UNASSIGNED: The objectives of this study were to explore the rate and types of inappropriate referrals to the wellness services and to assess the impact of multi-level interventions on the rate of inappropriate referrals at Rawdat Al-Khail health center in Qatar.
UNASSIGNED: This study employed a retrospective analysis of all referrals data to Rawdat Al-Khail wellness services extracted from the Electronic Health Records (EHRs) between July 2022 and August 2023. The monthly rates and types of inappropriate referrals were calculated. In this study, pre-post analyses were performed to evaluate the impact of two sets of interventions on reducing inappropriate referral rates. The first set involved the development and distribution of e-referral pathways training manual in September 2022. The second set, implemented in April 2023, included close monitoring the rate and types of referrals, and the initiation of feedback communication between wellness services supervisors and referring physicians for advice and corrective actions.
UNASSIGNED: A total of 966 referrals were received during the study period, with 1:5 male-to-female ratio. Of all referrals, 34.9 % were classified as inappropriate, exhibiting considerable variations among different referring health centers. The most common reason for inappropriate referrals was due to the lack of \"exercise wellness gym assessment form\" (23.8 %). While interventions aimed at enhancing the referral process, they did not result in a significant overall reduction in inappropriate referral rates. However, there was a noteworthy reduction in the inappropriate referrals caused by the lack of \"exercise wellness gym assessment form\" observed from March to August 2023 (41 %-18 %).
UNASSIGNED: This study sheds light on the complexities of wellness services referrals, revealing a high rate of inappropriate referrals that require closer scrutiny. Despite interventions not significantly reducing the rate of these referrals, it emphasizes the need for ongoing improvement strategies. Structured, periodic interventions at higher levels are recommended to enhance referral appropriateness.

Risk perception and use of personal protective equipment (PPE) in pesticide use were studied in 109 farmers of northern Greece. Farmers differed in the levels of pesticide risk perception, with 26.6% showing very low and low levels, 34.9% showing moderate levels, and 38.5% showing high and very high levels. Pesticide risk perception was positively correlated with education and large cultivated area, but negatively with age and non-farming as a main profession. Most farmers (82.6%) showed adequate use of PPE (mostly face mask and gloves). The use of PPE was positively correlated with education and risk perception, but negatively with age and non-farming as a main profession. Farmers with high levels of risk perception used 1.3 and 2.6 times more PPE items than those with moderate and low levels of risk perception, respectively. High education was a positive predictor, whereas main profession other than farming was a negative predictor of PPE use.

Pressure ulcers carry a significant risk in clinical practice. This paper proposes a practical and interpretable approach to estimate the risk levels of pressure ulcers using decision tree models. In order to address the common problem of imbalanced learning in nursing classification datasets, various oversampling configurations are analyzed to improve the data quality prior to modeling. The decision trees built are based on three easily identifiable and clinically relevant pressure ulcer risk indicators: mobility, activity, and skin moisture. Additionally, this research introduces a novel tabular visualization method to enhance the usability of the decision trees in clinical practice. Thus, the primary aim of this approach is to provide nursing professionals with valuable insights for assessing the potential risk levels of pressure ulcers, which could support their decision-making and allow, for example, the application of suitable preventive measures tailored to each patient\'s requirements. The interpretability of the models proposed and their performance, evaluated through stratified cross-validation, make them a helpful tool for nursing care in estimating the pressure ulcer risk level.

Change in lifestyle leads to change in disease patterns from infectious diseases and malnutrition to degenerative diseases, such as coronary heart disease (CHD). The increasing prevalence of cardiovascular diseases among Indonesian workers and the general public will not only burden medical care expenses but also reduce work productivity, leading to more work-related injuries and work-related losses. The aim of this study was to determine the risk factors for CHD (age, sex, blood pressure, smoking, diabetes mellitus, body mass index, and weekly physical activity) and the CHD risk level among university workers. A cross-sectional study was conducted at workers at School of Medicine, Universitas Malikussaleh, Lhokseumawe, Indonesia. The risk level of CHD was calculated using Jakarta Cardiovascular Score and predicting model analyzed with multiple logistic regression model. Our data found that 58.2%, 25.5% and 16.3% of the university workers had low-, medium- and high-risk to have CHD. The final model indicted that the risk of heart disease was determined by gender, age, and the presence of hypertension and diabetes mellitus. Being male had odds ratio (OR) 30.84, aged >41 years old had OR 11.52, having hypertension had OR 4.87 and having diabetes mellitus had OR 13.99 for having high risk of CHD compared to female, those younger than 41 years old, having no hypertension and having no diabetes mellitus, respectively. In conclusion, our data suggests that more than 15% the respondents (university employees) have high risk of CHD and being male and older, and having hypertension and diabetes mellitus are associated with risk of CHD. Implantation of the preventive measures is therefore important to be implemented at the universities.

