Identifying Fraudulent Responses and Imposters in Research Recruitment of Subjects Through Social Media.

OBJECTIVE: The aim of this study was to describe strategies to manage bots and frauds (B/F) during online recruitment of research subjects. BACKGROUND: Bots mimic human responses in surveys using sophisticated algorithms. Fraudulent responses occur when false or misleading information is provided to...

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Publicado en:Journal of Nursing Administration (JONA) Vol. 55; no. 7; pp. 388 - 395
Autores principales: Webber-Ritchey, Kashica J., Ally, Felisha, Galura, Sandra, Buck, Jacalyn, Brockway, Cindy, Chipps, Esther, Ponder, Tiffany, Simonovich, Shannon D., Spurlark, Roxanne S., Vancil, Barbara, Monturo, Cheryl
Formato: research tables/charts Journal Article
Publicado: Lippincott Williams & Wilkins Jul/Aug2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul/Aug2025
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        atl: Identifying Fraudulent Responses and Imposters in Research Recruitment of Subjects Through Social Media.
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          Webber-Ritchey, Kashica J.
          Ally, Felisha
          Galura, Sandra
          Buck, Jacalyn
          Brockway, Cindy
          Chipps, Esther
          Ponder, Tiffany
          Simonovich, Shannon D.
          Spurlark, Roxanne S.
          Vancil, Barbara
          Monturo, Cheryl
        affil: Author Affiliations: Associate Professor (Dr Webber-Ritchey), School of Nursing, College of Science and Health, DePaul University, Chicago, Illinois
      sug:
        subj:
          Research, Nursing
          Research Subject Recruitment
          Social Media
          Chatbot
          Patient Selection Methods
          Fraud Prevention and Control
          Human
          United States
          Nurse Managers
          Multimethod Studies
          Snowball Sample
          Descriptive Statistics
          Validation Studies
          Motivation
          Artificial Intelligence
          Eligibility Determination
          Collaboration
          Nursing Organizations
          Professional Organizations
          Data Collection, Computer Assisted
          Data Management
          Checklists
      ab: OBJECTIVE: The aim of this study was to describe strategies to manage bots and frauds (B/F) during online recruitment of research subjects. BACKGROUND: Bots mimic human responses in surveys using sophisticated algorithms. Fraudulent responses occur when false or misleading information is provided to gain research incentives. This research team identified substantial issues with fraudulent responses and imposters. This issue has not been well reported in the literature. METHODS: Nurse managers recruited through social media completed an online survey in a national nurse-led research study. A gift card stipend was offered to participants for survey completion. An unexpected surge in survey responses prompted researchers to halt recruitment. Multiple B/F mitigation and data validation strategies were implemented to ensure data integrity and are discussed in this article. RESULTS: Of the 836 surveys, only 152 (18.2%) were complete and valid. CONCLUSIONS: When using social media for online research, incorporating preemptive mitigation strategies to combat B/F responses is essential.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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