ArticleInternational journal of environmental research and public health2021
Designing an Indoor Radon Risk Exposure Indicator (IRREI): An Evaluation Tool for Risk Management and Communication in the IoT Age.
Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Radon exposure: a major cause of lung cancer in nonsmokers.Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia · 2023Review
- Impacts of Indoor Radon on Health: A Comprehensive Review on Causes, Assessment and Remediation Strategies.International journal of environmental research and public health · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The explosive data growth in the current information age requires consistent new methodologies harmonized with the new IoT era for data analysis in a space-time context. Moreover, intuitive data visualization is a central feature in exploring, interpreting, and extracting specific insights for subsequent numerical data representation. This integrated process is normally based on the definition of relevant metrics and specific performance indicators, both computed upon continuous real-time data, considering the specificities of a particular application case for data validation. This article presents an IoT-oriented evaluation tool for Radon Risk Management (RRM), based on the design of a simple and intuitive Indoor Radon Risk Exposure Indicator (IRREI), specifically tailored to be used as a decision-making aid tool for building owners, building designers, and buildings managers, or simply as an alert flag for the problem awareness of ordinary citizens. The proposed methodology was designed for graphic representation aligned with the requirements of the current IoT age, i.e., the methodology is robust enough for continuous data collection with specific Spatio-temporal attributes and, therefore, a set of adequate Radon risk-related metrics can be extracted and proposed. Metrics are summarized considering the application case, taken as a case study for data validation, by including relevant variables to frame the study, such as the regulatory International Commission on Radiological Protection (ICRP) dosimetric limits, building occupancy (spatial dimension), and occupants' exposure periods (temporal dimension). This work has the following main contributions: (1) providing a historical perspective regarding RRM indicator evolution along time; (2) outlining both the formulation and the validation of the proposed IRREI indicator; (3) implementing an IoT-oriented methodology for an RRM indicator; and (4) a discussion on Radon risk public perception, undertaken based on the results obtained after assessment of the IRREI indicator by applying a screening questionnaire with a total of 873 valid answers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.