On the QS forums, Christian Kleineidam asked:
While doing Quantified Self public relations I lately meet the challenge of explaining how our lives are going to change if everything in QS goes the way we want. A lot of what I do in quantified self is about boring details. . . . Let’s imagine a day 20 years in the future and QS is successful. How will that day be different than [now]?
Self-measurement has helped me two ways. One is simple and clear. It has helped me be healthy. Via QS, I have found new ways to sleep better, lose weight, be in a better mood, have fewer colds (due to better immune function), reduce inflammation in my body, have better balance, have a better-functioning brain, have better blood sugar, and so on. I am not an expert in any of these areas — I am not a professional sleep researcher, for example. I believe that this will be a large part of the long-term importance of QS: it will help non-experts make useful discoveries about health and it will help spread those discoveries. Non-experts have important advantages over professional researchers. The non-experts (the personal scientists) are only concerned with helping themselves, not with pleasing their colleagues or winning grants, promotions, or prizes; they can take as long as necessary; and they can test “crazy” ideas. In a QS-successful world, many non-experts would make such discoveries and what they learned would reach a wide audience. Lots of people would know about them and take them seriously. As a result, people would be a lot healthier.
Self-measurement has also helped me in a more subtle way. It made me believe I have more power over my health than I thought. This change began when I studied my acne. I did not begin with any agenda, any point I wanted to make, I just wanted to practice experimentation. I counted my pimples (the QS part) and did little experiments. My results showed that one of the drugs my dermatologist had prescribed (tetracycline, an antibiotic) didn’t work. My dermatologist hadn’t said this was possible. Either he had done nothing to learn if worked or he had reached the wrong answer. What stunned me was how easy it had been to find out something important a well-trained experienced expert didn’t know. My dermatologist was not an original thinker. He did what he was told to do by med school professors (antibiotics are a very common treatment for acne). It was the fact that I could improve on their advice that stunned me. I didn’t have a lab. I didn’t have a million-dollar grant. Yet I had learned something important about acne that dermatology professors with labs and grants had failed to learn (antibiotics may not work, be sure to check).
Skepticism about mainstream medicine is helpful, yes, but only a little bit. More useful is finding a better way. For example, it’s useful to point out that antidepressants don’t work well. It’s more useful to find new ways to combat depression. Two years ago, the psychiatrist Daniel Carlat came out with a book called Unhinged that criticized modern psychiatry: too much reliance on pills. No kidding. Carlat recommended more talk therapy, as if that worked so well. As far as I could tell, Carlat had no idea that you need better research to find better solutions and had no idea what better research might be. This is where QS comes in. By encouraging people to study themselves, it encourages study of a vast number of possible depression treatments that will never (or not any time soon) be studied by mainstream researchers. By providing a way to publicize what people learn by doing this, it helps spread encouraging results. In the case of depression, I found that seeing faces in the morning produced an oscillation in my mood (high during the day, low at night). This has obvious consequences for treating depression. This sort of thing will not be studied by mainstream researchers any time soon but it can easily be studied by someone tracking their mood.
In a QS-successful world, many people would have grasped the power that they have to improve their own health. (You can’t just measure yourself, you have to do experiments and choose your treatments wisely, but measuring yourself is a good start.) They would have also grasped the power they have to improve other people’s health because (a) they can test “crazy” solutions mainstream researchers will never test, (b) they can run more realistic tests than mainstream researchers, (c) they can run longer tests than mainstream researchers, and (d) no matter what the results, they can publicize them. In a QS-successful world, there will be a whole ecosystem that supports that sort of thing. Such an ecosystem is beginning to grow, no doubt about it.
My personal science introduced me to a research method I have never seen used in research articles or described in discussions of scientific method. It might be called wait and see. You measure something repeatedly, day after day, with the hope that at some point it will change dramatically and you will be able to determine why. In other words: 1. Measure something repeatedly, day after day. 2. When you notice an outlier, test possible explanations. In most science, random (= unplanned) variation is bad. In an experiment, for example, it makes the effects of the treatment harder to see. Here it is good.
