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Investment regulates finance such that its value can grow and generate future profits. In Indonesia, investment is increasing yearly. The increase is supported by millennials who have adapted to technology that makes it easier to make digital mutual investments. Although the increase in mutual investment in Indonesia is quite rapid, it does not preclude the possibility that there are still many people who have not invested. The reason people have not invested is that they are afraid to take risks, and their income is low. These reasons can be minimized with the use of technology. Innovation in investing has given rise to modern technological advances such as fintech or financial technology like Robo Advisor. The method used in this study was the Partial Least Squares Structural Equation Modelling analysis technique, which was operated using SmartPLSver. 3 software. Data were collected through questionnaires. The study used quantitative methods and a sample of 200 respondents who had or would have invested through the Bibit application with the use of the Robo Advisor feature. The results of this study found that Robo Advisor can affect millennials' investing through risk profiling, financial planning, and rebalancing. [ABSTRACT FROM AUTHOR]

The current corpus of evidence-based information for chronic disease prevention and treatment is vast and growing rapidly. Behavior change theories are increasingly more powerful but difficult to operationalize in the current healthcare system. Millions of Canadians are unable to access personalized preventive and behavior change care because our in-person model of care is running at full capacity and is not set up for mass education and behavior change programs. We propose a framework to utilize data from electronic medical records to identify patients at risk of developing chronic disease and reach out to them using digital health tools that are overseen by the primary care team. The framework leverages emerging technologies such as artificial intelligence, digital health tools, and patient-generated data to deliver evidence-based knowledge and behavior change to patients across Canada at scale. The framework is flexible to enable new technologies to be added without overwhelming providers, patients or implementers. [ABSTRACT FROM AUTHOR]

Irina-Maria Popescu,1 Madalin-Marius Margan,2 Mariana Anghel,1 Alexandra Mocanu,3 Sorina Maria Denisa Laitin,1 Roxana Margan,4 Ionut Dragos Capraru,1 Alexandra-Andreea Tene,5 Emanuela-Georgiana Gal-Nadasan,6 Daniela Cirnatu,5,7 Gratiana Nicoleta Chicin,5,8 Cristian Oancea,9 Andrei Anghel10 1Department of Infectious Diseases, Discipline of Epidemiology, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 2Department of Functional Sciences, Discipline of Public Health, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 3Department of Infectious Diseases, Discipline of Infectious Diseases, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 4Department of Functional Sciences, Discipline of Physiology, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 5Regional Center of Public Health Timisoara, Timisoara, Romania; 6Department of Balneology, Medical Rehabilitation and Rheumatology, Discipline of Medical Rehabilitation, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 7Department of Medicine, “Vasile Goldis” Western University, Faculty of Medicine, Arad, Romania; 8Department of Epidemiology, Infectious Diseases and Preventive Medicine, “Vasile Goldis” Western University, Faculty of Medicine, Arad, Romania; 9Center for Research and Innovation in Precision Medicine of Respiratory Disease, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 10Department of Biochemistry and Pharmacology, Discipline of Biochemistry, “Victor Babes” University of Medicine and Pharmacy, Timisoara, RomaniaCorrespondence: Madalin-Marius Margan, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square, No. 2, Timisoara, 300041, Romania, Tel +40 726 277 354, Email marganmm@gmail.comPurpose: Coronavirus disease is a global pandemic with millions of confirmed cases and hundreds of thousands of deaths worldwide that continues to create a significant burden on the healthcare systems. The aim of this study was to determine the patient clinical and paraclinical profiles that associate with COVID-19 unfavourable outcome and generate a prediction model that could separate between high-risk and low-risk groups.Patients and Methods: The present study is a multivariate observational retrospective study. A total of 483 patients, residents of the municipality of Timișoara, the biggest city in the Western Region of Romania, were included in the study group that was further divided into 3 sub-groups in accordance with the disease severity form.Results: Increased age (cOR=1.09, 95% CI: 1.06– 1.11, p< 0.001), cardiovascular diseases (cOR=3.37, 95% CI: 1.96– 6.08, p< 0.001), renal disease (cOR=4.26, 95% CI: 2.13– 8.52, p< 0.001), and neurological disorder (cOR=5.46, 95% CI: 2.71– 11.01, p< 0.001) were all independently significantly correlated with an unfavourable outcome in the study group. The severe form increases the risk of an unfavourable outcome 19.59 times (95% CI: 11.57– 34.10, p< 0.001), while older age remains an independent risk factor even when disease severity is included in the statistical model. An unfavourable outcome was positively associated with increased values for the following paraclinical parameters: white blood count (WBC; cOR=1.10, 95% CI: 1.05– 1.15, p< 0.001), absolute neutrophil count (ANC; cOR=1.15, 95% CI: 1.09– 1.21, p< 0.001) and C-reactive protein (CRP; cOR=1.007, 95% CI: 1.004– 1.009, p< 0.001). The best prediction model including age, ANC and CRP achieved a receiver operating characteristic (ROC) curve with the area under the curve (AUC) = 0.845 (95% CI: 0.813– 0.877, p< 0.001); cut-off value = 0.12; sensitivity = 72.3%; specificity = 83.9%.Conclusion: This model and risk profiling may contribute to a more precise allocation of limited healthcare resources in a clinical setup and can guide the development of strategies for disease management.Keywords: ANC, CRP, risk profiling, unfavourable outcome

ObjectiveThe aim of this study was to improve the performance of the Chronic Related Score (CReSc) in predicting mortality and healthcare needs in the general population.MethodsA population-based study was conducted, including all beneficiaries of the Regional Health Service of Lombardy, Italy, aged 18 years or older in January 2015. Each individual was classified as exposed or unexposed to 69 candidate predictors measured before baseline, updated to include four mental health disorders. Conditions independently associated with 5-year mortality were selected using the Cox regression model on a random sample including 5.4 million citizens. The predictive performance of the obtained CReSc-2.0 was assessed on the remaining 2.7 million citizens through discrimination and calibration.ResultsA total of 35 conditions significantly contributed to the CReSc-2.0, among which Alzheimer's and Parkinson's diseases, dementia, heart failure, active neoplasm, and kidney dialysis contributed the most to the score. Approximately 36% of citizens suffered from at least one condition. CReSc-2.0 discrimination performance was remarkable, with an area under the receiver operating characteristic curve of 0.83. Trends toward increasing short-term (1-year) and long-term (5-year) rates of mortality, hospital admission, hospital stay, and healthcare costs were observed as CReSc-2.0 increased.ConclusionCReSC-2.0 represents an improved tool for stratifying populations according to healthcare needs.

