[Cross-sectional study on the use of masks among occupational groups with high-risk positions for overseas import and pollution transmission].

Objective: To investigate the wearing of masks and the knowledge of masks among high-risk positions for overseas import and pollution transmission. Methods: From May 14 to 17, 2022, a convenient sampling method was used to conduct an online survey among 963 workers in high-risk positions for overseas import and pollution transmission in Beijing. The behaviors of individual use and wearing masks, the distribution and supervision of the unit, the knowledge of personal mask protection and the subjective feelings of wearing masks were analyzed. The χ(2) test and logistic regression model were used to analyze the influencing factors of the correct selection of masks. Results: The majority of the workers in high-risk positions for overseas import and pollution transmission were male (86.0%, 828/963), age concentration in 18-44 years old (68.2%, 657/963), and the majority of them had college or bachelor degrees (49.4%, 476/963). 79.4%(765/963) of the workers chose the right type of masks, female, 45-59 years old and high school education or above were the risk factors for correct selection of masks (P <0.05). Workers had good behaviors such as wearing/removing masks, but only 10.5% (101/963) could correctly rank the protective effect of different masks. 98.4% (948/963) of the workers believed that their work units had provided masks to their employees, and 99.1% (954/963) and 98.2%(946/963) of them had organized training and supervision on the use of masks, respectively. 47.4%(456/963) of the workers were uncomfortable while wearing masks. Conclusion: The overall selection and use of masks among occupational groups in high-risk positions for overseas import and pollution transmission in China need to be further standardized. It is necessary to strengthen supervision and inspection on the use of masks among occupational groups, and take improvement measures to improve the comfort of wearing masks.

Following Guidelines During a Crisis

The guidance states, "These preventative measures can include steps to prepare personnel such as: * "Educating employees on topics such as, in the case of a pandemic, personal hygiene (hand washing and coughing and sneezing etiquette), social distancing, and appropriate use of sick leave * "Encouraging employees to get immunized as appropriate by providing information on local vaccination services or by offering on-site vaccination services, if reasonable * "Providing information for and encouraging employees to develop family emergency preparedness plans * "Reviewing CGMP [current good manufacturing practice] regulations regarding appropriate sanitation practices and restriction of ill or sick employees from production areas (see 21 CFR [Code of Federal Regulations] 211.28)" (2). Examples include: * "Production equipment routine maintenance * "Utility system performance checks and maintenance (e.g., air temperature, lighting, compressed air) * "Environmental monitoring of facilities such as cell culture, harvesting, and purification rooms during production * "Stability testing for certain drug products and components * "Periodic examinations of data and of reserve samples" (2). EMA, Guidance on the Format of the Risk Management Plan (RMP) in the EU-in Integrated Format, EMA/164014/2018 Rev.2.0.1 accompanying GVP Module V Rev.2 Human Medicines Evaluation (EMA, 31 October 2018).

COVID-19: District level vulnerability assessment in India.

OBJECTIVES: COVID-19 Pandemic has brought a threatening challenge to the world and as well as for Indian society and economy. In India, it has become a public health disaster and its' intensity increasing continuously. For the disaster risk reduction, and capacity building against the COVID-19 pandemic understanding of the relationship between socio-environmental conditions with the pandemic is very necessary. The objective of the present work is to construct a socio-environmental vulnerability index of the potential risk of community spread of COVID-19 using socio-economic and environmental variables. METHODOLOGY: In this, cross-sectional study principal component analyses have been used to drive SoEVI. 4 uncorrelated sub-index has been extracted from 16 sub-indicators which reflects 59% of the variance. Aggregation of 4 Sub-Index has been done to obtain the final vulnerability Index. RESULTS: Results show that there is spatial variability in vulnerability based on environmental and socio-economic conditions. Districts of north and central India found more vulnerable then south India. Statistical significance has been tested using regression analysis, positive relation has been found between vulnerability index and confirmed and active cases. CONCLUSION: The vulnerability index has highlighted environmentaly and socioeconomicallybackward districts. These areas will suffer more critical problems against COVID-19 pandemic for their socio-environmental problem.