Here are examples where wait and see paid off for me:
1. Acne and benzoyl peroxide. When I was a graduate student, I started counting the number of pimples on my face every morning. One day the count improved. It was two days after I started using benzoyl peroxide more regularly. Until then, I did not think benzoyl peroxide worked well — I started using it more regularly because I had run out of tetracycline (which turned out not to work).
2. Sleep and breakfast. I changed my breakfast from oatmeal to fruit because a student told me he had lost weight eating foods with high water content (such as fruit). I did not lose weight but my sleep suddenly got worse. I started waking up early every morning instead of half the time. From this I figured out that any breakfast, if eaten early, disturbed my sleep.
3. Sleep and standing (twice). I started to stand a lot to see if it would cause weight loss. It didn’t, but I started to sleep better. Later, I discovered by accident that standing on one leg to exhaustion made me sleep better.
4. Brain function and butter. For years I measured how fast I did arithmetic. One day I was a lot faster than usual. It turned out to be due to butter.
5. Brain function and dental amalgam. My brain function, measured by an arithmetic test, improved over several months. I eventually decided that removal of two mercury-containing fillings was the likely cause.
6. Blood sugar and walking. My fasting blood sugar used to be higher than I would like — in the 90s. (Optimal is low 80s.) Even worse, it seemed to be increasing. (Above 100 is “pre-diabetic.”) One day I discovered it was much lower than expected (in the 80s). The previous day I had walked for an hour, which was unusual. I determined it was indeed cause and effect. If I walked an hour per day, my fasting blood sugar was much better.
This method and examples emphasize the point that different scientific methods are good at different things and we need all of them (in contrast to evidence-based medicine advocates who say some types of evidence are “better” than other types — implying one-dimensional evaluation). One thing we want to do is test cause-effect ideas (X causes Y). This method doesn’t do that at all. Experiments do that well, surveys are better than nothing. Another thing we want to do is assess the generality of our cause-effect ideas. This method doesn’t do that at all. Surveys do that well (it is much easier to survey a wide range of people than do an experiment with a wide range of people), multi-person experiments are better than nothing. A third thing we want to do is come up with cause-effect ideas worth testing. Most experiments are a poor way to do this, surveys are better than nothing. This method is especially good for that.
The possibility of such discoveries is a good reason to self-track. Professional scientists almost never use this method. But you can.
I recently had lunch with Richard Sprague, an engineer at Microsoft Beijing. He raised the possibility of starting a Quantified Self Meetup group in Beijing. The meetings could be held in one of Microsoft’s two brand new buildings, which are in the exact center of Zhongguancun. If you might attend, please let me know (e.g., by commenting on this post).
I have blogged many times about biohacker Tara Grant’s discovery that she slept much better if she took Vitamin D3 in the morning rather than later. Many people reported similar experiences, with a few exceptions. Lots of professional research has studied Vitamin D3 but the researchers appear to have no idea of this effect. They don’t control the time of day that subjects take D3 and don’t measure sleep. If the time of day of Vitamin D3 makes a big difference, measuring Vitamin D3 status via blood levels makes no sense. Quite likely other benefits of Vitamin D3 require taking it at the right time of day. Taking Vitamin D3 at a bad time of day could easily produce the same blood level as taking it at a good time of day.
I too had no idea of the effect that Grant discovered. I had taken Vitamin D3 several times — never in the morning — but after noticing no change stopped. I tested Grant’s discovery by taking Vitamin D3 at 8 or 9 am. First, taking it at 8 am, I gradually increased the dose from 2000 IU to 8000 IU. Then I shifted the time to 9 am. The experiment ended earlier than I would have liked because I had to fly to San Francisco.
When I woke up in the morning I rated how rested I felt on a 0-100 scale, where 0 = not rested at all and 100 = completely rested. I’d been using this scale for years. Here are the results (means and standard errors):
Vitamin D3 had a clear effect, but the necessary dose was more than 2000 IU. If Vitamin D3 acts like sunlight, you might think that taking it in the morning would make me wake up earlier. Here are the results for the time I woke up:
There was no clear effect of dosage on when I got up. Shifting the time from 8 am to 9 am may have had an effect (I wish I had 3 more days at 9 am).