ABSTRACT Shiga toxin-producing Escherichia coli (STEC) can give rise to a range of clinical outcomes from diarrhea to the life-threatening systemic condition hemolytic-uremic syndrome (HUS). Although STEC O157:H7 is the serotype most frequently associated with HUS, a major outbreak of HUS occurred in 2011 in Germany and was caused by a rare serotype, STEC O104:H4. Prior to 2011 and since the outbreak, STEC O104:H4 strains have only rarely been associated with human infections. From 2012 to 2020, intensified STEC surveillance was performed in Germany where the subtyping of ~8,000 clinical isolates by molecular methods, including whole-genome sequencing, was carried out. A rare STEC serotype, O181:H4, associated with HUS was identified, and like the STEC O104:H4 outbreak strain, this strain belongs to sequence type 678 (ST678). Genomic and virulence comparisons revealed that the two strains are phylogenetically related and differ principally in the gene cluster encoding their respective lipopolysaccharide O-antigens but exhibit similar virulence phenotypes. In addition, five other serotypes belonging to ST678 from human clinical infection, such as OX13:H4, O127:H4, OgN-RKI9:H4, O131:H4, and O69:H4, were identified from diverse locations worldwide. IMPORTANCE Our data suggest that the high-virulence ensemble of the STEC O104:H4 outbreak strain remains a global threat because genomically similar strains cause disease worldwide but that the horizontal acquisition of O-antigen gene clusters has diversified the O-antigens of strains belonging to ST678. Thus, the identification of these highly pathogenic strains is masked by diverse and rare O-antigens, thereby confounding the interpretation of their potential risk.

Despite mechanization, improved working condition, and stringent and exhaustive safety laws, mining is still one of the most hazardous occupations on the earth and the troll of accidents in Indian mining industries is one of the highest in the world. Previous studies affirmed that an individual’s risk tolerance is one of the primary reasons for their unsafe acts at the workplace. In order to improve the safety performance of an organization, it is essential to reduce individual employees’ risk tolerance. Even under identical work conditions and environments, two different people behave differently and may have different risk tolerance. The present study focuses on identifying all the factors influencing an individual’s risk tolerance level at mine workings in the Indian mining industry. The factors have been identified comprehensively and categorized into four major categories: (1) Organizational factors, (2) Human factors, (3) Task environment and task condition factors, (4) Social factors. It is proposed in the study that the effect of each factor on an individual’s risk tolerance at the workplace may be assessed through computational intelligence techniques for developing a prediction model to predict an individual’s risk tolerance level. Based on that, effective recommendations may be made for reducing the risk tolerance of individuals to prevent accidents in the mining industry. [ABSTRACT FROM AUTHOR]

Background: A shortage of beds in ICUs and conventional wards during the COVID-19 pandemic led to a collapse of health care resources.Research Question: Can admission data and minor criteria by the Infectious Diseases Society of America (IDSA) and the American Thoracic Society (ATS) help identify patients with low-risk SARS-CoV-2 pneumonia?Study Design and Methods: This multicenter cohort study included 1,274 patients in a derivation cohort and 830 (first wave) and 754 (second wave) patients in two validation cohorts. A multinomial regression analysis was performed on the derivation cohort to compare the following patients: those admitted to the ward (assessed as low risk); those admitted to the ICU directly; those transferred to the ICU after general ward admission; and those who died. A regression analysis identified independent factors for low-risk pneumonia. The model was subsequently validated.Results: In the derivation cohort, similarities existed among those either directly admitted or transferred to the ICU and those who died. These patients could, therefore, be merged into one group. Five independently associated factors were identified as being predictors of low risk (not dying and/or requiring ICU admission) (ORs, with 95% CIs): peripheral blood oxygen saturation/Fio2 > 450 (0.233; 0.149-0.364); < 3 IDSA/ATS minor criteria (0.231; 0.146-0.365); lymphocyte count > 723 cells/mL (0.539; 0.360-0.806); urea level < 40 mg/dL (0.651; 0.426-0.996); and C-reactive protein level < 60 mg/L (0.454; 0.285-0.724). The areas under the curve were 0.802 (0.769-0.835) in the derivation cohort, and 0.779 (0.742-0.816) and 0.801 (0.757-0.845) for the validation cohorts (first and second waves, respectively).Interpretation: Initial biochemical findings and the application of < 3 IDSA/ATS minor criteria make early identification of low-risk SARS-CoV-2 pneumonia (approximately 80% of hospitalized patients) feasible. This scenario could facilitate and streamline health care resource allocation for patients with COVID-19. [ABSTRACT FROM AUTHOR]

Abstract We envisage the development of new Brain Health Services to achieve primary and secondary dementia prevention. These services will complement existing memory clinics by targeting cognitively unimpaired individuals, where the focus is on risk profiling and personalized risk reduction interventions rather than diagnosing and treating late-stage disease. In this article, we review key potentially modifiable risk factors and genetic risk factors and discuss assessment of risk factors as well as additional fluid and imaging biomarkers that may enhance risk profiling. We then outline multidomain measures and risk profiling and provide practical guidelines for Brain Health Services, with consideration of outstanding uncertainties and challenges. Users of Brain Health Services should undergo risk profiling tailored to their age, level of risk, and availability of local resources. Initial risk assessment should incorporate a multidomain risk profiling measure. For users aged 39–64, we recommend the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) Dementia Risk Score, whereas for users aged 65 and older, we recommend the Brief Dementia Screening Indicator (BDSI) and the Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI). The initial assessment should also include potentially modifiable risk factors including sociodemographic, lifestyle, and health factors. If resources allow, apolipoprotein E ɛ4 status testing and structural magnetic resonance imaging should be conducted. If this initial assessment indicates a low dementia risk, then low intensity interventions can be implemented. If the user has a high dementia risk, additional investigations should be considered if local resources allow. Common variant polygenic risk of late-onset AD can be tested in middle-aged or older adults. Rare variants should only be investigated in users with a family history of early-onset dementia in a first degree relative. Advanced imaging with 18-fluorodeoxyglucose positron emission tomography (FDG-PET) or amyloid PET may be informative in high risk users to clarify the nature and burden of their underlying pathologies. Cerebrospinal fluid biomarkers are not recommended for this setting, and blood-based biomarkers need further validation before clinical use. As new technologies become available, advances in artificial intelligence are likely to improve our ability to combine diverse data to further enhance risk profiling. Ultimately, Brain Health Services have the potential to reduce the future burden of dementia through risk profiling, risk communication, personalized risk reduction, and cognitive enhancement interventions.