Thermodynamic imaging calculation model on COVID-19 transmission and epidemic cities risk level assessment-data from Hubei in China.

Novel coronavirus pneumonia in 17 city (Hubei) provinces was analyzed by using the principle of thermodynamics. A thermodynamic imaging model of infectious diseases was established to calculate the cumulative superimposed density of epidemic in 17 cities (prefectures). An evaluation rule of urban risk grade is established and evaluates the COVID-19 risk of 17 cities. The results show that (1) the higher the superimposed density of urban epidemic, the more infected people. (2) In the incubation stage, the thermodynamic imaging shows a point distribution, random walk, and outward diffusion trend. In the initial stage, the color of thermodynamic imaging gradually deepened and the range gradually expanded. During the burst stage, the thermodynamic imaging color deepens rapidly and the scope expands rapidly. In the stable stage, the thermodynamic imaging color becomes darkest and the range is extended to the pole. (3) According to the situation of COVID-19 transmission in Hubei Province, the cumulative superimposed density of Wuhan epidemic is far more than 10,000, ranking as "highest-risk." Xiaogan and other 10 cities have a cumulative superimposed density within the range of [1000, 10,000], ranking as "high-risk." Shiyan and other 5 cities have accumulated superimposed density values within the range of [100, 1000], ranking as "medium-risk." Shennongjia cumulative superimposed density value is less than 100, and the level is "low-risk."

Investigation of the Effect of COVID-19 Perceived Risk on Death Anxiety, Satisfaction With Life, and Psychological Well-Being.

This study aims to examine the effect of COVID-19 perceived risk on death anxiety, satisfaction with life, and psychological well-being. The application part of the research was conducted on staff working in a public hospital. A convenience sample of staff working in a public hospital was used and data were obtained from 573 individuals. The result of the analysis determined that the COVID-19 perceived risk explains 13.5% of the total variance on death anxiety. The regression models identified that the increase in COVID-19 risk perceptions of the participants statistically increased their death anxiety and decreased their satisfaction with life and psychological well-being.

Suicidal behavior during the COVID-19 pandemic: clinical aspects and associated factors / Comportamento suicida durante a pandemia da COVID-19: aspectos clínicos e fatores associados / Comportamiento suicida durante la pandemia de COVID-19: aspectos clínicos y factores asociados

Resumo Objetivo Analisar os aspectos clínicos e os fatores associados ao comportamento suicida durante a pandemia da COVID-19. Métodos Estudo transversal e analítico, realizado com registros assistenciais de 130 pacientes que buscaram atendimento em emergência psiquiátrica após ideação, planejamento ou tentativa de suicídio. Utilizou-se um formulário para caracterização sociodemográfica, clínica e terapêutica, assim como para identificação das necessidades de cuidados e dos fatores associados. A análise dos dados foi constituída pelos testes Exato de Fischer, Qui-quadrado de Pearson e pela Regressão de Poisson, considerando nível de significância de 5%. Resultados O comportamento suicida foi expresso pela tentativa de suicídio, ideação e planejamento, predominando no sexo feminino, em adultos jovens, desempregados e de baixa renda familiar, assim como em pacientes com histórico de transtorno mental, de internação psiquiátrica, de tentativas prévias e de abandono terapêutico. As principais alterações psíquicas envolveram ansiedade, depressão, sentimentos de desesperança, alucinações audiovisuais e delírios persecutórios. O consumo de substâncias psicoativas elevou em até 13,8 vezes o risco para tentativa de suicídio e as crises situacionais em 10,6 vezes a ideação. Ainda, a perda de renda e a internação anterior foram associados à manifestação do comportamento. As evidências de cuidados envolveram intervenções medicamentosas, medidas de vigilância e admissão hospitalar. Conclusão Durante a pandemia da COVID-19, o comportamento suicida foi associado à maior predisposição para o consumo de substâncias psicoativas, crises situacionais e perda de renda. Destaca-se a necessidade de políticas públicas voltadas para identificação, prevenção e gerenciamento adequado dos estados de risco.

