Events Calendar

Interested in learning more about implementation science and dissemination and implementation strategies?

You are invited to a virtual Dissemination and Implementation Science Special Interest Group Meeting on Tuesday, December 1, 10:00-11:00AM to present your research project, solicit feedback from other members, and receive advice from Tufts CTSI faculty leads Denise Daudelin, RN, MPH, and Sara Folta, PhD.

Even if you do not have a current project, you are welcome to join to learn more about this emerging field and hear from fellow researchers.

Details

Date: Tuesday, December 1, 10:00-11:00AM

Registration

To attend, please enroll here via Tufts CTSI I LEARN.

Does your study follow the best practice of communicating end results to participants? Are you disseminating findings to affected communities that are understandable and actionable?

The new Common Rule (NIH 2017) emphasizes the need for clinical research investigators and teams to provide participants with information they can read, understand and act on. In a recent survey of past clinical trial participants (CISCRP 2019), 68% said they wanted to receive a post-study summary of results they could understand and use, but only 38% reported receiving any such communication.

In this asynchronous, online workshop, participants will learn about health literacy and plain language as a strategic effort to communicate more clearly throughout the clinical research life cycle, practice plain language writing and design techniques to communicate end of study findings, and engage in dialogue and reflection on how to apply lessons learned in practice.

Details

Date: Access course materials at any time from December 2 through December 9, 2020.

Location: I LEARN course management system

Audience: Clinical research investigators and coordinators, and anyone on the clinical research team responsible for communicating results to study participants, are encouraged to attend, especially investigators and study teams with results ready to share.

If you are an investigator with experience sharing study results with study participants and the public, please contact sabrina.kurtz_rossi@tufts.edu so that we may incorporate your experience, questions, and challenges into the content of the training.

To join in this asynchronous training, participants must be able to access the Internet. Participants will be asked to log onto the I LEARN course management system to access all training materials.

Course enrollment priority is given to researchers from Tufts CTSI partner institutions.
If your participation needs to be approved by your supervisor or a person responsible for your time release, you may provide their contact information when you register for the program.

Registration

Enroll in Dissemination of Research Results to Participants and the Public.

What is your role in being an anti-racist researcher and creating a trustworthy research enterprise?

This webinar will focus on looking at the history of malfeasance in research including up to the present day. We will explore how mistrust of research is mediated through historical and generational trauma and how it impacts present day perceptions of research. We will discuss how we can flip the narrative around mistrust of research as a “barrier” to focus on what researchers can do to become more trustworthy. We will outline specific steps you can take to bring awareness to your labs and study teams to engage in anti-racism and anti-oppression in your work.

You will come away with concrete steps that you can take, resources you can utilize, and continued support from Tufts CTSI to engage in dialogue with your teams and colleagues.

Details

Date: December 9, 2020, noon-1:00PM

Location: I LEARN course management system

Registration

Enroll in Taking Responsibility for Building a Trustworthy Research Enterprise.

Interested in learning how to make your data analysis and other scientific computations reproducible?

The Center for Quantitative Methods and Data Science, in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center and the Data-Intensive Studies Center (DISC) will host a virtual seminar series on a Wednesday each month from 2:00-3:00PM.

The session on Wednesday, December 16 will feature Karl Broman, PhD. He will give a talk titled Steps Toward Reproducible Research.

Abstract

A minimal standard for data analysis and other scientific computations is that they be reproducible: that the code and data are assembled in a way so that another group can re-create all of the results (e.g., the figures and table in a paper). Adopting a workflow that will make your results reproducible will ultimately make your life easier; if a problem or question arises somewhere down the line, it will be much easier to correct or explain.

But organizing analyses so that they are reproducible is not easy. It requires diligence and a considerable investment of time: to learn new computational tools, and to organize and document analyses as you go. Nevertheless, partially reproducible is better than not at all reproducible. Just try to make your next paper or project better organized than the last. There are many paths toward reproducible research, and you shouldn’t try to change all aspects of your current practices all at once. Identify one weakness, adopt an improved approach, refine that a bit, and then move on to the next thing. Dr. Karl Broman will offer some suggestions for the initial steps to take towards making your work reproducible.

Faculty

Dr. Karl Broman is a Professor in the Department of Biostatistics & Medical Informatics at the University of Wisconsin-Madison. Dr. Broman is an applied statistician working on the genetics of complex diseases in experimental organisms. He develops the R package, R/qtl, has written a number of short tutorials useful for data scientists, and is very keen to develop tools for interactive data visualization (to view an example, click here).

Details

Date: Wednesday, December 16, 2020, 2:00-3:00PM

Registration

To attend, please enroll via Tufts CTSI I LEARN here.