Using the precaution adoption process model and the health belief model to understand radon testing and mitigation: a pre-post quasi-experimental study
Bibliographic record
Abstract
BACKGROUND: Despite being the leading cause of lung cancer for non-smokers, few Canadians take action to test for and mitigate radon. This study's aim was twofold: (1) to investigate predictors of radon testing and mitigation using the Precaution Adoption Process Model (PAPM) and Health Belief Model (HBM); and (2) to assess the impact on beliefs of receiving radon results above health guidelines. METHODS: A convenience sample within Southeastern Ontario households was recruited to test their homes for radon (N = 1,566) for a pre-post quasi-experimental study. Prior to testing, participants were surveyed on risk factors and HBM constructs. All participants whose homes tested above the World Health Organization's radon guideline (N = 527) were surveyed after receiving their results and followed for up to 2 years after. Participants were classified into PAPM stages and regression analyses were conducted to determine predictors between different stages (from deciding to test onwards). Paired bivariate analyses compared responses before and after receiving results. RESULTS: Perceived benefits from mitigating was associated with progressing through all stages in the study's scope. Perceived susceptibility to and severity of illness and perceptions of cost and time to mitigate were associated with progression through some PAPM stages. Homes with smokers or individuals under 18 were associated with not progressing through some stages. Home radon level was associated with mitigation. Attitudes towards many HBM constructs significantly decreased after receiving a high radon result. CONCLUSIONS: Public health interventions should target specific radon beliefs and stages to ensure households test and mitigate for radon.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".