To quickly isolate suspected cases to control the epidemics, this study proposes a body temperature monitoring system with a thermography based on the Internet of Things (IoT) architecture. The collected data are transmitted to a back-end platform via wireless communication. Using the analyzed data, the platform provides services, such as instant alerts for any anomalies, infectious disease outbreak prediction, and risk level assessment for a given area, and it will be a great help to epidemic prevention. The mean absolute percentage error and root mean square error of the proposed monitoring system under an extensive series of experiments are 0.04% and 0.0204°C, respectively. It shows that the body temperature measured by the thermal imaging sensor in the system can accurately represent the actual body temperature after specific calibrations that take the environmental temperature into account. It can also be expanded to a decision supporting system to help schools or government agencies to make proper decisions to stop the spread of infectious diseases.

Flooding is one of the most widespread and catastrophic natural disasters. The exposure of cropland to floods is directly related to the quality of cropland and food security, so it is particularly important to map the spatiotemporal evolution of this exposure, with a specific focus on longer time series and higher resolution scales. This study is the first of its kind to analyse the worldwide spatiotemporal variability of Cropland Exposure to Flooding (CEF) with the 30 m resolution of Global Land Analysis & Discovery (GLAD) dataset during 2000-2019. The findings indicate that: (1) the global CEF area increased by a total of 83,429.50 km2 or 7.75 %, from 2000 to 2019; (2) only North America\'s CEF showed a downward trend, and the region with the largest increase in CEF was South Asia; (3) the CEF in 23 river basins, including Ganges, Indus, Mississippi, Yangtze, and Danube, accounted for 79.88 % of the global total in 2019P; (4) in 2019P, China had the largest CEF globally, reaching 239,525.07 km2. The fastest growing CEF was India, contributing 16.36 % of the global CEF growth. The CEF of United States experienced a reduction trend; (5) two constructed indicators were used in evaluating the CEF of countries worldwide, and a total of 46 countries are considered to be at the highest level of risk, mainly in Europe and Asia. Based on these conclusions, we carried out a cold/hot spot analysis to reveal the spatial heterogeneity and possible driving factors in this phenomenon, and we offer management suggestions to limit the risks to cropland in the floodplains.

BACKGROUND: Work-related low back pain (LBP) increases the workforce disability and healthcare costs. This study evaluated the LBD risk level associated with handling the ACGIH TLVs in lifting tasks corresponding to various horizontal and vertical zones.
OBJECTIVE: The aim of this study was to compare the low-risk ACGIH TLV to risk outcomes from various validated lifting assessment methods, including the OSU LBD Risk Model, NIOSH Lifting Equation, and LiFFT.
METHODS: Twenty-four subjects were recruited for this study to perform various lifting conditions. The various ergonomic assessment methods were then used to obtain the risk assessment outcomes.
RESULTS: The selected assessment methods showed that the ACGIH-defined TLVs are associated with less than high-risk for LBD for all the assessed tasks. The findings showed a moderate agreement (Kendall\'s W = 0.477) among the various assessment methods risk outcomes. The highest correlation (ρ= 0.886) was observed between the NIOSH Lifting Equation and LiFFT methods risk assessment outcomes.
CONCLUSIONS: The findings showed that ACGIH-defined TLVs possesses less than high-risk for LBD. The outcomes of the selected ergonomic assessment methods moderately agree to each other.

