Evidence map›Paper›PMID 37745929›Full record

ArticleJournal of clinical and translational science2023

Cost-effectiveness of social media advertising as a recruitment tool: A systematic review and meta-analysis.

Vladislav Tsaltskan, Roel Sanchez Baez, Gary S Firestein

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Vladislav TsaltskanDepartment of Medicine, University of California San Diego, La Jolla, CA, USA.ORCID https://orcid.org/0000-0002-1359-0674
Roel Sanchez BaezDepartment of Medicine, University of California San Diego, La Jolla, CA, USA.
Gary S FiresteinDepartment of Medicine, University of California San Diego, La Jolla, CA, USA.ORCID https://orcid.org/0000-0003-3495-960X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Recruitment of study participants is challenging and can incur significant costs. Social media advertising is a promising method for recruiting clinical studies and may improve cost efficiency by targeting populations likely to match a study's qualifications. Prior systematic reviews of social media as a recruitment tool have been favourable, however, there are no meta-analyses of its cost-effectiveness. Methods: Studies evaluating recruitment costs through social media and non-social media methods were identified on MEDLINE and EMBASE. Articles were screened through a two-step process in accordance with PRISMA guidelines. Cost data were extracted from selected articles and meta-analyzed using the Mantel-Haenszel method. The primary outcome was the relative cost-effectiveness of social media compared to non-social media recruitment, defined as the odds ratio of recruiting a participant per US dollar spent. The secondary outcome was the cost-effectiveness of social media recruitment compared to other online recruitment methods only. Results: In total, 23 studies were included in the meta-analysis. The odds ratio of recruiting a participant through social media advertising compared to non-social media methods per dollar spent was 1.97 [95% CI 1.24-3.00, Conclusions: Social media advertising may be more cost-effective than other methods of recruitment, however, the magnitude of cost-effectiveness is highly variable between studies. There are limited data on newer social media platforms and on difficult-to-reach populations such as non-English speakers or older individuals.

Indexed as

costmeta-analysisrecruitmentSocial mediasystematic review

Identifiers

PMID37745929
PMCPMC10514690

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Registered trials

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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.