Many people have reported that taking Vitamin D3 in the morning gave them more energy during the day. I usually take a nap in the early afternoon so I measured its effect on the length of those naps:
Maybe my naps were shorter with 6000 and 8000 IU at 8 am. It’s interesting that 4000 IU seemed to be enough to improve how rested how I felt but not enough to shorten my naps.
What do these results add to what we already know? First, the large-enough dose was more than 2000 IU. (A $22 million study of Vitamin D3 is using a dose of 2000 IU.) The dose needed to get more afternoon energy may be more than 4000 IU. Second, careful experimentation and records helped, even though many people found the effect so large it was easy to notice without doing anything special. For example, these results suggest the minimum dose you need to get the effect. Three, these support the value of supplements. Many people say it is better to get necessary nutrients from food rather than supplements. However, supplements allow much better control of dosage and timing and these results suggest that small changes in both can matter. I cannot imagine this effect being discovered with Vitamin D3 in food.
Note from Alex: Gwern Branwen also sent in this detailed post on Vitamin D and sleep.
A New York lawyer named Greg reports remarkably clear evidence about the effect of butter on blood lipid levels: It improved them. For a few years he measured his HDL and LDL regularly with a home cholesterol device. For unrelated reasons, he started eating more butter. He ate a half stick (about 60 g)/day, like me. Here’s what happened.
The first five measurements are from lab tests. The rest are from his home machine.
I asked Greg for details.
I’m 36. I bought the cholesterol meter last July after my doctor said he couldn’t figure out why my numbers were a bit high. We both agreed it was not something to worry too much about and that there was no point charging my insurance company for a VAP test every 6 months. We both also agreed that going on a statin was a bad idea. I picked up the meter out of curiosity. I had previously been monitoring my blood sugar (since 2009) and found it to be very interesting, so I thought I could have some fun with the numbers. The result is all the more surprising because I did not expect it. I was tracking my numbers around the time of the experiment [with butter] to make sure they did not go the wrong way like everyone says they should.
The machine is a CardioChek PA [about $600], which is designed for use in doctors offices, not for the consumer market. The device is “CLIA-waived”, which means that the FDA considers it so simple that the user does not need any special training in clinical chemistry (home glucometers fall into the same category). The machine gives significantly different numbers for different people, suggesting it is measuring something real and not spitting out random numbers.
I asked what the reaction to this data has been.
Most people I’ve spoken to have been receptive to the idea [that butter improves blood lipids], but I got no sense that they would be willing to try it for themselves. Most people I know seem to be quite willing to accept the fact that the old stories about cholesterol are not true. In contrast, one conservative cardiologist said I must have “unique genetics”.
In 2007, Jon Cousins started tracking his mood to help NHS psychiatrists decide if he was cyclothymic (a mild form of bipolar disorder). After a few months of tracking, he started sharing his scores with a friend, who expressed concern when his score was low. Jon’s mood sharply improved, apparently because of the sharing. This led him to start Moodscope, a website that makes it easy to track your mood and share the results.
I was curious about the generality of what happened to Jon — how does sharing mood ratings affect other people? In January, Jon kindly posted a short survey about this. More than 100 people replied.
Their answers surprised me. First, in a survey about sharing your mood — not about tracking your mood — most respondents did not share their mood. It is as if, in a survey about being tall, most respondents were not tall. Second, although Jon’s mood sharply rose as soon as he started sharing, this was not the usual experience. Sharing helped, some people said, but other people said sharing hurt. For example, one person said her mood was used against her in arguments. Finally, the respondents gave all sorts of persuasive reasons that rating their mood helped them. To me, at least, the value of mood rating isn’t obvious. I can list a dozen hypothetical benefits but whether they actually happen is unclear to me. I rated my mood for years and did it only to learn about the effects of morning faces. MoodPanda, another mood-rating site, gives a few brief vague unenthusiastic reasons to track your mood. And their site is all about mood rating.
