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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.
The SAGE Working Group on Vaccine Hesitancy concluded that vaccine hesitancy refers to delay in acceptance or refusal of vaccination despite availability of vaccination services. Vaccine hesitancy is complex and context specific, varying across time, place and vaccines. It is influenced by factors such as complacency, convenience and confidence. The Working Group retained the term 'vaccine' rather than 'vaccination' hesitancy, although the latter more correctly implies the broader range of immunization concerns, as vaccine hesitancy is the more commonly used term. While high levels of hesitancy lead to low vaccine demand, low levels of hesitancy do not necessarily mean high vaccine demand. The Vaccine Hesitancy Determinants Matrix displays the factors influencing the behavioral decision to accept, delay or reject some or all vaccines under three categories: contextual, individual and group, and vaccine/vaccination-specific influences.
Internet-based health research is increasing, and often offers financial incentives but fraudulent behavior by participants can result. Specifically, eligible or ineligible individuals may enter the study multiple times and receive undeserved financial compensation. We review past experiences and approaches to this problem and propose several new strategies. Researchers can detect and prevent Internet research fraud in four broad ways: (1) through the questionnaire/instrument (e.g., including certain questions in survey; and software for administering survey); (2) through participants' non-questionnaire data and seeking external validation (e.g., checking data for same email addresses, usernames, passwords, and/or fake addresses or phone numbers; (3) through computer information, (e.g., IP addresses and cookies), and 4) through study design (e.g., avoid lump sum compensation and interviewing participants). These approaches each have pros and cons, and raise ethical, legal, and logistical questions, given that ethical tensions can emerge between preserving the integrity of research vs. protecting the privacy and confidentiality of study respondents. While past discussions concerning the ethics of online research have tended to focus on the participants' ability to trust the researchers, needs now arise to examine researchers' abilities to trust the participants. This analysis has several critical implications for future practice, policy, and research.
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