Resumen Objetivo Analizar los aspectos clínicos y los factores asociados al comportamiento suicida durante la pandemia de COVID-19. Métodos Estudio transversal y analítico, realizado con registros asistenciales de 130 pacientes que buscaron atención en emergencia psiquiátrica después de ideación, planificación o intento de suicidio. Se utilizó un formulario para la caracterización sociodemográfica, clínica y terapéutica, como también para la identificación de las necesidades de cuidados y de los factores asociados. El análisis de los datos estuvo constituido por la prueba Exacta de Fisher, Ji cuadrado de Pearson y por la Regresión de Poisson, considerando un nivel de significancia del 5 %. Resultados El comportamiento suicida se expresó a través del intento de suicidio, ideación y planificación, con predominio del sexo femenino, adultos jóvenes, desempleados y con bajos ingresos familiares, así como pacientes con historial de trastorno mental, de internación psiquiátrica, de intentos previos y de abandono terapéutico. Las principales alteraciones psíquicas incluyeron ansiedad, depresión, sentimientos de desesperanza, alucinaciones audiovisuales y delirios de persecución. El consumo de substancias psicoactivas aumentó 13,8 veces el riesgo de intento de suicidio, y las crisis situacionales aumentaron 10,6 veces la ideación. Además, la pérdida de ingresos e internaciones anteriores se asociaron a la manifestación del comportamiento. Las evidencias de cuidados incluyeron intervenciones medicamentosas, medidas de vigilancia y admisión hospitalaria. Conclusión Durante la pandemia de COVID-19, el comportamiento suicida se asoció a un aumento de la predisposición al consumo de sustancias psicoactivas, crisis situacionales y pérdida de ingresos. Se destaca la necesidad de políticas públicas orientadas hacia la identificación, prevención y una gestión adecuada de los estados de riesgo.

Abstract Objective To analyze the clinical aspects and factors associated with suicidal behavior during the COVID-19 pandemic. Methods Cross-sectional analytical study performed with care records of 130 patients who sought care in the psychiatric emergency department after suicidal ideation, planning or attempt. A form was used for sociodemographic, clinical and therapeutic characterization, and for identification of care needs and associated factors. Data analysis consisted of Fischer's exact test, Pearson's chi-square test and Poisson's regression, considering a significance level of 5%. Results Suicidal behavior was expressed by suicide attempt, ideation and planning. It was predominant in the female sex, young adults, unemployed, with low family income, and in patients with a history of mental disorder, psychiatric hospitalization, previous attempts and of therapeutic abandonment. The main psychic alterations involved anxiety, depression, feelings of hopelessness, audiovisual hallucinations and persecutory delusions. The consumption of psychoactive substances increased by up to 13.8 times the risk for suicide attempt, while situational crises increased suicidal ideation by up to 10.6 times. The loss of income and previous hospitalization were associated with manifestation of the behavior. Evidence of care involved drug interventions, surveillance measures, and hospital admission. Conclusion During the COVID-19 pandemic, suicidal behavior was associated with a greater predisposition to consume psychoactive substances, situational crises and loss of income. The need for public policies aimed at the identification, prevention and adequate management of risk states stands out.

