Abstract
To deal with drawbacks of paper-based data collection procedures, the QuestionSys approach empowers researchers with none or little programming knowledge to flexibly configure mobile data collection applications on demand. The mobile application approach of QuestionSys mainly pursues the goal to mitigate existing drawbacks of paper-based collection procedures in mHealth scenarios. Importantly, researchers shall be enabled to gather data in an efficient way. To evaluate the applicability of QuestionSys, several studies have been carried out to measure the efforts when using the framework in practice. In this work, the results of a study that investigated psychological insights on the required mental effort to configure the mobile applications are presented. Specifically, the mental effort for creating data collection instruments is validated in a study with participants across two sessions. Thereby, participants were categorized into novices and experts based on prior knowledge on process modeling, which is a fundamental pillar of the developed approach. Each participant modeled 10 instruments during the course of the study, while concurrently several performance measures are assessed (e.g., time needed or errors). The results of these measures are then compared to the self-reported mental effort with respect to the tasks that had to be modeled. On one hand, the obtained results reveal a strong correlation between mental effort and performance measures. On the other, the self-reported mental effort decreased significantly over the course of the study, and therefore had a positive impact on measured performance metrics. Altogether, this study indicates that novices with no prior knowledge gain enough experience over the short amount of time to successfully model data collection instruments on their own. Therefore, QuestionSys is a helpful instrument to properly deal with large-scale data collection scenarios like clinical trials.
Highlights
A multitude of domains, such as healthcare, psychology, and social sciences, still heavily relies on paper-based instruments to collect data in various situations and for different purposes
research questions (RQs) 3: How are the performance measures of novices and experts compared to the self-reported mental effort across all data collection instruments?
How are performance measures of novices and experts compared to the self-reported mental effort across all data collection instruments?
Summary
A multitude of domains, such as healthcare, psychology, and social sciences, still heavily relies on paper-based instruments (e.g., self-report questionnaires [1]) to collect data in various situations and for different purposes. When dealing with large-scale studies like clinical trials, paper-based procedures are time-consuming and error-prone To deal with such shortcomings, many web-based questionnaire applications (e.g., Qualtrics or SmartSurvey) have been developed, allowing researchers to create online questionnaires themselves. In this context, the authors of [2] estimate that 50–60% of the costs related to collecting, transferring, and processing data could be saved when using digital instruments instead of paper-based ones. Smart mobile devices (e.g., smartphones, tablets, etc.), in turn, may provide the required features in order to enable researchers to collect the data in the demanded scenarios, like healthcare [9,10,11]. RQ 3: How are the performance measures of novices and experts compared to the self-reported mental effort across all data collection instruments?
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