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Measuring Mental Effort for Creating Mobile Data Collection Applications

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ijerph-17-01649-v2.p ... (1.602Mb)

peer-reviewed

Erstveröffentlichung
2020-03-03
Autoren
Schobel, Johannes
Probst, Thomas
Reichert, Manfred
Schlee, Winfried
Schickler, Marc
et al.
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/ijerph17051649
Fakultäten
Fakultät für Ingenieurwissenschaften, Informatik und Psychologie
Medizinische Fakultät
Institutionen
Institut für Medizinische Systembiologie
Institut für Datenbanken und Informationssysteme
Externe Kooperationen
Donau-Universität Krems
Universität 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
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
Lizenz
CC BY 4.0 International
https://creativecommons.org/licenses/by/4.0/

Metadata
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DOI & 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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