspecific, but if they were to increase, they might be diagnosed as hypothyroidism. We’re curious to see if they increase on low, subclinical doses. 

We worked with Troof (a science blogger who has recently been studying nootropics) to put together a survey (a PDF version is available on the OSF) asking nootropics enthusiasts about the doses of lithium they have tried, if any, and the effects they experienced on each dose. (In case you’re not familiar, here’s the Wikipedia page for nootropics.)

The survey was pretty straightforward. First, we asked people for their basic demographic information. Then, we asked them to describe their previous experience with lithium. 

We allowed people to record information for up to five different doses of lithium — different in either being different amounts (e.g. 1 mg/day vs 5 mg/day), different compounds (e.g. lithium as lithium orotate vs. as lithium carbonate), or both. 

For each dose, we asked people to tell us what compound they took, how much they took per day, and approximately how many days they tried the dose for. 

We also asked them what effects they experienced on each dose. Our list of effects was based on this page from Mayo Clinic, though our list did not include all the effects mentioned on this page.  

We make no claims that our list is any sort of principled selection — it’s just a subset of effects we decided to include. There were too many to include all of them, so we made some calls. 

In particular, we focused on “milder” side effects, since we knew that the nootropics folks would be on lower doses than a clinical population and would probably not experience the more severe effects. We also combined some effects to avoid redundancy — for example, we combined multiple effects related to passing gas into the single effect “flatulence” on our list. 

We do regret cutting “fruit-like breath odor” and “eyeballs bulge out of the eye sockets”. Now those are side effects.

In any case, the final list was: 

  • Increased clarity / focus  
  • Increased calm  
  • Improved mood  
  • Improved sleep  
  • Trouble sleeping  
  • Weight gain
  • Weight loss
  • Confusion, poor memory, or lack of awareness
  • Fainting
  • Fast, pounding, or irregular heartbeat or pulse
  • Frequent urination  
  • Increased thirst  
  • Slow heartbeat
  • Stiffness of the arms or legs  
  • Troubled breathing (especially during hard work or exercise) 
  • Unusual tiredness or weakness  
  • Brain fog  
  • Dizziness  
  • Eye pain  
  • Headache  
  • Vision problems  
  • Depression  
  • Diarrhea  
  • Drowsiness  
  • Lack of coordination  
  • Loss of appetite  
  • Muscle weakness  
  • Fatigue  
  • Nausea  
  • Ringing in the ears  
  • Slurred speech  
  • Trembling (severe)  
  • Bloating or indigestion  
  • Flatulence  
  • Decreased libido  
  • Loss in sexual ability, desire, drive, or performance  
  • Tooth pain

We also included an option for “other”.

Finally, because we are especially interested in weight changes, we also asked for each dose, “If you lost / gained weight, what was approximately the magnitude of the loss / gain”, with answers in kilograms. 

Recruitment

Nootropics enthusiasts often take small amounts of lithium, usually because they believe it has a variety of beneficial effects at low doses, effects including balanced mood and reduced stress. So recruiting from the nootropics subreddit seemed like a good way to find people who already have experience with subclinical doses.

We put out the survey on r/Nootropics, in a post titled, “We’re Collecting People’s Experiences with Lithium. All Results and Data Will Be Posted Publicly. If You Have Experience with Lithium, Please Contribute!” This was our only recruitment strategy and, as far as we know, all responses came from people on r/Nootropics. 

A total of 40 people filled out the survey, providing data on at least one regimented dose (an amount taken daily for a period of time) of lithium. Of these, 20 people also reported on a second dose, 5 reported on a third dose, 2 reported on a fourth dose, and one person reported on a fifth dose. From this we can see that of the respondents, 50% have tried at least two different doses of lithium at some point.

For now, we will ignore that some of these doses are the same people, and just treat these as 68 different individual doses. Going back and doing more complex modeling at some point would be a good idea, we encourage that, but it’s not the focus of the post today. To keep it clear, we will call these “cases”. There are 40 people who gave us 68 cases.

Two people don’t report how much they were taking for their second dose, however, so we will be ignoring these cases. In the end we have 66 cases.

This is all self-report, and we haven’t been at all strict about kicking people out. In fact, we didn’t kick anyone out. Some of the data do look a little strange. One person reported taking 5 mg/day of lithium carbonate, which seems unlikely. But we’re taking the data at face value for now. 

Doses

First of all, we want to see how much elemental lithium everyone is taking. 

Many people reported a single number for their daily lithium dose, but some people reported a range, e.g. “5mg-20mg”. To convert this into a single number for analysis, whenever a person gave a range of values, we went with the average of the range endpoints. In this example, a report of “5mg-20mg” would be converted to 12.5 mg.

Different lithium compounds contain different amounts of elemental lithium. This is the “active ingredient”, so to speak. We did our best to estimate elemental lithium from the numbers people reported. In most cases, this was pretty straightforward. Lithium carbonate is prescribed by the weight of the compound, and the elemental dose is 18.8% of the weight of the listed dose. Lithium orotate usually lists elemental lithium on the packaging, and so most of the time, no conversion is needed.

However, we did have to guess on a few. For example, one person said that they were taking lithium orotate, but said they were taking 130 mg per day. Based on what we know about lithium orotate doses available on the market (see e.g. here), we think 130 mg elemental is very unlikely — this is probably 5 mg elemental, so we coded it as 5 mg. For all these conversions, you should be able to double-check our numbers in the raw data (available on the OSF). 

