The Use of Facebook in Recruiting Participants for Health Research Purposes: A Systematic Review

1Social media is a popular Web-based tool that allows users to communicate and exchange information. It allows digital content such as pictures, videos, and websites to be shared, discussed, republished, and endorsed by its users, their friends, and businesses. Adverts can be posted and promoted to specific target audiences by demographics such as region, age, or gender.

2Social media has grown tremendously with Facebook, increasing from 6m to 1bn daily users from 2005 to 2015. This visibility lead to most social media sites monetizing adverts, with 92% of the private sector currently using social media as one of their employee recruitment strategies. In 2014, 66% of the UK population used social media, with 96% of those users choosing Facebook. It continued to grow in 2016, with 72% of the population using social media and 97% of them choosing Facebook.

3Recruiting for health research is complex with strict requirement criteria imposed on the participants. Traditional research recruitment relies on flyers, newspaper adverts, radio and television broadcasts, letters, emails, website listings, and word of mouth. These methods are potentially poor at recruiting hard to reach demographics, can be slow, and expensive. Recruitment via social media, in particular Facebook, may be faster and cheaper.

4This paper aims to summarize the available evidence regarding Facebook as a recruitment tool for health research in terms of cost, speed, and its ability to find and represent hard to reach demographic groups (see Table 1 for common definitions). It will be compared with traditional methods and deemed successful if it shows equal or better costing and representation of target demographics. This will be the first systematic review the authors are aware of to summarize and appraise this data.

5A search of six databases, namely MEDLINE, EMBASE, Web of Science, PubMed, PsycInfo, Google Scholar, and an additional hand search of reference lists was performed in March 2017. It spanned the past 12 years due to the rise of social media from a negligible entity in 2006. A combination of the following keywords was implemented as a search strategy looking within the title or abstract:

6Facebook, social media*, social network* AND internet, online, web* AND recruit*, research*, volunteer*, participant*, respondent*, patient select*, stud*, epidemiology, clinical*, health communication*, survey*

7All the papers identified were exported to RefWorks, and duplicates were removed. Subsequently, the following exclusion criteria were applied: (1) Non-English language; (2) those not using Facebook as the recruitment tool; (3) those not recruiting for health research purposes; (4) those not constituting original research; (5) conference proceedings, letters to editors, posters, comments, and dissertations (due to difficulty accessing the full text and probable lack of detail); and (6) systematic reviews (although their reference lists were examined for eligible papers).

8Full papers were appraised using the Critical Appraisal Skills Programme (CASP) checklist, and those deemed invalid were excluded (scoring less than 7/9; see Multimedia Appendix 1). Results tabulated included target demographic, number recruited, recruitment length, impressions, cost per ad click, conversion rate, eligibility, and cost per participant. Data was exported to Microsoft Excel for statistical analysis. Major outliers were removed (outside three standard deviations [SDs]), after which mean, median, and interquartile range were calculated.

9A total of 5818 records were identified during the initial searches. Duplicates were removed (n=1239) and 4579 records were screened against the exclusion criteria (Figure 1). Additionally, 123 full papers were assessed for quality using the study design specific CASP checklist revealing 35 papers (scoring 7-9/9) to be included in the review (see Multimedia Appendix 1). Quantitative and qualitative data was tabulated (Tables 2 and 3), allowing comparison of cost and demographic recruited.

10Most studies were conducted in the United States (n=22) with some in Australia (n=9) and Canada (n=2) and one in Japan and Germany, respectively. Some studies also tested interventions (n=10); three recruited for smoking cessation, two for human papillomavirus (HPV) vaccination, two for healthier lifestyle intervention; and one each for perinatal studies, human immunodeficiency virus (HIV) prevention via soap opera viewing, and depression intervention. Ten papers recruited those aged 18 years and over, 7 the age group of 18-25 years, and 16 recruited different ages (See Tables 3 and 4 for more demographic information).

