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Combating Fraudulent Participation in Urban American Indian and Alaska Native Virtual Health Research: Protocol for Increasing Data Integrity in Online Research (PRIOR).

作者信息

Reed Nicole D, Bull Sheana, Shrestha Umit, Sarche Michelle, Kaufman Carol E

机构信息

Centers for American Indian and Alaska Native Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.

Community and Behavioral Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.

出版信息

JMIR Res Protoc. 2024 Jun 13;13:e52281. doi: 10.2196/52281.


DOI:10.2196/52281
PMID:38869930
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11211704/
Abstract

BACKGROUND: While the advantages of using the internet and social media for research recruitment are well documented, the evolving online environment also enhances motivations for misrepresentation to receive incentives or to "troll" research studies. Such fraudulent assaults can compromise data integrity, with substantial losses in project time; money; and especially for vulnerable populations, research trust. With the rapid advent of new technology and ever-evolving social media platforms, it has become easier for misrepresentation to occur within online data collection. This perpetuation can occur by bots or individuals with malintent, but careful planning can help aid in filtering out fraudulent data. OBJECTIVE: Using an example with urban American Indian and Alaska Native young women, this paper aims to describe PRIOR (Protocol for Increasing Data Integrity in Online Research), which is a 2-step integration protocol for combating fraudulent participation in online survey research. METHODS: From February 2019 to August 2020, we recruited participants for formative research preparatory to an online randomized control trial of a preconceptual health program. First, we described our initial protocol for preventing fraudulent participation, which proved to be unsuccessful. Then, we described modifications we made in May 2020 to improve the protocol performance and the creation of PRIOR. Changes included transferring data collection platforms, collecting embedded geospatial variables, enabling timing features within the screening survey, creating URL links for each method or platform of data collection, and manually confirming potentially eligible participants' identifying information. RESULTS: Before the implementation of PRIOR, the project experienced substantial fraudulent attempts at study enrollment, with less than 1% (n=6) of 1300 screened participants being identified as truly eligible. With the modified protocol, of the 461 individuals who completed a screening survey, 381 did not meet the eligibility criteria assessed on the survey. Of the 80 that did, 25 (31%) were identified as ineligible via PRIOR. A total of 55 (69%) were identified as eligible and verified in the protocol and were enrolled in the formative study. CONCLUSIONS: Fraudulent surveys compromise study integrity, validity of the data, and trust among participant populations. They also deplete scarce research resources including respondent compensation and personnel time. Our approach of PRIOR to prevent online misrepresentation in data was successful. This paper reviews key elements regarding fraudulent data participation in online research and demonstrates why enhanced protocols to prevent fraudulent data collection are crucial for building trust with vulnerable populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT04376346; https://www.clinicaltrials.gov/study/NCT04376346. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52281.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3ee/11211704/06b56516f7d0/resprot_v13i1e52281_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3ee/11211704/06b56516f7d0/resprot_v13i1e52281_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3ee/11211704/06b56516f7d0/resprot_v13i1e52281_fig1.jpg

相似文献

[1]
Combating Fraudulent Participation in Urban American Indian and Alaska Native Virtual Health Research: Protocol for Increasing Data Integrity in Online Research (PRIOR).

JMIR Res Protoc. 2024-6-13

[2]
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[9]
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引用本文的文献

[1]
Imposters, Bots, and Other Threats to Data Integrity in Online Research: Scoping Review of the Literature and Recommendations for Best Practices.

Online J Public Health Inform. 2025-8-29

[2]
Culture and COVID-19 Related Impacts on Alcohol-Exposed Pregnancy Risk Among Urban American Indian and Alaska Native Young Adults: A Path Analysis.

J Adolesc Health. 2025-2-19

[3]
Challenges and Lessons Learned in Managing Web-Based Survey Fraud for the Garnering Effective Outreach and Research in Georgia for Impact Alliance-Community Engagement Alliance Survey Administrations.

JMIR Public Health Surveill. 2024-12-24

[4]
Identifying and Removing Fraudulent Attempts to Enroll in a Human Health Improvement Intervention Trial in Rural Communities.

Methods Protoc. 2024-11-9

本文引用的文献

[1]
Identifying and preventing fraudulent responses in online public health surveys: Lessons learned during the COVID-19 pandemic.

PLOS Glob Public Health. 2023-8-23

[2]
A virtual randomized controlled trial of an alcohol-exposed pregnancy prevention mobile app with urban American Indian and Alaska Native young women: Native WYSE CHOICES rationale, design, and methods.

Contemp Clin Trials. 2023-5

[3]
Centering Native Youths' Needs and Priorities: Findings from the 2020 Native Youth Health Tech Survey.

Am Indian Alsk Native Ment Health Res. 2022

[4]
The Indian Health Service and American Indian/Alaska Native Health Outcomes.

Annu Rev Public Health. 2022-4-5

[5]
Ensuring survey research data integrity in the era of internet bots.

Qual Quant. 2022

[6]
Threats of Bots and Other Bad Actors to Data Quality Following Research Participant Recruitment Through Social Media: Cross-Sectional Questionnaire.

J Med Internet Res. 2020-10-7

[7]
Participant carelessness and fraud: Consequences for clinical research and potential solutions.

J Abnorm Psychol. 2020-1

[8]
Youth Study Recruitment Using Paid Advertising on Instagram, Snapchat, and Facebook: Cross-Sectional Survey Study.

JMIR Public Health Surveill. 2019-10-9

[9]
Disparities in Cancer Incidence and Trends among American Indians and Alaska Natives in the United States, 2010-2015.

Cancer Epidemiol Biomarkers Prev. 2019-10

[10]
Web-Based Eligibility Quizzes to Verify Opioid Use and County Residence Among Rural Young Adults: Eligibility Screening Results from a Feasibility Study.

JMIR Res Protoc. 2019-6-18

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