Having made these conversions, we find that people were taking doses between 0.25 and 282 mg per day elemental lithium, over spans ranging from 1 day to 4 years. We use dose per day because it’s easy to track. Here’s the distribution: 

As you can see, most people were taking less than 50 mg/day. In fact, most were taking less than 25 mg/day. The median daily dose in this sample is 10 mg/day, the mean is 39.6 mg/day, and the mode (15 people) is 5 mg/day. The next most popular dose after the mode is actually 1 mg/day — 6 people were trying that amount.

In comparison, the average therapeutic dose is 50-300 mg/day elemental lithium, usually delivered as lithium carbonate. So overall, these nootropics folks are taking rather small doses.

Lithium orotate was by far the most popular compound in our sample. This makes a lot of sense — lithium orotate can be purchased over the counter, or over the internet, without a prescription, and comes in relatively low elemental doses, all of which makes it an ideal nootropic. Of the 66 cases, 42 people were taking lithium orotate, 22 were taking lithium carbonate, and one each were taking lithium aspartate and “Lithium Chloride / Ionic Lithium”. 

We keep saying “doses”, but it’s important to keep in mind that from a biological point of view, these are not really doses — these are deltas, a change in the daily dose. People are already getting some small daily dose of lithium every day from their food and water, so whatever they are taking as a nootropic is a dose in addition to the dose they were already getting. We don’t currently know what kinds of doses people are getting from food and water — the literature is a little confused at points — but we’re confident that it’s more than zero.

So while we don’t know if the average American is getting 5 mg/day from their food or just 0.05 mg/day, we know they’re getting some amount — for now, let’s call the average everyday dose X. If someone is taking 5 mg/day as a nootropic, they’re not getting a total dose of 5 mg/day, they’re getting X + 5 mg/day.

Weight Change

Let’s start by looking at weight change on these low doses.

Like the doses themselves, weight change was also reported as a range in a few cases. Like the doses, whenever someone gave a range, we took the mean of that range as our point estimate value. 

Here are the weight changes people reported compared to the daily elemental dose they were taking. Note that the weight changes here are in kilograms:

That plot is a little hard to read because most people are taking low doses (< 50 mg/day) so most of the points are crammed in over on the left side. To make it easier to read, here’s the same plot with the x-axis log10 transformed (with some jitter in the x-axis to keep points from overlapping):

One caveat is that these plots include many people who didn’t actually mention any weight change at all. Since they didn’t mention it, we assumed the weight change on their dose was effectively zero. This seems like a pretty safe assumption, but just in case, here’s the same plot with only the people who explicitly said something about their weight change: 

Most people didn’t see any weight change, or at least, they didn’t report any. But 8 of the 66 cases did report some weight change. 

The first weight change reported is a loss of 3 kg, at a dose of 5 mg/day. This is a low dose, and it’s weight lost, not weight gained, which makes it something of an outlier. 

The first weight gain reported is an increase of 5 kg on 20 mg/day, which this participant reported taking for approximately 365 days. The next weight gain is 8 kg on 50 mg/day, which the person reported taking for only 60 days.

After 50 mg, weight gain seems to be more common, though certainly not universal. Of people who took more than 50 mg/day elemental, 6 of 18 reported weight gain, which is 33%. The highest weight gain reported was 35 kg (not pounds, he was quite clear) on 56.4 mg/day elemental taken as 300 mg/day lithium carbonate, over 4 years.

So, keeping the limitations of the small sample in mind, this suggests that the weight gain effects kick in around the range of 20–50 mg/day of elemental lithium, for somewhere in the ballpark of one third of people. 

The sample size is quite small, but if you squint, it does kind of look like weight gain kicks in a bit earlier for Lithium Orotate than for Lithium Carbonate. We didn’t expect this, but while we were working on this project, a reader pointed us to a small literature finding that lithium orotate is sometimes effective at a lower dose than lithium carbonate. 

This is a literature that currently seems to be driven by Anthony Pacholko and Lane Bekar, two Canadian researchers from Saskatchewan, building off of the work of Hans Nieper in the 1970s. In the interest of full disclosure, we should tell you that Wikipedia describes Nieper as “​a controversial German alternative medicine practitioner” whose therapies have “been discredited as ineffective and unsafe.” The “see also” links at the bottom of his page are “List of unproven and disproven cancer treatments” and “Quackery”. Caveat lector

In any case, there is a review by Pacholko and Bekar from 2021, which does cite many sources outside Nieper, and says in the abstract, “[lithium orotate] is proposed to cross the blood–brain barrier and enter cells more readily than [lithium carbonate], which will theoretically allow for reduced dosage requirements and ameliorated toxicity concerns”. They also have an empirical study published in 2022, which reports benefits of lithium orotate over lithium carbonate in mice.  

We’re not going to review the whole literature here, but it’s worth noting. Let’s mark it down for now as suggestive. 

Other Effects

Weight gain is not the only effect of lithium. It might not even be the most interesting effect.

The nootropics people on reddit dragged us for mostly including negative effects — which, you know what, totally fair. We should have included more positive effects. We’re interested in seeing when the bad stuff kicks in, but while we were at it, we should have looked at when everything kicked in. If we study this again, we’ll include more positive effects.

We also now realize that we should have asked for the effects on a scale (1-7, 0-3, something like that). Asking just “did you experience increased thirst or not” gives us very little information for most of these symptoms. If we study this again, we’ll use more detailed measures. 

