Finding the Individual In Aggregated Study Data
On the importance of not denying the individual and his/her experiences
Posted Dec 31, 2017
I recently attended a conference titled "Music and Death" in Vienna, Austria. While the conference was attended by mostly academics, it had a very different feel to what I was used to, and to what I was expecting.
In particular, there was a lot of story sharing, with people candidly describing how much music has changed their life. From the death of loved ones, to poor health, to being abused, to suicidal thoughts, to finding life devoid of meaning, there music was as a place of solace, strength and meaning. Where the shit of life was, music was there as a close friend.
Now, I typically look at data sets in which maybe 200-300 people have provided data. I search for patterns in that data and then I decide whether or not to publish those detected patterns in academic journals, and/or to share them in my blog.
When I look at those data points, I must confess that I often lose the individual amidst the numbers. When someone tells me their experience doesn't seem to match up with the results, I have in the past had a tendency to get annoyed and think "well the data are the data." But my experience at this conference (and some related experiences with some colleagues at my university), has me really regretting those choices.
Sure, people do not always know what influences their actions, thoughts and emotions. The unconscious (or subconscious if you prefer) is very powerful (for instance). And sure, people also tend to underestimate the role of social influences in their decision making. But, when someone says that the results of the study do not match their experience, that is powerful in itself. Who am I to deny their experience?
And besides, I have known all along anyway that collective data can not necessarily speak to any one person in the data set. Any one individual - or even many individuals - might run counter to the results and this is hidden in the aggregate data so long as more people show the other pattern (or even a small number show the pattern strongly).
Finding the individual in the data is also important for remembering why this research is done in the first place. That person scoring a "7" on a 1-9 scale of X variable is an individual who has lived a life behind that score. He or she is a person who can benefit from the research potentially as well. He or she is not just part of a pattern of data that is interesting to a group of people studying whatever topic.
In terms of appreciating music, I could probably read hundreds of data based studies on the positive impact of music and it would have less of an impact on me than hearing these individuals stories. I know the research, for instance, on the impact of listening to sad music and how it isn't always a good thing. But perhaps lost in that data are people who have been extraordinarily touched by sad music, or angry music, or whatever else type of music that people might not typically associate with positive outcomes. And if they are telling me that this type of music changed their lives in enormously positive ways, even raising the possibility that it has kept them alive, then the aggregate data needs to not be used to create the impression that these people are wrong about their own experiences.
I know to many reading this this might seem quite obvious. But when you live in a world of aggregate data, sometimes you need a reminder that there are individuals within that data.