Measurement of Interviewer Workload within the Survey and an Exploration of Workload Effects on Interviewers’ Field Efforts and Performance
| Autor: | Celine Wuyts, Geert Loosveldt |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Operationalization
Interview Statistics 05 social sciences Applied psychology interviewer effort Sample (statistics) Workload paradata 01 natural sciences Field (computer science) Paradata HA1-4737 0506 political science European Social Survey 010104 statistics & probability nonresponse interviewer effects Respondent 050602 political science & public administration time-varying interviewer characteristics 0101 mathematics Psychology |
| Zdroj: | Journal of Official Statistics, Vol 36, Iss 3, Pp 561-588 (2020) |
| ISSN: | 2001-7367 |
| DOI: | 10.2478/jos-2020-0029 |
| Popis: | Interviewer characteristics are usually assumed fixed over the fieldwork period. The number of sample units that require the interviewers’ attention, however, can vary strongly over the fieldwork period. Different workload levels produce different constraints on the time interviewers have available to contact, recruit and interview each target respondent, and may also induce different motivational effects on interviewers’ behavior as they perform their different tasks. In this article we show that fine-grained, time-varying operationalizations of project-specific workload can be useful to explain differences in interviewers’ field efforts and achieved response outcomes over the fieldwork period. We derive project-specific workload for each interviewer on each day of fieldwork in two rounds of the European Social Survey in Belgium from contact history and assignment paradata. Project-specific workload is measured as (1) the number of sample units which have been and remain assigned on any day t (assigned case workload), and (2) the number of sample units for which interviewer activity has started and not yet ceased on any day t (active case workload). Capturing temporal variation in interviewers’ workloads in a direct way, the time-varying operationalizations, are better predictors than are the interviewer-level operationalizations of typical (active or potential) workload that are derived from them, as well as the traditional total-count workload operationalization. |
| Databáze: | OpenAIRE |
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