Temporal trends of morbidities, and risk and protective factors for noncommunicable diseases in elderly residents in Brazilian capitals / Tendências temporais de morbidades e fatores de risco e de proteção para doenças crônicas não transmissíveis em pessoas idosas residentes nas capitais brasileiras

ABSTRACT Objective: To analyze the temporal trends of prevalence of morbidities, risk and protection factors for noncommunicable diseases in elderly residents in Brazilian capitals between 2006 and 2021. Methods: A time series study with data from the Surveillance System of Risk and Protective Factors for Chronic Diseases by Telephone Inquiry. The variables analyzed were: high blood pressure, diabetes, smoking, overweight, obesity, consumption of alcoholic beverages, soft drinks, fruits and vegetables, and the practice of physical activity. Prais-Winsten regression and Interrupted Time Series from 2006 to 2014 and 2015 to 2021 were used. Results: From 2006 to 2021, for the total elderly population, there was an increase in diabetes (19.2 to 28.4%), alcohol consumption (2.5 to 3.2%), overweight (52.4 to 60.7%) and obesity (16.8 to 21.8%), and a reduction in the prevalence of smokers (9.4 to 7.4%) and in soft drink consumption (17 to 8.7%). By the interrupted series, between 2015 and 2021, there was stability in the prevalence of diabetes, female smokers, overweight among men, obesity in the total and male population, and soft drink consumption. Conclusion: Over the years, there have been changes and worsening in the indicators analyzed, such as an increase in diabetes, alcohol consumption, overweight, and obesity, which reinforces the importance of continuous monitoring and sustainability programs to promote the health, especially in the context of economic crisis, austerity, and COVID-19 pandemic.

RESUMO Objetivo: Analisar as tendências temporais das prevalências de morbidades e dos fatores de risco e de proteção para as doenças crônicas não transmissíveis em pessoas idosas residentes nas capitais brasileiras entre 2006 e 2021. Métodos: Estudo de série temporal com dados do Sistema de Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico. Analisaram-se as variáveis: hipertensão arterial; diabetes; tabagismo; excesso de peso; obesidade; consumo de bebidas alcoólicas, refrigerantes, frutas e hortaliças; e prática de atividade física. Empregaram-se o modelo de regressão de Prais-Winsten e a séries temporais interrompidas (de 2006 a 2014 e de 2015 a 2021). Resultados: De 2006 a 2021, para a população total de idosos, houve aumento de diabetes (19,2 para 28,4%), do consumo de álcool (2,5 para 3,2%), do dexcesso de peso (52,4 para 60,7%) e da obesidade (16,8 para 21,8%), e redução do tabagismo (9,4 para 7,4%) e consumo de refrigerantes (17,0 para 8,7%). Pelas séries interrompidas, entre 2015 e 2021, houve estabilidade da prevalência de diabetes, fumantes do sexo feminino, excesso de peso nos homens, obesidade na população total e no sexo masculino e consumo de refrigerante. Conclusão: Ao longo dos anos houve mudanças e piora dos indicadores analisados, como aumento de diabetes, do consumo de álcool, do excesso de peso e da obesidade, o que reforça a importância do monitoramento contínuo e da sustentabilidade de programas de promoção da saúde, especialmente no contexto de crise econômica, austeridade e pandemia decorrente da COVID-19.

Long COVID syndrome after SARS-CoV-2 survival in patients with pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension.

Pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH) patients have a more severe COVID-19 course than the general population. Many patients report different persistent symptoms after SARS-CoV-2 infection. The aim of our study is to analyze the prevalence of long COVID-19 symptoms and assess if COVID-19 affects pulmonary hypertension (PH) prognosis. PAH/CTEPH patients who survived COVID-19 for at least 3 months before visiting the PH centers were included in the study. The patients were assessed for symptoms in acute phase of SARS-CoV-2 infection and persisting in follow-up visit, WHO functional class, 6-min walk distance, NT-proBNP concentration. The COMPERA 2.0 model was used to calculate 1-year risk of death due to PH at baseline and at follow-up. Sixty-nine patients-54 (77.3%) with PAH and 15 (21.7%) with CTEPH, 68% women, with a median age of 47.5 years (IQR 37-68)-were enrolled in the study. About 17.1% of patients were hospitalized due to COVID-19 but none in an ICU. At follow-up (median: 155 days after onset of SARS-CoV-2 symptoms), 62% of patients reported at least 1 COVID-19-related symptom and 20% at least 5 symptoms. The most frequently reported symptoms were: fatigue (30%), joint pain (23%), muscle pain (17%), nasal congestion (17%), anosmia (13%), insomnia (13%), and dyspnea (12%). Seventy-two percent of PH patients had a low or intermediate-low risk of 1-year death due to PH at baseline, and 68% after COVID-19 at follow-up. Over 60% of PAH/CTEPH patients who survived COVID-19 suffered from long COVID-19 syndrome, but the calculated 1-year risk of death due to PH did not change significantly after surviving mild or moderate COVID-19.

