Measuring Mental Effort for Creating Mobile Data Collection Applications.

Int J Environ Res Public Health

Institute of Clinical Epidemiology and Biometry, University of Würzburg, 97070 Würzburg, Germany.

Published: March 2020

AI Article Synopsis

  • QuestionSys helps researchers with little programming experience create mobile data collection apps to replace traditional paper methods, especially in mHealth.
  • The study evaluates how much mental effort is required for users to configure data collection instruments, comparing novices and experts across various performance metrics.
  • Results show that while mental effort is strongly related to performance, novices quickly improve their skills, suggesting QuestionSys effectively supports large-scale data collection in clinical settings.

Article 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 N = 80 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7084515PMC
http://dx.doi.org/10.3390/ijerph17051649DOI Listing

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