Research
My current research focuses on the quality of digital behavioral data and how they can complement survey data to better measure attitudes, behaviors, and social interactions. In particular, I am interested in how to jointly collect self-reports (usually via (mobile) web surveys) and passive measurement from smartphone and wearable sensors, online and device log files, Internet search queries, and other digital traces to better study research questions on migration, employment, and inequality. Below are a number of research projects, I am currently working on:
Concerns and willingness to use smartphones for data collection
Smartphone use is on the rise worldwide, and researchers are exploring novel ways to leverage the capabilities of smartphones for data collection, including mobile surveys and the use of smartphone features that allow researchers to automatically measure an even broader set of characteristics and behaviors of users (e.g., taking pictures of receipts to better measure expenditure, tracking of movements to create exact measures of mobility and transportation, automatically log app use, Internet searches, and phone calling and text messaging behavior to measure social interaction). These new forms of data collection provide rich data and have the potential to decrease respondent burden and measurement error. However, agreeing to engage in these forms of data collection from smartphones is an additional step in the consent process, and participants might feel uncomfortable sharing specific data with researchers due to security, privacy, and confidentiality concerns. Read more...
KODAQS - Competence Center for Data Quality in the Social Sciences
The Competence Center for Data Quality in the Social Sciences (KODAQS) aims to support and communicate the quality-assured use of social science data as a place of learning, research and networking. In addition to the traditional survey or self-report data that is still predominantly used, digital behavioral data and links between these and other data (e.g., geodata) are also included. KODAQs are intended to sensitize researchers to data quality and train them in its determination. Offers will be created that allow the use, processing, analysis and linking of social science data in a transparent and replicable manner. Read more...
Measurement of Physical Activity in older adults through Data Donation (MPADD)
Physical activity (PA) is a key predictor of many health outcomes, especially for older adults. Usually, PA is measured through self-reports which are prone to measurement error. Using an innovative methodological approach, we propose to leverage the fact that many older adults now have smartphones that track PA. Individuals can share these passively collected PA data in a privacy-preserving way through a data donation tool with researchers. We intend to investigate determinants of consent and selection bias in PA data donation among 2,000 individuals aged 50 and older in the Netherlands, to assess the quality of the donated PA data, and to evaluate how multi-source PA data can predict health outcomes. Read more...
Understanding, Measuring, and Alleviating Inequalities in Digital Technology Use
Digital technologies, such as smartphones and tablets, are increasingly integrated into people's everyday lives. Social scientists have also started to use these technologies for data collection, such as through apps and sensors embedded in smartphones and wearable devices. Despite the increasing device penetration in the general population, inequalities in the access to and use of digital technologies persist, reflecting existing social inequalities. Digital exclusion additionally becomes a methodological issue if the digitally disadvantaged population subgroups are not well represented in social studies.
The project investigates digital inequalities in Europe and the United States by focusing on three aims: 1) studying the correlates and mechanisms of digital technology acceptance, 2) improving the measurement of digital skills and technology use, and 3) identifying effective interventions to reduce inequalities in digital technology use. Read more...
Willingness to link digital behavioral data in surveys
The widespread use of digital technologies including smartphones, wearables, and other IoT-devices produce a plethora of digital behavioral data about how people interact with online systems but also about their behaviors and social interactions in the real world (e.g., physical activity, health, mobility). The transformative potential of digital technologies in data collection allows researchers to go beyond traditional survey methods and incorporate additional sources to enhance the richness of datasets in the social sciences. However, low willingness of individuals to link and share digital behavioral data with data from self-reports limits its current application due to concerns about bias. Read more...
Past projects
Concerns and willingness to use smartphones for data collection
Smartphone use is on the rise worldwide, and researchers are exploring novel ways to leverage the capabilities of smartphones for data collection, including mobile surveys and the use of smartphone features that allow researchers to automatically measure an even broader set of characteristics and behaviors of users (e.g., taking pictures of receipts to better measure expenditure, tracking of movements to create exact measures of mobility and transportation, automatically log app use, Internet searches, and phone calling and text messaging behavior to measure social interaction). These new forms of data collection provide rich data and have the potential to decrease respondent burden and measurement error. However, agreeing to engage in these forms of data collection from smartphones is an additional step in the consent process, and participants might feel uncomfortable sharing specific data with researchers due to security, privacy, and confidentiality concerns. Read more...
KODAQS - Competence Center for Data Quality in the Social Sciences
The Competence Center for Data Quality in the Social Sciences (KODAQS) aims to support and communicate the quality-assured use of social science data as a place of learning, research and networking. In addition to the traditional survey or self-report data that is still predominantly used, digital behavioral data and links between these and other data (e.g., geodata) are also included. KODAQs are intended to sensitize researchers to data quality and train them in its determination. Offers will be created that allow the use, processing, analysis and linking of social science data in a transparent and replicable manner. Read more...
Measurement of Physical Activity in older adults through Data Donation (MPADD)
Physical activity (PA) is a key predictor of many health outcomes, especially for older adults. Usually, PA is measured through self-reports which are prone to measurement error. Using an innovative methodological approach, we propose to leverage the fact that many older adults now have smartphones that track PA. Individuals can share these passively collected PA data in a privacy-preserving way through a data donation tool with researchers. We intend to investigate determinants of consent and selection bias in PA data donation among 2,000 individuals aged 50 and older in the Netherlands, to assess the quality of the donated PA data, and to evaluate how multi-source PA data can predict health outcomes. Read more...
Understanding, Measuring, and Alleviating Inequalities in Digital Technology Use
Digital technologies, such as smartphones and tablets, are increasingly integrated into people's everyday lives. Social scientists have also started to use these technologies for data collection, such as through apps and sensors embedded in smartphones and wearable devices. Despite the increasing device penetration in the general population, inequalities in the access to and use of digital technologies persist, reflecting existing social inequalities. Digital exclusion additionally becomes a methodological issue if the digitally disadvantaged population subgroups are not well represented in social studies.
The project investigates digital inequalities in Europe and the United States by focusing on three aims: 1) studying the correlates and mechanisms of digital technology acceptance, 2) improving the measurement of digital skills and technology use, and 3) identifying effective interventions to reduce inequalities in digital technology use. Read more...
Willingness to link digital behavioral data in surveys
The widespread use of digital technologies including smartphones, wearables, and other IoT-devices produce a plethora of digital behavioral data about how people interact with online systems but also about their behaviors and social interactions in the real world (e.g., physical activity, health, mobility). The transformative potential of digital technologies in data collection allows researchers to go beyond traditional survey methods and incorporate additional sources to enhance the richness of datasets in the social sciences. However, low willingness of individuals to link and share digital behavioral data with data from self-reports limits its current application due to concerns about bias. Read more...
Past projects