TY - JOUR
T1 - Improving survey participation
AU - Legleye, Stéphane
AU - Charrance, Géraldine
AU - Razafindratsima, Nicolas
AU - Bohet, Aline
AU - Bajos, Nathalie
AU - Moreau, Caroline
N1 - Funding Information:
Stéphane Legleye is the head of the Survey and Sampling Department (SSD) at the National Institute for Demographic Research (INED), Paris, France; he is also associate researcher at the National Institute of Health and Medical Research (INSERM), University Paris-Sud and University Paris Descartes, Paris, France. Géraldine Charrance and Nicolas Razafindratsima are in the SSD, INED, Paris, France. Aline Bohet is on the Gender, Sexual, and Reproductive Health (GRSH) team at the Centre for Research in Epidemiology and Population Health (CESP), INSERM, Paris, France. Nathalie Bajos is research director on the GRSH team at the CESP, and associate researcher at the INED, Paris, France. Caroline Moreau is assistant professor in the Department of Population, Family, and Reproductive Health at the Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, and senior researcher on the GRSH team at the CESP, Paris, France. The authors would like to thank the respondents to the survey. The FECOND survey was supported by a grant from the French Ministry of Health, a grant from the French National Agency of Research [#ANR-08-BLAN-0286-01 to N. B. and C. M.], and funding from the INSERM and the INED. The authors have no conflict of interest to declare. *Address correspondence to Stéphane Legleye, INED, 133 Boulevard Davout, Paris, France; e-mail: stephane. legleye@ined.fr.
PY - 2013/9
Y1 - 2013/9
N2 - The general decrease in telephone survey response rates leads to potential selection and estimation biases. As nonrespondents can be broken down into noncontacts and refusals, different strategies can be deployed - increasing the number of call attempts before abandoning a number, and calling back refusals/abandonments to persuade them to participate. Using a two-stage random-digit-dialing sample of 8,645 individuals aged 15-49 for a survey on sexual and reproductive health (SRH), we compared the effects of the two strategies: including hard-to-contact respondents (more than twenty call attempts with no upper limit) and including respondents from two successive waves of call-back among initial refusals/abandonments. Comparisons were based on sociodemographic bias, differences in SRH behaviors, multivariate logistic modeling of SRH behaviors, post-calibration weighting, and cost estimation. The sociodemographic profile of hard-to-contact and call-back respondents differed from that of easy-to-interview respondents. Including hard-to-contact respondents decreased the socio- demographic bias of the sample, while including call-back respondents increased it. Several significant differences in SRH behaviors emerged between easy-to-interview and hard-to-contact respondents, but none between first-wave and call-back respondents. Nevertheless, the determinants of SRH behaviors in call-back and hard-to-contact respondents differed with respect to easy-to-interview respondents. The trade-off between bias and financial costs suggests that the best protocol would be to mix the two strategies but with only one call-back wave involving a limited number of call attempts to achieve a sufficient sample size with optimal quality.
AB - The general decrease in telephone survey response rates leads to potential selection and estimation biases. As nonrespondents can be broken down into noncontacts and refusals, different strategies can be deployed - increasing the number of call attempts before abandoning a number, and calling back refusals/abandonments to persuade them to participate. Using a two-stage random-digit-dialing sample of 8,645 individuals aged 15-49 for a survey on sexual and reproductive health (SRH), we compared the effects of the two strategies: including hard-to-contact respondents (more than twenty call attempts with no upper limit) and including respondents from two successive waves of call-back among initial refusals/abandonments. Comparisons were based on sociodemographic bias, differences in SRH behaviors, multivariate logistic modeling of SRH behaviors, post-calibration weighting, and cost estimation. The sociodemographic profile of hard-to-contact and call-back respondents differed from that of easy-to-interview respondents. Including hard-to-contact respondents decreased the socio- demographic bias of the sample, while including call-back respondents increased it. Several significant differences in SRH behaviors emerged between easy-to-interview and hard-to-contact respondents, but none between first-wave and call-back respondents. Nevertheless, the determinants of SRH behaviors in call-back and hard-to-contact respondents differed with respect to easy-to-interview respondents. The trade-off between bias and financial costs suggests that the best protocol would be to mix the two strategies but with only one call-back wave involving a limited number of call attempts to achieve a sufficient sample size with optimal quality.
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U2 - 10.1093/poq/nft031
DO - 10.1093/poq/nft031
M3 - Article
AN - SCOPUS:84886618295
VL - 77
SP - 666
EP - 695
JO - Public Opinion Quarterly
JF - Public Opinion Quarterly
SN - 0033-362X
IS - 3
ER -