ArticleJMIR formative research2024
Data Verification and Respondent Validity for a Web-Based Sexual Health Survey: Tutorial.
Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed.
- Exploring Methods to Mitigate Fraud in Web-Based Surveys: Multicase Study Analysis.Journal of medical Internet research · 2025Trial
- Let's Talk aBOT Scam Online Survey Completions in Health Behavior Research: Tutorial With Case Studies, Practical Guidance, and a Checklist for Researchers.JMIR public health and surveillance · 2025Article
- A nationwide survey of orthopedic residency training in Türkiye: Theoretical education, surgical exposure, faculty engagement, and mentorship influence on resident competence.Acta orthopaedica et traumatologica turcica · 2025Article
- Advancing translational science through trial integrity: REDCap-based approaches to mitigating fraud and bias.Journal of clinical and translational science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: As technology continues to shape the landscape of health research, the utilization of web-based surveys for collecting sexual health information among adolescents and young adults has become increasingly prevalent. However, this shift toward digital platforms brings forth a new set of challenges, particularly the infiltration of automated bots that can compromise data integrity and the reliability of survey results. Objective: We aimed to outline the data verification process used in our study design, which employed survey programming and data cleaning protocols. Methods: A 26-item survey was developed and programmed with several data integrity functions, including reCAPTCHA scores, RelevantID fraud and duplicate scores, verification of IP addresses, and honeypot questions. Participants aged 15-24 years were recruited via social media advertisements over 7 weeks and received a US $15 incentive after survey completion. Data verification occurred through a 2-part cleaning process, which removed responses that were incomplete, flagged as spam by Qualtrics, or from duplicate IP addresses, or those that did not meet the inclusion criteria. Final comparisons of reported age with date of birth and reported state with state inclusion criteria were performed. Participants who completed the study survey were linked to a second survey to receive their incentive. Responses without first and last names and full addresses were removed, as were those with duplicate IP addresses or the exact same longitude and latitude coordinates. Finally, IP addresses used to complete both surveys were compared, and consistent responses were eligible for an incentive. Results: Over 7 weeks, online advertisements for a web-based survey reached 1.4 million social media users. Of the 20,585 survey responses received, 4589 (22.3%) were verified. Incentives were sent to 462 participants; of these, 14 responses were duplicates and 3 contained discrepancies, resulting in a final sample of 445 responses. Conclusions: Confidential web-based surveys are an appealing method for reaching populations-particularly adolescents and young adults, who may be reluctant to disclose sensitive information to family, friends, or clinical providers. Web-based surveys are a useful tool for researchers targeting hard-to-reach populations due to the difficulty in obtaining a representative sample. However, researchers face the ongoing threat of bots and fraudulent participants in a technology-driven world, necessitating the adoption of evolving bot detection software and tailored protocols for data collection in unique contexts.
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