Chances are good that if you’ve been diagnosed with bipolar disorder, you’ll have been told that you should keep a mood chart. Remarkably, no one ever told me this. Maybe because I started mood charting when I first started suspecting that I’m bipolar. By now, I have over 450 days of consistent data, and that’s a very powerful tool. Yes, I’m a professional data geek. It has its advantages.
This is a two-part series on mood charts. Today’s lesson focuses on a couple of mood chart tools, graphing values as time series with Excel, and visually interpreting them. Tomorrow, I’ll discuss a few basic statistics that help you get additional insight out of that mood data. Both of these posts are illustrated with examples from my mood chart data, so hopefully that will make it easier to understand. Feel free to ask questions – data analysis is one of the things I’m pretty good at, and I’m excited to share it with others.
A mood chart is exactly what it sounds like: a tracking tool to help you stay aware and on top of mood changes. There are tons of different mood charts out there. I found many of them too complicated or clunky. I now wish I’d chosen one of the slightly more dimensional ones, but maybe I’ll switch someday. These are all pretty decent, depending on how detail-oriented you are and what other information you want to track:
In addition to being consistent about recording mood scores, an important aspect of mood charting is tracking covariates. Most mood charts have a space for this, but if you’re bipolar you should always include hours of sleep. Alcohol/drug use is another good one, and med dosages is wise. For the ladies, keeping track of your period will help you figure out how much your cycle is messing with your moods. I use a separate iPhone app for this because it predicts the start of the next cycle pretty accurately, but I also record it on my mood chart.
I ended up using a mood chart that has a simple 9-point scale with spaces for tracking meds, hours of sleep, and periods. I can tuck it into my relatively small mood journal, where it serves as a placeholder and a reminder to jot down a few details about what’s been going on with side effects and so on. Tracking numbers isn’t the whole story, after all.
But wait, there’s more! There are tons of mobile phone apps for mood tracking. I even have a couple of them, but I never got into the swing of using them. I do use a web-based mood tracker, Moodscope, which is getting a lot of recognition for good reason. It’s awesome and free! It uses a 20-item questionnaire with flip cards that have 4 choices on them, and automatically scores them on a 100-point scale. It often surprises me, but I like the way it works – I can’t rig the results because I don’t know what it will return, so there’s no faking it.
Newly introduced Moodscope features include the “affectogram” and “triggergram” which are useful for better understanding your overall mood trends on a per-item basis and the things that set you off. Another cool thing about Moodscope is that it lets you share your mood scores with a buddy by email, so if there’s someone you need to keep posted, this is an easy way to do it. I use this feature to keep my hubby tuned into how I’m feeling, since I don’t always express my moods very well. The main feedback you get from Moodscope is your mood graph; my graph from the last year shows a lot of instability, which at this point surprises no one.
What else can you do with mood charts? If you’re a data geek, or even if not, then there’s a lot more you can do with this data. Fire up a spreadsheet program (like Excel) and enter the data by date. Yes, this is time consuming, but rewarding in the end! As mentioned, I track a whole lot of stuff. What I discovered in pretty short order from tracking all those details was that only two of them really matter for me: my mood scores and the number of hours of sleep that I get. How did I figure that out? Two things – making a chart and running a couple of statistical tests. I’ll talk more about statistical tests tomorrow.
I’m including several graphs here, but the first one is just my two sets of mood scores – from the paper sheet with a simple 9-point scale and from Moodscope – with the values adjusted so that you can look at them in the same numeric range (divided Moodscope scores by 10, added 5 to paper chart scores). This graph covers 11 months, pre-diagnosis to post-diagnosis and into treatment.
In case you can’t see the legend (click on the image for a larger one), the blue line is my paper chart score, and the red line is my Moodscope score. I haven’t been 100% reliable on the Moodscope score the whole time, but it is much more useful for statistics. As you can see, the two scores parallel each other pretty well. This is called convergent validity. It basically verifies that both ways of charting my moods are yielding very similar results, and are measuring the same thing (obviously, right?)
To better understand all of these graphs, you need to know the way I’m tracking my moods. Measurement methods matter! I record both scores at the same time of day, first thing in the morning about a half hour after waking, while I have my espresso and bask in the blue glow of my light box. I record the Moodscope score for how I feel right now, and I record the paper chart score for how yesterday went overall. One is in-the-moment, the other is retrospective, but never recorded more than a day late due to memory biases. That’s why some Moodscope scores are missing; the measures are too sensitive to memory errors, and occasionally I’m off the grid (yes, really!) Having these two methods of keeping records for each day lets me track how my mood might have changed during the day. For example, I might wake up in a great mood, and then have everything fall apart on me around lunchtime, ending the day in a pit of despair. In that case, the two scores would be different. Obviously from the chart above, that doesn’t happen all that often.
There are two charts in the next set, and these show the comparison of hours of sleep (in green) with mood scores. In both graphs, the raw numbers are manipulated (scaled) to make a graph that lets me see what I need to. Basically I just multiply each set of values by a constant or add/subtract a constant value, so that the values end up having approximately the same middle point. The Moodscope chart uses a red line and covers 11 months; the paper chart uses a blue line and covers the entire 15 months since I started tracking my moods. Yes, I record a score every single day. I told you I’m a data geek.
Since we already know that the two sets of mood scores are similar, we’re going to see similar things in both graphs; one just covers a bit more time. Whenever I can, I like to look at the information in multiple ways because sometimes it shows me something new. So what can we see in these charts?
- Sleep mirrors mood. The more sleep I get, the worse my mood is. The less sleep I get, the better my mood is. Causality is not shown here (which came first, sleep or mood?) but the relationship is undeniable. This is actually “normal” to a point, but the patterns here are extreme. The regularity is pretty striking too.
- December 2010 through March 2011 were pretty volatile, but things calmed down a little in April, and June was fairly stable.
- July 2011 was pretty rough with constant, severe rapid cycling featuring rather deep depression. Yes, I can confirm that. It was brutal.
- Something interesting happens in November of 2011. Can you guess what it is? Well, I’m going to tell you anyway: bipolar dx, started Lamictal, started managing sleep better.
Pretty cool, right? Well, that’s not all you can do with mood chart data! Tomorrow, Part 2 will go into some easy statistics for getting more out of your mood charts.