The real challenge to many practitioners in the financial and investment sector is to accurately profile risk-averse investors to still be inclusive of these investors in the wealth creation process. This study aims to profile risk-averse investors through a structural equation model based on endogenous and exogenous factors. The final sample size consisted of 463 individual investors in the economic hub of South Africa, Gauteng province. These endogenous and exogenous factors may bring about increases or decreases in the risk tolerance levels of investors and accordingly, influence their decisions to initiate, amend or terminate financial behaviours. These factors significantly contributed towards explaining low-risk tolerance behaviour, which assisted with the successful development of a model to profile the risk tolerance behaviour of risk-averse investors. This risk profiling model makes a remarkable and unique contribution to the field of study and the financial industry, since it will assist financial practitioners to profile the risk tolerance behaviour of risk-averse investors more accurately, which will lead to the successful implementation of investment strategies.

Assessing the baseline knowledge status and expectations of the target population of any health promotion and secondary prevention program is essential to the success of such intervention. To obtain this information about the Hong Kong population a priori to implementing these preventive strategies for oral cancer in addition to determining the willingness of potential screening participants to take risk-profiling assessments, a cross-sectional survey was conducted between November 2019 and March 2020. A total of 964 residents between the ages 18 and 86 years were invited to participate in this study across the three geographical areas in Hong Kong. Most participants self-reported being aware of oral cancer (86.3%), although the proportion of those with substantial knowledge on salient risk factors and early identifiable signs were very low (2.9%). Age and level of education were the only demographic characteristics associated with the knowledge status. The proportion of participants willing to attend community screening and partake in risk profiling assessment was high (83.9% and 80.9% respectively). Willingness to attend community screening was directly associated with respondents' self-reported oral cancer awareness status (OR: 1.9, 95% CI: 1.22–2.96). Also, we observed that those participants who were willing to attend screening are more inclined to take risk prediction assessments that those not willing to attend. These findings have showcased the need to intensify health promotion via personal skills development to encourage early disease presentation and will assist in the planning of these programs accordingly in the Hong Kong population. [ABSTRACT FROM AUTHOR]

The COVID-19 epidemic poses a significant challenge to the operation of society and the resumption of work and production. How to quickly track the resident location and activity trajectory of the population, and identify the spread risk of the COVID-19 in geospatial space has important theoretical and practical significance for controlling the spread of the virus on a large scale. In this study, we take the geographical community as the research object, and use the mobile phone trajectory data to construct the spatiotemporal profile of the potential high-risk population. First, by using the spatiotemporal data collision method, identify, and recover the trajectories of the people who were in the same area with the confirmed patients during the same time. Then, based on the range of activities of both cohorts (the confirmed cases and the potentially infected groups), we analyze the risk level of the relevant places and evaluate the scale of potential spread. Finally, we calculate the probability of infection for different communities and construct the spatiotemporal profile for the transmission to help guide the distribution of preventive materials and human resources. The proposed method is verified using survey data of 10 confirmed cases and statistical data of 96 high-risk neighborhoods in Chengdu, China, between 15 January 2020 and 15 February 2020. The analysis finds that the method accurately simulates the spatiotemporal spread of the epidemic in Chengdu and measures the risk level in specific areas, which provides an objective basis for the government and relevant parties to plan and manage the prevention and control of the epidemic.

Breast cancer-related lymphedema (BCRL) is chronic condition that occurs in 5% to 75% of women following treatment for breast cancer. However, little is known about the risk factors and mechanisms associated with a worse BCRL profile. Identify distinct BCRL profiles in women with the condition (i.e., lower vs. higher risk phenotype) and evaluate for associations with pro- and anti-inflammatory genes. Latent class profile analysis (LCPA) was used to identify the BCRL profiles using phenotypic characteristics evaluated prior to surgery. Candidate gene analyses were done to identify cytokine genes associated with the two BCRL profiles. Of the 155 patients evaluated, 35.5% (n = 55) were in the Lower and 64.5% (n = 100) were in the Higher Risk classes. Risk factors for membership in the Higher class included: lower functional status, having sentinel lymph node biopsy, axillary lymph node dissection, mastectomy, higher number of positive lymph nodes, and receipt of chemotherapy. Polymorphisms for interleukin (IL)1-beta and IL6 were associated with membership in the Higher Risk class. The readily available and clinically relevant phenotypic characteristics associated with a worse BCRL profile can be used by clinicians to identify higher risk patients. If confirmed, these characteristics can be tested in predictive risk models. In addition, the candidate gene findings may guide the development of mechanistically-based interventions to decrease the risk of BCRL. [ABSTRACT FROM AUTHOR]

The real challenge to many practitioners in the financial and investment sector is to accurately profile risk-averse investors to still be inclusive of these investors in the wealth creation process. This study aims to profile risk-averse investors through a structural equation model based on endogenous and exogenous factors. The final sample size consisted of 463 individual investors in the economic hub of South Africa, Gauteng province. These endogenous and exogenous factors may bring about increases or decreases in the risk tolerance levels of investors and accordingly, influence their decisions to initiate, amend or terminate financial behaviours. These factors significantly contributed towards explaining low-risk tolerance behaviour, which assisted with the successful development of a model to profile the risk tolerance behaviour of risk-averse investors. This risk profiling model makes a remarkable and unique contribution to the field of study and the financial industry, since it will assist financial practitioners to profile the risk tolerance behaviour of risk-averse investors more accurately, which will lead to the successful implementation of investment strategies. [ABSTRACT FROM AUTHOR]

The risk taken by the investor depends on several independent variables like: personality, biological age, investment experience and income. The main aim of this article is to combine all these variables in order to build an exhaustive risk profile on the basis of the Big Five Personality dimensions. The research method applied is exploratory in nature and questionnaire survey method was employed to gather data from 436 secondary equity market investors residing in the Chennai city of India. ANOVA was employed to develop the risk profile. The outcome of the research was an exhaustive risk profile combining all the related variables and a regression model predicting the equity returns. The main conclusions of the study are that the investors with the more of the conscientiousness personality tend to take less risk. This finding was also consistent among the senior investors, high income investors and those with mediocre/ high investment experience. The study also concluded that the agreeable investors with high income/high investment experience, tend to take less risk. Only the young investors with more of the conscientiousness personality tend to take more risk and with more of the extraversion personality tend to take less risk. This study serves as a guidance for advisors to provide appropriate recommendations on the basis of the risk appetite and personality of the investors.