But for now, let’s look at the data we have. And the data we have are already pretty interesting. People reported experiencing all sorts of effects:

And, to our surprise, they reported lots of these effects even on pretty low doses: 

As before, this is a little hard to read because of the squashing. Here’s the same thing with the x-axis log10 transformed:

Even below 10 mg/day elemental (a 1 on the x-axis above, since this is log10), most people are reporting a few of these effects, and some of them are reporting several. Above 10 mg/day elemental, almost everyone reports multiple effects! It’s clear that stuff starts kicking in at pretty small doses. 

Moving beyond the aggregated effects, we can ask, what effects popped up specifically? Here’s the list, with the number of cases that mentioned each effect:

  • Increased clarity / focus: 14  
  • Increased calm: 38  
  • Improved mood: 35  
  • Improved sleep: 23  
  • Trouble sleeping: 7  
  • Confusion, poor memory, or lack of awareness: 12  
  • Fainting: 0
  • Fast, pounding, or irregular heartbeat or pulse: 1
  • Frequent urination: 10  
  • Increased thirst: 11  
  • Slow heartbeat: 0
  • Stiffness of the arms or legs: 1  
  • Troubled breathing: 2  
  • Unusual tiredness: 5  
  • Brain fog: 13  
  • Dizziness: 5  
  • Eye pain: 2  
  • Headache: 3  
  • Vision problems: 1  
  • Depression: 5  
  • Diarrhea: 4  
  • Drowsiness: 5  
  • Lack of coordination: 4  
  • Loss of appetite: 5  
  • Muscle weakness: 2  
  • Fatigue: 8  
  • Nausea: 2  
  • Ringing in the ears: 3  
  • Slurred speech: 2  
  • Trembling (severe): 3  
  • Bloating or indigestion: 4  
  • Flatulence: 2  
  • Decreased libido: 10  
  • Loss in sexual ability, desire, drive, or performance: 4  
  • Tooth pain: 0

And here are the top 10:

  • Increased calm: 38  
  • Improved mood: 35  
  • Improved sleep: 23  
  • Increased clarity / focus: 14  
  • Brain fog: 13  
  • Confusion, poor memory, or lack of awareness: 12  
  • Increased thirst: 11  
  • Frequent urination: 10  
  • Decreased libido: 10  
  • Fatigue: 8  

We see that the four positive effects are the most commonly reported, which is what we would expect from a population of nootropics users who are taking lithium in search of positive effects. More than half of the cases reported “increased calm” and “improved mood”, and around a third reported “improved sleep”. On top of this, 14 reported “increased clarity / focus”. Of the 66 cases, 50 (about 75%) reported at least one of these four positive effects. 

But this also makes it especially striking that so many people reported negative effects. If anything, this population is inclined to downplay the negative effects of lithium, but negative effects were reported quite frequently.

The most commonly reported negative effect was brain fog (13), followed by “confusion, poor memory, or lack of awareness” (12). These sound like the same thing, but there wasn’t perfect overlap. We see that 7 people reported brain fog without reporting confusion, and 6 reported confusion without reporting brain fog. 

It’s pretty weird that “increased clarity / focus” is the fourth most common effect and “brain fog” and “confusion, poor memory, or lack of awareness” are effects #5 and #6. Aren’t these polar opposites? Why are they right next to each other in the rankings? Sounds like a possible paradoxical reaction.

The next most common effects were increased thirst (11) and frequent urination (10), which also seem related. 

After that, the next most common is decreased libido (10), which is supported by a less common but related effect, “loss in sexual ability, desire, drive, or performance” (4). These are both reported at rather low doses, as low as 1 mg/day.

The next most common are fatigue (8), and trouble sleeping (7), and then we get into numbers too small to go over individually. But even so, almost every symptom we put on our list was reported by at least one person — we certainly did not expect that. The only three symptoms that no one reported were fainting, slow heartbeat, and tooth pain. 

Some of these symptoms, like ringing in the ears (3), are only reported by people who were taking more than 50+ mg/day. But lots of effects start appearing at very low doses. 

C5H3LiN2O4 , his name is my name too

Like with the weight gain, there might be more effects for orotate than for carbonate at the same elemental dose. Don’t take this as conclusive — there’s not all that much evidence. But it is intriguing.

We can even do a regression looking at just the data from cases where people were taking carbonate or orotate. This brings us to a somewhat unusual finding. 

When the dose of elemental lithium is used to predict the total number of lithium effects, the regression model finds significant main effects of both dose (p = .0008) and compound (p = .021), and a significant dose-by-compound interaction (p = .0019). The total R-squared is 0.257, which is pretty good. This model suggests that lithium orotate does bring on more effects at a lower dose than lithium carbonate.

But, there is only a main effect of dose (p = .005) when dose of elemental lithium is log10 transformed. In this case, the compound (p = .899) and the interaction (p = .718) are not significant, though the R-squared is pretty similar (0.245).

This difference is pretty clear when we plot both models with their regression lines. Here’s the situation if you don’t log-transform the daily lithium dose. You can clearly see that the slopes of the two lines are very different:

But here’s the situation if you do log-transform the daily lithium dose. You can clearly see that the slopes of the two lines are nearly identical:

This is a little weird. On the one hand, that’s a pretty clear interaction in the non-transformed data. On the other hand, we would expect log transformation to be the appropriate transformation for this analysis. Make of that what you will.

