Surveys, questionnaires, polls and other forms of self-report are popular ways of gathering data for numerous reasons. They are a cost-effective, fast, and easy to distribute to large samples. However, there are many dangers in relying only on self-reporting data.
Respondents can both consciously and unconsciously be less than honest in order to uphold an aspirational image they have of themselves (in a survey, you may respond that you go to the gym 5 days a week, when in actuality you go to the gym twice a week); or respondents may answer on availability heuristic, the tendency for people to rely on immediate examples that come to mind when evaluating a specific topic (if the questionnaire asks if you are social, and you just went to a birthday party that day, you would be inclined to base your answer on the fact you went to a birthday party recently); or respondents might even interpret the question in different ways unrelated to the purpose of the inquiry.
Because of self-reporting’s unreliability, many researchers have experimented and developed new methods to obtain more accurate data, such as Roger Mills-Koonce from UNC-Chapel Hill. His team is exploring ways to understand children’s mental representations and interpersonal relationships within their family through pictures. In the study, researchers asked 6-year-old children to draw their families on a piece of paper and then they analyzed them. The study was done on 6 year olds because they were old enough to hold the crayons, yet young enough to have not yet internalize society’s idea of the “perfect” family.
It is not a new concept to interpret drawings, but the important part about Mills-Koonce’s work is their effort to make abstract data more reliable by developing a system of objective evaluation so that anyone can interpret the drawings similarly and arrive at the same conclusions.
At Antedote, we believe in leveraging the latest technology to develop new methods that will allow us to get to the heart of true insights. One of our latest tools for discovering fresh insights in crowded marketplaces (which had recently won the 2014 MRS Award for Best Innovation) allows us to bring order and sense to otherwise abstract data. We applaud and join the efforts of researchers like Mills-Koonce for pushing the industry forward with new innovative systems and approaches.