A framework for integrating evidence to assess hazards and risk.

To accurately characterize human health hazards, human, animal, and mechanistic data must be integrated and the relevance to the research question of all three lines of evidence must be considered. Mechanistic data are often critical to the full integration of animal and human data and to characterizing relevance and uncertainty. This novel evidence integration framework (EIF) provides a method for synthesizing data from comprehensive, systematic, quality-based assessments of the epidemiological and toxicological literature, including in vivo and in vitro mechanistic studies. It organizes data according to both the observed human health effects and the mechanism of action of the chemical, providing a method to support evidence synthesis. The disease-based component uses the evidence of human health outcomes studied in the best quality epidemiological literature to organize the toxicological data according to authors' stated purpose, with the pathophysiology of the disease determining the potential relevance of the toxicological data. The mechanism-based component organizes the data based on the proposed mechanisms of effect and data supporting events leading to each endpoint, with the epidemiological data potentially providing corroborating information. The EIF includes a method to cross-classify and describe the concordance of the data, and to characterize its uncertainty. At times, the two methods of organizing the data may lead to different conclusions. This facilitates identification of knowledge gaps and shows the impact of uncertainties on the strength of causal inference.

Current and anticipated future state of cachexia care in patients with cancer.

Aims: We assessed care in cancer patients with cachexia across leading health systems (LHSs). Patients & methods: Qualitative interviews and quantitative surveys were conducted with LHSs executives and frontline health care personnel, representing 46 total respondents and 42 unique LHSs and including oncology service line leaders, supportive care services, dietitians and surgical oncologists. Results: Cachexia was not considered a top priority, and formal diagnoses were rare. Participants highlighted the importance of addressing barriers to increase clinical trial enrollment and support frontline health care personnel and patients in early detection of cachexia. Conclusion: Cachexia prioritization needs to be elevated across LHSs executives to obtain capital and strategic imperatives to advance related care.

[Box: see text].

Risk assessment for people living with dementia: a systematic review.

OBJECTIVE: This systematic review identified key components of risk assessment for people with dementia, examined attitudes toward risk identification and risk assessment, and appraised existing risk assessment tools. METHODS: Systematic searches of five databases on two platforms (EBSCO, OVID) and gray literature databases (Open Grey, Base) were conducted. Studies were screened for inclusion based on predetermined eligibility criteria and quality assessed using the Mixed Methods Appraisal Tool. Findings were tabulated and synthesized using thematic synthesis. RESULTS: Our review found people with dementia, their family carers, and healthcare professionals differed in how risk is conceptualized, with views being shaped by media perceptions, personal experiences, socio-cultural influences, dementia knowledge, and dementia severity. We found that mobilization (causing falls inside and getting lost outside) is the most frequently identified risk factor. Our findings show people with dementia are generally risk-tolerant, while healthcare professionals may adopt risk-averse approaches because of organizational requirements. We found factors that disrupt daily routines, living and caring arrangements, medication management, and unclear care pathways contribute toward adverse risk events. We discovered that most studies about risk and risk assessment scales did not consider insight of the person with dementia into risks although this is important for the impact of a risk. No risk instrument identified had sufficient evidence that it was useful. CONCLUSION: Accurate risk assessment and effective communication strategies that include the perspectives of people with dementia are needed to enable risk-tolerant practice. No risk instrument to date was shown to be widely acceptable and useful in practice.

Assessment of work safety analysis performance among rural hospitals of Chirumanzu district of midlands province, Zimbabwe.