Real-time risk ranking of emerging epidemics based on optimized moving average prediction limit-taking the COVID-19 pandemic as an example.

BACKGROUND: Mathematical models to forecast the risk trend of the COVID-19 pandemic timely are of great significance to control the pandemic, but the requirement of manual operation and many parameters hinders their efficiency and value for application. This study aimed to establish a convenient and prompt one for monitoring emerging infectious diseases online and achieving risk assessment in real time. METHODS: The Optimized Moving Average Prediction Limit (Op-MAPL) algorithm model analysed real-time COVID-19 data online and was validated using the data of the Delta variant in India and the Omicron in the United States. Then, the model was utilized to determine the infection risk level of the Omicron in Shanghai and Beijing. RESULTS: The Op-MAPL model can predict the epidemic peak accurately. The daily risk ranking was stable and predictive, with an average accuracy of 87.85% within next 7 days. Early warning signals were issued for Shanghai and Beijing on February 28 and April 23, 2022, respectively. The two cities were rated as medium-high risk or above from March 27 to April 20 and from April 24 to May 5, indicating that the pandemic had entered a period of rapid increase. After April 21 and May 26, the risk level was downgraded to medium and became stable by the algorithm, indicating that the pandemic had been controlled well and mitigated gradually. CONCLUSIONS: The Op-MAPL relies on nothing but an indicator to assess the risk level of the COVID-19 pandemic with different data sources and granularities. This forward-looking method realizes real-time monitoring and early warning effectively to provide a valuable reference to prevent and control infectious diseases.

Impact of Pandemic SARS COVID-19 on Different Construction Project Management: Problems and Solutions.

This study discusses risk management strategies caused by pandemic-related (Covid-19) suspensions in thirty-six engineering projects of different types and sizes selected from countries in the middle east and especially Iraq. The primary data collection method was a survey and questionnaire completed by selected project crew and laborers. Data were processed using Microsoft Excel to construct models to help decision-makers find solutions to the scheduling problems that may be expected to occur during a pandemic. A theoretical and practical concept for project risk management that addresses a range of global and local issues that affect schedule and cost is presented and results indicate that the most significant delays are due to a lack of good project risk management skills and remote project management capability which is exacerbated by shortfalls in technical development and information technology.

A risk-sharing-based resilient renewable energy supply network model under the COVID-19 pandemic.

Over the past few months, the COVID-19 pandemic has postponed many renewable energy projects because of disruptions in the technology and finance supply. Additionally, the existing power plants are inefficient because of a record drop in demand for goods and services caused by lockdowns in cities. This situation poses huge challenges to the resilience of renewable energy supply networks in the face of deeply hazardous events, such as the COVID-19 pandemic. Therefore, the purpose of this study was to design a resilient renewable energy supply network considering supply, demand, and payment risks caused by COVID-19. The objective of the proposed model was to determine the optimal amount of electric power generated and stored to meet the demands and the risk-sharing effort index to maximize the total resilient profit of the power plant and determine the optimal price adjustment index to minimize the cost to consumers. A government subsidy-based risk-sharing model was developed to enhance the resilience of the concerned renewable energy supply network under the pandemic. To overcome uncertainties in both random and risk events, a robust fuzzy-stochastic programming model was proposed to solve these research problems. Computational experiments were conducted on the test supply network in Vietnam. The results showed that the resilient energy supply network with the risk-sharing model tended to stabilize the total profit with the different impact levels of COVID-19 compared to the network without risk-sharing. The proposed model efficiently tackled both uncertainties in random and hazardous events and had a higher profit and shorter CPU time compared to the robust optimization mode.