In contrast, Moodscope users were clear and enthusiastic about the value of tracking. Here are some reasons they liked mood-tracking:
It is useful to look back sometimes to help you find ways of ‘keeping up’ a positive mood/outlook.
My mood range has definitely narrowed since starting mood stabilizers, so using Moodscope has given me solid evidence that the treatment is working well. I also run statistical analyses of my mood charts against variables like sleep, medication use, and alcohol consumption. The correlations were not particularly meaningful using a 9-point Likert-like scale from a standard mood chart. When I used my Moodscope scores instead, I suddenly found that some of the correlations are (ridiculously!) statistically significant, which also made me feel more certain about what I need to do and change to better manage my mental health.
I could express my miserableness in total safety, without leaning on anybody else. It has proved wonderful. My profile has risen from a score of 7 on day 1 (11 months ago) to the 90s now. Being able to track my reasons for feeling better or worse has been part of this. The patterns are visible, ditto the triggers that send me up or down.
The great benefit of Moodscope has been to confirm the advantages of my own lifestyle management for coping with bipolar disorder. It has shown that what I felt was bad for me, is indeed bad, and what I felt was good for me, is indeed good. (I know that I have to take the meds.)
It helps that I can post things about sleep hours in the comments and see the correlation to the chart.
I have found the tool immensely helpful in gaining insight into how my own behaviour and thoughts can impact upon my mental health. I have gained more control.
It helps me to gain insight into my moods, take responsibility for them and steer a calmer, more productive course through life.
It allows me not to panic when I am low as I can see that ups and downs are all part of life.
Pre-Moodscope, I would not realize i was on the way down until 10 or so days had passed, and so I had done nothing. But with Moodscope, I can see if it’s a trend and do something immediately. It means I deliberately intervene earlier.
I use my scores, and comments, to understand what triggers my low mood and take steps to stop it getting lower, in so far as I am able.
I view it as a diary of sorts, private for my own contemplation.
I want to catch myself before I make a deep plunge and stay down too long. I do use the info with my doctor. I love having something concrete to show and talk about.
It has helped me feel like there is a greater safety net there, and given me a greater awareness of when I’m slipping back into my treacle pit; I now know that any score between 20 and 30 means I am in dangerous territory and need to take some remedial action, and if I get below 20 then I’m really in a bad way.
Moodscope has helped me identify incidents in my life with my mood. For example if I have to assert myself strongly with someone, I feel exhilarated and very proud of myself for about two day then gradually my mood will lower and a week later I will feel apathetic and down. I love that it is helping me make sense of my emotions and as a result I am not judgmental of them.
I’ve found Moodscope really useful in finding out what influences my moods. I am bipolar and after 20 years on lithium I’m managing without any meds. Don’t worry, I came off it slowly, under medical supervision!
I use Moodscope as a sort of diary of how I am feeling. Looking back I can see what really pushed my mood down and oddly it’s not always the major things that you’d imagine. In my case depression is brought on more by physical health problems – I am a CFS sufferer.
I sum up their reasons like this: 1. Helps understand causality (what causes mood to be low or high?). 2. Immediate guidance (should I take action to raise it?). 3. Self-expression (similar to diary). 4. Reassurance (low moods are “part of life”). Alexandra Carmichael wrote about the value of mood-tracking and mood-sharing. Her experience did not repeat Jon’s: She found little initial benefit of sharing, but great eventual benefits (“a kind of deep, healing therapy”). This was the main benefit of tracking for her — that it allowed this sharing. Kari Sullivan also tried Moodscope. She didn’t share her mood. The benefits she list fall under the heading of Reason #1 (helps understand causality). For example, she learned “most social interaction lowers my mood,” which surprised her.
Not everyone liked tracking:
My girlfriend . . . stopped using Moodscope. In her words, “I don’t want Moodscope to remind me how terrible I’m doing.”
She has now decided to give up on taking the test as it just reinforces her feelings of general greyness and sometimes despair.
At a website devoted to collecting new ideas about health, Moodscope ranked #1 out of about 500 ideas.
