Development and pilot of the BC Wildfire Smoke and Extreme Heat Action Plan: empowering patients with climate health readiness
Bibliographic record
Abstract
Globally, wildfire smoke and extreme heat events are increasing in frequency and intensity. Western Canada, including the Province of British Columbia (BC), is impacted annually by these events, resulting in the accelerated development of public health messaging and emergency preparedness. It is particularly important to reach, educate and empower individuals who are highly susceptible to climate events, such as those with respiratory diseases, through targeted communication strategies delivered by trusted sources. We aimed to develop an evidence-informed action plan (AP) tool and pilot integration into clinical encounters with patients living with asthma and chronic obstructive pulmonary disease (COPD).The project team developed a draft tool-a BC Wildfire Smoke and Extreme Heat AP document inspired by the concept of an Asthma AP-along with a guide to support healthcare providers in addressing questions during patient counselling sessions. Iterative feedback from trained patient partners, clinicians and knowledge translation specialists was incorporated to refine messaging and delivery. Use of the tool was piloted in clinical encounters between certified respiratory educators (CREs) and patients living with asthma and COPD in two regional health authorities. Additional process and content feedback was gathered via questionnaires and focus groups.Patients (project participants) reported that AP tool use increased their understanding and preparedness for wildfire smoke and extreme heat events. While the plan was positively received by providers in a CRE role, time constraints and staffing capacity were highlighted as barriers to implementation. Suggested improvements included strengthened public awareness, preseason deployment and enhancement of content and delivery. Additional quality improvement cycles are needed to increase readability, accessibility and actionability.
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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 | 0.022 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".