Pre- and Post-Pandemic Religiosity and Mental Health Outcomes: A Prospective Study.

Relatively few studies have prospectively examined the effects of known protective factors, such as religion, on pandemic-related outcomes. The aim of this study was to evaluate the pre- and post-pandemic trajectories and psychological effects of religious beliefs and religious attendance. Male and female adults (N = 189) reported their beliefs in religious importance (RI) and their religious attendance (RA) both before (T1) and after (T2) the pandemic's onset. Descriptive and regression analyses were used to track RI and RA from T1 to T2 and to test their effects on psychological outcomes at T1 and T2. The participants who reported a decrease in religious importance and attendance were greater in number than those who reported an increase, with RI (36.5% vs. 5.3%) and RA (34.4% vs. 4.8%). The individuals with decreased RI were less likely to know someone who had died from COVID-19 (O.R. =0.4, p = 0.027). The T1 RI predicted overall social adjustment (p < 0.05) and lower suicidal ideation (p = 0.05). The T2 RI was associated with lower suicidal ideation (p < 0.05). The online RA (T2) was associated with lower depression (p < 0.05) and lower anxiety (p < 0.05). Further research is needed to evaluate the mechanisms driving decreases in religiosity during pandemics. Religious beliefs and online religious attendance were beneficial during the pandemic, which bodes well for the use of telemedicine in therapeutic approaches.

Impact of the COVID-19 pandemic on some modifiable risk factors of dementia in an aging, rural Indian population.

Introduction: The impact of the COVID-19 pandemic and associated lockdowns is likely to have caused adverse changes in lifestyle-related/cardiovascular risk factors and other such modifiable risk factors of dementia. We aimed to examine the pandemic's impact on some modifiable risk factors of dementia among rural Indians belonging to a large, prospective aging cohort-Srinivaspura Aging, NeuoSenescence, and COGnition (SANSCOG). Methods: This was a cross-sectional study among adults aged ≥ 45 years (n = 3,148; 1,492 males and 1,656 females) residing in the villages of Srinivaspura in Karnataka state, India. SANSCOG study data (clinical and biochemical assessments) of these participants were obtained from three distinct periods: (i) the "pre-COVID period"-before India's nationwide lockdown on 24 March 2020, (ii) the "COVID period"-during the first and second waves of the pandemic, wherein the social restrictions were prominent (25 March 2020 to 30 September 2021), and (iii) the "post-COVID period"-after easing of restrictions (from 1 October 2021 onward). Proportions of participants with diabetes, hypertension, obesity, dyslipidemia (diagnosed using standard criteria), and depression (diagnosed using the Geriatric Depression Scale) were compared between the above three periods. Results: The odds of having obesity, abnormal triglycerides, and depression among individuals in the COVID period were 1.42 times, 1.38 times, and 2.65 times more than the odds in the pre-COVID period, respectively. The odds of having hypertension, obesity, abnormal total cholesterol, abnormal triglycerides, abnormal LDL, and depression among individuals in the post-COVID period were 1.27 times, 1.32 times, 1.58 times, 1.95, 1.23, and 3.05 times more than the odds in the pre-COVID period, respectively. The odds of diabetes did not differ between any of the three periods. Discussion: We found significantly higher odds of some of the studied risk factors in the COVID and post-COVID periods compared to the pre-COVID period, suggesting that the pandemic adversely impacted the physical and psychological health of this marginalized, rural Indian population. We call for urgent public health measures, such as multimodal, lifestyle-based, and psychosocial interventions, to mitigate this negative impact and reduce the future risk of dementia.

Use of Bluetooth contact tracing technology to model COVID-19 quarantine policies in high-risk closed populations.

