I've been reading a very interesting book on daily diary surveys. One of the chapters, by Norbert Schwarz, makes some interesting points about how frequent measurement might not be the same as a one-time measurement of similar phenomena.
Schwarz points to the well-known studies that he did where they varied the scale of measurement. One of the questions was about how much TV people watch. One scale had a maximum of something like 10 or more hours per week, while the other had a maximum of 2.5 hours per week. The reported distributions changed across the two different scales. It seems that people were taking normative cues from the scale, i.e. if 2.5 hours is a lot, "I must view less than that," or "I don't want to report that I watch that much TV when most other people are watching less."
He points out that daily surveys may provide similar context clues about normative behavior. If you ask someone about depressive episodes every day, they may infer that the norm is to have frequent depressive episodes. This may influence their response. If the goal is to get more accurate data, these sorts of influences of the method are not good.
Schwarz points to the well-known studies that he did where they varied the scale of measurement. One of the questions was about how much TV people watch. One scale had a maximum of something like 10 or more hours per week, while the other had a maximum of 2.5 hours per week. The reported distributions changed across the two different scales. It seems that people were taking normative cues from the scale, i.e. if 2.5 hours is a lot, "I must view less than that," or "I don't want to report that I watch that much TV when most other people are watching less."
He points out that daily surveys may provide similar context clues about normative behavior. If you ask someone about depressive episodes every day, they may infer that the norm is to have frequent depressive episodes. This may influence their response. If the goal is to get more accurate data, these sorts of influences of the method are not good.
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