BACKGROUND: Despite technological advancement in the field of healthcare, the worldwide burden of illness caused by cardio-vascular diseases (CVDs) is rising, owing mostly to a sharp increase in developing nations that are undergoing fast health transitions. People have been experimenting with techniques to extend their lives since ancient times. Despite this, technology is still a long way from attaining the aim of lowering mortality rates.
METHODS: From methodological perspective, a design Science Research (DSR) approach is adopted in this research. As such, to investigate the current healthcare and interaction systems created for predicting cardiac disease for patients, we first analyzed the body of existing literature. After that, a conceptual framework of the system was designed using the gathered requirements. Based on the conceptual framework, the development of different components of the system was completed. Finally, the evaluation study procedure was developed taking into account the effectiveness, usability and efficiency of the developed system.
RESULTS: To attain the objectives, we proposed a system consisting of a wearable device and mobile application, which allows the users to know their risk levels of having CVDs in the future. The Internet of Things (IoT) and Machine Learning (ML) techniques were adopted to develop the system that can classify its users into three risk levels (high, moderate and low risk of having CVD) with an F1 score of 80.4% and two risk levels (high and low risk of having CVD) with an F1 score of 91%. The stacking classifier incorporating best-performing ML algorithms was used for predicting the risk levels of the end-users utilizing the UCI Repository dataset.
CONCLUSIONS: The resultant system allows the users to check and monitor their possibility of having CVD in near future using real-time data. Also, the system was evaluated from the Human-Computer Interaction (HCI) point of view. Thus, the created system offers a promising resolution to the current biomedical sector.
BACKGROUND: Not Applicable.

The international literature emphasizes the importance of physical activity (PA) in the first steps after cancer surgery. The regular practice of physical exercise causes positive adaptations on several functional capacities, with positive consequences on patients\' quality of life. This project aims to evaluate the effect of a post-operative training protocol, structured by taking into account both cancer-related issues and the presence of comorbidities, on functional capacities and quality of life of breast cancer survivors. Therefore, it was necessary to create a synergy between oncologists (referring physicians), sport medicine physicians (risk stratification and exercise prescription) and kinesiologists (trainers). Thirty-five post-surgery BC patients decided on a voluntary basis to attend an online Adapted PA (APA) protocol for 4 months, twice a week (APA Group) or Usual Care Group (UC Group). Functional capacity of the APA Group significantly increased, by 13.1% (p = 0.000), whereas perceived exertion decreased by 19.7% (p = 0.020). In the same group, the general health evaluated through the questionnaire EORTC-QLQ-C30 increased (p = 0.050). No differences were found in the UC Group. Operation Phalco, creating a network between oncologists, sports medicine physicians and kinesiologists, confirms the importance of structuring a post-operative path where APA should be included as early as possible in the cancer patient care.

The COVID-19 pandemic spurred some regulators in the USA to require occupational health and safety programs to prevent COVID-19 transmission in workplaces. The objective of this study was to describe such state and federal regulations enacted between January 2020 and January 2022. Regulations, including emergency temporary standards (ETS) and permanent standards, were identified through a search of Nexis Uni and Bloomberg Law and review of US OSHA websites and the Federal Register. Full texts were reviewed for regulatory scope, hazard and exposure definitions, determination of exposure or risk levels, and control strategies. Four state (California, Michigan, Virginia, and Oregon) and two federal regulations were identified. All regulations described respiratory aerosols as the primary source of SARS-CoV-2 and recognized person-to-person transmission by droplet, airborne, and contact routes. Only the US OSHA ETS for healthcare explicitly stated that inhalation of respiratory particles was the most likely method of COVID-19 transmission. The Virginia, Michigan, and Oregon regulations described different categories of risk defined by exposure frequency and duration or specific workplace activities. California described exposure as places and times when employees come into contact or congregate with other people. The US OSHA ETS for healthcare described exposure as involving close contact with suspected or confirmed COVID-19 patients. While all of the state regulations required strategies from across the hierarchy, only the Virginia regulations specifically incorporated the hierarchy of controls. Only the California and Virginia regulations explicitly linked control strategies to the transmission route, while Virginia demarcated control strategies by risk level. Oregon linked risk level to occupancy levels and physical distancing requirements and referred to the use of a layered approach for transmission control. The US OSHA ETS for healthcare defined droplet and airborne precautions but made no mention of the hierarchy of controls or risk levels. Respirators were discussed in most of the regulations. The first Michigan regulation explicitly required respirators appropriate to exposure risk. The California regulations noted that respirators protect the wearer while face coverings protect people around the wearer. These regulations offer insights for a permanent US OSHA infectious disease regulation, such as the need to consider a range of transmission modes including near- and far-range aerosol inhalation, endemic and novel pathogens, workplaces beyond healthcare settings, factors that contribute to exposure and risk, the hierarchy of controls, the role of vaccination, and the importance of written exposure assessment and infection prevention plans.