Measuring Mental Effort for Creating Mobile Data Collection Applications
Bibliographic Data
| ID | 15477383 |
|---|---|
| Authors | Johannes Schobel (0000-0002-6874-9478, Universität Ulm, corresponding author), Thomas Probst (0000-0002-6113-2133, Universität für Weiterbildung Krems), Manfred Reichert (0000-0003-2536-4153, Universität Ulm), Winfried Schlee (0000-0001-7942-1788, University of Regensburg), Marc Schickler (0000-0003-4774-6670, Universität Ulm), Hans A Kestler (0000-0002-4759-5254, Universität Ulm), Rüdiger Pryss (0000-0003-1522-785X, University of Würzburg) |
| Year | 2020 |
| Volume | 17 |
| Issue | 5 |
| Pages | 1649-1649 |
| Publication date | 2020-03-03 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph17051649 |
| PMID | 32138381 |
| OpenAlex | W3010109773 |
| Language | EN |
| Citations received | 2 |
| References cited | 33 |
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
Data collection · Data mining · Data science · Measure (data warehouse · mHealth · Mobile device · Process (computing · Psychological intervention · World Wide Web · Computer Science · Digital Mental Health Interventions · Mobile Health and mHealth Applications · Psychology · Technology Adoption and User Behaviour
| Citations per year | 0.4 |
|---|---|
| Citation span | 2021 - 2021 (1) |
| Highly cited | No |