11Other than basic demographic information including age and sex, most papers recruited participants with specific characteristics (n=18), including parents of children, nulliparous women at the beginning of their pregnancy, Brazilian and Portuguese speakers, emergency nurses, those with post-traumatic stress disorder (PTSD), those with Klinefilter syndrome, those in sexual relationships, those living in a metropolitan area, US veterans, parents of children with Fontan-associated protein losing enteropathy, and those of positive HIV status. Two papers had no targeting features except being over 18 years old.

12There were several pieces of data that outlay three SDs and so were removed from statistical analysis, namely, a recruitment length of 36 months, an impression count of 127 million, a cost per click of US $1.74, a conversion rate of 48%, and a cost per participant of US $110.00.

13Table 5 shows median data: 264 recruited participants, a 3-month recruitment period, 3.3 million impressions, cost per click of US $0.51, conversion rate of 4% (range 0.06-29.50), eligibility of 61% (range 17-100), and cost per participant of US $14.41.

14Most studies (n=24) compared their recruited participants with either a control group recruited by traditional methods or to national data. This showed the recruited participants to be relatively representative except for some minor differences:

15There was over representation of females in 5 papers and of males in 2 papers.

16Four papers reported an over representation of white ethnicity, two of African American representation, and 1 an over representation of Hispanic or Latino ethnicities.

17Four papers suggested over representation of a young adult group, including Frandsen M (2014), who found Web-based age to be significant younger than from the control groups recruited by mail, newspaper ads, and flyers.

18Four papers reported a higher degree of education and two a higher rate of income than that of the general population.

19Fenner Y (2012) reported an over representation of people with a higher body mass index (BMI) in Australia, whereas Miyagi, E (2014) reported an over representation of low BMI in Japan.

20Nelson EJ (2014) reported a higher rate of HPV vaccination than predicted in Australia, whereas Remschmidt C (2014) shows it to be representative of the general population in Germany.

21Bauermeister JA (2012) showed the participants to be representative of the general population for alcohol consumption, marijuana, ecstasy, and cocaine use, with Jones R (2012) showing representation of marijuana use, sexually transmitted infection (STI) rates, and sexual relationship history.

22Full time employment and nonsmoker status where each under represented once compared with the general population.

23This paper summarizes the available evidence regarding the success of Facebook as a recruitment tool for research purposes. Some of the results can only be compared with Web-based advertising, namely, the impressions, cost per click, and conversion rate as traditional recruitment uses different markers. The remaining data on recruitment number, length of study, eligibility, and cost per participant can be compared widely with other forms of traditional recruitment.

24Cost per click only varied slightly across studies, especially when targeting similar groups. The median cost per click from this review was US $0.51 compared with US $0.27—the mean cost per click on Facebook as a whole. This shows people are less likely to interact with a health recruitment ad. The conversion rate of 4% can also be compared with the mean value of 2.4% across all Web-based advertising. This suggests that although people are less interested in health research ads overall, those who do interact with them are more likely to convert. This increase in conversion rate however, doesn’t appear large enough to counteract the increased cost per click with health recruitment still costing more than general advertising.

25The cost per participant on Facebook was shown to be less than traditional methods. Our median value of US $14.41 compares favorably with rates suggested by Tate, D (2014) of US $1094.27 per participant for television recruitment, US $811.99 for printed media, US $635.92 for radio, and US $37.77 for email when recruiting for a survey on English language competency. Carlini BH (2015) had similar findings with a mean cost per participant of US $16.22 via Google ads, and between US $13.12 and US $250.00 for other traditional methods when recruiting young adults for weight gain analysis.

26The cost per participant values contained a major outlier; Raviotta JM (2016) reported a cost of US $110 per recruited participant. The cost per click of the study (US $1.24) fell slightly outside one SD of the median and did not explain the increased cost per participant. On closer inspection, the reason for the expense became clear, “the difference in time and effort required to complete a 7-13 month study with two blood draws and three vaccine injections vs. a 30 minute survey...explains the increased cost”.

