Includes bibliographical references. / Objective: To determine the accuracy, measured by error rate, with which Clinical Research Workers (CRWs), with minimal experience in data entry, could capture data on a feature phone during an interview using two different mobile phone applications, compared to the accuracy with which they could record data on paper Case Report Forms (CRFs). Design: A comparative study was performed where 10 participating CRWs performed 90 mock interviews using either paper CRFs or one of two mobile phone applications. The phone applications were a commonly used open source application and an application custom built for this study that followed a simplified, less flexible user interface paradigm. The answers to the interview questions were randomly generated and provided to the interviewees in sealed envelopes prior to the scheduling of the mock interview. Error rates of the captured data were calculated relative to the randomly generated expected answers. Results and Conclusion: The study aimed to show that error rates of clinical research data captured using a mobile phone application would not be inferior to data recorded on paper CRFs. For the custom application, this desired result was not found unequivocally. An error in judgment when designing the custom phone application resulted in dates being captured in a manner unfamiliar to the study participants, leading to high error rates for this type of data. If this error is condoned by excluding the date type from the results for the custom application, the custom application is shown to be non-inferior, at the 95 confidence level, to standard paper forms when capturing data for clinical research.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/9200 |
| Date | January 2014 |
| Creators | Workman, Michael |
| Contributors | Marsden, Gary, Hawkridge, Anthony |
| Publisher | University of Cape Town, Faculty of Science, Department of Computer Science |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Master Thesis, Masters, MSc |
| Format | application/pdf |
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