One Health and EcoHealth in Ontario: a qualitative study exploring how holistic and integrative approaches are shaping public health practice in Ontario
Bibliographic record
Abstract
BACKGROUND: There is a growing recognition that many public health issues are complex and can be best understood by examining the relationship between human health and the health of the ecosystems in which people live. Two approaches, One Health and Ecosystem Approaches to Health (EcoHealth), can help us to better understand these intricate and complex connections, and appear to hold great promise for tackling many modern public health dilemmas. Although both One Health and EcoHealth have garnered recognition from numerous health bodies in Canada and abroad, there is still a need to better understand how these approaches are shaping the practice of public health in Ontario.The purpose of this study was to characterize how public health actors in Ontario are influenced by the holistic principles which underlie One Health and EcoHealth, and to identify important lessons from their experiences. METHODS: Ten semi-structured interviews were conducted with ten participants from the public health sphere in Ontario. Participants encompassed diverse perspectives including infectious disease, food systems, urban agriculture, and environmental health. Interviews were recorded, transcribed and analyzed using qualitative content analysis to identify major themes and patterns. RESULTS: Four major themes emerged from the interviews: the importance of connecting human health with the environment; the role of governance in promoting these ideas; the value of partnerships and collaborations in public health practice; and the challenge of operationalizing holistic approaches to public health. Overall study participants were found to be heavily influenced by concepts couched in EcoHealth and One Health literature, despite a lack of familiarity with these fields. CONCLUSIONS: Although One Health and EcoHealth are lesser known approaches in the public health sphere, their holistic and systems-based principles were found to influence the thoughts, values and experiences of public health actors interviewed in this study. This study also highlights the critical role of governance and partnerships in facilitating a holistic approach to health. Further research on governance and partnership models, as well as systems-based organizational working practices, is needed to close the gap between One Health and EcoHealth theory and public health practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".