In a risk society, personal values can be important resources, useful for managing uncertainty and guiding people in the perception of risk. The goal of this article is to explore the relationship between risk intelligence and personal values. The participants were 731 Italian adults aged between 18 and 65 years (M = 30.25; DS = 10.71). The survey was composed of the following measures: Subjective Risk Intelligence Scale and Portrait Values Questionnaire. Data analyses have found significant relationships between some types of personal values and risk intelligence: subjective risk intelligence is negatively related to conservation and positively related to openness to change and self-transcendence, but it was not related to self-enhancement. Furthermore, values of openness to change and self-transcendence mediate the relationship between age and subjective risk intelligence, while conservation values and self-enhancement values did not mediate the same relationship. Implication for practice and future research will be discussed.
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http://dx.doi.org/10.3390/bs11080109 | DOI Listing |
Sci Rep
December 2024
College of Mechanical and Electronic Engineering, Dalian Minzu University, Dalian, 116650, Liaoning, China.
The novel coronavirus (COVID-19) has affected more than two million people of the world, and far social distancing and segregated lifestyle have to be adopted as a common solution in recent years. To solve the problem of sanitation control and epidemic prevention in public places, in this paper, an intelligent disinfection control system based on the STM32 single-chip microprocessor was designed to realize intelligent closed-loop disinfection in local public places such as public toilets. The proposed system comprises seven modules: image acquisition, spraying control, disinfectant liquid level control, access control, voice broadcast, system display, and data storage.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
View Article and Find Full Text PDFFront Public Health
December 2024
Department of Data Integration and Analysis, Statens Serum Institut, Copenhagen, Denmark.
Except for a few countries, comprehensive all-cause surveillance for bacteremia is not part of mandatory routine public health surveillance. We argue that time has come to include automated surveillance for bacteremia in the national surveillance systems, and explore diverse approaches and challenges in establishing bacteremia monitoring. Assessed against proposed criteria, surveillance for bacteremia should be given high priority.
View Article and Find Full Text PDFBackground: Seeking sexual partners in men who have sex with men (MSM) venues has been regarded as a high-risk behavior for HIV among MSM. Nevertheless, with the implementation of venue-based interventions and the change in the way MSM seek sexual partners, the continued status of MSM venues as the HIV risk factor remains inconclusive. This study endeavors to delve into this ambiguity by examining the MSM sexual contact network (SCN) as a foundation.
View Article and Find Full Text PDFHealth Inf Sci Syst
December 2025
School of Nursing, National Taipei University of Nursing and Health Sciences, No. 365, Ming-Te Road, Peitou District, Taipei, 112 Taiwan.
Background: Health risks associated with phthalate esters depend on exposure level, individual sensitivities, and other contributing factors.
Purpose: This study employed artificial intelligence algorithms while applying data mining techniques to identify correlations between phthalate esters [di(2-ethylhexyl) phthalate, DEHP], lifestyle factors, and disease outcomes.
Methods: We conducted exploratory analysis using demographic and laboratory data collected from the Taiwan Biobank.
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