23
views
0
recommends
+1 Recommend
1 collections
    0
    shares

      Submit your digital health research with an established publisher
      - celebrating 25 years of open access

      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

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

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Recruitment of health research participants through social media is becoming more common. In the United States, 80% of adults use at least one social media platform. Social media platforms may allow researchers to reach potential participants efficiently. However, online research methods may be associated with unique threats to sample validity and data integrity. Limited research has described issues of data quality and authenticity associated with the recruitment of health research participants through social media, and sources of low-quality and fraudulent data in this context are poorly understood.

          Objective

          The goal of the research was to describe and explain threats to sample validity and data integrity following recruitment of health research participants through social media and summarize recommended strategies to mitigate these threats. Our experience designing and implementing a research study using social media recruitment and online data collection serves as a case study.

          Methods

          Using published strategies to preserve data integrity, we recruited participants to complete an online survey through the social media platforms Twitter and Facebook. Participants were to receive $15 upon survey completion. Prior to manually issuing remuneration, we reviewed completed surveys for indicators of fraudulent or low-quality data. Indicators attributable to respondent error were labeled suspicious, while those suggesting misrepresentation were labeled fraudulent. We planned to remove cases with 1 fraudulent indicator or at least 3 suspicious indicators.

          Results

          Within 7 hours of survey activation, we received 271 completed surveys. We classified 94.5% (256/271) of cases as fraudulent and 5.5% (15/271) as suspicious. In total, 86.7% (235/271) provided inconsistent responses to verifiable items and 16.2% (44/271) exhibited evidence of bot automation. Of the fraudulent cases, 53.9% (138/256) provided a duplicate or unusual response to one or more open-ended items and 52.0% (133/256) exhibited evidence of inattention.

          Conclusions

          Research findings from several disciplines suggest studies in which research participants are recruited through social media are susceptible to data quality issues. Opportunistic individuals who use virtual private servers to fraudulently complete research surveys for profit may contribute to low-quality data. Strategies to preserve data integrity following research participant recruitment through social media are limited. Development and testing of novel strategies to prevent and detect fraud is a research priority.

          Related collections

          Most cited references30

          • Record: found
          • Abstract: found
          • Article: not found

          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            The Use of Facebook in Recruiting Participants for Health Research Purposes: A Systematic Review

            Background Social media is a popular online tool that allows users to communicate and exchange information. It allows digital content such as pictures, videos and websites to be shared, discussed, republished and endorsed by its users, their friends and businesses. Adverts can be posted and promoted to specific target audiences by demographics such as region, age or gender. Recruiting for health research is complex with strict requirement criteria imposed on the participants. Traditional research recruitment relies on flyers, newspaper adverts, radio and television broadcasts, letters, emails, website listings, and word of mouth. These methods are potentially poor at recruiting hard to reach demographics, can be slow and expensive. Recruitment via social media, in particular Facebook, may be faster and cheaper. Objective The aim of this study was to systematically review the literature regarding the current use and success of Facebook to recruit participants for health research purposes. Methods A literature review was completed in March 2017 in the English language using MEDLINE, EMBASE, Web of Science, PubMed, PsycInfo, Google Scholar, and a hand search of article references. Papers from the past 12 years were included and number of participants, recruitment period, number of impressions, cost per click or participant, and conversion rate extracted. Results A total of 35 studies were identified from the United States (n=22), Australia (n=9), Canada (n=2), Japan (n=1), and Germany (n=1) and appraised using the Critical Appraisal Skills Programme (CASP) checklist. All focused on the feasibility of recruitment via Facebook, with some (n=10) also testing interventions, such as smoking cessation and depression reduction. Most recruited young age groups (16-24 years), with the remaining targeting specific demographics, for example, military veterans. Information from the 35 studies was analyzed with median values being 264 recruited participants, a 3-month recruitment period, 3.3 million impressions, cost per click of US $0.51, conversion rate of 4% (range 0.06-29.50), eligibility of 61% (range 17-100), and cost per participant of US $14.41. The studies showed success in penetrating hard to reach populations, finding the results representative of their control or comparison demographic, except for an over representation of young white women. Conclusions There is growing evidence to suggest that Facebook is a useful recruitment tool and its use, therefore, should be considered when implementing future health research. When compared with traditional recruitment methods (print, radio, television, and email), benefits include reduced costs, shorter recruitment periods, better representation, and improved participant selection in young and hard to reach demographics. It however, remains limited by Internet access and the over representation of young white women. Future studies should recruit across all ages and explore recruitment via other forms of social media.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              The Use of Social Media in Recruitment for Medical Research Studies: A Scoping Review