Ensuring workplace safety for healthcare workers is vital considering the important role they play in various societies which is to save life. Healthcare workers face different risks when performing tasks in various departments within hospitals, hence there is a need to assess work safety analysis procedures among healthcare workers. As a result, this study aims to assess the effectiveness of work safety analysis procedures among healthcare workers at Muvonde and Driefontein Sanatorium rural hospitals in Chirumanzu district. The research applied the descriptive cross-sectional design, combining quantitative and qualitative data collection methods. A questionnaire with both closed and open ended questionnaire was used for data collection among 109 healthcare workers at Muvonde hospital and 68 healthcare workers at Driefontein Sanatorium hospital. Secondary data sources, observations and interviews were also included as data collection methods. Quantitative data collected during the study was analysed using SPSS version 25. Braun and Clarke (2006)'s six phase framework was applied for qualitative data analysis. Ethical approval form was obtained from the District Medical Officer and Midlands State University. Findings of the study indicated that risks identified at Muvonde and Driefontein Sanatorium rural hospitals are classified as ergonomic, physical, chemical, psychosocial and biological risks. Respondents specified that these risks occur as a result of inadequate equipment, poor training, negative safety behaviour, poor management and pressure due to high workload. Safety inspection, safety workshops and monitoring of worker's safety behaviour were mentioned as measures to manage risks. However, the strengths and weaknesses of the current safety procedures need to be assessed to highlight areas for improvement to reduce occurrence of risks within the hospitals.

Risk identification and prediction of complaints and misconduct against health practitioners: a scoping review.

Identifying the risk and predicting complaints and misconduct against health practitioners are essential for healthcare regulators to implement early interventions and develop long-term prevention strategies to improve professional practice and enhance patient safety. This scoping review aims to map out existing literature on the risk identification and prediction of complaints and misconduct against health practitioners. This scoping review followed Arksey and O'Malley's five-stage methodological framework. A comprehensive literature search was conducted on MEDLINE, EMBASE, and CINAHL databases and finished on the same day (6 September 2021). Articles meeting the eligibility criteria were charted and descriptively analysed through a narrative analysis method. The initial search generated 5473 articles. After the identification, screening, and inclusion process, 81 eligible studies were included for data charting. Three key themes were reported: methods used for identifying risk factors and predictors of the complaints and misconduct, synthesis of identified risk factors and predictors in eligible studies, and predictive tools developed for complaints and misconduct against health practitioners. The findings reveal that risk identification and prediction of complaints and misconduct are complex issues influenced by multiple factors, exhibiting non-linear patterns and being context specific. Further efforts are needed to understand the characteristics and interactions of risk factors, develop systematic risk prediction tools, and facilitate the application in the regulatory environment.

Medical device-related pressure injuries in intensive care patients: A prospective and descriptive study.

BACKGROUND: Treatment and care of patients in intensive care units require the use of many medical and technological instruments. Pressure injuries occur when medical devices, which are used more in intensive care patients and are in direct or indirect contact with the skin, cause focal and localized forces on the superficial or deep tissues. OBJECTIVE: In this study, it was aimed to examine the risk factors, incidence and characteristics of medical device-related pressure injuries in intensive care patients. METHODS: This study has a prospective and descriptive design. The study was carried out in the adult intensive care unit of a healthcare institution located in the western Turkey. 138 intensive care patients treated in the level 3 adult intensive care unit were enrolled in the study. The first observations and evaluations of intensive care patients in terms of pressure injuries were made within the first 24 h after admission to the clinic. Observations continued daily during the hospitalization period of the patient. Data were collected with the Intensive Care Patient Information Form, Glasgow Coma Scale, Braden Pressure Ulcer Risk Assessment Scale and Identification Form for Medical device-related Pressure Ulcers. Analysis of data was performed with descriptive statistical methods, Shapiro-Wilk Test, Mann-Whitney U Test and Chi-Square analysis. RESULTS: Medical device-related pressure injury developed in 11.6% (n = 16) of intensive care patients. Anatomically, pressure injury occurred most frequently on the lip (37.5%) and most frequently due to the intubation tube (37.5%). Most of the developed wounds (75.0%) were found to be stage 2. Multinominal logistic regression analysis, which was performed to determine the effect of independent variables on medical device-related pressure injuries in intensive care patients, was found to be statistically significant (X2 = 37.098, p < 0.001). When the regression coefficients were examined, it was found that total hospitalization time in the intensive care unit (ß = 0.948, p < 0.01) and PaCO2 level (ß = 0.923, p < 0.01) had a positive, and duration of aerobic respiration with nasal cannula or mask (ß = -0.920, p < 0.01) and Braden score (ß = -0.948, p < 0.01) had a negative and significant effect on medical device-related pressure injuries. CONCLUSIONS: In this study found that the MDRPIs development rate was lower than other studies. It was observed that pressure injuries due to medical devices developed more frequently in patients with longer hospitalization days, higher PaCO2 levels, shorter duration of oxygenated breathing with nasal cannula or mask, and lower Braden scores.