We envisage the development of new Brain Health Services to achieve primary and secondary dementia prevention. These services will complement existing memory clinics by targeting cognitively unimpaired individuals, where the focus is on risk profiling and personalized risk reduction interventions rather than diagnosing and treating late-stage disease. In this article, we review key potentially modifiable risk factors and genetic risk factors and discuss assessment of risk factors as well as additional fluid and imaging biomarkers that may enhance risk profiling. We then outline multidomain measures and risk profiling and provide practical guidelines for Brain Health Services, with consideration of outstanding uncertainties and challenges. Users of Brain Health Services should undergo risk profiling tailored to their age, level of risk, and availability of local resources. Initial risk assessment should incorporate a multidomain risk profiling measure. For users aged 39–64, we recommend the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) Dementia Risk Score, whereas for users aged 65 and older, we recommend the Brief Dementia Screening Indicator (BDSI) and the Australian National University Alzheimer's Disease Risk Index (ANU-ADRI). The initial assessment should also include potentially modifiable risk factors including sociodemographic, lifestyle, and health factors. If resources allow, apolipoprotein E ɛ4 status testing and structural magnetic resonance imaging should be conducted. If this initial assessment indicates a low dementia risk, then low intensity interventions can be implemented. If the user has a high dementia risk, additional investigations should be considered if local resources allow. Common variant polygenic risk of late-onset AD can be tested in middle-aged or older adults. Rare variants should only be investigated in users with a family history of early-onset dementia in a first degree relative. Advanced imaging with 18-fluorodeoxyglucose positron emission tomography (FDG-PET) or amyloid PET may be informative in high risk users to clarify the nature and burden of their underlying pathologies. Cerebrospinal fluid biomarkers are not recommended for this setting, and blood-based biomarkers need further validation before clinical use. As new technologies become available, advances in artificial intelligence are likely to improve our ability to combine diverse data to further enhance risk profiling. Ultimately, Brain Health Services have the potential to reduce the future burden of dementia through risk profiling, risk communication, personalized risk reduction, and cognitive enhancement interventions. [ABSTRACT FROM AUTHOR]

The risk taken by the investor depends on several independent variables like: personality, biological age, investment experience and income. The main aim of this article is to combine all these variables in order to build an exhaustive risk profile on the basis of the Big Five Personality dimensions. The research method applied is exploratory in nature and questionnaire survey method was employed to gather data from 436 secondary equity market investors residing in the Chennai city of India. ANOVA was employed to develop the risk profile. The outcome of the research was an exhaustive risk profile combining all the related variables and a regression model predicting the equity returns. The main conclusions of the study are that the investors with the more of the conscientiousness personality tend to take less risk. This finding was also consistent among the senior investors, high income investors and those with mediocre/high investment experience. The study also concluded that the agreeable investors with high income/high investment experience, tend to take less risk. Only the young investors with more of the conscientiousness personality tend to take more risk and with more of the extraversion personality tend to take less risk. This study serves as a guidance for advisors to provide appropriate recommendations on the basis of the risk appetite and personality of the investors. [ABSTRACT FROM AUTHOR]

Background: Due to their accessibility and anonymity, web-based counseling services are expanding at an unprecedented rate. One of the most prominent challenges such services face is repeated users, who represent a small fraction of total users but consume significant resources by continually returning to the system and reiterating the same narrative and issues. A deeper understanding of repeated users and tailoring interventions may help improve service efficiency and effectiveness. Previous studies on repeated users were mainly on telephone counseling, and the classification of repeated users tended to be arbitrary and failed to capture the heterogeneity in this group of users., Objective: In this study, we aimed to develop a systematic method to profile repeated users and to understand what drives their use of the service. By doing so, we aimed to provide insight and practical implications that can inform the provision of service catering to different types of users and improve service effectiveness., Methods: We extracted session data from 29,400 users from a free 24/7 web-based counseling service from 2018 to 2021. To systematically investigate the heterogeneity of repeated users, hierarchical clustering was used to classify the users based on 3 indicators of service use behaviors, including the duration of their user journey, use frequency, and intensity. We then compared the psychological profile of the identified subgroups including their suicide risks and primary concerns to gain insights into the factors driving their patterns of service use., Results: Three clusters of repeated users with clear psychological profiles were detected: episodic, intermittent, and persistent-intensive users. Generally, compared with one-time users, repeated users showed higher suicide risks and more complicated backgrounds, including more severe presenting issues such as suicide or self-harm, bullying, and addictive behaviors. Higher frequency and intensity of service use were also associated with elevated suicide risk levels and a higher proportion of users citing mental disorders as their primary concerns., Conclusions: This study presents a systematic method of identifying and classifying repeated users in web-based counseling services. The proposed bottom-up clustering method identified 3 subgroups of repeated users with distinct service behaviors and psychological profiles. The findings can facilitate frontline personnel in delivering more efficient interventions and the proposed method can also be meaningful to a wider range of services in improving service provision, resource allocation, and service effectiveness., (©Yucan Xu, Christian Shaunlyn Chan, Evangeline Chan, Junyou Chen, Florence Cheung, Zhongzhi Xu, Joyce Liu, Paul Siu Fai Yip. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 30.05.2024.)

