In sum, the collection of self-report data has undergone an interesting evolution. From studies involving interviews to those using electronic diaries to collect momentary data, the techniques for understanding peoples' experiences have become more refined, comprehensive, and have moved from the office to the field. Some of the challenges that researchers using EMA (in particular, with EDs)
must address are analytical issues (handling and interpreting the large amount of data generated) and cost issues incurred from using state-of-the-art technology (both hardware and software). However, the benefits include having a large amount of data for each individual (making clinically relevant, within-person analyses possible), being able to monitor compliance (thus, being confident that compliance is not being "faked"), assessing people in their normal environment (to increase ecological validity), and making decisions a priori about the time frame to assess each construct (to reduce recall bias). Depending on the research hypothesis being studied, these benefits may outweigh the challenges. Thus, EMA is the next step for self-report research to attain the goal of measuring real-world data.
FIGURE 6.4. A visual display of the design and materials in the cup Web experiment, showing the four experimental conditions to which participants are randomly distributed as well as the folders and Web pages used in the Web experiment. The display is created in Step 9 in WEXTOR.
Visual display of your experimental design
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