Troof points out that a lot of this interaction seems to be driven by a single participant, who looks kind of unusual and is taking an unusually high dose of lithium orotate. If you look at the plots, you can see them as a somewhat clear outlier (taking the most orotate and having the most effects of anyone on that compound). So probably don’t put too much trust in this data point, and without it, the case for an interaction basically disappears.

Conclusion

These results suggest that many effects of lithium kick in at subclinical levels. In this sample, the majority of people who took at least 1 mg of elemental lithium a day reported at least one effect, and people on doses above 5 mg/day tended to report experiencing several effects. 

The most common effects people reported were the four positive effects we asked about, but several negative effects of lithium were commonly reported as well, especially brain fog, “confusion, poor memory, and lack of awareness”, increased thirst, frequent urination, decreased libido, “loss in sexual ability, desire, drive, or performance”, fatigue, and trouble sleeping. A slight majority of cases (53%) reported at least one negative effect.

Weight gain was not a common effect, but it was reported at relatively low doses. The lowest dose for reported weight gain was on a dose of 20 mg/day, and the next lowest was on 50 mg/day. The greatest reported weight gain was on a dose of only 56.4 mg/day. Taken together, this suggests that in the current environment, lithium can cause noticeable weight gain on elemental doses below 50 mg/day, and possibly as low as 20 mg/day.

Unfortunately, this does not tell us all that much about the dose-response curve. There are just too many degrees of freedom, and we don’t know that X value, the amount that people are getting from their food and water. It could be that X is well below the dose-response curve, and +50 mg/day is needed to push you onto the curve:

But it could equally be the case that X is well onto the curve — past the point of greatest sensitivity! — and a big delta like +50 mg/day is needed just to see any weight change at all. 

This evidence doesn’t rule anything in, but it does rule some things out. Given these findings, we can mostly rule out the idea that doses below 10 mg/day have no effects. We can also rule out the idea that weight gain starts kicking in at just 0.1 mg/day — it seems pretty clear that you need a bigger delta than that. But we can also mostly rule out the idea that weight gain only occurs above 600 mg/day.

So while it’s good that some things are ruled out, we still don’t know enough to pin down the dose-response curve.

At least, not for weight gain. We do see what looks like evidence of the dose-response curves for other effects.

Troof also played around with the data a bit, and sent us the following graph. The pattern is clear for some effects and rather messy for others, but we see what looks very clearly like the start of a dose-response curve for increased thirst. We also see what look like dose-response curves for improved mood, improved sleep, increased calm, and increased clarity, where rates of the effects increase and then level off. But there isn’t a clear curve for brain fog or confusion, at least not in these data. 

One weird thing we noticed is that most of these dose-response curves come down at the highest dose level, suggesting that some of these effects actually get less likely past a certain point. Not sure what’s going on there, we’re interested to hear what people think.

Human Challenge

At this point you might be wondering: should someone do a human challenge trial for low-dose lithium? You know, round up some brave souls on the internet, get them all to take 10 mg’s worth of lithium orotate every day for a month, and see what happens to them by the end. Is that a good idea?

We don’t think this is a good idea, for a couple reasons. First of all, we don’t know what X is, which means that increasing the dose by a fixed amount isn’t actually all that informative. 

Second, we’re pretty sure that X is different in different places and for different people. Combine this with the fact that different people probably have different dose-response curves for strictly genetic reasons, and the results begin seeming hopelessly complicated. 

Finally, while low-dose lithium does seem to have positive effects for many people, some of its effects are quite nasty. We wouldn’t want to subject volunteers to unnecessary brain fog and fatigue. If we were sure that the study would teach us a lot, then maybe it would be worth it, maybe we would be open to convincing people to give it a go. Maybe we would try it ourselves. But since we don’t think it would really answer any of our biggest questions, we don’t think a lithium supplementation study would be worth anyone’s while. 

However, Troof has convinced us that there are more than 40 people out there who have already tried subclinical doses of lithium, and that at least some of them will be reading this post. So we’ve put together an updated version of our survey that fixes some of the problems we mentioned above — it asks about the magnitude of each effect, includes more positive effects, and includes more effects in general. If you’ve taken lithium before, you can fill out the survey here, and if we get enough responses, we will post another analysis. If you filled out the first survey, you can fill this one out too, because this one is a little more detailed — just check the box that indicates that you took the first survey, so we can make sure not to double-count you.

Every Bug is Shallow if One of Your Readers is an Entomologist

The Cathedral and the Bazaar is an essay/book about how Linus Torvalds threw all the normal rules of software out the window when he wrote the operating system Linux

Back in the day, people “knew” that the way to write good software was to assemble an elite team of expert coders and plan things out carefully from the very beginning. But instead of doing that, Linus just started working, put his code out on the internet, and took part-time help from whoever decided to drop by. Everyone was very surprised when this approach ended up putting out a solid operating system. The success has pretty much continued without stopping — Android is based on Linux, and over 90% of servers today run a Linux OS.

Before Linux, most people thought software had to be meticulously designed and implemented by a team of specialists, who could make sure all the parts came together properly, like a cathedral. But Linus showed that software could be created by inviting everyone to show up at roughly the same time and place and just letting them do their own thing, like an open-air market, a bazaar.

Let’s consider in particular Chapter 4, Release Early, Release Often. One really weird thing Linus did was he kept putting out new versions of the software all the time, sometimes more than once a day. New versions would go out with the paint still wet, no matter how much of a mess they were.

