Measuring Mental Effort for Creating Mobile Data Collection Applications
peer-reviewed
Erstveröffentlichung
2020-03-03Autoren
Schobel, Johannes
Probst, Thomas
Reichert, Manfred
Schlee, Winfried
Schickler, Marc
Wissenschaftlicher Artikel
Erschienen in
International Journal of Environmental Research and Public Health ; 17 (2020), 5. - Art.-Nr. 1649. - eISSN 1660-4601
Link zur Originalveröffentlichung
https://dx.doi.org/10.3390/ijerph17051649Fakultäten
Fakultät für Ingenieurwissenschaften, Informatik und PsychologieMedizinische Fakultät
Institutionen
Institut für Medizinische SystembiologieInstitut für Datenbanken und Informationssysteme
Externe Kooperationen
Donau-Universität KremsUniversität Regensburg
Julius-Maximilians-Universität Würzburg
Dokumentversion
Veröffentlichte Version (Verlags-PDF)Zusammenfassung
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
Publikationsförderung
Gefördert vom Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg
Open-Access-Förderung durch die Universität Ulm
Open-Access-Förderung durch die Universität Ulm
Schlagwörter
[GND]: Telemedizin[MeSH]: Telemedicine | Mobile applications
[Freie Schlagwörter]: data collection | smart mobile devices | end-user programming | mental effort | usability study
[DDC Sachgruppe]: DDC 000 / Computer science, information & general works | DDC 150 / Psychology
Metadata
Zur LanganzeigeDOI & Zitiervorlage
Nutzen Sie bitte diesen Identifier für Zitate & Links: http://dx.doi.org/10.18725/OPARU-36777
Schobel, Johannes et al. (2021): Measuring Mental Effort for Creating Mobile Data Collection Applications. Open Access Repositorium der Universität Ulm und Technischen Hochschule Ulm. http://dx.doi.org/10.18725/OPARU-36777
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