Survey data collection faces significant changes due to digitization and evolving participant habits. While Computer-Assisted Personal Interviewing (CAPI) was the gold-standard for many decades and has the advantage of offering respondents’ direct assistance with the survey questions, it is increasingly replaced by faster, less costly self-administered data collection modes such as Computer-Assisted Web Interviewing (CAWI).
However, CAWI lacks the data quality benefits of interviewer administration. Thus, Computer-Assisted Live Video Interviewing (CALVI) combines the advantages of interviewer administration with the flexibility and cost-effectiveness of remote participation. Despite growing literature on CALVI, little is known about its performance in longitudinal contexts, with limited experimental evidence available. Existing research shows higher overall nonresponse rates and sample composition effects, but data quality comparable to CAPI.
Our study evaluates the use of Computer-Assisted Live Video Interviewing (CALVI) as a data collection mode on a large scale in a long-running German general population household panel, the Innovation Sample of the Socio-economic Panel Study (SOEP-IS). We implemented CALVI as a new survey mode and switched a proportion of each subsample—those with CAPI and CAWI backgrounds respectively—to CALVI.
The project aims to contribute to answering the following questions:
- 1) Is CALVI a feasible additional survey mode in a German general population mixed mode (CAPI/CAWI) household panel survey? What are good practices for its implementation?
- 2) How can we develop a targeted multi-mode survey design which encompasses CALVI together with CAPI and CAWI to maximize response rates and data quality at a fixed budget?
- 3) Which are the potentials and challenges of recording video interviews for data quality assessments and enhancements of the survey setting?