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Factors Affecting Risk Perception of Electromagnetic Waves From 5G Network Base Stations.

ABSTRACT: The coverage of the fifth-generation network has increased steadily since the network was introduced in 2019. However, public protests around the globe against the construction of 5G network base stations have continued to occur for fear that electromagnetic (EM) waves emitted from the stations would cause adverse health effects. To identify factors that have contributed to such increased risk perception, we conducted a cross-sectional study using data obtained from a survey that assessed Korean adults' risk perception of EM wave-related objects. We found that female gender, high level of perceived exposure to EM waves, evaluation of public policies as ineffective, and high level of objective knowledge on EM waves were associated with increased risk perception. Furthermore, we found that higher ratings on a few risk characteristics such as "personal knowledge," "seriousness of the risk to future generations," "dreadfulness," and "severity of consequences" were also associated with increased risk perception as well. Bioelectromagnetics. © 2020 The Authors. Bioelectromagnetics published by Wiley Periodicals LLC on behalf of Bioelectromagnetics Society.

SUBMITTER: Koh TH

PROVIDER: S-EPMC7540494 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Factors Affecting Risk Perception of Electromagnetic Waves From 5G Network Base Stations.

Koh Tae Hwan TH Choi Jae Wook JW Seo Myungsoon M Choi Hyung-Do HD Kim KyungHee K

Bioelectromagnetics 20200831 7

The coverage of the fifth-generation network has increased steadily since the network was introduced in 2019. However, public protests around the globe against the construction of 5G network base stations have continued to occur for fear that electromagnetic (EM) waves emitted from the stations would cause adverse health effects. To identify factors that have contributed to such increased risk perception, we conducted a cross-sectional study using data obtained from a survey that assessed Korean ...[more]

PMID: 32865268

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Project description:Osteoporosis is a disease characterized by impairment of bone microarchitecture that causes high socioeconomic impacts in the world because of fractures and hospitalizations. Although dual-energy X-ray absorptiometry (DXA) is the gold standard for diagnosing the disease, access to DXA in developing countries is still limited due to its high cost, being present only in specialized hospitals. In this paper, we analyze the performance of Osseus, a low-cost portable device based on electromagnetic waves that measures the attenuation of the signal that crosses the medial phalanx of a patient's middle finger and was developed for osteoporosis screening. The analysis is carried out by predicting changes in bone mineral density using Osseus measurements and additional common risk factors used as input features to a set of supervised classification models, while the results from DXA are taken as target (real) values during the training of the machine learning algorithms. The dataset consisted of 505 patients who underwent osteoporosis screening with both devices (DXA and Osseus), of whom 21.8% were healthy and 78.2% had low bone mineral density or osteoporosis. A cross-validation with k-fold = 5 was considered in model training, while 20% of the whole dataset was used for testing. The obtained performance of the best model (Random Forest) presented a sensitivity of 0.853, a specificity of 0.879, and an F1 of 0.859. Since the Random Forest (RF) algorithm allows some interpretability of its results (through the impurity check), we were able to identify the most important variables in the classification of osteoporosis. The results showed that the most important variables were age, body mass index, and the signal attenuation provided by Osseus. The RF model, when used together with Osseus measurements, is effective in screening patients and facilitates the early diagnosis of osteoporosis. The main advantages of such early screening are the reduction of costs associated with exams, surgeries, treatments, and hospitalizations, as well as improved quality of life for patients.

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Factors Affecting Risk Perception of Electromagnetic Waves From 5G Network Base Stations.

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Factors Affecting Risk Perception of Electromagnetic Waves From 5G Network Base Stations.

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