Safeguarding Online Research in Eating Disorders Against Fraud: Increasing Risks and Practical Recommendations.
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| Title: | Safeguarding Online Research in Eating Disorders Against Fraud: Increasing Risks and Practical Recommendations. |
|---|---|
| Authors: | Pennesi, Jamie‐Lee (AUTHOR), Pellizzer, Mia L. (AUTHOR), Wade, Tracey D. (AUTHOR) |
| Source: | International Journal of Eating Disorders. Jul2026, Vol. 59 Issue 7, p1451-1468. 18p. |
| Subjects: | Fraud prevention, Patient selection, Consensus (Social sciences), Research funding, Qualitative research, Human research subjects, Artificial intelligence, Internet, Eating disorders, Surveys, Acquisition of data, Medical research, Delphi method, Data analysis software |
| Abstract: | Objective: Recent growth of online research has been accompanied by an increase in reports of fraudulent participants, which can significantly comprise research validity. Drawing from our experience using Qualtrics with open recruitment, existing literature, and emerging studies in eating disorders (ED), we outline the risk and provide simple, practical recommendations for preventing, detecting, and managing fraudulent participants in online ED research. Method: Over the conduct of a three‐round Delphi consensus study with 138 English‐speaking individuals aged 18 and older, we were inundated with fraudulent sign‐ups between July and August 2024, despite implementing multiple fraud prevention strategies. In response, we introduced additional fraud mitigation strategies and established a three‐step procedure for identifying and managing fraudulent participants. Results: The additional fraud mitigation measures, including a second reCAPTCHA, a duplicate question for consistency checks, and modified attention check questions, potentially aided in preventing further fraudulent sign‐ups. Our procedure involving manual comprehensive review of all incoming survey data and checks against a fraudulent participants' profile enabled us to identify and withdraw suspected or likely fraudulent participants. Discussion: With increasing fraudulent participation rates and rapidly advancing technological advancements such as artificial intelligence, all online studies are at risk and researchers need to be proactive in their use of antifraud practices to safeguard online research. Our practical recommendations can assist future researchers in managing fraudulent participants. Summary: Fraudulent participation in online research is rising rapidly and presents a significant threat to research integrity.All online studies are at risk and researchers must adopt proactive antifraud practices to safeguard data quality.We provide straightforward, practical recommendations for preventing, detecting, and managing fraudulent participation in online research. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Eating Disorders is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
| FullText | Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 195039067 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Safeguarding Online Research in Eating Disorders Against Fraud: Increasing Risks and Practical Recommendations. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Pennesi%2C+Jamie‐Lee%22">Pennesi, Jamie‐Lee</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pellizzer%2C+Mia+L%2E%22">Pellizzer, Mia L.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wade%2C+Tracey+D%2E%22">Wade, Tracey D.</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Eating+Disorders%22">International Journal of Eating Disorders</searchLink>. Jul2026, Vol. 59 Issue 7, p1451-1468. 18p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Fraud+prevention%22">Fraud prevention</searchLink><br /><searchLink fieldCode="DE" term="%22Patient+selection%22">Patient selection</searchLink><br /><searchLink fieldCode="DE" term="%22Consensus+%28Social+sciences%29%22">Consensus (Social sciences)</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Qualitative+research%22">Qualitative research</searchLink><br /><searchLink fieldCode="DE" term="%22Human+research+subjects%22">Human research subjects</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Internet%22">Internet</searchLink><br /><searchLink fieldCode="DE" term="%22Eating+disorders%22">Eating disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Surveys%22">Surveys</searchLink><br /><searchLink fieldCode="DE" term="%22Acquisition+of+data%22">Acquisition of data</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+research%22">Medical research</searchLink><br /><searchLink fieldCode="DE" term="%22Delphi+method%22">Delphi method</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Objective: Recent growth of online research has been accompanied by an increase in reports of fraudulent participants, which can significantly comprise research validity. Drawing from our experience using Qualtrics with open recruitment, existing literature, and emerging studies in eating disorders (ED), we outline the risk and provide simple, practical recommendations for preventing, detecting, and managing fraudulent participants in online ED research. Method: Over the conduct of a three‐round Delphi consensus study with 138 English‐speaking individuals aged 18 and older, we were inundated with fraudulent sign‐ups between July and August 2024, despite implementing multiple fraud prevention strategies. In response, we introduced additional fraud mitigation strategies and established a three‐step procedure for identifying and managing fraudulent participants. Results: The additional fraud mitigation measures, including a second reCAPTCHA, a duplicate question for consistency checks, and modified attention check questions, potentially aided in preventing further fraudulent sign‐ups. Our procedure involving manual comprehensive review of all incoming survey data and checks against a fraudulent participants' profile enabled us to identify and withdraw suspected or likely fraudulent participants. Discussion: With increasing fraudulent participation rates and rapidly advancing technological advancements such as artificial intelligence, all online studies are at risk and researchers need to be proactive in their use of antifraud practices to safeguard online research. Our practical recommendations can assist future researchers in managing fraudulent participants. Summary: Fraudulent participation in online research is rising rapidly and presents a significant threat to research integrity.All online studies are at risk and researchers must adopt proactive antifraud practices to safeguard data quality.We provide straightforward, practical recommendations for preventing, detecting, and managing fraudulent participation in online research. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Eating Disorders is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=195039067 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/eat.70083 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 1451 Subjects: – SubjectFull: Fraud prevention Type: general – SubjectFull: Patient selection Type: general – SubjectFull: Consensus (Social sciences) Type: general – SubjectFull: Research funding Type: general – SubjectFull: Qualitative research Type: general – SubjectFull: Human research subjects Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Internet Type: general – SubjectFull: Eating disorders Type: general – SubjectFull: Surveys Type: general – SubjectFull: Acquisition of data Type: general – SubjectFull: Medical research Type: general – SubjectFull: Delphi method Type: general – SubjectFull: Data analysis software Type: general Titles: – TitleFull: Safeguarding Online Research in Eating Disorders Against Fraud: Increasing Risks and Practical Recommendations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Pennesi, Jamie‐Lee – PersonEntity: Name: NameFull: Pellizzer, Mia L. – PersonEntity: Name: NameFull: Wade, Tracey D. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 02763478 Numbering: – Type: volume Value: 59 – Type: issue Value: 7 Titles: – TitleFull: International Journal of Eating Disorders Type: main |
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