Innovative applications of new technologies for longitudinal measurement

All network activities in this third thematic area will focus on new technologies for data collection and the receptiveness of aging populations to the use of these technologies. Within the scope of methodological innovation in this third area are wearable devices for the collection of health outcomes (e.g., fitbits); passive data collection via smartphone sensors (e.g., steps walked per day, travel patterns); the use of focus groups and participatory design workshops to better understand the receptiveness of aging populations to the use of these devices for measurement; and expanding measurement capabilities (e.g., event-triggered data collection, health trackers (apps), ecological momentary assessment, biomeasures, cognition, etc.).


Bähr, S., Haas, G.-C., Keusch, F., Kreuter, F., & Trappmann, M. (2022). Missing data and other measurement quality issues in mobile geolocation sensor data. Social Science Computer Review, 40, 212-235. 10.1177/0894439320944118

Summary: Smartphones can provide valuable insight into human behavior patterns that cannot be measured through surveys. Although this data can be very useful and convenient to collect, there is some question around the quality of smartphone data, as errors can arise through geolocation measurement, or different individuals sharing a smartphone. 

Cornesse, C, Krieger, U, Sohnius, M-L, et al. From German Internet Panel to Mannheim Corona Study: Adaptable probability-based online panel infrastructures during the pandemic. J R Stat Soc Series A. (2022); 185, 773– 797.

Summary: COVID-19 has created an immediate need for frequently updated information surrounding the societal impacts of the pandemic. The Mannheim Corona Study (MCS) was designed to collect this data, based on the existing probability-based online panel infrastructure of the German Internet Panel (GIP). 

Keusch, F., Bähr, S., Haas, G., Kreuter, F., Trappmann, M., & Eckman, S. (2022). Non‐participation in smartphone data collection using research apps. Journal of the Royal Statistical Society: Series A (Statistics in Society), 185(S2). doi:10.1111/rssa.12827

Summary: Utilizing smartphone applications can be an extremely useful tool for administering surveys and collecting behavioral data. The likelihood of using a smartphone application was found to be lower for women and older adults, as well as for those with higher levels of educational attainment. 

Keusch, F. & Conrad F. G. (2022). Using smartphones to capture and combine self-reports and passively measured behavior in social research. Journal of Survey Statistics and Methodology, 10, 863-885. 10.1093/jssam/smab035

Summary: Smartphones make it possible to collect both self-reported data as well as passively measured behavior data simultaneously. Utilizing these data sources in conjunction with one another can be especially useful in measuring and contextualizing data, but can be difficult to implement due to concerns around privacy and individual’s willingness to share their smartphone data. 

Keusch, F., Wenz, A., & Conrad, F. (2022). Do you have your smartphone with you? Behavioral barriers for measuring everyday activities with smartphone sensors. Computers in Human Behavior, 127, 107054. 10.1016/j.chb.2021.107054

Summary: Smartphones can be extremely useful in collecting data about daily activities (sleep, physical activity, etc.), as they are typically in close proximity to their users. The feasibility of using smartphones to collect this sort of information depends largely on the ability to translate raw smartphone sensor data to activity outcomes, which can be influenced by both sociodemographic and smartphone-related characteristics. 

Rivas, Alda, Christopher Antoun, Shelley Feuer, Thomas Mathew, Elizabeth Nichols, Erica Olmsted-Hawala, and Lin Wang. 2022. “Comparison of Three Navigation Button Designs in Mobile Survey for Older Adults.” Survey Practice, August.

Summary: Given the increase in utilization of smartphones to conduct web surveys, it has become increasingly more important to consider the challenges that older adults may face when taking mobile surveys. Using a within-subjects experimental design (the same participants tested each survey design), this study determined that a below-content design promotes higher data quality and participant satisfaction, and is therefore recommended for use in mobile surveys for older adults.

Trappmann, M., Bähr, S., Malich, S., Keusch, F., Schwarz, S., Haas, G.-C., & Kreuter, F. (2022). Augmenting survey data with other data types: Is there a threat to panel retention? Journal of Survey Statistics and Methodology. Published online before print June 28, 2022. 10.1093/jssam/smac023

Summary: Linking trace data to existing panel survey data can improve the analysis potential of the data, but can be sometimes difficult to implement due to requiring additional consent and completion of tasks from survey participants. In order to address these concerns, a group of participants were invited to install a smartphone app to share additional data, but this request was found to decrease panel retention in the following wave.