11 research outputs found
Association of germline variants in the <i>APOBEC3</i> region with cancer risk and enrichment with APOBEC-signature mutations in tumors
Are Emergency Departments in the United States Following Recommendations by the Emergency Severity Index to Promote Quality Triage and Reliability?
Functional analysis of the host defense peptide Human Beta Defensin-1: New insight into its potential role in cancer
Environmental Risk Perceptions and the White Male Effect: Pollution Concerns among Deep-South Coastal Residents
An Examination of the Relationship between House Orientation and Thermal Efficiency in the American Southwest
Initiatives to reduce overcrowding and access block in Australian emergency departments: A literature review
Implementing stakeholder engagement to explore alternative models of consent: An example from the PREP-IT trials
Introduction: Cluster randomized crossover trials are often faced with a dilemma when selecting an optimal model of consent, as the traditional model of obtaining informed consent from participant's before initiating any trial related activities may not be suitable. We describe our experience of engaging patient advisors to identify an optimal model of consent for the PREP-IT trials. This paper also examines surrogate measures of success for the selected model of consent. Methods: The PREP-IT program consists of two multi-center cluster randomized crossover trials that engaged patient advisors to determine an optimal model of consent. Patient advisors and stakeholders met regularly and reached consensus on decisions related to the trial design including the model for consent. Patient advisors provided valuable insight on how key decisions on trial design and conduct would be received by participants and the impact these decisions will have. Results: Patient advisors, together with stakeholders, reviewed the pros and cons and the requirements for the traditional model of consent, deferred consent, and waiver of consent. Collectively, they agreed upon a deferred consent model, in which patients may be approached for consent after their fracture surgery and prior to data collection. The consent rate in PREP-IT is 80.7%, and 0.67% of participants have withdrawn consent for participation. Discussion: Involvement of patient advisors in the development of an optimal model of consent has been successful. Engagement of patient advisors is recommended for other large trials where the traditional model of consent may not be optimal