Implementation Science (ImS)

Hi all,

As you know, CANVAS has been the subject of a ransomware attack.  Although some functionality has been restore, the IMS Program has decided not to provide access to the site until full functionality, stability, and security has been restored. 

Accessing course material: As a temporary measure, we will utilize this Collaborative Learning Environment (CLE) website for the next few weeks. This course website includes all of the resources (videos, slides, readings, and assignments) of the CANVAS site.

Homework Assignments:  All users will have the same password for this temporary website. Thus, you will not be able to upload assignments or comment on other students work. Please upload your homework (Parts 1, 2, and 4) to your small group leader using this Box folder.  You can also submit via email to this email address: IMS_241.xkcinj13bym0jk6n@u.box.com. Your small group leader will provide comments to you via email. 

Please feel free to reach out to any of us with any questions or issues. 

Revised Assignment Plan

Module 5: Stepped Wedge Designs

Learners to re-submit Parts 1 and 2 to the Box on Monday, May 11 for marking

Part 3 feedback is cancelled for this module.

Learners to submit Part 4 to the Box on Friday, May 15

Module 6: Hybrid Designs

Parts 1 and 2 will be due in Box by Friday, May 15.

Part 3 peer feedback is cancelled for this module

There is no Part 4 homework for this module.

Module 7: Factorial and MOST Designs

Parts 1 and 2 will be due in Box by Tuesday, May 19.

Part 3 peer feedback is cancelled

Part 4 / Analysis Lab assignment will be due in Box by Friday, May 22.

Beginning with Module 8 (SMART) we hope to return to Canvas and resume the usual assignment schedule: Parts 1 and 2 due Tuesday, Part 3 peer feedback due Thursday, and Part 4 due Friday.

Mixed methods research is “an approach to research in the social, behavioral, and health sciences in which the investigator gathers both quantitative (closed-ended) and qualitative (open-ended) data, integrates the two, and then draws interpretations based on the combined strengths of both sets of data to understand research problems.” A mixed methods course goes beyond specific quantitative and qualitative methods to equip learners to integrate elements of both for a more complete understanding of issues. This includes addressing Who, What, Where, When, and Why in the same studies. In implementation, science is critical to understanding both if an intervention worked and how it worked.