Using Facebook Advertising to Recruit Representative Samples: Feasibility Assessment of a Cross-Sectional Survey

Abstract

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Facebook has shown promise as an economical means of recruiting participants for health research. However, few studies have evaluated this recruitment method in Canada, fewer still targeting older adults, and, to our knowledge, none specifically in Newfoundland and Labrador (NL). Objective: To assess Facebook advertising as an economical means of recruiting a representative sample of adults ages 35 to 74 in NL for a cross-sectional health survey. Methods: Facebook advertising was used to recruit for an online survey on cancer awareness and prevention during April-May 2018; during recruitment, additional ads were targeted to increase representation of demographics that we identified as being underrepresented in our sample. Sociodemographic and health characteristics of the study sample were compared to distributions of the underlying population to determine representativeness. Cramer’s V indicates the magnitude of the difference between the sample and population distributions, interpreted as small (Cramer’s V = 0.10), medium (0.30), and large (0.50). Sample characteristics were considered representative if there was no statistically significant difference in distributions (chi-square P > .01) or if V ≤ 0.10, and practically representative if 0.10 < V ≤ 0.20. Cost per recruit of Facebook advertising was compared to a quote for a random digit dialling (RDD)-recruited postal survey to determine if this method was economical. Results: Facebook advertising is feasible and economical for survey research, reaching 34,012 people, of which 2,067 clicked on the ad, for a final sample size of 1048 people at $2.18 CAD per recruit, versus the quoted $23,316.05 CAD for 400 recruits ($35.52 CAD per recruit) via RDD. The sample was representative of rural/urban geography (P = 0.021, V = 0.073), practically representative of age (P = .003, V = 0.145) and income (P < .001, V = 0.188), and over-representative of women (P < .001, V = 0.507) and higher levels of education (P < .001, V = 0.488). The sample was representative of the proportion of people with a regular healthcare provider (P = 0.938, V = 0.025) and diabetes prevalence (P = .002, V = 0.096), and practically representative of smoking status (P < .001, V = 0.14), body mass index (P < .001, V = 0.135), and having had a colonoscopy or sigmoidoscopy (P < .001, V = 0.124). The sample was not representative of arthritis prevalence (P < .001, V = 0.573), perceived health (P < .001, V = 0.384), or time since last seasonal flu shot (P < .001, V = 0.449). Conclusions: Facebook advertising offers an easy, rapid, and economical means to recruit a partially representative (representative or practically representative of eight of the thirteen characteristics studied) sample of middle-aged and older adults for health survey research. As Facebook uses a non-random targeting algorithm, caution is warranted in its applications for certain types of research.