PHDA testimonials

"The courses that provided me the greatest benefit included the Population Health and Geographic Information Systems (GIS), and Spatial Epidemiology and Outbreak Detection.

Using the GIS and SAS skills that I learned from the PHDA program, I was able to create a Normalized Difference Vegetation Index (NDVI) layer using GIS software, which showed peak greenness for the entire country over a ten-year period. Using this data and other administrative databases a team of researchers led by Dr. Dan Crouse and myself, conducted a research study that looked at how living by residential greenspace can impact longevity."

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"PHDA 06 Health Services Program Monitoring and Evaluation course was a bit different as it did not have an SRTL lab component. I had taken a very similar course within my Master’s degree but it wasn’t as applied as the PHDA 06 course which had a very practical project component. I found the instructor’s experience and feedback as well as the peer review work really enabled me to get a lot out of the course evaluation project I completed."

"I found PHDA 05 (Longitudinal Analysis and Multi-level Modelling of Population Health Data) to be the most rewarding as it exposed me to higher level quantitative analyses."

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"The labs and the access to the SRTL were the biggest strengths of these courses. The SRTL had all the software, and all the data, and was really easy to access, and was well maintained and organized. The labs were applied, and had very tangible learning outcomes associated with them. They were practical in purpose, and effective in implementation via the SRLT. The labs were very smooth and impactful."

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Overall, I had a positive program experience. I greatly appreciated the asynchronous format as it allowed me to develop my skills without risking my other professional commitments. I believe the skills I have learned through this program will be directly relevant to my current research interests. The PHDA program is a great program for anyone who is interested in further exploring population-level analyses."

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