Containment measures in high-risk closed settings, like migrant worker (MW) dormitories, are critical for mitigating emerging infectious disease outbreaks and protecting potentially vulnerable populations in outbreaks such as coronavirus disease 2019 (COVID-19). The direct impact of social distancing measures can be assessed through wearable contact tracing devices. Here, we developed an individual-based model using data collected through a Bluetooth wearable device that collected 33.6M and 52.8M contact events in two dormitories in Singapore, one apartment style and the other a barrack style, to assess the impact of measures to reduce the social contact of cases and their contacts. The simulation of highly detailed contact networks accounts for different infrastructural levels, including room, floor, block, and dormitory, and intensity in terms of being regular or transient. Via a branching process model, we then simulated outbreaks that matched the prevalence during the COVID-19 outbreak in the two dormitories and explored alternative scenarios for control. We found that strict isolation of all cases and quarantine of all contacts would lead to very low prevalence but that quarantining only regular contacts would lead to only marginally higher prevalence but substantially fewer total man-hours lost in quarantine. Reducing the density of contacts by 30% through the construction of additional dormitories was modelled to reduce the prevalence by 14 and 9% under smaller and larger outbreaks, respectively. Wearable contact tracing devices may be used not just for contact tracing efforts but also to inform alternative containment measures in high-risk closed settings.

"No more COVID-19 messages via social media, please": the mediating role of COVID-19 message fatigue between information overload, message avoidance, and behavioral intention.

Employing the stressor-strain-outcome framework, this study demonstrates that COVID-19 information overload on social media exerts a significant effect on the level of fatigue toward COVID-19-related messages. This feeling of message fatigue also makes people avoid another exposure to similar types of messages while diminishing their intentions to adopt protective behaviors in response to the pandemic. Information overload regarding COVID-19 on social media also has indirect effects on message avoidance and protective behavioral intention against COVID-19, respectively, through the feeling of fatigue toward COVID-19 messages on social media. This study emphasizes the need to consider message fatigue as a significant barrier in delivering effective risk communication.

Myocardial Infarction in Young Individuals: A Review Article.

Although myocardial infarction (MI) primarily affects patients over the age of 45, it can also affect young women and men. Still, when it occurs at an early age, it has severe morbidity and psychological and financial burdens for the patient and his or her relatives. Four classes can be used to categorize the causes of MI in individuals below the age of 45. These are drug abuse-related MI, hyper-coagulable conditions, atheromatous coronary artery disease (CAD), and non-atheromatous CAD. There is a significant overlap between each category. Elevated blood pressure, smoking, diabetes, obesity, high cholesterol, inactivity, an unbalanced diet, binge drinking alcohol, and related substances are all risk factors. The primary mechanism of an MI is typically the total obstruction of a vessel caused by breaking an atheromatous plaque. This article covers the research and focuses on the practical concerns related to young adults with MI.

Occupational health: the role of demographic factors in the condition of increased risk.

OBJECTIVES: The paper analyses the impact of socio-demographic characteristics of the employees in conditions of uncertainty in the organizations. MATERIAL AND METHODS: The study was conducted on a sample of 210 employees using the Mental Health Inventory - 38 (MHI-38), Satisfaction with life scale (SWLS), and the Center for Epidemiological Studies - Depression (CES-D). RESULTS: The results showed that female respondents had significantly higher scores on ANX (t = 2,278, p < 0.05), while male employees had higher scores on life satisfaction (t = 2.103, p < 0.05). Older employees have a higher tendency for loss of emotional-behavioral control (F = 4.427, p < 0.05). Respondents who have satisfying living standards have also higher scores on SWLS (t = 2.257, p < 0.05). Respondents who have dissatisfying living standard have higher scores on generally positive affect (t = 3.152, p < 0.01), life satisfaction (t = 3.571, p < 0.01), psychological distress (t = 2.929, p < 0.01) and loss of emotional- behavioral control (t = 2.361, p < 0.05). Employees with different levels of educational background have similar tendencies in life satisfaction, mental health, and depressive symptoms (p > 0.05). CONCLUSIONS: The study showed that the specific socio-demographic profile of the employees is related to higher levels of mental health issues. Specifically, the mental health of female and older employees have been especially affected and disturbed by uncertain conditions. The results can be potentially used both in the terms of designing activities that support the mental health of the population, as well as in relation to the mental health of employees. Int J Occup Med Environ Health. 2023;36(2):250-62.