Public Surveillance of Social Media for Suicide Using Advanced Deep Learning Models in Japan: Time Series Study From 2012 to 2022.

BACKGROUND: Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people's expressions on social media. However, there is not enough evidence to conclude that social media provides public surveillance for suicide without aligning suicide risks detected on social media with actual suicidal behaviors. Corroborating this alignment is a crucial foundation for suicide prevention and intervention through social media and for estimating and predicting suicide in countries with no reliable suicide statistics. OBJECTIVE: This study aimed to corroborate whether the suicide risks identified on social media align with actual suicidal behaviors. This aim was achieved by tracking suicide risks detected by 62 million tweets posted in Japan over a 10-year period and assessing the locational and temporal alignment of such suicide risks with actual suicide behaviors recorded in national suicide statistics. METHODS: This study used a human-in-the-loop approach to identify suicide-risk tweets posted in Japan from January 2013 to December 2022. This approach involved keyword-filtered data mining, data scanning by human efforts, and data refinement via an advanced natural language processing model termed Bidirectional Encoder Representations from Transformers. The tweet-identified suicide risks were then compared with actual suicide records in both temporal and spatial dimensions to validate if they were statistically correlated. RESULTS: Twitter-identified suicide risks and actual suicide records were temporally correlated by month in the 10 years from 2013 to 2022 (correlation coefficient=0.533; P<.001); this correlation coefficient is higher at 0.652 when we advanced the Twitter-identified suicide risks 1 month earlier to compare with the actual suicide records. These 2 indicators were also spatially correlated by city with a correlation coefficient of 0.699 (P<.001) for the 10-year period. Among the 267 cities with the top quintile of suicide risks identified from both tweets and actual suicide records, 73.5% (n=196) of cities overlapped. In addition, Twitter-identified suicide risks were at a relatively lower level after midnight compared to a higher level in the afternoon, as well as a higher level on Sundays and Saturdays compared to weekdays. CONCLUSIONS: Social media platforms provide an anonymous space where people express their suicidal thoughts, ideation, and acts. Such expressions can serve as an alternative source to estimating and predicting suicide in countries without reliable suicide statistics. It can also provide real-time tracking of suicide risks, serving as an early warning for suicide. The identification of areas where suicide risks are highly concentrated is crucial for location-based mental health planning, enabling suicide prevention and intervention through social media in a spatially and temporally explicit manner.

A risk-based approach to cumulative effects assessment for large marine ecosystems to support transboundary marine spatial planning: A case study of the yellow sea.

Cumulative effects assessment (CEA) should be conducted at ecologically meaningful scales such as large marine ecosystems to halt further ocean degradation caused by anthropogenic pressures and facilitate ecosystem-based management such as transboundary marine spatial planning (MSP). However, few studies exist at large marine ecosystems scale, especially in the West Pacific seas, where countries have different MSP processes yet transboundary cooperation is paramount. Thus, a step-wise CEA would be informative to help bordering countries set a common goal. Building on the risk-based CEA framework, we decomposed CEA into risk identification and spatially-explicit risk analysis and applied it to the Yellow Sea Large Marine Ecosystem (YSLME), aiming to understand the most influential cause-effect pathways and risk distribution pattern. The results showed that (1) seven human activities including port, mariculture, fishing, industry and urban development, shipping, energy, and coastal defence, and three pressures including physical loss of seabed, input of hazardous substances, nitrogen, and phosphorus enrichment were the leading causes of environmental problems in the YSLME; (2) benthic organisms, fishes, algae, tidal flats, seabirds, and marine mammals were the most vulnerable ecosystem components on which cumulative effects acted; (3) areas with relatively high risk mainly concentrated on nearshore zones, especially Shandong, Liaoning, and northern Jiangsu, while coastal bays of South Korea also witnessed high risk; (4) certain risks could be observed in the transboundary area, of which the causes were the pervasive fishing, shipping, and sinking of pollutants in this area due to the cyclonic circulation and fine-grained sediments. In future transboundary cooperation on MSP, risk criteria and evaluation of existing management measures should be incorporated to determine whether the identified risk has exceeded the acceptable level and identify the next step of cooperation. Our study presents an example of CEA at large marine ecosystems scale and provides a reference to other large marine ecosystems in the West Pacific and elsewhere.

