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.

/pdf/threats-of-bots-and-other-bad-actors-to-data-quality-4ujx209ejq.pdf

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

The Internet has been a popular source of data amongst academic researchers for many years, and for good reason. Online data collection is fast, provides access to hard-to-reach populations, and is often less expensive than in-lab recruitment. With these benefits also come risks, such as duplicate responses or participant inattention, which can significantly reduce data quality. Very recently, researchers have become aware of another concern associated with online data collection. Bots, also known as automatic survey-takers or fraudsters, have begun infiltrating scientific surveys, largely threatening the integrity of academic research conducted online. The aim of this paper is to warn researchers of the threat posed by bots and to highlight practical strategies that can be used to detect and prevent these bots. We first discuss strategies recommended in the literature that we implemented to identify bot responses from online survey data we collected in the past six months. We then share which strategies proved to be most and least effective in detecting bots. Finally, we discuss the implications of bot-generated data for the integrity of online research and the imminent future of bots in online data collection.

/pdf/got-bots-practical-recommendations-to-protect-online-survey-2waztl6zdu.pdf

Got Bots? Practical Recommendations to Protect Online Survey Data from Bot Attacks

Benefits of Sexual Activity on Psychological, Relational, and Sexual Health During the COVID-19 Breakout.

Ways to Identify Children with Medical Complexity and the Importance of Why.

Veterans underutilize mental health services. We investigated the association between treatment seeking stigma and utilization of mental health services in a sample of 812 young adult veterans. Higher perceived public stigma of treatment seeking was significantly related to lower treatment utilization. Although many veterans were concerned about negative perceptions if they were to seek treatment, a much smaller number of them endorsed that they would judge a fellow veteran negatively in similar situation. Targeting perceived public stigma of treatment seeking, through perceived norms interventions, might help in narrowing the gap between the need and receipt of help among veterans.

Help-Seeking Stigma and Mental Health Treatment Seeking Among Young Adult Veterans

The Pediatric Evaluation of Disability Inventory (PEDI) was originally developed to provide a parent/clinician-reported functional test that was normed on children up to the age of 7 ½ years.1 The PEDI has a long history of application in developmental medicine, serving as a functional outcome measure for clinical research and practice.2 The original PEDI was a fixed-format test in which all items needed to be administered in order to derive a score. In addition to some finding the administration of all PEDI items potentially burdensome, the restriction of norms to only young children also limited its use.3 The purpose of this article is to report on the revision of the PEDI into a series of computer-adaptive tests (CAT) that cover the 0 to 21 year age range.

CATs are being promoted as the next logical step to more efficient health outcome assessments.4 To employ a CAT, Item Response Theory (IRT) modeling is used to express the association between an individual’s response to an item and the outcome domain. IRT measurement models are a class of statistical procedures used to develop measurement scales. The measurement scales are comprised of items with a known relationship between item responses and positions on an underlying functional continuum. Using this approach, probabilities of children scoring a particular response on an item at various functional ability levels can be modeled. These probability estimates are used to determine the child’s most likely position along the functional dimension. When assumptions of a particular IRT model are met, estimates of a child’s functional ability do not strictly depend on a particular fixed set of items. This scaling feature allows one to compare persons along a functional outcome dimension even if they have not completed the identical set of functional items. CAT also optimizes the items administered, providing items most likely to yield the greatest information for score estimation. CATs will generally require fewer items than a comparable length fixed form instrument to achieve similar precision, although the gains in efficiency may not be uniform throughout the full scale.5

Early work has highlighted the possible benefits of using CAT in the assessment of children’s functioning, including improved efficiency with minimal loss of precision.6–9 We have shown that the original PEDI can be successfully engineered into efficient CAT programs.8, 10 The North American Shriners Orthopedic Hospitals have recently developed a series of parent- and child-reported CAT measures of physical functioning and participation for their network with promising results.11–15

The aims of this project were to build and test new PEDI-CAT item banks for an age range of 0 to 21 years and use simulations based on the combined normative and disability calibration samples to assess the accuracy and precision of the PEDI-CAT.

http://www.bu.edu/kidsincontext/files/2009/09/Accuracy-and-precision-of-the-Pediatric-Evaluation-of-Disability-Inventory-computer-adaptive-tests-PEDI-CAT.pdf

Accuracy and precision of the Pediatric Evaluation of Disability Inventory computer-adaptive tests (PEDI-CAT).

Emerging methodological research suggests that the World Wide Web (“Web”) is an appropriate venue for survey data collection, and a promising area for delivering behavioral intervention. However, the use of the Web for research raises concerns regarding sample validity, particularly when the Web is used for recruitment and enrollment. The purpose of this paper is to describe the challenges experienced in two different Web-based studies in which participant misrepresentation threatened sample validity: a survey study and an online intervention study. The lessons learned from these experiences generated three types of strategies researchers can use to reduce the likelihood of participant misrepresentation for eligibility in Web-based research. Examples of procedural/design strategies, technical/software strategies and data analytic strategies are provided along with the methodological strengths and limitations of specific strategies. The discussion includes a series of considerations to guide researchers in the selection of strategies that may be most appropriate given the aims, resources and target population of their studies. Copyright © 2014 John Wiley & Sons, Ltd.

Strategies to address participant misrepresentation for eligibility in Web-based research.

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Accuracy and precision of the Pediatric Evaluation of Disability Inventory computer-adaptive tests (PEDI-CAT).

Strategies to address participant misrepresentation for eligibility in Web-based research.