Open AccessUsing Facebook Advertising to Recruit Representative Samples: Feasibility Assessment of a Cross-Sectional Survey
Author(s) -
Lance Garrett Shaver,
Ahmed Khawer,
Yanqing Yi,
Kris AubreyBassler,
Holly Etchegary,
Barbara Roebothan,
Shabnam Asghari,
Peter Wang
Publication year - 2019
Publication title -
jmir. journal of medical internet research/journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/14021
Subject(s) - random digit dialing , sample (material) , representativeness heuristic , population , cross sectional study , sample size determination , advertising , psychology , medicine , demography , environmental health , statistics , social psychology , mathematics , business , sociology , chemistry , chromatography , pathology
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 This study aimed to assess Facebook advertising as an economical means of recruiting a representative sample of adults aged 35 to 74 years in NL for a cross-sectional health survey. Methods Facebook advertising was used to recruit for a Web-based survey on cancer awareness and prevention during April and May 2018; during recruitment, additional advertisements 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 with distributions of the underlying population to determine representativeness. Cramer V indicates the magnitude of the difference between the sample and population distributions, interpreted as small (Cramer 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 the difference was small (V≤0.10), and practically representative if 0.10