When I started my self-experimentation I didn’t get anywhere for a long time (after initial success with acne). After 1990, however, I was astonished at the progress I made. One useful discovery after another — how to lose weight, sleep better, be in a better mood, and so on. Over the next 20 years, I improved my health considerably more than all the other scientists in the world put together. I came to see what was happening as a kind of catalysis. The useful information was already there; my personal science was the catalyst that turned it into something useful. (Lack of people like me was why the discoveries were so abundant — a counter-example to Tyler Cowen’s lack-of-low-hanging fruit explanation for stagnation.) Professional scientists were too restricted in what they did.
The Moodscope story is similar. Psychologists have been studying and measuring mood for a long time. The Profile of Mood States is an important result of their research. But no psychologist saw it as an agent of change. It was simply a research tool, albeit a popular one. Only when Jon Cousins started using it for his own selfish purposes did it become clear how useful it could be. He was the catalyst.
Both my story and Jon’s are examples of what I say about DIYization of science: It gets tools into the hands of a larger and more diverse group of possible innovators, who are less “stuck” — less committed to old ways of doing things — than the professionals. They are also more motivated to do something useful than the professionals, who are weighed down with other big concerns — about status, job security, money, and so on.
When I moved to Ireland in 2007, I began to have skin problems. It began gradually and I attributed it to the move, to stress, to late nights drinking with developers and clients, to travel, to whatever excuses I could think of. The stress was multiplied by the anxiety of being embarrassed about how my face looked, but also because my new job in Ireland involved me being on stage in front of large audiences constantly, often several times a week. A year later my skin was perpetually inflamed, red, full of sores and very painful. When one spot would go away, two more would spring up in its place. It was a tough time. I cried a lot.
Frustrated, I went to see my hometown dermatologist while I was home for holidays. He told me that a) this was completely normal and b) there was nothing I could do but go on antibiotics for a year (in addition to spending a fortune on creams and pills). I didn’t believe either of those things.
I was not interested in being on an antibiotic for a year, nor was I interested in Accutane (my best friend has had it multiple times and it hasn’t had long term results, plus it can be risky). What I was interested in was figuring out why this was happening and changing my life to make it stop. I refused to accept my dermatologist’s insistence that what you put in your body has no effect on how you look and feel.
I began systematically cutting things out of my diet to see how I reacted. First chicken and soy, based on a recommendation from a food allergist. Over the course of a year I cut out sugar, gluten, carbs, starches, caffeine, meat, fish until finally the magical month of December 2010 when I cut out dairy. My skin was my own again by New Year’s day this year.
It took a year to figure it out. It was completely worth it. There’s nothing wrong with Irish dairy, it just doesn’t work for me. I drink Americanos instead of lattes now, I don’t eat cereal; none of that is a huge deal. For what it’s worth, I can drink goat’s milk.
A great example of the power of self-experimentation compared to trusting doctors.
At the end of her post she makes a very important point:
Quantified Self isn’t for everyone, but everyone should feel they have the power to change things in their body and their life for the better.
I agree. By learning about examples of people who have done just that — such as Martha — we will come closer to having that power. Right now, as far as I can tell, most people feel helpless. They do what doctors or other experts tell them to do, even if it doesn’t work very well.
Long ago, hardly anyone could read. This left them in the grip of those who could. But eventually came mass literacy, when the benefits of reading finally exceeded the costs (e.g., because more books were available at lower prices). Reading is primitive science: if you read about things that happened, it is information gathering. It resembles doing a survey. Nowadays, almost everyone (in rich countries) reads, but almost no one does experimental science. This leaves them in the grip of those who can do experimental science (e.g., drug companies). I think my work and Martha’s work suggest we are close to another turning point, where, for nonscientists, the benefits of doing experiments exceed the costs.
Thanks to Gary Wolf.
I measure my arithmetic speed (how fast I do simple arithmetic problems, such as 3+ 4) daily. I assume it reflects overall brain function. I assume something that improves brain function will make me faster at arithmetic.
Two years ago I discovered that butter — more precisely, substitution of butter for pork fat — made me faster. This raised the question: how much is best? For a long time I ate 60 g of butter (= 4 tablespoons = half a stick) per day. Was that optimal? I couldn’t easily eat more but I could easily eat less.