Firefighters encounter numerous complex and ever-changing hazards when carrying out emergency response activities, necessitating the development of effective risk profiling methods to enhance both their safety and operational efficiency. This study outlines a comprehensive approach to constructing risk profiles tailored specifically for firefighters, integrating various methodologies to create a robust and adaptable framework. The methods used incorporating historical incident data, environmental variables, and individual firefighter characteristics to identify and assess potential risks. Additionally, the risk profiling framework include Psychosocial risk factors are also considered, allowing for a holistic understanding of the human element in firefighting risk assessment. By developing risk profiles to the specific needs and characteristics of firefighters, this method aims to significantly improve their safety, ability to make decisions, and overall operational efficiency in the demanding and ever-changing setting of emergency response situations. This article discussed methods•To identify safety cultures using questionnaires•To analyse risk from incident reports using content analysis•To verify and validate risk using thematic analysis from Focus Group Discussion., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

In this study, we describe the relative contributions of and interactions between individual risk factors associated with ineffective pregnancy prevention among female adolescents in Portugal. Our sample consisted of 856 sexually experienced female adolescents (10-19 years) who did not intend to become pregnant. Of these, 379 were pregnant, and the residual (477) had never been pregnant. We used classification tree analysis to describe the interplay among a set of established sociodemographic, familial, reproductive, and relationship factors as predictors of ineffective pregnancy prevention. The tree model showed good predictive properties. Seven profiles predicted one-half to all the cases of ineffective pregnancy prevention. Ineffective pregnancy prevention was predicted by adolescents' grade level and different combinations of variables, specifically female age, age at the time of first sexual intercourse, religious beliefs, place of residence, maternal pregnancy before age 20, household structure in childhood, and partner's age difference. According to our findings, limiting assessments to the cumulative presence of risk factors may be insufficient to accurately identify adolescents at elevated risk of unwanted pregnancy, as the impact of any given risk factor may vary according to other factors. Our findings may contribute to the development of a risk assessment tool that may support healthcare providers' efforts to provide individualized risk assessment for adolescent patients and, thus, to better support pregnancy prevention. [ABSTRACT FROM AUTHOR]

Abstract This report assesses peer‐reviewed and grey literature on risk communication concepts and practices, as requested by the European Commission to support the implementation of a ‘General Plan for Risk Communication’, i.e. an integrated framework for EU food safety risk assessors and risk managers at Union and national level, as required by the revised EU General Food Law Regulation. We conducted a scoping review of social research studies and official reports in relation to risk communication in the following areas: understanding and awareness of risk analysis roles and tasks, reducing misunderstanding of the different meaning of the terms ‘hazard’ and ‘risk’, tackling misinformation and disinformation, enhancing confidence in EU food safety, taking account of risk perceptions, key factors in trade‐offs about risks, audience segmentation and tools, channels and mechanisms for coordinated risk communications. We structured our findings as follows: i) definitions of key concepts, ii) audience analysis and information requirements, iii) risk profiling, models and mechanisms, iv) contributions to communication strategies. We make several recommendations for consideration by the Commission, both in terms of actions to support the design and implementation of the general plan, and research needs that we consider crucial to further inform appropriate risk communication in the EU. EFSA carried out a targeted consultation of experts and a public consultation open to all interested parties including the general public, in preparing and finalising this report.

This report assesses peer‐reviewed and grey literature on risk communication concepts and practices, as requested by the European Commission to support the implementation of a ‘General Plan for Risk Communication’, i.e. an integrated framework for EU food safety risk assessors and risk managers at Union and national level, as required by the revised EU General Food Law Regulation. We conducted a scoping review of social research studies and official reports in relation to risk communication in the following areas: understanding and awareness of risk analysis roles and tasks, reducing misunderstanding of the different meaning of the terms ‘hazard’ and ‘risk’, tackling misinformation and disinformation, enhancing confidence in EU food safety, taking account of risk perceptions, key factors in trade‐offs about risks, audience segmentation and tools, channels and mechanisms for coordinated risk communications. We structured our findings as follows: i) definitions of key concepts, ii) audience analysis and information requirements, iii) risk profiling, models and mechanisms, iv) contributions to communication strategies. We make several recommendations for consideration by the Commission, both in terms of actions to support the design and implementation of the general plan, and research needs that we consider crucial to further inform appropriate risk communication in the EU. EFSA carried out a targeted consultation of experts and a public consultation open to all interested parties including the general public, in preparing and finalising this report.This publication is linked to the following EFSA Journal articles: http://onlinelibrary.wiley.com/doi/10.2903/j.efsa.2021.e190401/full and http://onlinelibrary.wiley.com/doi/10.2903/j.efsa.2021.e190402/full [ABSTRACT FROM AUTHOR]

