Overview of the Health Communication Curriculum in Canadian Master of Public Health Programs
Bibliographic record
Abstract
CONTEXT: Competency-based public health education ensures practitioners are well equipped to positively influence the health of the public. The Public Health Agency of Canada's Core Competencies for Public Health has named communication as an essential competency area for practitioners. However, little is known about how Master of Public Health (MPH) programs in Canada support trainees in developing the recommended core competencies in communication. OBJECTIVE: Our research aims to provide an overview of the extent to which communication is embedded in the curriculum of MPH programs in Canada. DESIGN: We conducted an online scan of Canadian MPH course titles and descriptions to determine how many MPH programs offer communication-focused courses (ie, health communication), knowledge mobilization courses (eg, knowledge translation), and other courses that may support communication skills. Two researchers coded the data; discrepancies were resolved via discussion. RESULTS: Of the 19 MPH programs in Canada, less than half (n = 9) offer courses specifically focused on communication (ie, health communication); these courses are mandatory in only 4 programs. Seven programs offer knowledge mobilization courses; none are mandatory. Sixteen MPH programs offer a total of 63 other public health courses that are not focused on communication but contain communication terms (eg, marketing, literacy) in their course descriptions. No Canadian MPH program has a communication-focused stream or option. CONCLUSION: Canadian-trained MPH graduates may not be receiving sufficient communication training to equip them for effective and precise public health practice. This is particularly concerning, given that current events have underlined the importance of health, risk, and crisis communication.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".