People found this confusing. They thought putting out early versions was bad policy, “because early versions are almost by definition buggy versions and you don’t want to wear out the patience of your users.” Why the hell would you put out software if it were still crawling with bugs? Well,

Linus was behaving as though he believed something like this:

> Given a large enough beta-tester and co-developer base, almost every problem will be characterized quickly and the fix obvious to someone.

Or, less formally, “Given enough eyeballs, all bugs are shallow.” I dub this: “Linus’s Law”.

This bottom-up method benefits from two key advantages: the Delphi Effect and self-selection.

More users find more bugs because adding more users adds more different ways of stressing the program. This effect is amplified when the users are co-developers. Each one approaches the task of bug characterization with a slightly different perceptual set and analytical toolkit, a different angle on the problem. The “Delphi effect” seems to work precisely because of this variation. In the specific context of debugging, the variation also tends to reduce duplication of effort.

So adding more beta-testers may not reduce the complexity of the current “deepest” bug from the developer’s point of view, but it increases the probability that someone’s toolkit will be matched to the problem in such a way that the bug is shallow to that person.

One special feature of the Linux situation that clearly helps along the Delphi effect is the fact that the contributors for any given project are self-selected. An early respondent pointed out that contributions are received not from a random sample, but from people who are interested enough to use the software, learn about how it works, attempt to find solutions to problems they encounter, and actually produce an apparently reasonable fix. Anyone who passes all these filters is highly likely to have something useful to contribute.

Linus’s Law can be rephrased as “Debugging is parallelizable”. Although debugging requires debuggers to communicate with some coordinating developer, it doesn’t require significant coordination between debuggers. Thus it doesn’t fall prey to the same quadratic complexity and management costs that make adding developers problematic.

In practice, the theoretical loss of efficiency due to duplication of work by debuggers almost never seems to be an issue in the Linux world. One effect of a “release early and often” policy is to minimize such duplication by propagating fed-back fixes quickly.

Research is difficult because reality is complex and many things are confusing or mysterious. But with enough eyeballs, all research bugs are shallow too.

Without a huge research budget and dozens of managers, you won’t be able to coordinate a ton of researchers. But the good news is, you didn’t really want to coordinate everyone anyways. You can just open the gates and let people get to work. It works fine for software!

The best way to have troubleshooting happen is to let it happen in parallel. And the only way to make that possible is for everyone to release early and release often. If you sit on your work, you’re only robbing yourself of the debugging you could be getting for free from every interested rando in the world. 

In the course of our obesity research, we’ve talked to water treatment engineers, social psychologists, software engineers, emeritus diabetes researchers, oncologists, biologists, someone who used to run a major primate lab, multiple economists, entrepreneurs, crypto enthusiasts, physicians from California, Germany, Austria, and Australia, an MD/PhD student, a retired anthropologist, a mouse neuroscientist, and a partridge in a pear tree a guy from Scotland

Some of them contributed a little; some of them contributed a lot! Every one had a slightly different toolkit, a different angle on the problem. Bugs that were invisible to us were immediate and obvious to them, and each of them pointed out different things about the problem.

For example, in our post recruiting for the potato diet community trial, we originally said that we weren’t sure how Andrew Taylor went a year without supplementing vitamin A, and speculated that maybe there was enough in the hot sauces he was using. But u/alraban on reddit noticed that Andrew included sweet potatoes in his diet, which are high in vitamin A. We totally missed this, and hadn’t realized that sweet potatoes are high in vitamin A. But now we recommend that people either eat some sweet potato or supplement vitamin A. We wouldn’t have caught this one without alraban.

In another discussion on reddit, u/evocomp challenged us to consider the Pima, a small ethnic group in the American southwest that were about 50% obese well before 1980, totally bucking the global trend. “What’s the chance that [this] population … [is] highly sensitive and equally exposed to Lithium, PFAS, or whatever contaminants are in SPAM or white bread?” evocomp asked. This led us to discover that the Pima in fact had been exposed to abnormal levels of lithium very early on, about 50x the median American exposure in the early 1970s. Before this, lithium had been just one hypothesis among many, but evocamp’s challenge and the resulting discoveries promoted it to the point where we now think it is the best explanation for the obesity epidemic. Good thing the community is helping us debug!

My original formulation was that every problem “will be transparent to somebody”. Linus demurred that the person who understands and fixes the problem is not necessarily or even usually the person who first characterizes it. “Somebody finds the problem,” he says, “and somebody else understands it. And I’ll go on record as saying that finding it is the bigger challenge.”

This is a classic in the history of science. One person notices something weird; then, 100 years later, someone else figures out what is going on. 

Brownian motion was first described by the botanist Robert Brown in 1827. He was looking at a bit of pollen in water and was startled to see it jumping all over the place, but he couldn’t figure out why it would do that. This bug sat unsolved for almost eighty years, until Einstein came up with a statistical explanation in 1905, in one of his four Annus Mirabilis papers. Bits of pollen jumping around in a glass of water doesn’t sound very interesting or mysterious, but this was a big deal because Einstein showed that Brownian motion is consistent with what would happen if the pollen was being bombarded from all sides by tiny water molecules. This was strong evidence for the idea that all matter is made up of tiny indivisible particles, which was not yet well-established in 1905!

