Creating a Virtual Indigenist Community-Based Participatory Approach: Lessons Learned from Centering Urban Native Young Women in Research

Reed, Nicole D.; Sarche, Michelle; Shrestha, Umit; Bull, Sheana; Howley, Caitlin T.; Shangreau, Carly; Asdigian, Nancy L.; Vossberg, Raeann L.; Leon, Josefa S.; Kaufman, Carol E.

doi:10.1007/s42844-023-00114-z

Cited by 1 publication

(2 citation statements)

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“…The procedures associated with this study and the RCT, including ethical approval and oversight, have been approved by the Colorado Multiple Institutional Review Board (#18-0574). Additionally, a data safety monitoring board was created to review all protocols associated with the RCT, while also providing oversight on data collection and analyses and the interpretation of results [ 39 ]. Informed consent was obtained from all participants, and a US $50 Amazon gift card was issued as compensation for their time.…”

Section: Methodsmentioning

confidence: 99%

“…The resultant generational grief, exacerbated by unscrupulous research practices, has deepened the mistrust of research among both urban- and reservation-based American Indian and Alaska Native communities. This suspicion is a strong call to researchers to rebuild trust [ 37 , 39 ]. Ensuring data authenticity can play a crucial role in helping to bridge this trust between the researcher and the community.…”

Section: Introductionmentioning

confidence: 99%

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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)

Reed,

Bull,

Shrestha

et al. 2024

JMIR Res Protoc

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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 ...

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%