              Background Recruiting an adequate number of participants into medical research studies is challenging for many researchers. Over the past 10 years, the use of social media websites has increased in the general population. Consequently, social media websites are a new, powerful method for recruiting participants into such studies. Objective The objective was to answer the following questions: (1) Is the use of social media more effective at research participant recruitment than traditional methods? (2) Does social media recruit a sample of research participants comparable to that recruited via other methods? (3) Is social media more cost-effective at research participant recruitment than traditional methods? Methods Using the MEDLINE, PsycINFO, and EMBASE databases, all medical research studies that used social media and at least one other method for recruitment were identified. These studies were then categorized as either interventional studies or observational studies. For each study, the effectiveness of recruitment, demographic characteristics of the participants, and cost-effectiveness of recruitment using social media were evaluated and compared with that of the other methods used. The social media sites used in recruitment were identified, and if a study stated that the target population was “difficult to reach” as identified by the authors of the study, this was noted. Results Out of 30 studies, 12 found social media to be the most effective recruitment method, 15 did not, and 3 found social media to be equally effective as another recruitment method. Of the 12 studies that found social media to be the best recruitment method, 8 were observational studies while 4 were interventional studies. Of the 15 studies that did not find social media to be the best recruitment method, 7 were interventional studies while 8 were observational studies. In total, 8 studies stated that the target population was “hard-to-reach,” and 6 of these studies found social media to be the most effective recruitment method. Out of 14 studies that reported demographic data for participants, 2 studies found that social media recruited a sample comparable to that recruited via traditional methods and 12 did not. Out of 13 studies that reported cost-effectiveness, 5 studies found social media to be the most cost-effective recruitment method, 7 did not, and 1 study found social media equally cost-effective as compared with other methods. Conclusions Only 12 studies out of 30 found social media to be the most effective recruitment method. There is evidence that social media can be the best recruitment method for hard-to-reach populations and observational studies. With only 30 studies having compared recruitment through social media with other methods, more studies need to be done that report the effectiveness of recruitment for each strategy, demographics of participants recruited, and cost-effectiveness of each method.
                Bookmark

                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J Med Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                October 2020
                7 October 2020
                : 22
                : 10
                : e23021
                Affiliations
                [1 ] Phyllis F Cantor Center for Research in Nursing and Patient Care Services Dana-Farber Cancer Institute Boston, MA United States
                [2 ] School of Nursing University of Rochester Rochester, NY United States
                [3 ] McGraw/Patterson Center for Population Sciences Dana-Farber Cancer Institute Boston, MA United States
                [4 ] Department of Psychosocial Oncology and Palliative Care Dana-Farber Cancer Institute Boston, MA United States
                [5 ] Department of Data Sciences Dana-Farber Cancer Institute Boston, MA United States
                [6 ] Survey and Data Management Core Dana-Farber Cancer Institute Boston, MA United States
                [7 ] Department of Biobehavioral Nursing and Health Informatics University of Washington Seattle, WA United States
                Author notes
                Corresponding Author: Rachel Pozzar rachel_pozzar@ 123456dfci.harvard.edu
                Author information
                https://orcid.org/0000-0002-5033-5701
                https://orcid.org/0000-0002-9561-6144
                https://orcid.org/0000-0002-1433-5915
                https://orcid.org/0000-0002-9776-7114
                https://orcid.org/0000-0002-7458-0453
                https://orcid.org/0000-0001-8049-0086
                https://orcid.org/0000-0003-2543-9231
                https://orcid.org/0000-0001-7935-2807
                Article
                v22i10e23021
                10.2196/23021
                7578815
                33026360
                8c311cec-48a7-4e16-a126-e881932d0b2f
                ©Rachel Pozzar, Marilyn J Hammer, Meghan Underhill-Blazey, Alexi A Wright, James A Tulsky, Fangxin Hong, Daniel A Gundersen, Donna L Berry. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 07.10.2020.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 30 July 2020
                : 14 September 2020
                : 16 September 2020
                : 16 September 2020
                Categories
                Original Paper
                Original Paper

                Medicine
                social media,internet,methods,data accuracy,fraud
                Medicine
                social media, internet, methods, data accuracy, fraud

                Comments

                Comment on this article