Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Mar 22, 2019
Open Peer Review Period: Mar 25, 2019 - May 20, 2019
Date Accepted: Jun 27, 2019
(closed for review but you can still tweet)
An Assessment of Facebook Advertising for Recruiting a Representative Sample of a Canadian Adult Population for a Health Survey
ABSTRACT
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.
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