Tag: imposter participants
-
Experts Call for Action Against Imposter Participants in Health Studies
What are imposter participants? Imposter participants are individuals who provide deceptive or inaccurate data to participate in health research, or automated computer bots that mimic human responses. As online recruitment becomes central to modern health studies—from surveys to randomized trials—the potential for these imposters to skew results grows. The concern, highlighted by Eileen Morrow and…
-
Imposter Participants Threaten Health Studies: Experts Call for Stronger Safeguards
The rising challenge of imposter participants in health research Health studies increasingly rely on online recruitment to reach diverse populations quickly and at scale. But this shift has brought a troubling problem to the fore: imposter participants. In a commentary published in The BMJ, Eileen Morrow and colleagues from the University of Oxford argue that…
-
Imposter Participants in Health Research: A Growing Threat
Background: Why imposter participants matter in health research Imposter participants—individuals who deliberately provide false or misleading data, or automated bots that mimic human responses—pose a growing challenge to health research. As The BMJ highlights, this issue undermines not only the data used to derive clinical insights but also the policies and medical decisions built on…
-
Is this response real? Imposters threaten health studies
What is at stake when imposters join health studies? Recent concerns from researchers highlight a troubling trend: impostor participants slipping into quantitative health studies. The integrity of data collected in surveys and trials can be compromised when individuals misrepresent themselves or automate their responses for ulterior motives. When the underlying data are unreliable, the clinical…
-
Is this response real? Imposters are putting health studies at risk
Imposters in health research: a growing threat to data integrity Researchers conducting health studies increasingly worry about a quiet but serious problem: imposter participants. These aren’t misclassified data points from honest respondents. They are fraudulent entries or bots that masquerade as legitimate study participants, potentially skewing results, misinforming policy, and leading to questionable clinical decisions.…