To find out, I did an experiment. At first I continued my usual intake (60 g /day). Then I ate 30 g/day for several days. Finally I returned to 60 g/day. Here are the main results:
The graph shows that when I switched to 30 g/day, I became slower. When I resumed 60 g/day, I became faster. Comparing the 30 g/day results with the combination of earlier and later 60 g/day results, t = 6, p = 0.000001.
The change in error rates raised the possibility that the speed changes were due to movement along a speed-accuracy tradeoff function (rather than to genuine improvement, which would correspond to a shift in the function). To assess this idea, I plotted speed versus accuracy (each point a different day).
If differences between conditions were due to differences in speed-accuracy tradeoff, then the points for different days should lie along a single downward-sloping line. They don’t. They don’t lie along a single line. Within conditions, there was no sign of a speed-accuracy tradeoff (the fitted lines do not slope downward). If this is confusing, look at the points with accuracy values in the middle. Even when equated for accuracy, there are differences between the 30 g/day phase and the 60 g/day phases.
What did I learn?
1. How much butter is best. Before these results, I had no reason to think 60 g/day was better than 30 g/day. Now I do.
2. Speed of change. Environmental changes may take months or years to have their full effect. Something that makes your bones stronger may take months or years to be fully effective. Here, however, changes in butter intake seemed to have their full effect within a day. I noticed the same speed of change with pork fat and sleep: How much pork fat I ate during a single day affected my sleep that night (and only that night). With omega-3, the changes were somewhat slower. A day without it made little difference. You can go weeks without Vitamin C before you get scurvy. Because of the speed of the butter change, in the future I can do better balanced experiments that change conditions more often.
3. Better experimental design. An experiment that compares 60 g/day and 0 g/day probably varies many things besides butter consumption (e.g., preparing the butter to eat it). An experiment that compares 60 g/day and 30 g/day is less confounded. When I ate less butter, I ate more of other food. Compared to a 60 g/0 g experiment, this experiment (60 g/30 g) has less variation in other food. Another sort of experiment, neither better nor worse, would vary type of fat rather than amount. For example, replace 30 g of butter with 30 g of olive oil. Because the effect of eliminating 30 g/day of butter was clear, replacement experiments become more interesting — 30 g/day olive oil is more plausible as a sustainable and healthy amount than 60 g/day.
4. Generality. This experiment used cheaper butter and took place in a different context than the original discovery. I discovered the effect of butter using Straus Family Creamery butter. “One of the top premium butters in America, ” says its website, quoting Food & Wine magazine This experiment used a cheaper less-lauded butter (Land O’Lakes). Likewise, I discovered the effect in Berkeley. I did this experiment in Beijing. My Beijing life differs in a thousand ways from my Berkeley life.
The results suggest the value of self-experimentation, of course. Self-experimentation made this study much easier. But other things also mattered.
First, reaction-time methodology. In the 1960s my friend and co-author Saul Sternberg, a professor of psychology at the University of Pennsylvania, introduced better-designed reaction-time experiments to study cognition. They turned out to be far more sensitive than the usual methods, which involved measuring percent correct. (Saul’s methodological advice about these experiments.)
Second, personal science (science done to help yourself). I benefited from the results. Normal science is part of a job. The self-experimentation described in books was mostly (or entirely) done as part of a job. Before I collected this data, I put considerable work into these measurements. I discovered the effect of butter in an unusual way (measuring myself day after day), I tried a variety of tasks (I started by measuring balance), I refined the data analysis, and so on. Because I benefited personally, this was easy.
Third, technological advances. Twenty years ago this experiment would have been more difficult. I collected this data outside of a lab using cheap equipment (a Thinkpad laptop running Windows XP). I collected and analyzed the data with R (free). A smart high school student could do what I did.
There is more to learn. The outlier in the speed data (one day was unusually fast) means there can be considerable improvement for a reason I don’t understand.