Stratifying residents at increased risk for fractures in long-term care facilities (LTCFs) can potentially improve awareness and facilitate the delivery of targeted interventions to reduce risk. Although several fracture risk assessment tools exist, most are not suitable for individuals entering LTCF. Moreover, existing tools do not examine risk profiles of individuals at key periods in their aged care journey, specifically at entry into LTCFs. Our objectives were to identify fracture predictors, develop a fracture risk prognostic model for new LTCF residents and compare its performance to the Fracture Risk Assessment in Long term care (FRAiL) model using the Registry of Senior Australians (ROSA) Historical National Cohort, which contains integrated health and aged care information for individuals receiving long term care services. Individuals aged ≥65 years old who entered 2079 facilities in three Australian states between 01/01/2009 and 31/12/2016 were examined. Fractures (any) within 365 days of LTCF entry were the outcome of interest. Individual, medication, health care, facility and system-related factors were examined as predictors. A fracture prognostic model was developed using elastic nets penalised regression and Fine-Gray models. Model discrimination was examined using area under the receiver operating characteristics curve (AUC) from the 20 % testing dataset. Model performance was compared to an existing risk model (i.e., FRAiL model). Of the 238,782 individuals studied, 62.3 % (N = 148,838) were women, 49.7 % (N = 118,598) had dementia and the median age was 84 (interquartile range 79–89). Within 365 days of LTCF entry, 7.2 % (N = 17,110) of individuals experienced a fracture. The strongest fracture predictors included: complex health care rating (no vs high care needs, sub-distribution hazard ratio (sHR) = 1.52, 95 % confidence interval (CI) 1.39–1.67), nutrition rating (moderate vs worst, sHR = 1.48, 95%CI 1.38–1.59), prior fractures (sHR ranging from 1.24 to 1.41 depending on fracture site/type), one year history of general practitioner attendances (≥16 attendances vs none, sHR = 1.35, 95%CI 1.18–1.54), use of dopa and dopa derivative antiparkinsonian medications (sHR = 1.28, 95%CI 1.19–1.38), history of osteoporosis (sHR = 1.22, 95%CI 1.16–1.27), dementia (sHR = 1.22, 95%CI 1.17–1.28) and falls (sHR = 1.21, 95%CI 1.17–1.25). The model AUC in the testing cohort was 0.62 (95%CI 0.61–0.63) and performed similar to the FRAiL model (AUC = 0.61, 95%CI 0.60–0.62). Critical information captured during transition into LTCF can be effectively leveraged to inform fracture risk profiling. New fracture predictors including complex health care needs, recent emergency department encounters, general practitioner and consultant physician attendances, were identified. • At least 7.2% of older Australians had a fracture within a year after entry into long-term care facilities (LTCFs). • We developed a tailored and moderately well performing prognostic model to identify new LTCF residents most at risk for fractures using routinely collected data and identified 31 predictors of fracture risk upon entry. • The discriminative power of our prognostic model in the testing cohort was AUC=0.62 (95% confidence interval (CI) 0.61-0.63). • Our model's performance was similar to the recreated Fracture Risk Assessment in Long term care (FRAiL) model using our datasets (AUC=0.61, 95%CI 0.60-0.62). • Critical information captured during transition into LTCF can be effectively leveraged to inform fracture risk profiling. • These tools can assist health and aged care providers to identify those at greatest risk and inform risk-based prevention strategies for fracture at entry into LTCFs. [ABSTRACT FROM AUTHOR]

Failure to rescue (FTR), mortality after a major postoperative complication, is a superior surgical quality metric compared to surgical mortality or complications rates alone. Our objective was to develop and validate a novel pediatric profiling to identify high-risk subjects among the subset of children who develop serious post-operative complications. We performed a retrospective study of children who developed one or more serious postoperative complications following inpatient surgery across NSQIP-Pediatric hospitals (2012–2017). We evaluated the rate of FTR according to pre-operative comorbidity burden. We identified 45,504 surgical cases with major post-operative complications (FTR rates: 2.4%). Surgical cases with greater than six pre-operative comorbidities (n = 12,148;28%) accounted for 80% of FTR events. The expected probability of FTR was 0.1%(95%CI:0.1%–0.2%) among low-risk cases, 3.3%(95%CI:3.0%–3.5%) among intermediate-risk cases, and 22.6%(95%CI:20.9%–24.3%) among high-risk cases. About half of surgical cases in the high-risk profile group died within 48 h of surgery. Comparatively, cases in the intermediate-risk group had a much longer time to mortality (10 days). We propose a prognostic index to accurately identify children at risk for FTR. The use of such an index may provide surgeons with a window of opportunity to implement aggressive monitoring and therapeutic strategies to reduce mortality. IV [ABSTRACT FROM AUTHOR]

In this paper we examine the complex and changing configurations of social media risks in organizations. To gain a deeper understanding of the nature, structure and interrelatedness of social media risks we develop a framework for risk analysis that provides multifaceted profiles of risk types and risk incidents. Through the process of developing the risk analysis framework key insights into social media risks in organizations were made visible. Social media risks were found to be: i) evolving, overlapping and highly interrelated leading to derivative risks and risk chains; ii) spatiotemporal in nature, having broad spatial reach, both geographical and relationally and long temporal frames that link current risks to future consequences, emphasizing the need for a longitudinal view iii) representing multiple stakeholder interests and risk appetites, and iv) blurring the boundaries between business, professional and individual risks and perceptions of risk. These insights open up imperatives for further research and invite the potential for alternative theoretical lenses to examine these variations in perceptions and spatiotemporal perspectives on social media risk. [ABSTRACT FROM AUTHOR]

Background: Decision for the best optimal treatment for the elderly is always a challenge, in particular when deciding for surgery. Studies have showed for frail elderly with limited life expectancy, primary endocrine therapy alone may be appropriate with equivalent survival. Those patients with longer life expectancy could have survival gain from surgery. A comprehensive geriatric assessment (CGA) would be useful to predict the survival probability and guide the optimal treatment. Methods: Consecutive new patients aged 70 or above with a diagnosis of stage I to III breast cancer, were recruited from July to December 2017. The decision of treatment was independently made regardless of the study assessment. A prospective cross-sectional study using CGA was conducted. Scoring for each component of CGA was measured and the correlation with the treatment was analysed. Results: Twenty-four patients were recruited during the study period. Nineteen of them received surgical treatment whereas five received non-surgical treatment. Older age (p = 0.010), higher Eastern Cooperative Oncology Group (ECOG) score (p = 0.028), higher degree of dependence by the instrumental activities of daily living (p = 0.018), cognitive impairment by the Hong Kong version of montreal cognitive assessment (HK-MoCA) (p = 0.006), and very high Charlson comorbidity index (> 5) (p = 0.047) were significantly related to non-surgical treatment. Conclusion: This pilot study confirmed the feasibility in conducting CGA to personalize treatment options for older breast cancer patients. A larger prospective trial is ongoing to validate the impact of each CGA domain in relation to the treatment outcome. [ABSTRACT FROM AUTHOR]

Diarrhoeal diseases remain a major public health problem, causing more than half a million child deaths every year, particularly in low- and middle-income countries (LMICs). Despite existing knowledge on the aetiologies and causes of diarrhoeal diseases, relatively little is known about its spatial patterns in LMICs, including Senegal. In the present study, data from a cross-sectional survey carried out in 2016 were analysed to describe the spatial pattern of diarrhoeal prevalence in children under the age of 5 years in the secondary city of Mbour in the south-western part of Senegal. Bayesian conditional autoregressive (CAR) models with spatially varying coefficients were employed to determine the effect of sociodemographic, economic and climate parameters on diarrhoeal prevalence. We observed substantial spatial heterogeneities in diarrhoea prevalence. Risk maps, stratified by age group, showed that diarrhoeal prevalence was higher in children aged 25-59 months compared to their younger counterparts with the highest risk observed in the north and south peripheral neighbourhoods, especially in Grand Mbour, Médine, Liberté and Zone Sonatel. The posterior relative risk estimate obtained from the Bayesian CAR model indicated that a unit increase in the proportion of people with untreated stored drinking water was associated with a 29% higher risk of diarrhoea. A unit increase in rainfall was also associated with an increase in diarrhoea risk. Our findings suggest that public health officials should integrate disease mapping and cluster analyses and consider the varying effects of sociodemographic factors in developing and implementing areaspecific interventions for reducing diarrhoea.

