ArticleDigital health
Navigating online recruitment for health research: A case study.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
Objective: The objective was to recruit 800 participants for a research study examining online health information exposure and engagement. Removing duplicate and/or fraudulent responses emerged as a major challenge during data collection. Methods: Most recruitment took place online through U.S. national volunteer registries. Participants were required to share Facebook timeline data and take an online survey. We describe initial indicators of fraud and our process to create a prevention and exclusion protocol. We added three automatic prevention methods: CAPTCHA, blocking users with Virtual Private Network (VPN) and non-U.S. IP addresses, and requiring at least three years of Facebook timeline history. Additionally, we manually reviewed all responses, checking payment information, demographics, and IP addresses. Results: During the two months that the VPN/IP block was live, 7% of entries were blocked for using a VPN or having an IP address outside the U.S. 7% of consented participants who shared Facebook data were automatically excluded based on having insufficient timeline post history. Two months after implementing the VPN check, fraudulent enrollments stopped. Ultimately, 9.6% of enrollments were excluded based on suspected fraud. Conclusion: Other than the Facebook post history check the VPN/IP block had the largest impact on preventing misrepresentative and/or fraudulent entries. We share three strategies for online recruitment: create and test a protocol for preventing and excluding fraud before data collection starts; review participants before payment; and add a VPN block to the beginning of your survey.
Indexed as
Identifiers
What OpenQuestion holds
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.