Can Happiness Apps Generate Nationally Representative Datasets? - a Case Study Collecting Data on People’s Happiness Using the German Socio-Economic Panel
- 101 Downloads
In the last few years, apps have become an important tool to collect data. Especially in the case of data on people’s happiness, two projects have received substantial attention from both the media and the scientific world: “Track your happiness” from Killingsworth and Gilbert (Science, 330, 932-932, 2010), and “Mappiness,” from MacKerron (2012). Both happiness apps used the experience sampling method to ask people a few times per day how they feel, what they do, with whom, and where. The collected data are then displayed for the participants in simple graphs to help them understand what makes them happy and what does not. Both studies have collected considerable data without giving participants any financial rewards. But quantity is not everything that matters with respect to data collection, and thus, understanding whether nationally representative datasets can be collected using such happiness apps is crucial. To address this question, we built a new happiness app and ran a case-study with over 4000 participants of the innovation sample of the German Socio-Economic Panel (Richter and Schupp in Schmollers Jahrbuch, 135(3), 389–399, 2015). Participants were informed that the app collects data on everyday happiness after a household interview and asked whether they would like to use the app. In the first year (2015), participants did not receive any reward, and in the second year (2016), a different group of participants received a 50 Euro Amazon voucher for their participation. The results showed that our happiness app cannot generate nationally representative datasets if it is not controlled that all demographic sub-groups have access to a smartphone, are highly motivated with a sufficient reward and data is collected with quota sampling.
KeywordsApp surveys Representativity Happiness Experience sampling method Day reconstruction method
Compliance with Ethical Standards
Conflict of Interest
We hereby confirm that no one of the authors has any conflict of interest with this publication. Additionally, we declare that this research was conducted in line with the Declaration of Helsinki which explains all main rules for human research ethics.
- German Census (2011). https://www.destatis.de/DE/Methoden/Zensus_/Zensus.html. Retrieved: October 20th 2017.
- German Statistical Office (2015). https://www.destatis.de/DE/PresseService/Presse/Pressemitteilungen/2015/05/PD15_172_631.html Retrieved: October 20th 2017.
- Kantar World Panel (2015). https://www.kantarworldpanel.com/global/smartphone-os-market-share/intro. Retrieved: October 20th 2017.
- Ludwigs, K. & Erdtmann, S. (2017). The happiness analyzer – A new technique for measuring subjective well-being. Working Paper. Google Scholar
- MacKerron, G. (2012). Happiness and environmental quality. PhD thesis, London School of Economics and Political Science. Available from: http://etheses.lse.ac.uk/383/. Retrieved: October 25th 2017.
- OECD (2013). OECD guidelines on measuring subjective well-being. OECD Publishing. https://doi.org/10.1787/9789264191655-en. Retrieved: October 26th 2017.
- Sarracino, F., Riillo, C. A. F., & Mikucka, M. (2017). Comparability of web and telephone surveys for the measurement of subjective well-being. Survey Research Methods, 11(2), 141–169.Google Scholar
- Statista (2019). https://www.statista.com/statistics/568095/predicted-smartphone-user-penetration-rate-in-germany/ Retrieved: March 12th 2019.
- Vicente, P., & Lopes, I. (2016). Attitudes of older mobile phone users towards mobile phones. Communications-European Journal of Communication Research, (1), 71–86.Google Scholar