Predictive care: a protocol for a computational ethnographic approach to building fair models of inpatient violence in emergency psychiatry.

INTRODUCTION: Managing violence or aggression is an ongoing challenge in emergency psychiatry. Many patients identified as being at risk do not go on to become violent or aggressive. Efforts to automate the assessment of risk involve training machine learning (ML) models on data from electronic health records (EHRs) to predict these behaviours. However, no studies to date have examined which patient groups may be over-represented in false positive predictions, despite evidence of social and clinical biases that may lead to higher perceptions of risk in patients defined by intersecting features (eg, race, gender). Because risk assessment can impact psychiatric care (eg, via coercive measures, such as restraints), it is unclear which patients might be underserved or harmed by the application of ML. METHODS AND ANALYSIS: We pilot a computational ethnography to study how the integration of ML into risk assessment might impact acute psychiatric care, with a focus on how EHR data is compiled and used to predict a risk of violence or aggression. Our objectives include: (1) evaluating an ML model trained on psychiatric EHRs to predict violent or aggressive incidents for intersectional bias; and (2) completing participant observation and qualitative interviews in an emergency psychiatric setting to explore how social, clinical and structural biases are encoded in the training data. Our overall aim is to study the impact of ML applications in acute psychiatry on marginalised and underserved patient groups. ETHICS AND DISSEMINATION: The project was approved by the research ethics board at The Centre for Addiction and Mental Health (053/2021). Study findings will be presented in peer-reviewed journals, conferences and shared with service users and providers.

Persistent symptoms and risk factors predicting prolonged time to symptom-free after SARS­CoV­2 infection: an analysis of the baseline examination of the German COVIDOM/NAPKON-POP cohort.

PURPOSE: We aimed to assess symptoms in patients after SARS-CoV-2 infection and to identify factors predicting prolonged time to symptom-free. METHODS: COVIDOM/NAPKON-POP is a population-based prospective cohort of adults whose first on-site visits were scheduled ≥ 6 months after a positive SARS-CoV-2 PCR test. Retrospective data including self-reported symptoms and time to symptom-free were collected during the survey before a site visit. In the survival analyses, being symptom-free served as the event and time to be symptom-free as the time variable. Data were visualized with Kaplan-Meier curves, differences were tested with log-rank tests. A stratified Cox proportional hazard model was used to estimate adjusted hazard ratios (aHRs) of predictors, with aHR < 1 indicating a longer time to symptom-free. RESULTS: Of 1175 symptomatic participants included in the present analysis, 636 (54.1%) reported persistent symptoms after 280 days (SD 68) post infection. 25% of participants were free from symptoms after 18 days [quartiles: 14, 21]. Factors associated with prolonged time to symptom-free were age 49-59 years compared to < 49 years (aHR 0.70, 95% CI 0.56-0.87), female sex (aHR 0.78, 95% CI 0.65-0.93), lower educational level (aHR 0.77, 95% CI 0.64-0.93), living with a partner (aHR 0.81, 95% CI 0.66-0.99), low resilience (aHR 0.65, 95% CI 0.47-0.90), steroid treatment (aHR 0.22, 95% CI 0.05-0.90) and no medication (aHR 0.74, 95% CI 0.62-0.89) during acute infection. CONCLUSION: In the studied population, COVID-19 symptoms had resolved in one-quarter of participants within 18 days, and in 34.5% within 28 days. Over half of the participants reported COVID-19-related symptoms 9 months after infection. Symptom persistence was predominantly determined by participant's characteristics that are difficult to modify.