Details
Originalsprache | Englisch |
---|---|
Aufsatznummer | 627509 |
Fachzeitschrift | Frontiers in Public Health |
Jahrgang | 9 |
Publikationsstatus | Veröffentlicht - 20 Sept. 2021 |
Extern publiziert | Ja |
Abstract
Digital health data that accompany data from traditional surveys are becoming increasingly important in health-related research. For instance, smartphones have many built-in sensors, such as accelerometers that measure acceleration so that they offer many new research possibilities. Such acceleration data can be used as a more objective supplement to health and physical fitness measures (or survey questions). In this study, we therefore investigate respondents' compliance with and performance on fitness tasks in self-administered smartphone surveys. For this purpose, we use data from a cross-sectional study as well as a lab study in which we asked respondents to do squats (knee bends). We also employed a variety of questions on respondents' health and fitness level and additionally collected high-frequency acceleration data. Our results reveal that observed compliance is higher than hypothetical compliance. Respondents gave mainly health-related reasons for non-compliance. Respondents' health status positively affects compliance propensities. Finally, the results show that acceleration data of smartphones can be used to validate the compliance with and performance on fitness tasks. These findings indicate that asking respondents to conduct fitness tasks in self-administered smartphone surveys is a feasible endeavor for collecting more objective data on physical fitness levels.
ASJC Scopus Sachgebiete
- Medizin (insg.)
- Öffentliche Gesundheit, Umwelt- und Arbeitsmedizin
Ziele für nachhaltige Entwicklung
Zitieren
- Standard
- Harvard
- Apa
- Vancouver
- BibTex
- RIS
in: Frontiers in Public Health, Jahrgang 9, 627509, 20.09.2021.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Squats in Surveys
T2 - Investigating the Feasibility of, Compliance With, and Respondents' Performance on Fitness Tasks in Self-Administered Smartphone Surveys Using Acceleration Data
AU - Elevelt, Anne
AU - Höhne, Jan Karem
AU - Blom, Annelies G.
N1 - Funding Information: The authors acknowledge that the data collection of the web survey was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) through the Collaborative Research Center (SFB) 884 Political Economy of Reforms (SFB 884; Project-ID: 139943784). Furthermore, the authors acknowledge that the first author's stay in Mannheim was funded by the German Acadamic Exchange Service (Deutscher Akademischer Austaschdienst; DAAD; Research Tandem Grant). In addition, the authors would like to thank Peter Lugtig (Utrecht University), Daniel Qureshi (University of Frankfurt), Stephan Schlosser (University of Göttingen), and Vera Toepoel (Utrecht University) for their cooperation, inspiration, and support.
PY - 2021/9/20
Y1 - 2021/9/20
N2 - Digital health data that accompany data from traditional surveys are becoming increasingly important in health-related research. For instance, smartphones have many built-in sensors, such as accelerometers that measure acceleration so that they offer many new research possibilities. Such acceleration data can be used as a more objective supplement to health and physical fitness measures (or survey questions). In this study, we therefore investigate respondents' compliance with and performance on fitness tasks in self-administered smartphone surveys. For this purpose, we use data from a cross-sectional study as well as a lab study in which we asked respondents to do squats (knee bends). We also employed a variety of questions on respondents' health and fitness level and additionally collected high-frequency acceleration data. Our results reveal that observed compliance is higher than hypothetical compliance. Respondents gave mainly health-related reasons for non-compliance. Respondents' health status positively affects compliance propensities. Finally, the results show that acceleration data of smartphones can be used to validate the compliance with and performance on fitness tasks. These findings indicate that asking respondents to conduct fitness tasks in self-administered smartphone surveys is a feasible endeavor for collecting more objective data on physical fitness levels.
AB - Digital health data that accompany data from traditional surveys are becoming increasingly important in health-related research. For instance, smartphones have many built-in sensors, such as accelerometers that measure acceleration so that they offer many new research possibilities. Such acceleration data can be used as a more objective supplement to health and physical fitness measures (or survey questions). In this study, we therefore investigate respondents' compliance with and performance on fitness tasks in self-administered smartphone surveys. For this purpose, we use data from a cross-sectional study as well as a lab study in which we asked respondents to do squats (knee bends). We also employed a variety of questions on respondents' health and fitness level and additionally collected high-frequency acceleration data. Our results reveal that observed compliance is higher than hypothetical compliance. Respondents gave mainly health-related reasons for non-compliance. Respondents' health status positively affects compliance propensities. Finally, the results show that acceleration data of smartphones can be used to validate the compliance with and performance on fitness tasks. These findings indicate that asking respondents to conduct fitness tasks in self-administered smartphone surveys is a feasible endeavor for collecting more objective data on physical fitness levels.
KW - acceleration data
KW - compliance
KW - fitness task
KW - physical fitness measures
KW - smartphone survey
KW - SurveyMotion
UR - http://www.scopus.com/inward/record.url?scp=85116497003&partnerID=8YFLogxK
U2 - 10.3389/fpubh.2021.627509
DO - 10.3389/fpubh.2021.627509
M3 - Article
C2 - 34616703
AN - SCOPUS:85116497003
VL - 9
JO - Frontiers in Public Health
JF - Frontiers in Public Health
M1 - 627509
ER -