Elemental metals are critical raw material attributes which can impact cell culture performance and associated therapeutic protein product quality profiles. Metals such as copper and manganese act as cofactors and reagents for numerous metabolic pathways which govern cell growth, protein expression, and glycosylation, thus mandating elemental monitoring. The growing complexity of modern cell culture media formulations adds additional opportunities for elemental variance and its associated impact risks. This article describes an analytical technique applying inductively coupled plasma mass spectrometry to characterize a list of common raw materials and media powders used in mammalian cell culture and therapeutic protein production. We aim to describe a method qualification approach suitable for biopharmaceutical raw materials. Furthermore, we present detailed profiles of many common raw materials and discuss trends in raw material subtypes. Finally, a case study demonstrating the impact of an unexpected source of raw material variation is presented along with recommendations for raw material elemental risk profiling and control. [ABSTRACT FROM AUTHOR]

Zika virus is transitioning to become a long-term public health challenge, and countries should remain informed of the risk for emergence. We developed a stochastic epidemiologic model to profile risk for Zika virus emergence, including trimester-specific fetal risk across time, in all 3,208 counties in the United States, including Puerto Rico. Validation against known transmission in North America demonstrated accuracy to predict epidemic dynamics and absolute case counts across scales (R2 = 0.98). We found that, although sporadic single transmission events could occur in most US counties, outbreaks will likely be restricted to the Gulf Coast region and to late spring through autumn. Seasonal fluctuations in birth rates will confer natural population-level protection against early-trimester infections. Overall, outbreak control will be more effective and efficient than prevention, and vaccination will be most effective at >70% coverage. Our county-level risk profiles should serve as a critical resource for resource allocation. [ABSTRACT FROM AUTHOR]

Risk maps facilitate discussion among different stakeholders and provide a tool for spatial targeting of health interventions. We present maps documenting shrinking risk profiles after deworming with respect to soil-transmitted helminthiasis among schoolchildren from disadvantaged neighbourhoods in Port Elizabeth, South Africa. Children were examined for soil-transmitted helminth infections using duplicate Kato-Katz thick smears in March 2015, October 2015 and May 2016, and subsequently treated with albendazole after each survey. The mean infection intensities for Ascaris lumbricoides were 9,554 eggs per gram of stool (EPG) in March 2015, 4,317 EPG in October 2015 and 1,684 EPG in March 2016. The corresponding figures for Trichuris trichiura were 664 EPG, 331 EPG and 87 EPG. Repeated deworming shrank the risk of soil-transmitted helminthiasis, but should be complemented by other public health measures.

Abstract Background Schistosomiasis is a water-based disease that affects an estimated 250 million people, mainly in sub-Saharan Africa. The transmission of schistosomiasis is spatially and temporally restricted to freshwater bodies that contain schistosome cercariae released from specific snails that act as intermediate hosts. Our objective was to assess the contribution of remote sensing applications and to identify remaining challenges in its optimal application for schistosomiasis risk profiling in order to support public health authorities to better target control interventions. Methods We reviewed the literature (i) to deepen our understanding of the ecology and the epidemiology of schistosomiasis, placing particular emphasis on remote sensing; and (ii) to fill an identified gap, namely interdisciplinary research that bridges different strands of scientific inquiry to enhance spatially explicit risk profiling. As a first step, we reviewed key factors that govern schistosomiasis risk. Secondly, we examined remote sensing data and variables that have been used for risk profiling of schistosomiasis. Thirdly, the linkage between the ecological consequence of environmental conditions and the respective measure of remote sensing data were synthesised. Results We found that the potential of remote sensing data for spatial risk profiling of schistosomiasis is – in principle – far greater than explored thus far. Importantly though, the application of remote sensing data requires a tailored approach that must be optimised by selecting specific remote sensing variables, considering the appropriate scale of observation and modelling within ecozones. Interestingly, prior studies that linked prevalence of Schistosoma infection to remotely sensed data did not reflect that there is a spatial gap between the parasite and intermediate host snail habitats where disease transmission occurs, and the location (community or school) where prevalence measures are usually derived from. Conclusions Our findings imply that the potential of remote sensing data for risk profiling of schistosomiasis and other neglected tropical diseases has yet to be fully exploited.

Objective: The aim of this study was to improve the performance of the Chronic Related Score (CReSc) in predicting mortality and healthcare needs in the general population., Methods: A population-based study was conducted, including all beneficiaries of the Regional Health Service of Lombardy, Italy, aged 18 years or older in January 2015. Each individual was classified as exposed or unexposed to 69 candidate predictors measured before baseline, updated to include four mental health disorders. Conditions independently associated with 5-year mortality were selected using the Cox regression model on a random sample including 5.4 million citizens. The predictive performance of the obtained CReSc-2.0 was assessed on the remaining 2.7 million citizens through discrimination and calibration., Results: A total of 35 conditions significantly contributed to the CReSc-2.0, among which Alzheimer's and Parkinson's diseases, dementia, heart failure, active neoplasm, and kidney dialysis contributed the most to the score. Approximately 36% of citizens suffered from at least one condition. CReSc-2.0 discrimination performance was remarkable, with an area under the receiver operating characteristic curve of 0.83. Trends toward increasing short-term (1-year) and long-term (5-year) rates of mortality, hospital admission, hospital stay, and healthcare costs were observed as CReSc-2.0 increased., Conclusion: CReSC-2.0 represents an improved tool for stratifying populations according to healthcare needs., Competing Interests: GC received research support from the European Community (EC), the Italian Agency of Drugs (AIFA), and the Italian Ministry for University and Research (MIUR). He took part in a variety of projects that were funded by pharmaceutical companies (i.e., Novartis, GSK, Roche, AMGEN, and BMS). He also received honoraria as a member of the advisory board to Roche. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Corrao, Bonaugurio, Chen, Franchi, Lora, Leoni, Pavesi and Bertolaso.)

