%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 19
%N 3
%P e61
%T Online Recruitment: Feasibility, Cost, and Representativeness in a Study of Postpartum Women
%A Leach,Liana S
%A Butterworth,Peter
%A Poyser,Carmel
%A Batterham,Philip J
%A Farrer,Louise M
%+ National Centre for Epidemiology and Population Health, Research School of Population Health, The Australian National University, Building 54, Mills Road, Canberra, 2614, Australia, 61 261259725, Liana.Leach@anu.edu.au
%K online
%K Internet
%K recruitment
%K feasibility
%K representativeness
%K postpartum
%D 2017
%7 08.03.2017
%9 Original Paper
%J J Med Internet Res
%G English
%X Background: Online recruitment is feasible, low-cost, and can provide high-quality epidemiological data. However, little is known about the feasibility of recruiting postpartum women online, or sample representativeness. Objective: The current study investigates the feasibility of recruiting a population of postpartum women online for health research and examines sample representativeness. Methods: Two samples of postpartum women were compared: those recruited online as participants in a brief survey of new mothers (n=1083) and those recruited face-to-face as part of a nationally representative study (n=579). Sociodemographic, general health, and mental health characteristics were compared between the two samples. Results: Obtaining a sample of postpartum women online for health research was highly efficient and low-cost. The online sample over-represented those who were younger (aged 25-29 years), were in a de facto relationship, had higher levels of education, spoke only English at home, and were first-time mothers. Members of the online sample were significantly more likely to have poor self-rated health and poor mental health than the nationally representative sample. Health differences remained after adjusting for sociodemographic differences. Conclusions: Potential exists for feasible and low-cost e-epidemiological research with postpartum populations; however, researchers should consider the potential influence of sample nonrepresentativeness. 
%M 28274906
%R 10.2196/jmir.5745
%U http://www.jmir.org/2017/3/e61/
%U https://doi.org/10.2196/jmir.5745
%U http://www.ncbi.nlm.nih.gov/pubmed/28274906