Or consider DNA. DNA was first isolated from pus and salmon sperm by the Swiss biologist Friedrich Miescher in 1869, but it took until the 1950s before people figured out DNA’s structure. 

Complex multi-symptom errors also tend to have multiple trace paths from surface symptoms back to the actual bug. … each developer and tester samples a semi-random set of the program’s state space when looking for the etiology of a symptom. The more subtle and complex the bug, the less likely that skill will be able to guarantee the relevance of that sample.

For simple and easily reproducible bugs, then, the accent will be on the “semi” rather than the “random”; debugging skill and intimacy with the code and its architecture will matter a lot. But for complex bugs, the accent will be on the “random”. Under these circumstances many people running traces will be much more effective than a few people running traces sequentially—even if the few have a much higher average skill level.

This is making an important point: if you want to catch a lot of bugs, a bunch of experts isn’t enough — you want as many people as possible. You do want experts, but you gain an additional level of scrutiny from having the whole fuckin’ world look at it.

Simple bugs can be caught by experts. But complex or subtle bugs are more insane. For those bugs, the number of people looking at the problem is much more important than the average skill of the readers. This is a strong particular argument for putting things on the internet and making them super enjoyable and accessible, rather than putting them in places where only experts will see them.

Not that we need any more reasons, but this is also a strong argument for publishing your research on blogs and vlogs instead of in stuffy formal journals. If you notice something weird that you can’t figure out, you should get it in front of the scientifically-inclined public as soon as possible, because one of them has the best chance of spotting whatever you have missed. Back in the day, the fastest way to get an idea in front of the scientifically-inclined public was to send a manuscript to the closest guy with a printing press, who would put it in the next journal. (Or if possible, go to a conference and give a talk about it.)

But journals today only want complete packages. If you write to them about the tiny animals you found in your spit, they aren’t going to want to publish that. Times have changed. Now the fastest way to get out your findings is to use a blog, newsletter, twitter, etc.

Job Posting: Reddit Research Czar

Job postings are a kinda weird phenomenon. For one thing, they’re very modern. It used to be that most people either inherited a job (I’m a baker because my pa was a baker and our tiny hamlet needs a baker) or noticed an opportunity and ran with it (lots of hungry travelers cross that bridge every day, I bet I could make a living selling pancakes).

We’re talking about the second thing today, the opportunity just waiting for someone to snap it up. This is a job posting, but we’re not hiring. Reddit is hiring. Well, not REDDIT. The abstract spirit of reddit is hiring. The universe is hiring. 

hmmm yes

Let us try to explain.

Czar was originally a term for East and South Slavic monarchs, most notably the Russian emperor — it’s another spelling of Tsar and yet another corruption of the Roman title Caesar, just like Kaiser. But at some point in the middle of the 20th century it became a term in the US and UK for government officials “granted broad power to address a particular issue”. The Industry Czar is in charge of industry, the Milk Czar is in charge of milk, the Asian Carp Czar is in charge of Asian Carp (no, really), and so on and so forth.

Carp Czar Gone Wild

There are lots of problems in the world; some are covered, but there are many others where existing institutions have totally dropped the ball. Often, more research would help. But the academy just doesn’t move as fast as it used to. If you’ve ever looked at something and been like, “someone should do a study”, you know what we mean.

Reddit is a bizarre, amazing place. Literally millions of people have come together to this place on the internet and self-sorted into about 3.4 million communities, called subreddits. True, many subreddits are dedicated to very niche porn or insane crypto schemes. But if you want to build a desktop gaming rig, get male or female fashion advice, or discover long, plush horrors, there’s a subreddit for that. You can learn so much about any topic or hobby, maybe too much if you’re not careful (compare). 

We’d like to apologize to the ghost of Alan Turing

This means there are lots of special populations on reddit, people who have a condition or illness, maybe a rare one, who are extreme outliers (e.g. very tall and/or live in a submarine), or who have a burning obsession with some niche idea. Subreddits bring people together, to commiserate, to try to help each other solve a problem, or to post insane fanart.

These people are all very interested in their shared topic. They are all highly motivated. Many of them are ready to self-experiment, or are already self-experimenting. A lot of things count as self-experimentation. If you’re doing a diet, or trying to get more sunlight, or even just trying to drink more water, that’s self-experimentation too. So a subreddit for a given problem or topic is a powder keg of interest and motivation, just waiting for a spark. 

Because while subreddits are very motivated, they’re largely untapped for organized research. Even in subreddits with good leadership, it’s rare for the leadership to have a research background. Most communities lack someone with the methods skills to design a good study, and the statistical analysis skills to examine the data afterwards. 

If you have these skills, and you are familiar with reddit, you could show up and start helping people organize research. You could collaborate with people to help them solve their problems, or at least learn more about their problems, and you could start doing it tomorrow. 

Redditors could never be coordinated enough to pull off something as complex as scientific research!

Crowdsourcing research like this is under-explored. Almost no one has ever done studies organized like this, so in our opinion, there’s virtually guaranteed to be low-hanging fruit all over the place. Anything that isn’t sexy enough for a major journal or doesn’t sound serious enough for the NIH to spend their time on is ripe for the picking.

The current research world is very narrow-minded. Doctors and researchers are quick to blame a person’s behavior or hygiene and very slow to blame environmental contaminants. If you’re more creative or more open-minded, and you’re willing to consider other paradigms, you can just move faster. If doctors don’t take the pathogen paradigm for chronic disease and digestive disorders seriously, then by becoming the “Pathogenic Disease Czar”, you might be able to rack up discoveries really quickly.