While tendering for jobs, a contractor is expected to analyse the various risks in each prospective project and price them appropriately. Contingencies are included in the tender price to cater for the various risks based on their impacts on the project targets and profit margin. Currently in New Zealand (NZ), there is little or no information on the various contractual risks and their mitigation measures. This has led to contractors over compensating or under compensating for risks with costly consequences. This study aimed to establish priority contractual risks in the NZ construction industry, and their mitigation measures. The research was based on a questionnaire survey of consultants and contractors. Descriptive statistics and multi-attribute techniques were used in the data analysis. Results showed 21 risk factors which were segregated into 6 broad categories in diminishing levels of significance as follows: Site conditions, main contractor, pricing, subcontractor, external and client- related risks. Putting tags and conditions to risky price items in the tender bids, and transferring the risks onto other parties were analysed as the 2 most effective out of the 5 key risk mitigation measures identified. Being cautious of the priority risks and application of the identified effective risk mitigation measures could guide contractors and the project team to more appropriately budget for and respond to risks, thereby ensuring more satisfactory project outcomes.

International mail articles present an important potential vector for biosecurity and other regulatory risk. Border intervention is a key element in Australia's biosecurity strategy. Arriving international mail articles are inspected and those that are intercepted with biosecurity risk material are documented, including the address to which the article was to be delivered. Knowledge about patterns in the intended destinations of mail article permits more detailed biosecurity intervention. We used geo-location software to identify the delivery address of mail articles intercepted with biosecurity risk material from 2008-2011. We matched these addresses with demographic data that were recorded at a regional level from the Australian Bureau of Statistics 2011 Census and used random forest statistical analyses to correlate various demographic fields at the regional level with the counts of seized mail articles. The analysis of the seizure counts against demographic characteristics suggests a high correlation between having higher numbers of university students that speak a particular language in a region and higher quantities of intercepted mail articles destined for that region. We also explore metropolitan and regional patterns in the destinations of seized materials. These results can be used to provide information on policy and operational actions to try to reduce the rate at which mail articles that contain biosecurity risk material are sent to Australia. [ABSTRACT FROM AUTHOR]

The European legal framework requires that financial consultants assess their clients’ risk tolerance before advising them on investments. The study aims at further testing an alternative measure to quantify the risk attitudes of investors: The Implicit Association Test (IAT). This study examines differences in implicit, unconscious, and explicit cognitive attitudes of men and women. The results of the IAT are compared with their answers from a risk tolerance questionnaire used by practitioners and self-selected asset allocation (portfolio). The data show that implicit attitude, and, thus, unconscious and uncontrolled thinking, can differ from conscious processes. Furthermore, in this study, there is no gender gap in risk attitude and risk tolerance. The findings suggest that experience and financial knowledge are likely the most important determinants of risk attitudes with no significant difference between men and women. [ABSTRACT FROM AUTHOR]

Background: Strongyloides stercoralis and hookworm are two soil-transmitted helminths (STH) that are highly prevalent in Cambodia. Strongyloides stercoralis causes long-lasting infections and significant morbidity but is largely neglected, while hookworm causes the highest public health burden among STH. The two parasites have the same infection route, i.e. skin penetration. The extent of co-distribution, which could result in potential high co-morbidities, is unknown in highly endemic settings like Cambodia. The aim of this study was to predict the spatial distribution of S. stercoralis-hookworm co-infection risk and to investigate determinants of co-infection in Preah Vihear Province, North Cambodia. Methods: A cross-sectional survey was conducted in 2010 in 60 villages of Preah Vihear Province. Diagnosis was performed on two stool samples, using combined Baermann technique and Koga agar culture plate for S. stercoralis and Kato-Katz technique for hookworm. Bayesian multinomial geostatistical models were used to assess demographic, socioeconomic, and behavioural determinants of S. stercoralis-hookworm co-infection and to predict co-infection risk at non-surveyed locations. Results: Of the 2576 participants included in the study, 48.6% and 49.0% were infected with S. stercoralis and hookworm, respectively; 43.8% of the cases were co-infections. Females, preschool aged children, adults aged 19-49 years, and participants who reported regularly defecating in toilets, systematically boiling drinking water and having been treated with anthelmintic drugs had lower odds of co-infection. While S. stercoralis infection risk did not appear to be spatially structured, hookworm mono-infection and co-infection exhibited spatial correlation at about 20 km. Co-infection risk was positively associated with longer walking distances to a health centre and exhibited a small clustering tendency. The association was only partly explained by climatic variables, suggesting a role for underlying factors, such as living conditions and remoteness. Conclusions: Both parasites were ubiquitous in the province, with co-infections accounting for almost half of all cases. The high prevalence of S. stercoralis calls for control measures. Despite several years of school-based de-worming programmes, hookworm infection levels remain high. Mebendazole efficacy, as well as coverage of and compliance to STH control programmes should be investigated. [ABSTRACT FROM AUTHOR]

In this paper, the risk profile of two pastoral production systems in New Zealand are examined. All farmers must manage and mitigate a multitude of risks. Traditionally, a farm budget is solely undertaken to satisfy a lending institution. Limited variance analysis takes place, usually for output prices and inputs such as: interest rates, energy costs, and fertiliser. The authors of this paper use "@Risk", a risk profiling plug-in tool for Microsoft Excel to demonstrate how farm budgets can be more relevant to farmers. Many risk factors that affect farm financial performance, such as climate and commodity prices, are not controlled by the farmer. Wet summers help hill country sheep and beef pastoral farmers, as more grass growth occurs, which thereby reduces the cost of production and increases revenue, as more stock is finished. Whereas in drought years income falls as stock must be sold prior to finishing, in severe droughts capital stock may also be sold. Input costs also rise as pasture weed invasion occurs; health issues such as rye grass staggers may also add cost. Monte Carlo simulations on model farm budgets for a North Island sheep and beef property and a Canterbury dairy farm help demonstrate the risk profile of each farm type. [ABSTRACT FROM AUTHOR]