A colleague I’ll call John has decided to start tracking his mood for a long period of time (years). He explains why:
A few years ago, after a severe manic attack, I was diagnosed with bipolar disorder. The attack was preceded by an intense period of stress, then two weeks of elevated mood, increased social activity (hanging out and meeting people), and racing thoughts (hypomania). Then I skipped a few nights of sleep, wandered down roads in the middle of the night, and eventually became psychotic, in that I could no longer distinguish between reality and imagination. I was chased by cops on several occasions, and was involuntarily committed to the mental health wing of a hospital for a month. It put a massive dent in my life.
Family, medicine, and time helped me recover. Being out of control like that was fun only for the first two weeks. Having my life turned upside down was not fun either. As I recovered I became increasingly interested in finding ways to prevent a relapse. One doctor said: You have a vulnerability. You need to protect yourself. I agreed.
Looking back on the experience, I realized there was a rise in odd behaviors two weeks before I started to skip nights of sleep and fell into psychosis. There was an even longer buildup of stress, anxiety, and fear in the months before the mania hit. During the last two weeks before the mania, my behavior was different from what is normal for me. I felt elated and had a sense of general “breakthrough”. I suddenly felt no fear and anxiety. I felt on top of the world. I was constantly taking notes because ideas and thoughts were running through my head. I scheduled meetings and social activities almost constantly throughout these two weeks and shared my experiences as my new self. As I started to sleep less and skip nights of sleep, others later told me I seemed agitated and down.
Maybe it is possible to catch these early warning signs and take counter measures before they worsen into mania or depression. This is why I have started to track my behavior starting with mood and sleep. If I can get a baseline of my behavior and know what is ‘normal’ for me, it will be easier to notice when I am outside my normal range. I can alert myself or be alerted by others around me who are monitoring me. Long-term records of mood will also help me experiment to see which things influence my mood. This may give me more control over my mood.
Mood tracking might be a good idea for anyone to do, but it may be especially helpful for people with a bipolar diagnosis. Everyone has mood variation. For bipolars, however, mood swings can be more extreme (in both directions, up and down) , have far worse consequences (psychosis on one end and suicide on the other), change more rapidly, and be more vulnerable to environmental triggers like stress. The good news is that the first changes in mood can happen hours or days before more extreme changes. This gives people a chance to take countermeasures to prevent more extreme states.
The project name refers to the fact that Van Gogh had bipolar disorder.
In March I discovered that looking at a graph of my productivity (for the current day, with a percentile attached) was a big help. My “efficiency” — the time spent working that day divided by the time available to work — jumped as soon as the new feedback started (as this graph shows). The percentile score, which I can get at any moment during the day, indicates how my current efficiency score ranks according to scores from previous days within one hour of the same time. For example, a score of 50 at 1 p.m. means that half of the previous days’ scores from noon to 2 p.m. were better, half worse. The time available to work starts when I get up. For example, if I got up at 4 a.m., at 6 a.m. there were 2 hours available to work. The measurement period usually stops at dinner time or in the early evening.
This graph shows the results so far. It shows efficiency scores at the end of each day. (Now and then I take a day off.) One interesting fact is I’ve kept doing it. The data collection isn’t automated; I shift to R to collect it, typing “work.start” or “work.stop” or “work.switch” when I start, stop, or switch tasks. This is the third or fourth time I’ve tried some sort of work tracking system and the first time I have persisted this long. Another interesting fact is the slow improvement, shown by the positive slopes of the fitted lines. Apparently I am slowly developing better work habits.
The behavioral engineering is more complicated than you might think. My daily activities naturally divide into three categories: 1. things I want to do but have to push myself to do. This helps with that, obviously. 2. things I don’t want to do a lot of but have to push myself away from (e.g., web surfing). 3. things I want to do and have no trouble doing. But the recording system is binary. What do I do with activities in the third category? Eventually I decided to put the short-duration examples (e.g., standing on one foot, lasts 10 minutes) in the first category (counts as work), keeping the long-duration examples (e.g., walking, might last one hour) in the second category (doesn’t count as work).
Before I started this I thought of a dozen reasons why it wouldn’t work, but it has. In line with my belief that it is better to do than to think.