Talk:Experience sampling method

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Software

I;ve just added a link to a paper which describes available ESM software, but wonder whether some of this information should be included on this page? For example, we could have a list of commercial and open-source software used to run ESM studies, with links to the wiki pages for the larger projects, or websites for others. - Any thoughts? — Preceding unsigned comment added by Benwhalley (talk • contribs) 14:33, 5 December 2013 (UTC)[reply]

Section from Sampling (statistics)

The following section was added to the Sampling (statistics) article by User:Rucheleh. It was not well integrated and seemed too detailed for inclusion there, so I've moved it here for incorporation into this article. -- Avenue (talk) 21:44, 16 February 2009 (UTC)[reply]

Experience Sampling

Experience Sampling Methodology (ESM) differs from the above sampling techniques in that its focus is on data sampling over time, rather than participant sampling. Thus, it can be used in conjunction with one of the above techniques when appropriate. For example, within a randomly selected set of participants, data representing a variety of constructs, such as behavior, stress, attitudes, and physiological states, can be collected repeatedly over time. This allows a researcher to investigate participant states that may change over time. For example, if a researcher wanted to study how mood varies across the span of a day, he or she could select participants using random sampling from the sampling frame, and then administer surveys at multiple points during the day to assess the participants' moods. The key point is that while other sampling methods affect the ability to generalize to the whole population of interest, ESM enables generalization to the experience of interest over time. Using the above example, perhaps a researcher would conclude that in general, moods are highest in the morning and evening, and lower in the middle of the day.

There are multiple methods and techniques for conducting ESM. For example, measures such as diaries, questionnaires, or physiological monitoring (e.g., a heart rate monitor) can be used to collect data. In terms of when data is collected, there are several alternatives:

Event-Contingent ESM- data is recorded when significant events/experiences occur.
Interval-Contingent ESM- data is recorded at equal intervals.
Signal-Contingent ESM- data is collected at random intervals, whenever a signal (e.g., a watch that randomly beeps at various times)occurs. This approach can be especially helpful in preventing recall bias due to the participant "figuring out" when the next signal will be, and is therefore also useful when signals are closer together, such as when multiple measurements are taken within a single day.