Experience sampling method

Overview

There are different ways to signal participants when to take notes in their journal or complete a questionnaire, like using preprogrammed stopwatches. An observer can have an identically programmed stopwatch, so the observer can record specific events as the participants are recording their feelings or other behaviors. It is best to avoid letting subjects know in advance when they will record their feelings, so they can't anticipate the event, and will just be "acting naturally" when they stop and take notes on their current condition. Conversely, some statistical techniques require roughly equidistant time intervals, which has the limitation that assessments can be anticipated. Validity in these studies comes from repetition, so you can look for patterns, like participants reporting greater happiness right after meals. For instance, Stieger and Reips were able to replicate and refine past research about the dynamics of well-being fluctuations during the day (low in the morning, high in the evening) and over the course of a week (low just before the beginning of the week, highest near the end of the week). These correlations can then be tested by other means for cause and effect, such as vector autoregression, since ESM just shows correlation. Moreover, by using the experience sampling method different research questions can be analyzed regarding the use of mobile devices in research. Following on from this, Stieger and colleagues used the experience sampling method to show that smartphones can be used to transfer computer-based tasks (CBTs) from the lab to the field.

Some authors also use the term experience sampling to encompass passive data derived from sources such as smartphones, wearable sensors, the Internet of Things, email and social media that do not require explicit input from participants. These methods can be advantageous as they impose less demand on participants improving compliance and allowing data to be collected for much longer periods, are less likely to change the behaviour being studied and allow data to be sampled at much higher rates and with greater precision. Many research questions can benefit from both active and passive forms of experience sampling.