EMA rely on sampling moments from peoples' daily lives with a sampling protocol chosen according to the purpose(s) of the study (Delespaul, 1995; Wheeler & Reis, 1991). A few examples demonstrate this point. If the goal of a study was to measure the level of a person's fatigue, then many reports of momentary fatigue would likely be averaged to provide a single measure of fatigue. However, for this measure to represent all possible moments that a person could have been sampled, the sampling should be done randomly throughout the day. If this was not done and reports were taken primarily in the morning hours, then it is easy to see how an average taken from that sampling scheme is likely to be biased (toward whatever level of fatigue was typical for mornings). Thus, random sampling (and high levels of compliance) is crucial for providing unbiased estimates of typical experiences. A second, entirely different sampling protocol is necessary if an investigator was concerned with understanding the antecedents of an event (e.g., smoking a cigarette). In this case, it is important that a report be made just before the onset of smoking. This is called event-driven sampling and is predicated on having participants monitor their thoughts or actions and initiate a report whenever an event occurs or a threshold on a subjective variable (e.g., craving) is met. The third sampling scheme is based entirely on time (either time-of-day or time intervals) and is called interval-contingent sampling. An example of this protocol is to signal individuals every hour or every 20 minutes to make a recording. Actually, many ambulatory blood pressure monitors operate on exactly this scheme, and the investigator can adjust the interval between blood pressure readings. One issue with this sampling scheme considered important for self-reported data is that participants may come to expect signals given their predictability and alter their behavior so that they are able to make a report.
Although these three schemes represent the main classes used to date, a couple of comments are in order. First, one might wonder about the need for any sampling scheme whatsoever (i.e., why not have participants make recordings throughout the day when convenient?). In fact, some versions of pain diaries do just that or specify broad blocks of time (e.g., afternoon) for making recordings. The objection to this form of sampling is that participants will pick and choose the times in nonrandom ways that may be correlated with predictions or outcomes. For instance, in sampling pain levels in patients with chronic pain, patients may select times when they are in greater than average pain, believing that the investigator is interested in such times. Alternatively, periods of extreme pain might not be selected for reports, because the individual is so incapacitated that participating in research is the furthest activity from his or her mind. Either of these forms of self-selection have the capacity to distort our understanding of pain. Second, it is not unusual for research studies to incorporate two or more sampling schemes to meet study goals. Such hybrid protocols may not only be desirable, but in many instances are also conceptually necessary.
To return to the example of the antecedents of cigarette smoking (Shiffman et al., 2002), the information (e.g., examination of momentary stress levels to address the hypothesis that increased stress leads to smoking) collected from event-driven sampling indicates that stress was at a particular level prior to smoking. But with what stress levels should the data be compared to test the hypothesis? Some might argue that stress levels taken at random points throughout the day (random sampling)
might be the appropriate comparison, because the investigator could then conclude, compared to other times of the day, that stress was higher just before smoking. One could strengthen this result by determining the social and setting characteristics of the smoking episodes and then select episodes with those qualities from the random sampling. This eliminates the argument that it wasn't high stress that was associated with smoking, but certain situations or settings. Clearly, the strategy of using more than one type of sampling could prove useful for refining hypothesis testing.
Was this article helpful?
Did You Ever Thought You Could Quit Smoking And Live A Healthy Life? Here Are Some Life Saving Tips On How To Do It. Have you ever thought about quitting smoking, but either thought it was impossible or just simply wasn’t that important? Research shows that most smokers do want to quit smoking and they are waiting for that auspicious day eagerly.