ESM includes sampling methods that allow researchers to study ongoing experiences and events by taking assessments one or more times per day per participant (n=1) in the naturally occurring social environment.
[1][2] ESM enables researchers to study the prevalence of behaviors, promote theory development, and to serve an exploratory role.
The frequent sampling of events inherent in ESM enables researchers to measure the typology of activity and detect the temporal and dynamic fluctuations of experiences (e.g., at work, or in a relationship).
[3] In ESM, participants are asked to record their experiences and perceptions in a paper or electronic diary.
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.
[5] 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 high rates and with greater precision.
For example, it might be logical to use ESM in order to answer research questions which involve dependent variables with a great deal of variation throughout the day.
However, it is not likely that utilizing ESM will yield meaningful predictions when measuring someone performing a repetitive task throughout the day, when outcomes are long-term in nature (e.g., coronary heart problems), or inherently stable variables.