The paper addresses the issue of the inaccuracy of self-report data especially in the context of high-frequency, low-salience events (routine events). The study creates phone based situ surveys asking participants to recall their routine activities, and this data with the ground truth data obtained from wearable sensors. Based on this method they study the effect that were brought by changing the frequency of the survey to come up with the optimal ratio of survey presentation.
The study recruited 20 participants of different professions. They ask the participants to carry both a Mobile Sensor Platform for collecting factual data and Smart Phone running MyExperience for ESM (Experience Sampling Method) survey. The study last for 8 work days. On each day, participants were asked to perform three main tasks :(1) wearing MSP from the time they started their day in the morning until 7pm (2) answering 8 questions survey throughout the day varying number of times (3) answering a survey in the evening about the surveys they had during the day. The eight questions are divided into two groups by the two activities that were measured in the study, sitting and walking. The questions for each were (1) how many times the participant performed the target activity, what were the (2) longest and (3) shortest episodes of the activity, and (4) the total time spent performing the target activity. At the end of the study, an exit interview was performed.
The study shows a general the error of the recall declines with increasing number of surveys. And difference in error between 1 survey and 3 is huge. By analyzing participants with in two groups, office worker and non-office workers, the study shows that office workers make significantly lower recall errors than others. And with the data collected from the evening survey, they find out that the level of annoyance grows with the number of surveys. It was also found that it’s preferable for participants to receive surveys on a fixed schedule instead of having surveys randomly pop up to them.
This study is a perfect example of integrating quantitative research methods and qualitative research method together to answer the same research question. As was shown the study, the data collected using both research methods were consistent with each other and complementary with each other. The paper goes back and forth using both of these methods to illustrate the same points and the same finding. And together, the result seems more convincing and engaging than the ones I’ve seen only using one of them. I think this article can be a template for studies that aim to utilize both quantitative and qualitative research methods. I’ll definitely go back to this when I write UR 4.