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Experience Sampling Method
The experience sampling method (ESM) is a strategy for gathering information from individuals about their experience of daily life as it occurs. The method can be used to gather both qualitative and quantitative data, with questions for participants that are tailored to the purpose of the research. It is a phenomenological approach, meaning that the individual’s own thoughts, perceptions of events, and allocation of attention are the primary objects of study. In the prototypical ESM study, a smartphone application is used to signal participants randomly five to ten times daily, and at each signal they complete a brief questionnaire on the phone. Items elicit information regarding the participants’ location at the moment of the signal, as well as their activities, thoughts, social context, mood, cognitive efficiency, and motivation. Researchers have used ESM to study the effects of television viewing on mood and motivation, the dynamics of family relations, the development of adolescents, the experience of engaged enjoyment (or flow), and many mental and physical health issues. Other terms for ESM include time sampling, ambulatory assessment, and ecological momentary assessment; these terms may or may not signify the addition of other types of measures, such as of physiological markers, to the protocol.
Designing a Study Using ESM
In ESM studies, researchers need to select a sample of people from a population, but they must also choose a method to select a sample of moments from the population of all moments of experience. Many studies make use of signal-contingent sampling, a stratified random approach in which the day is divided into equal segments and the participant is signaled at a random moment during each segment. Other possibilities are to signal the participant at the same times every day (interval-contingent sampling) or to ask the participant to respond after every occurrence of a particular event of interest (event-contingent sampling). The number of times per day and the number of days that participants are signaled are parameters that can be tailored based on the research purpose and practical matters.
Before smartphone use became normative, researchers used a wristwatch or pager as a signaling device and a pen with a booklet of blank questionnaires as a recording device. This option is of course still viable and may be best for certain populations and contexts (e.g., prisons). For studies using smartphones, there is a wide variety of free and commercial applications for conducting an ESM study and a growing array of software or hardware add-ons to record data related to physical movement, GPS location, and physiological measures such as heart rate or neuroendocrine levels. Some designs also capture audio and video recordings. One design decision researchers must make is whether to allow for open-ended responses or to ask participants to choose from a list of options (e.g., with respect to locations or activities). The former provides greater richness to the data but may require more time and effort to analyze.
Analysis of ESM Data
The many repeated self-reports from each ESM participant over short time intervals result in what has been called intensive longitudinal data or micro-longitudinal data. Given that multiple waves of data are nested within each person, multilevel modeling (also called hierarchical linear modeling or mixed effects random regression analysis) is a recommended analytical strategy to avoid violating the independence assumption. These procedures allow the researcher to separate response-level from person-level effects and thereby test predictors of both intraindividual and interindividual variability.
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