Participation rates in health surveys have been declining over the past decade, and with even steeper declines in recent years [1]. This has raised concern among epidemiologists and survey researchers who attempt to obtain estimates from population-representative samples that are generalizable to the whole population. Consequently, survey design features affecting participation have been subject to extensive research. Design features suggested to affect participation include e.g. incentives, use of pre-notification, survey administration mode, the nature of the questionnaire (e.g. contents, length, design, layout and language), and use of reminders [1,2,3,4], and the literature shows that even subtle differences in design features can affect participation [5,6,7,8,9].
Recently, a growing number of researchers have further experimented with ways of targeting various design features to different sample subgroups to increase participation and sample balance. Hence, in the last decade, a gradual shift has been observed from surveys in which all procedures are completely standardised to surveys in which sample subgroups are treated differently [6, 10].
Targeted design is a variant of the non-standardised approach where a targeted design feature (or set of features) that is identified in advance of field work and is not then modified during field work is applied to each subgroup in the sample [10, 11]. Hence, targeted designs require information about sample units in advance of survey collection. This information is used to identify subgroups to be treated differently, and to identify the treatment to be applied to each group. Several studies indicate that a survey that adapts personalized design features achieves higher participation rates [10]. Targeted design features known to have heterogonous effect across subgroups of sample members include e.g. the form and value of incentives [12] and length of the cover letter [13].
The effectiveness of targeted designs depends partly on the richness of information available about sample members prior to field work. For this reason they have mainly been implemented on longitudinal studies where rich information about sample members is available from previous rounds and mainly to address non-response and attrition [10]. However, a few experiments have also been performed in the cross-sectional context [14, 15]. The method has proved to be useful. However, it is not standard practice yet. Further, experiments have mainly been conducted in the contexts of social surveys, and experiments have as far as we know not been conducted in the context of health surveys. Last, even though several studies of targeted design features have been identified, evidence of the effects of targeting remains limited [10].
In view of these limitations of existing studies, we wanted to examine the potential for targeted survey design features to improve response rates and sample composition in a cross-sectional health survey in Denmark. Participation can be stimulated by either a reduction in burden or an increase in motivation [5, 6, 10]. Targeted motivational statements in the cover letters or other survey materials could be ways of improving the motivation of sample members [6]. Hence, different aspects of the survey content could be emphasised in the cover letter and target different sample subgroups with the expectation of increasing the perceived relevance and saliency of the survey. [5, 6, 16].
The first research question in this study is therefor whether cover letters with targeted content can perform better than a generic letter. The proposition is that such letters should increase the willingness of some sample members to participate, and that this will be reflected in higher response rates. However, no evidence is available about which targeted content is the most effective in a cross-sectional health surveys, so in addition to examining whether it can be advantageous for response overall to use cover letters with additional motivating content, this study also examines the effect of different content across sample subgroups in order to identify how best to target the content in future surveys. Further, given that most sample members respond anyway, sample members who are swayed by the targeted letters must have relatively low response propensities (with the generic letter). Thus, we hypothesize that targeted letters should particularly improve response in subgroups known to have low response propensity (i.e. young men, unmarried, elderly women, non-Danish background) [17]. The last research question is, therefore, whether letters can be targeted to particularly improve response rates among sample subgroups with low response propensities.
