Dr. Lucie Lévesque

Professor

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Biography

Dr. Lévesque leads the Community-Engaged Health Promotion Research Group in the School of Kinesiology and Health Studies. Her research focuses on program evaluation and implementation science, particularly in the context of community-based physical activity interventions, utilizing an ecological approach. She has served as a long-time member of the Kahnawà:ke Schools Diabetes Prevention Program research team and frequently collaborates on Indigenous research initiatives. Dr. Lévesque possesses extensive experience in working with Indigenous communities using a community-based participatory research framework. Her work emphasizes community engagement and the production and dissemination of action-oriented knowledge. Moreover, her research encompasses both Indigenous and mainstream Western scientific approaches aiming to conduct research that is respectful and relevant to Indigenous communities across Canada. In addition to her work with Indigenous communities, she collaborates with public health researchers in local communities in Latin America and the Caribbean to conduct program evaluation research related to physical activity and health promotion.

Research Interests

Courses

KINE 301U KNPE 365 – Motivational Interviewing HLTH 416 – Program Planning Evaluation HLTH 417 – Community-Based Programming Evaluation KHS 830 – Health Promotion Research Seminar KHS 862 – Physical Activity Community: Planning, Implementation Evaluation

Requirements for Queen's University

Master Program
Requirements
GPA Requirement
Required:3.3
TOEFL
Listening
Required:20
Reading
Required:22
Writing
Required:24
Speaking
Required:22
Total
Required:88
IELTS
Overall
Required:7
Prerequisites
Honours Bachelor degree Background in Computing, Mathematics, Statistics, or Engineering
Application Checklist
  • Online application
  • Statement of Research Interest
  • Curriculum Vitae
  • Two academic references
  • Transcripts
Specialization Notes

Department of Computing offers research-based, project-based, and course-based patterns.