As a latest foray into lifelogging I’ve been playing with a tool called “Moodscope“, a lightweight daily quiz which tracks excursions into positive and negative moods. It appears to be rooted in the established psychometric metric of the Positive and Negative Affect Schedule (PANAS). In short, you take a short quiz, and get back a 0-100 score, with 50 being neutral, >50 being “positive affect” (er, “good mood”), <50 being “negative affect” (“bad mood”). Faced with such a temptation, I couldn’t resist seeing if this was all hooey or if there would be signal in the noise…
To cut to the chase … much to my surprise, I could actually track long term trends. Shown at left are both my daily and weekly-averaged data for the last three months. Even without the weekly averaging the ‘envelope’ of the raw data suggested trends. (I also have a pretty good intuitive understanding of the related causes, but there’s only so much I’m going to dump onto a public blog!)
Since much of my mood is driven by what’s going on at work (both negative, on the frustration side, and positive, on the “things that feed me” side), I next wondered if there were any weekly trends buried in the data. Switch the smoothing filter from 7-day to 3-day and … voila! :
There’s the expected weekly cycle, hiding out in the raw data. While I hypothesized there might be such a signal, I never anticipated it would be that strong. But in hindsight it makes sense, my work-weeks, while not routine, do tend to share some general characteristics week-to-week. Switching to a distribution-based view of the raw scores, the story becomes, “Tell Me Why I Don’t Like Monday’s” (that’s an easy one actually; it’s all staff meetings, ‘sync tags’, etc, with very few opportunities to interact with people in motivating or inspiring ways – all activity, no energy).
(For stats junkies, the indented boxplots are a cool graph the Mac stats program Aabel generates … fatter boxes at a given score mean more occurrences; diamonds show the mean value, solid horizontal bars show the median value).
Anyway, back to the data. After lousy-Mondays, I typically get to work a lot more with people on, well, actually creating stuff, rather than managing it. Whether or not I’m doing it myself or just coaching, this is what fires me up. Of course, then the week trudges along, energy gets drained, stress goes up, backlogs grow, opportunities for conflict increase, etc, leading to not-so-pleasant Fridays. By the weekend, I’m mostly in “recharge” mode (“meh”), hovering more around neutral values. Unfortunately the PANAS positive affect questions all seem to be skewed towards very “active” positive values (“determined”, “inspired”, “interested”, etc); there’s no way to get positive affect credit for things like “cozy”, “content”, “relaxed”, etc).
As a final exercise I took the weekly data and simplified it down to a simpler user’s guide; for any given day of the week, how likely is it that I’m going to have a good day (mood score > 60), a bad day (mood score < 40), or a “meh” day (40-60). Arbitrary thresholds, I just picked ones that divvied up the data well. And yes, these are now posted on my office door (how’s that for biofeedback?!)