Participation in a mobile app survey to collect expenditure data as part of a large-scale probability household panel: response rates and response biases (original) (raw)
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Survey research methods, 2019
This paper examines non-response in a mobile app study designed to collect expenditure data. We invited 2,383 members of the nationally representative Understanding Society Innovation Panel in Great Britain to download an app to record their spending on goods and services: participants were asked to scan receipts or report spending directly in the app every day for a month. We examine participation at different stages of the process. We further use data from the prior wave of the panel to examine the prevalence of potential barriers to participation, including access, ability and willingness to use different mobile technologies, and biases in the types of people who participate, considering socio-demographic characteristics, financial position and financial behaviours. While the participation rate was low, drop out was also low: over 80% of participants remained in the study for the full month. The main barriers to participation were access to, and frequency of use of mobile devices...
Mobile Research Methods: Opportunities and challenges of mobile research methodologies, 2015
In most countries the spread of mobile devices in the general population has increased very quickly in the last years, changing people's habits of accessing and using the web. Because of this, if one wants to involve respondents who access the web with the new devices, it is necessary to adapt web surveys to these devices. Nowadays, even if some probability-based online panels exist, the large majority of web surveys are done by means of non-probability-based panels (also called 'opt-in' or 'access' panels). People volunteer to participate in these panels. Thus, we can expect that the spread of mobile devices in these panels differs from the spread of mobile devices in the general population and is probably higher. However, little is known about the exact spread of different mobile devices (tablets and smartphones) within the population of panelists in access panels. Moreover, little knowledge has been acquired about which combination of devices panelists have, in general and in different countries. However, this is crucial information, since access panels represent the majority of web surveys and the participation of the panelists in these surveys is conditioned by the equipment they own. Therefore, in this chapter we study data How to cite this book chapter:
Sociological Methods & Research
Researchers are combining self-reports from mobile surveys with passive data collection using sensors and apps on smartphones increasingly more often. While smartphones are commonly used in some groups of individuals, smartphone penetration is significantly lower in other groups. In addition, different operating systems (OSs) limit how mobile data can be collected passively. These limitations cause concern about coverage error in studies targeting the general population. Based on data from the Panel Study Labour Market and Social Security (PASS), an annual probability-based mixed-mode survey on the labor market and poverty in Germany, we find that smartphone ownership and ownership of smartphones with specific OSs are correlated with a number of sociodemographic and substantive variables. The use of weighting techniques based on sociodemographic information available for both owners and nonowners reduces these differences but does not eliminate them.
Computers, Tablets, and Smart Phones: The Truth About Web-based Surveys
The exponential increase of smart phone, tablet, and laptop use places the topic of web-based surveys at the center of survey methodology discussions. As individuals now have a variety of options for taking online surveys, researchers must understand who completes their surveys through which device as it may impact completion rates and data quality. The analysis of two national online surveys (n=487 and n=1,046) revealed that individuals utilizing smart phones to complete the studies were signi cantly younger than those accessing surveys through computers, while only one study indicated a signi cant gender difference with females using smart phones more than males. Additionally, data showed that the respondent’s level of education did not signi cantly differ by device used to take the surveys.
Using mobile phones for survey research: a comparison with fixed phones
International Journal of Market Research, 2009
The increase in mobile phone penetration is stimulating a trend towards the use of mobile phones to supplement or even replace traditional telephone surveys. Despite this trend, few studies have systematically compared differences between the two modes. This paper describes a study in which both mobile and fixed phones were used to collect data on a national survey on internet and cultural practices. Findings revealed significant differences between mobile phone respondents and fixed phone respondents in terms of demographic characteristics and responses to some of the substantive items of the survey. In terms of data quality the mobile phone survey proved to be different from the fixed phone survey in two indicators: completion times and percentage of respondents with item omissions. The mobile phone survey was more difficult to implement than the fixed phone survey since much more screening was required to identify working phone numbers; in addition it yielded a lower response rate than the fixed phone survey.
Use of mobile devices to answer online surveys: implications for research
BMC Research Notes, 2013
Background: There is a growing use of mobile devices to access the Internet. We examined whether participants who used a mobile device to access a brief online survey were quicker to respond to the survey but also, less likely to complete it than participants using a traditional web browser. Findings: Using data from a recently completed online intervention trial, we found that participants using mobile devices were quicker to access the survey but less likely to complete it compared to participants using a traditional web browser. More concerning, mobile device users were also less likely to respond to a request to complete a six week follow-up survey compared to those using traditional web browsers. Conclusions: With roughly a third of participants using mobile devices to answer an online survey in this study, the impact of mobile device usage on survey completion rates is a concern. Trial registration: ClinicalTrials.gov: NCT01521078
Journal of survey statistics and methodology, 2022
Mobile apps are an attractive and versatile method of collecting data in the social and behavioral sciences. In samples of the general population, however, participation in app-based data collection is still rather low. In this article, we examine two potential ways of increasing participation and potentially reducing participation bias in app-based data collection: (1) inviting sample members to a mobile app study within an interview rather than by post and (2) offering a browser-based follow-up to the mobile app. We use experimental data from Spending Study 2, collected on the Understanding Society Innovation Panel and on the Lightspeed UK online access panel. Sample members were invited to download a spending diary app on their smartphone or use a browser-based online diary to report all their purchases for one month. The results suggest that inviting sample members to an app study within a face-to-face interview
2021
The main objective of the German Emigration and Remigration Panel Study (GERPS) is to establish a longitudinal data set that provides information on life trajectories of international migrants. However, a large amount of paradata were also collected in order to obtain meta-information on respondents’ survey participation. This auxiliary information can help to optimize data quality at all stages of the survey process. By continuing the existing discussion in the field of online surveys, this chapter pursues a twofold objective: it reflects device usage (mobile vs. computer) and elucidates determinants of device choice. In particular, it analyses whether selectivity effects due to respondent’s device choices bias the sample. Moreover, this chapter investigates differences in response time between devices to detect differences in response burden. The analysis of response burden differences by device is an important issue, since an increased device-specific response burden can be a pre...
Mobile Phone Surveys: The Slovenian Case Study
In 2004, the number of mobile phone subscriptions in Slovenia reached the total number of inhabitants. Consequently, the fixed telephone coverage has started to decline; almost 10% of households are now available only over the mobile phone. With this, Slovenia positions itself as a typical EU country and can serve as a case study for issues related to mobile phone interview surveys.