The “Happiness Experiment” Report: How NOT to Measure Happiness

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quantified self happinessAbout a month ago, inspired by the conversation with one of my readers, I embarked on a personal research project, which I dubbed “Happiness Experiment”. The objective was to design a series of self-experiments to find out what makes me happy. I decided to start last month, with a couple of easy things, like quality of sleep, and stress levels. The experimental design was simple: to measure my sleep, stress and happiness levels daily for a month, and then look at the correlations among them. Only after a couple of weeks into actual experiment I realized that my design had some flaws: I chose the wrong scale to measure happiness.

Since the project essentially about life and its meaning, I opted for a Life Satisfaction as a proxy for happiness. In fact, Dr. Diener’s “Satisfaction with Life” questionnaire is often cited as one of the methods to measure happiness and well-being. The original scale has 5 items, but I went with four:

  • In most ways my life is close to my ideal
  • So far I have gotten the important things I want in life
  • The conditions of my life are excellent
  • If I could live my life over, I would change almost nothing

I answered each of these questions, using 10-point scale (1 = “Disagree Completely”, 10 = “Agree Completely”) at the end of each day; the life satisfaction score was computed as an arithmetic average of responses. After second week, I realized that these questions do not really reflect my happiness on that particular day; when answering them, I tend to think about my life in general. As a result, the life satisfaction score was pretty much the same every day (the chart is based on three weeks of data, averaged daily life satisfaction levels):
quantified self happiness measures
With the exception for a couple of spikes, my life satisfaction most of the time was around 5.8. With the standard deviation of 0.39 (!), there is no much variability: in 95% of cases, my life satisfaction level will be “locked” between 5.0 and 6.5. While from psychometric point of view, such stability is great,  for my current research project this scale may not be “sensitive” enough to capture the current emotional and mental state. Just for comparison, here is distribution of average daily negative stress levels for the same time period (average stress level was 3.2, with standard deviation 1.2):

quantified self stress

Unhappy with the happiness scale, I stopped collecting data last week. Still, by that time I already had accumulated enough data points, so I ran some analysis. The findings were somewhat encouraging. The patterns are hard to spot in the chart (I added current mood to the mix, out of curiosity):

quantified self life satisfaction mood sleep and stress measures
but become more clear if you compute correlations (I have done this in Excel):

correlations between quantified self measures of sleep mood stress and sleep quality

As you would expect, there was moderate negative association between the stress levels and life satisfaction. The relationship between life satisfaction and current mood was surprisingly weak, although positive, as expected. However, the correlation between life satisfaction and sleep quality is puzzling. I have no explanation whatsoever why would sleeping better make me feel less happy. Hopefully, a more proper measure of happiness will fix this. I actually have looked into other measures of happiness, and already settled on the short version of the Oxford Happiness Questionnaire. The “Happiness Experiment” will resume in September. Stay tuned!

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5 Responses to The “Happiness Experiment” Report: How NOT to Measure Happiness

  1. Jay Bradfield says:

    “I have no explanation whatsoever why would sleeping better make me feel less happy”
    Or could it be that feeling more happy makes you sleep better? I don’t see any time series analysis here, so I’m not sure if we can draw conclusions around the direction of causation.

  2. Hi Jay,
    Great point about the causation! Correlation does not equal causation. However, in this particular case, the sleep quality readings were taken in the morning right after the sleep, and the happiness measures were taken afterwards, later in the day, so the antecedent in this case is clearly sleep quality.

  3. MOnce says:

    Being a follower of both QS and paleo I’ve tugohht about this topic for a while, and I feel that the distinction between the Paleo and QS movements is really the difference between explanation (theories) and observation (data). Science needs theories, without them it is not science, it is, at best pre-science or just the initial steps of the scientific method. Ironically, the data-driven mode of exploration that QSers engage in is often less scientific than the Paleo folks who rely much less on quantification. This is a huge meme in the paleo community, they have a deep distrust of observational studies, and they blame unthoughtful and premature quantification for the prevalence of erroneous theories such as the lipid hypothesis.What QSers should take away from the Paleo movement is that if you want to make any type of actual progress you need to base your data collection and quantification on a foundation of reasonable hypotheses and use experimentation to iterate upon them until you arrive at robust theories. In other words, QSers should be doing science not stamp collecting.

  4. Stan Capron says:

    Really enjoyed this blog post, is there any way I can receive an alert email whenever you publish a new post?

  5. Measured Me says:

    Hi Stan,

    You can subscribe to blog feed via e-mail.

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