Abstract
To compare the quality of data collection via electronic data capture (EDC) with voiced questionnaire (QNN) and data image capture features using a tablet versus standard paper-based QNN, to assess the user's perception of using the EDC tool, and to compare user satisfaction with the two methods. Randomised cross-over study. Study sites: This study was conducted in two villages along the Thailand-Myanmar border. This study included 30 community health volunteers (CHVs) and 120 Karen hill tribe villagers. Employing a cross-over study design, the CHVs were allocated randomly to two groups, in which they performed interviews in different sequences using EDC and QNN. Data discrepancies were found between the two data-collection methods, when data from the paper-based and image-capture methods were compared, and when conducting skip pattern questions. More than 90% of the CHVs perceived the EDC to be useful and easy to use. Both interviewers and interviewees were more satisfied with the EDC compared with QNN in terms of format, ease of use, and system speed. The EDC can effectively be used as an alternative method to paper-based QNNs for data collection. It produces more accurate data that can be considered evidence-based.
Highlights
Paper-based questionnaires (QNNs) are commonly used for data collection in public health surveys, and though they are simple to use and practical, they have several drawbacks and problems
The Electronic data capture (EDC) can effectively be used as an alternative method to paperbased QNNs for data collection
This study revealed that EDC can be used effectively for data collection as an alternative method to QNN
Summary
Paper-based questionnaires (QNNs) are commonly used for data collection in public health surveys, and though they are simple to use and practical, they have several drawbacks and problems. Once data have been collected, more errors are introduced during subsequent data entry into a relational database. These obstacles during data collection risk producing low data quality and lead to decisions based on the wrong information. An alternative is to collect data electronically, a method that could reduce errors commonly found in QNN. Electronic data capture (EDC) instruments for data collection have become more recognised due to the falling cost of devices and continued enhancements to their performance
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