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Record W6888534063 · doi:10.20381/ruor-23733

A Population Health Approach to Examine Ottawa-Gatineau Residents’ Perception of Radon Health Risk

2019· dissertation· en· W6888534063 on OpenAlexaboutno aff

Bibliographic record

VenueuO Research (University of Ottawa) · 2019
Typedissertation
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationPublic healthGovernment (linguistics)Psychological interventionWork (physics)

Abstract

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Background: Radon is a high impact environmental pollutant and is the second leading cause of lung cancer in Canada. Despite the gravity of the health risk, residents have inadequate awareness and have taken minimum preventive actions. The success of any population-level health awareness program is contingent on the views and actions of key decision makers at the household level. People's perceptions of the risk should inform health communication messaging that aims to motivate them to take preventive measures. The objective of this study was to measure the quantifiable associations and predictions between perceptions of radon health risk and their preventive actions; to explore and examines the social determinants that enable and hinder the adoption of preventive measures. Additionally, the best effective radon control systems for both the new and existing houses and relevant policy implications have been examined. 
\nMethods: A mixed methods study consisting of surveys (n=557) and qualitative interviews (n=35) was conducted with both homeowners and tenants of Ottawa-Gatineau areas. Descriptive, correlation and regression analyses addressed the quantitative research questions. Thematic, inductive analysis identified themes in the qualitative data. A mixed methods analysis triangulate both results. A registered systematic review of radon interventions around the world was conducted and radon policy analysis was done by applying interdisciplinary frameworks. 
\nResults: Residents’ perceptions of radon health risk, smoking at home, social influence, and care for family significantly correlated with their intention to test for radon; the same variables predicted their protection behaviours. Residents obtained information on radon from the media, individual search, workplace and social networks. Residents who had dual - cognitive and emotional awareness of the risk, were motivated enough to take action. Having an understanding of the risk, caring for family, knowing others who contracted lung cancer and being financially capable were enablers for action. Obstacles included lack of awareness, cost of mitigation, lack of home ownership and potential stigma in selling the house. Residents attributed primary responsibility to public agencies for disseminating information and suggested incentivizing and mandating actions to promote preventive measures. Indoor radon is best controlled by installing an active SSDS with additional measures to seal any entry points in the foundation. The policy analysis generated a list of recommendations that can be implemented through multisectoral systems level actions to address the social determinants of risk distribution. 
\nConclusions: Residents do not get the crucial information on radon health risk and report barriers in testing and engaging in protective action. Risk perceptions are subjective and influenced by micro and macro level factors. Inducing protective action to reduce risk requires comprehensive interventions taking into account dual perceptions of the threat. Future research can explore the dual aspects of risk perception and examine the contents of the risk communication message. Policy should address the shared responsibility of both governments and residents in tackling the issue with reasonable incentives and mandatory regulations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.143
GPT teacher head0.441
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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