27Three articles simultaneously used other social media sites to recruit participants, namely Twitter and MySpace. Bull S (2013) used MySpace but found it unsuccessful in recruiting any participants. This is unsurprising considering the massive drop in MySpace primary users from 2008 to 2011. Harris, M. L (2015) implemented recruitment via Facebook and Twitter but changed to use Facebook alone due to its increased success. Yuan P (2014) also used Twitter alongside Facebook. The study received 10,006 Facebook ad clicks and 161 Twitter interactions. It was found that the number of Facebook ad clicks was moderately correlated to the number recruited (r=.52 P<.001) but that there was little correlation between Twitter interactions and links clicked (r=.17, P=.06; r=.18, P=.06, respectively). These findings suggest Facebook is a superior recruitment tool when compared with Twitter and MySpace, although there is limited analysis across the three papers. This was an interesting albeit unintentional finding, but more research should be carried out in this area before making conclusions.

28Sociodemographic characteristics of the recruited participants were compared either with traditionally recruited participants or to available national statistics. Alcohol consumption; marijuana, ecstasy, and cocaine use; STI rates; and sexual relationship history were found to be representative of the total population. Those who use recreational drugs and have at risk sexual behavior tend to be found in hard to reach populations. The fact these studies mirror national statistics highlights the power of social media to target specific populations. Traditional methods tend to under represent these groups, meaning Facebook recruitment potentially yields more significant results.

29Another point highlighting the success of Facebook recruitment would be the differing BMI results from Miyagi E (2014) and Fenner Y (2012), with the latter Australian paper showing a considerably higher average than the Japanese study. This simply shows the different obesity rates of the two countries. Australia reports 64% of its population to have a BMI above 25kg/m2compared with 24% in Japan. This also seems true for the differences in reported rates of HPV vaccination between Nelson EJ (2014) and Remschmidt C (2014); 39.7% of adolescent females in America are vaccinated compared with 49% of Germans.

30Other demographic data was found to be representative of the target population and comparable with traditional recruitment with only a few exceptions:

31There was an over representation of white ethnicity. Facebook claims to be diverse, but papers suggest either these claims are not true, targeted marketing misses certain ethnicities, or that different groups have different response rates. This over representation is also shown in a review of traditional methods by Yancey AK (2005), suggesting the problem is not limited to social media recruitment.

32Four papers also showed over representation of females. This may be due to the fact that a higher percentage of women use Facebook or because fewer men respond to recruitment in general. Brown WJ (1998) found similar results using traditional methods, again suggesting the problem is not limited to Facebook.

33Education and income are often confounding factors, and it is perhaps unsurprising to find over representation in both these areas. This is comparable again with traditional recruitment methods, with Gorelick PB (1998) finding that more years in education increased the likelihood of entering and completing a clinical trial with those of lower levels “not wanting to be guinea pigs”.

34Strengths of this review include the wide search ensuring all available literature was gathered and the detailed cost analysis. The main limitation is the relatively small number of studies available with numerical data on costings and population comparisons. Several papers had substantial recruitment numbers (n=1578 [30), but many were small (n=26), reducing the reliability. Most papers focused on ages in the range of 18-30 years. Carter-Harris L (2016) recruited those aged 55-77 years, showing that although older people may be less likely to adopt newer technologies (of those over 65 years, 48% are active Facebook users compared with 64% for 50-64 year olds, 79% for 30-49 year olds, and 82% for 18-29 year olds), recruitment can still be successful, reporting US $1.51 cost per participant. The expected barrier from lack of Internet access or experience in the older population is smaller than most think.

35The percentage of people with access to the Internet is steadily increasing, and procedural methods can be put into place to prevent this misrepresentation of data. Young, SD (2013) found that even 79% of homeless youths manage to access social media sites once per week. Although Internet access currently remains to be a barrier, it seems to be smaller than barriers facing traditional methods and is set to improve in the future.

36There is growing evidence to suggest that Facebook is a successful recruitment tool, and its use, therefore, should be considered when implementing future health research. Benefits include reduced cost, shorter recruitment periods, better representation, and improved participant selection in young and hard to reach demographics. This may spell the end for traditional methods, although currently the minor limitations of Internet access and the over representation of young white women may make its use inappropriate in some settings.