ArticleJournal of medical Internet research2016
Can Facebook Be Used for Research? Experiences Using Facebook to Recruit Pregnant Women for a Randomized Controlled Trial.
Article in Journal of medical Internet research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02711644 (Promoting Healthy Weights, Lifestyles and Nutrition During Pregnancy Through Innovative Counselling Methods), which is not on this map. Cited by 37 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Promoting Healthy Weights, Lifestyles and Nutrition During Pregnancy Through Innovative Counselling Methods
Who cites it
37 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Use of Facebook, Instagram, and Twitter for recruiting healthy participants in nutrition-, physical activity-, or obesity-related studies: a systematic review.The American journal of clinical nutrition · 2022Pooled it
- Online Patient Recruitment in Clinical Trials: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2020Pooled it
- The Use of Facebook in Recruiting Participants for Health Research Purposes: A Systematic Review.Journal of medical Internet research · 2017Pooled it
- Using Social Media to Recruit a Diverse Sample of Participants for a Mobile Health (mHealth) Intervention to Increase Physical Activity: Exploratory Study.JMIR mHealth and uHealth · 2025Trial
- Recruiting and Engaging Women of Reproductive Age with Obesity: Insights from A Mixed-Methods Study within A Trial.International journal of environmental research and public health · 2022Trial
- The use of paracetamol during pregnancy: A qualitative study and possible strategies for a clinical trial.PloS one · 2022Trial
- Recruiting people facing social disadvantage: the experience of the Free Meds study.International journal for equity in health · 2021Trial
- Healthy conversation skills as an intervention to support healthy gestational weight gain: Experience and perceptions from intervention deliverers and participants.Patient education and counseling · 2019Trial
- Using Facebook for Large-Scale Online Randomized Clinical Trial Recruitment: Effective Advertising Strategies.Journal of medical Internet research · 2018Trial
- Using marketing strategies to improve recruitment and retention in clinical trials: a scoping review.Trials · 2026Article
- Leveraging Influencers to Reach and Engage Vulnerable Individuals With a Digital Health Intervention: Quasi-Experimental Field Study.Journal of medical Internet research · 2025Article
- A Long-Term Evaluation of Facebook for Recruitment and Retention in the ENDIA Type 1 Diabetes Pregnancy-Birth Cohort Study.Journal of diabetes science and technology · 2023Article
- Cost-effectiveness of social media advertising as a recruitment tool: A systematic review and meta-analysis.Journal of clinical and translational science · 2023Article
- Tailoring Perinatal Health Communication: Centering the Voices of Mothers at Risk for Maternal Mortality and Morbidity.International journal of environmental research and public health · 2022Article
- Social Media Recruitment Strategies to Recruit Pregnant Women Into a Longitudinal Observational Cohort Study: Usability Study.Journal of medical Internet research · 2022Observational
- Ethical Issues in Social Media Recruitment for Clinical Studies: Ethical Analysis and Framework.Journal of medical Internet research · 2022Review
- Refinement of the Well-being in Pregnancy (WiP) questionnaire: cognitive interviews with women and healthcare professionals and a validation survey.BMC pregnancy and childbirth · 2022Article
- Liar! Liar! Identifying eligibility fraud by applicants in digital health research.Internet interventions · 2021Article
- The Food, Feelings, and Family Study: comparison of the efficacy of traditional methods, social media, and broadcast email to recruit pregnant women to an observational, longitudinal nutrition study.BMC pregnancy and childbirth · 2021Observational
- The Role of Social Media in Enhancing Clinical Trial Recruitment: Scoping Review.Journal of medical Internet research · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRecruitment is often a difficult and costly part of any human research study. Social media and other emerging means of mass communication hold promise as means to complement traditional strategies used for recruiting participants because they can reach a large number of people in a short amount of time. With the ability to target a specified audience, paid Facebook advertisements have potential to reach future research participants of a specific demographic. This paper describes the experiences of a randomized controlled trial in Edmonton, Alberta, attempting to recruit healthy pregnant women between 8 and 20 weeks' gestation for participation in a prenatal study. Various traditional recruitment approaches, in addition to paid Facebook advertisements were trialed.
objectiveTo evaluate the effectiveness of paid advertisements on Facebook as a platform for recruiting pregnant women to a randomized controlled trial in comparison with traditional recruitment approaches.
methodsRecruitment using traditional approaches occurred for 7 months, whereas Facebook advertisements ran for a total of 26 days. Interested women were prompted to contact the study staff for a screening call to determine study eligibility. Costs associated with each recruitment approach were recorded and used to calculate the cost to recruit eligible participants. Performance of Facebook advertisements was monitored using Facebook Ads Manager.
resultsOf the 115 women included, 39.1% (n=45) of the women who contacted study staff heard about the study through Facebook, whereas 60.9% (n=70) of them heard about it through traditional recruitment approaches. During the 215 days (~7 months) that the traditional approaches were used, the average rate of interest was 0.3 (0.2) women/day, whereas the 26 days of Facebook advertisements resulted in an average rate of interest of 2.8 (1.7) women/day. Facebook advertisements cost Can $506.91 with a cost per eligible participant of Cad $20.28. In comparison, the traditional approaches cost Cad $1087, with approximately Cad $24.15 per eligible participant. Demographic characteristics of women were similar between the 2 recruitment methods except that women recruited using Facebook were significantly earlier in their pregnancy than those recruited using traditional approaches (P<.03).
conclusionsPaid Facebook advertisements hold promise as a platform for reaching pregnant women. The relative ease of placing an advertisement, the comparable cost per participant recruited, and the dramatically improved recruitment rates in comparison with traditional approaches highlight the importance of combining novel and traditional recruitment approaches to recruit women for pregnancy-related studies.
trial registrationClinicalTrials.gov NCT02711644; https://clinicaltrials.gov/ct2/show/NCT02711644 (Archived by WebCite at http://www.webcitation.org/6kKpagpMk).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.