There’s also the question of “why now”? Part of it is that the research world has slowed down. But another part is that the rest of the world has sped up. We’re more coordinated than ever. Today you can get 100 people reading your latest newsletter in 20 minutes. Today you can pop by a subreddit and consult with thousands of people in a matter of hours. Today you can cold-email an emeritus professor who worked on the problem in the 1970s and be on a Zoom call with them next week. 

Research tools are also opening up, getting more accessible every day. If you’re leading the reddit charge on some rare glandular disorder, it now takes only a couple hundred dollars per person for everyone involved to get their genome sequenced and it’s getting cheaper all the time. If there’s a genetic explanation, or genetics is involved in some way, it’s only recently gotten cheap enough that communities might able to find it on their own.

There are lots of interesting ideas where the only support for them is a single paper with 20 participants from 1994. If you can get a couple dozen volunteers together, boom, you’ve just advanced the state of the field, and discovered whether or not there was anything to that interesting idea.

One example is our own ongoing all-potato diet study, which we see as the first of what will hopefully be a long tradition of community trials and community RCTs (randomized controlled trials). We’ve mostly recruited from twitter for the potato diet, but we just as easily could have recruited from reddit. For reference, this was the response on one subreddit, and not even a subreddit directly related to dieting.

Sometimes just planting a flag in the sand is enough. People like to feel like a part of something and are excited to participate. One participant in the potato diet said:

How do we get stronger evidence [for the potato diet]? Well someone has to go out on a limb and run an experiment. This is a particularly important motivation for me. If this were not part of a larger study, I wouldn’t spend my energy on it (after all, it probably won’t work). But the fact that it might yield useful data makes it much more appealing.

Obesity and related issues (heart disease, diabetes, etc.) is just one example of a serious problem that people are invested in solving. It seems like there are lots of problems where we might be able to quickly learn a lot by rigorous self-experimentation and community research. 

Depression and anxiety are classic unsolved problems. Sure, we have some mildly effective treatments, but why don’t we have great ones? Why does a given treatment work for some people and not others? What about people with treatment-resistant depression? Why are things like exhaustion and brain fog symptoms of depression? Where does depression come from? There’s been a lot of discussion but our take is still “no one knows” or at least, “the jury’s still out”. We see that r/depression/ has over 800,000 members and a couple thousand are usually online at a given time. If you think you could help, they seem like they would be glad to have it. 

Crohn’s disease is debilitating and remains very poorly understood — Wikipedia, for example, says, “While the precise causes of Crohn’s disease (CD) are unknown, it is believed to be caused by a combination of environmental, immune, and bacterial factors in genetically susceptible individuals. …  While Crohn’s is an immune-related disease, it does not appear to be an autoimmune disease (in that the immune system is not being triggered by the body itself). The exact underlying immune problem is not clear; however, it may be an immunodeficiency state.” Sounds like more research is needed, and r/CrohnsDisease/ has 42,000 members.

If that’s not mysterious enough for your taste, there are all the really inexplicable digestive conditions, which go by names like IBS (irritable bowel syndrome) and GERD (gastroesophageal reflux disease). These can really fuck you up, so people will be really motivated to try things and find a treatment. And there might be weird treatments out there that really work. You can drop by r/ibs/ with 74,000 members or r/GERD/ with 42,000 members and start putting out surveys, today if you want! (But talk to the mods first, don’t get kicked out for being a weirdo.)

But you won’t be the first researcher on the scene. We see that u/OrganicSquare made a post titled “Let’s use machine learning to help us find solutions to our reflux. I need this whole community to answer this survey for data!!!” on r/GERD about a year ago. We can’t find the results — maybe she’s still analyzing the data — but this is exactly the sort of thing we’re talking about. OrganicSquare, you are the hero reddit needs, let us know if you want to collaborate.

There are also some populations that will be interesting not because they are facing a problem they want to solve, but because they are special in some other way. Trans people would love to have better resources for transitioning, and you could certainly drop by to help them study that. But we think the real reason to drop by r/TransDIY/ and similar subreddits is because you have literally thousands of people conducting n = 1 endocrinology experiments.

There’s a good chance the next great endocrinologist will be trans, just because of their personal familiarity with the subject and ability to self-experiment. If you want to see what effect testosterone/estrogen/progesterone/estradiol has on mood/energy/digestion/attention/nerve growth/body temperature/whatever, this is one of your few and best chances to get experimental data. 

This is nowhere near a complete list. In fact, please drop other subreddits that might be excited to do more community research in the comments.

It’s more common than you might think

We call this a job posting because we think this could easily be a full-time job. If you help a community or two get closer to solving their problem, even if you just help them coordinate and give them HOPE that their problem is solvable, it would be pretty easy to convince lots of them to chip in. It’s hard for an individual to hire an expert, but some of these communities have tens or hundreds of thousands of members. For a community that size, hiring some full-time research muscle is easy.

You set up a Patreon or a newsletter (we recommend Ghost), and ask for support. If you can get 1000 people to give you $3 a month, that’s $36,000 a year, enough to start thinking about doing this full-time.

You don’t need to solve anything up front. You just need to convince 1000 people that you’re doing enough to justify them spending $3 a month on something they think is important, which is not a hard sell. And if you get 10,000 people on board for $1, you’re even better off. (Incidentally, here is our patreon.)

