Search

Declining response rates worldwide have stimulated interest in understanding what may be influencing this decline and how it varies across countries and survey populations. In this paper, we describe the development and validation of a short 9-item survey attitude scale that measures three important constructs, thought by many scholars to be related to decisions to participate in surveys, that is, survey enjoyment, survey value, and survey burden. The survey attitude scale is based on a literature review of earlier work by multiple authors. Our overarching goal with this study is to develop and validate a concise and effective measure of how individuals feel about responding to surveys that can be implemented in surveys and panels to understand the willingness to participate in surveys and improve survey effectiveness. The research questions relate to factor structure, measurement equivalence, reliability, and predictive validity of the survey attitude scale.The data came from three probability-based panels: the German GESIS and PPSM panels and the Dutch LISS panel. The survey attitude scale proved to have a replicable three-dimensional factor structure (survey enjoyment, survey value, and survey burden). Partial scalar measurement equivalence was established across three panels that employed two languages (German and Dutch) and three measurement modes (web, telephone, and paper mail). For all three dimensions of the survey attitude scale, the reliability of the corresponding subscales (enjoyment, value, and burden) was satisfactory. Furthermore, the scales correlated with survey response in the expected directions, indicating predictive validity.

In an optimal design for mixed‐mode surveys, be it within a country or across countries, there are three phases that need attention. The first phase is the design phase: it is important to prevent mode measurement effects when designing the study. A richer source of additional data will help to achieve a better estimation of mode effects. After the data are collected, the next two phases are estimating the potential mode measurement effect due to different modes and adjusting for any such bias. Survey modes differ on several dimensions, for instance, interviewer‐administered versus self‐administered questionnaires and information transmission and communication. The use of well‐established and validated constructs and multiquestion scales across countries and modes helps achieving measurement equivalence countries and modes. Mixed‐mode designs and mode changes are often implemented for sound methodological reasons. Using a mixed‐mode design implies a careful trade‐off among coverage, nonresponse, measurement errors, and cost.

Mixed-mode surveys have been around since the late 1980s. In the past thirty years, major changes in technology and society influenced and changed data collection and survey methodology. However, in those years, mixed-mode strategies remained part of the daily survey practice, although the type of mix implemented followed the changes in technology and data collection methods. In this paper, I summarize the state of the art in traditional mixed-mode surveys and discuss implications for mixed device surveys., Survey Research Methods, Vol 12, No 2 (2018)

Household survey nonresponse is a matter of concern in many countries. In one of the first international trend analyses, de Leeuw and de Heer (2002) found that response rates declined over the years, and that countries differed in response rates and nonresponse trends. Their analyses cover longitudinal data on the Labour Force Survey from National Statistical Institutes for the period 1980 to 1997. We added a new data set, covering the period 1998 -2015, and analysed nonresponse data over time and countries. In these analyses we differentiated between voluntary and mandatory surveys. The trends visible in de Leeuw and de Heer (2002) continue with possibly a small deceleration in refusal rates.

This study investigates the impact of different modes and tailor-made response enhancing measures (TMREM)—such as bilingual interviewers with a shared ethnic background and translated questionnaires—on the measurement of substantive variables in surveys among minority ethnic groups in the Netherlands. It also provides insight into the ability to detect mode measurement effects of a recently developed method for disentangling mode measurement and mode selection effects, as well as into the tenability of the assumptions underlying this method. The data used in this study come from a large-scale survey design experiment among the four largest non-Western minority ethnic groups in the Netherlands comparing single-mode computer-assisted personal interviewing (CAPI) and sequential computer-assisted web interviewing, computer-assisted telephone interviewing, and CAPI-MM. The number and intensity of the TMREM varied among the four ethnic groups. The results show that mode measurement effects occur among all ethnic groups and are the result of a combination of the presence or absence of an interviewer and TMREM. Mode measurement effects occur more often on sociocultural questions, but also, on occasion, on more sociostructural or background questions. The method used to disentangle mode measurement and mode selection effects can be applied to detect mode measurement effects, but one should be cautious in interpreting them. Implausible mode measurement effects can be caused by the violation of the assumptions underlying this method.