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Comparing Paper and Tablet Modes of Retrospective Activity Space Data Collection
Scott T Yabiku1, Jennifer E Glick1, Elizabeth A Wentz2
1The Pennsylvania State University.
Summary
A new tablet-based approach significantly improved the accuracy of collecting activity space data compared to traditional paper maps. This method particularly benefited older and less healthy individuals in Nepal.
Area of Science:
- Social Sciences
- Human Geography
- Health Research
Background:
- Understanding human behavior requires accurate social context data, but collecting this data, especially activity spaces, is challenging.
- Existing methods for mapping activity spaces often lack precision, limiting research on behavior and well-being.
- Research on the influence of spatial context on human actions and health is hindered by data collection difficulties.
Purpose of the Study:
- To evaluate the accuracy of a computer-assisted interviewing (CAI) tablet-based approach for collecting activity space data.
- To compare the accuracy of the tablet approach against a traditional paper map-based method.
- To identify respondent subgroups that benefit most from the tablet-based data collection method.
Main Methods:
- A study was conducted in Chitwan, Nepal, comparing tablet-based CAI with paper map-based methods for activity space data collection.
- On-the-ground staff verified the accuracy of respondent-indicated locations against known locations.
- Statistical analysis examined differences in data accuracy between the two methods and across different respondent demographics.
Main Results:
- The tablet-based CAI approach demonstrated higher accuracy in recording activity space data compared to the paper map method.
- Verification by on-the-ground staff confirmed the superior accuracy of the tablet-derived location data.
- Older respondents and those reporting poorer health showed a greater improvement in data accuracy when using the tablet mode.
Conclusions:
- Tablet-based computer-assisted interviewing offers a more accurate method for collecting activity space data in diverse populations.
- This technology enhances data precision, particularly for vulnerable subgroups like older or less healthy individuals.
- Improved activity space data collection can facilitate more robust research into the links between spatial context, human behavior, and well-being.
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