Crowdfunding is the best and noblest option, but it’s not the only route you can take. Some communities will have a millionaire or two in the ranks, and if you start doing good work, people will come out of the woodwork to help. There are lots of granting agencies out there looking for stunning projects to throw money at. Start coordinating reddit research for a few months, show that you’re serious, make a little progress, and it should be easy to make the case for some grants.

And actually, you might also be able to get funding from reddit, up to $50,000! Starting June 2022, reddit will start distributing one million dollars in community funding to different subreddits. If you can make the case to a subreddit that you can lead their community research for a year, they can apply for $40,000 to be your salary, and there’s a good chance they’ll get it. The article linked above says, “I can’t wait to see what wild project the r/WallStreetBets crew tries to get $50,000 to pull off.” Yeah holy shit.

Finally, if you are financially independent / have a good job that gives you lots of free time, then this is DEFINITELY a job suited for you. You already don’t have to worry about money; maybe you even have enough that you could pay for a statistician / the chemical analysis of samples / new air quality monitors / sundry other research expenses. You’re looking for something interesting to spend your time on, something that also makes the world a better place. If you have the skills and inclination, nothing could be a better fit!

It’s worth touching for a moment on the skills we think would be important. Any research on reddit would probably start with a lot of surveys, so someone with lots of experience with survey-based methods might have the advantage here. Possibly a sociologist or psychologist? But on the other hand, a lot of the problems reddit communities would be interested in solving are medical, so maybe someone with a medical background is the best person for the role. On the other other hand, a lot of the advantage here might be statistical, having the skill to work with big strange datasets, so maybe a data scientist.

Or form a cabal if you want:

Reddit Research Cabal

Anyways, if this is the job you want, and you think you have the skills to do it, there are two general ways to approach this…

Go Specific

If you are a person who is a member of one of these communities, who is inclined towards research and wants to rally people to solve the problem, going specific might be the approach for you.

There are a couple winning examples already, let’s take a look. These two don’t use reddit for the most part — they have communities elsewhere — but it’s not hard to imagine recreating some of their successes in a subreddit rather than on a blog or on twitter.

Scott Alexander is pretty much the research czar for rationalists, in his reader surveys (both back on SSC and now on ACX), and in some more specific work like the nootropics survey. Rationalists aren’t a community with a rare disease to cure, but they are united in their interest in specific topics, like AI, IQ, and birth order effects. And Scott, being a psychiatrist, has a special interest in things like SSRIs. We’re very interested in the small amount of work he’s done on air quality / ventilation, which we’ll note has included at least a little self-experimentation.

Whorelord and “mad social scientist” Aella is kind of de facto sex worker / sex research czar for the whole internet. She also does psychology and psychedelics research, which must be reasonably well-regarded because her twitter followers include some big names in psychology, like Paul Bloom and Uri Simonsohn (and see this interaction). But mostly it’s sex stuff, and the quality of her research puts the average social science publication to shame: 

Scott is a rationalist and Aella has lots of sex / is a (former) sex worker, so they’re perfectly positioned to be the research czars for their communities. We’d recommend that the “go narrow” approach be taken with communities you are a part of as well.

There are clear advantages to going narrow. First off, you can self-experiment. You can pilot-test studies on yourself, and you can show people that you would never ask them to do anything you aren’t willing to try first. You can specialize and learn a lot about this one area of research. And you’ll understand the topic better, because you’ve lived it.

There are also a couple of disadvantages. This has a smaller scope, but some of you might like that. It’s less exciting, and maybe harder to get support and raise money for projects. But it’s also more practical.

Go Broad

The other option is to try to become the Czar of all the Reddits.

In this approach, you try to work with lots of different subreddits, lots of different communities, and try to solve lots of different problems. Instead of focusing on just one mystery at a time, you go broad. 

If you are a generalist with good research chops, who spends a lot of time on reddit and knows how it works, who likes the idea of working with tons of different people, on dozens of projects, this might be the approach for you.

This approach has some clear advantages. If you work on more projects, you will be able to get funding from more quarters. As you try more and more things, you’ll learn a lot about the metascience of doing this new kind of community research. You can switch between projects when you’re waiting for results. If you hit a dead end on one question, you can take some time off and switch to something else. More things to work on means it’s more likely something will be a success.

There are also a few disadvantages. You’ll always risk getting spread too thin, and you will spend lots of time getting familiar with new topics, instead of going deep on just a few. You probably won’t share most of the problems you want to help solve. Since you don’t have these diseases/conditions/whatevers, you won’t be able to self-experiment, and self-experimentation is an important part of research. And some communities won’t want or appreciate help from an outsider.

To Sum Up

Reddit is a big place. There’s a lot of questions to answer, problems to solve, and communities to rally to the mad science crusade. 

Probably by 2030 there will be several major researchers on reddit, and two or three of them will be getting close to being household names. Some of them will be generalists who hop around different subreddits, consulting on different problems. Some of them will be specialists, organizing their communities against shared problems. Different research czars will work together to make bigger and better projects, and problems will get solved faster than anyone today thinks possible. 

But why wait to see other people do it? If you think you have what it takes (or half of what it takes; don’t be afraid to learn on the job), there’s nothing stopping you from doing this starting tomorrow. We’d be happy to consult on stats and methods — and if you do anything interesting, we might blog about it. If you declare yourself Czar of X and you make a big breakthrough, we will send you a crown (though it will not be this nice).