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

随机数字拨号 样品(材料) 代表性启发 人口 横断面研究 样本量测定 广告 心理学 医学 人口学 环境卫生 统计 社会心理学 数学 业务 社会学 化学 色谱法 病理
作者
Lance Garrett Shaver,Ahmed Khawer,Yanqing Yi,Kris Aubrey‐Bassler,Holly Etchegary,Barbara Roebothan,Shabnam Asghari,Peter Wang
出处
期刊:Journal of Medical Internet Research [JMIR Publications]
卷期号:21 (8): e14021-e14021 被引量:88
标识
DOI:10.2196/14021
摘要

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<V≤0.20. The cost per recruit of Facebook advertising was compared with a quote for a random digit dialing (RDD)–recruited postal survey to determine if this method was economical. Results Facebook advertising is feasible and economical to conduct survey research, reaching 34,012 people, of which 2067 clicked on the ad, for a final sample size of 1048 people at Can $2.18 per recruit versus the quoted Can $23,316.05 for 400 recruits (Can $35.52 per recruit) via RDD. The sample was representative of rural and urban geography (P=.02; 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 health care provider (P=.94; V=0.025), diabetes prevalence (P=.002; V=0.096), and having had a colonoscopy or sigmoidoscopy (P=.27; V=0.034), and it was practically representative of smoking status (P<.001; V=0.14), and body mass index (P<.001; V=0.135). 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 8 of the 13 characteristics studied) sample of middle-aged and older adults for health survey research. As Facebook uses a nonrandom targeting algorithm, caution is warranted in its applications for certain types of research.
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