Missed Vision Screenings for School-Age Children During The COVID-19 Pandemic: A Survey Based Study of NASN Representatives.

During the 2020-21 academic year, COVID-19-related educational disruptions impacted school-based vision screenings. However, limited information regarding changes in vision screening and the number of students impacted has been reported. Delayed screenings can negatively impact students' referral to eye care providers, which may affect a child's ability to see clearly and academic success. This study aims to describe changes in school-based vision screening practices through a survey of National Association of School Nurses state representatives (n = 49). Among states with vision screenings mandates, participants reported that 23.7% (9/38) states waived screenings, 31.6% (12/38) continued screenings, and 36.8% (14/38) modified requirements, such as grades screened or assessments included (e.g., color vision and stereoacuity screenings). These results suggest that millions of students across the United States missed vision screenings during the 2020-21 academic year. Efforts by education and school health stakeholders should be directed towards addressing the pandemic-related disruption in vision screening.

Application of the Toxic Stress Schema: An Exemplar for School Nurses.

For many children of color, the cumulative impact of pre-existing stressors, disparities, and pandemic-related losses has contributed to a toxic level of stress. Toxic stress can disrupt healthy brain development making children vulnerable to physical and mental health problems. School nurses are the primary health professionals who interact with children daily during the academic year, which positions them to identify risk factors within the social determinants of health that contribute to the development of toxic stress. The Toxic Stress Schema (TSS) provides a framework for assessment and care planning related to social determinants of health and potential sources of stress and/or buffering support for the physical and mental well-being of children. A case study approach is used to demonstrate the application of the TSS to school nursing and provide the basis for conceptualizing a plan of care and identifying resources to support the child's physical and mental health.

Considerations in Building a School-Based Vision Program.

The burden of childhood visual impairment and disparities in access to pediatric vision care remain pressing issues in the United States. School-based vision programs (SBVPs) serve as one approach to advancing health equity. Operating at the intersection of schools and healthcare, SBVPs can increase access to pediatric vision services, improve academic performance, and facilitate referrals to community vision care providers. To maximize their impact, SBVPs must tailor their services to the individual needs and resources of local school communities. School nurses, who have strong ties to school health care services and the school community, are trusted partners in building SBVPs. This article aims to facilitate SBVP development, implementation, and sustainability processes by offering guidance for school nurses and other stakeholders who aim to build a SBVP, support local programs, or learn more about how SBVPs operate.

Hybrid Learning Modality Did Not Reduce the Risk of COVID-19 Among Colorado Students.

During the 2020-2021 school year, many schools adopted remote learning or a part-time in-person learning ("hybrid") approach to reduce the risk of in-school transmission of COVID-19. The purpose of this work is to describe case rates of COVID-19 in schools practicing different learning modalities on rates of COVID-19 to support risk-benefit decisions in the context of respiratory disease outbreaks. We conducted a person-time-at-risk analysis of rates of COVID-19, as well as testing and test positivity rates among Colorado students. Schools practicing remote learning had a lower adjusted rate of COVID-19 cases compared to either hybrid or in-person learning modalities. Students attending a school with remote learning had fewer reported tests, and test positivity was higher for remote learning. Our analysis found that both case rate and test positivity were similar in hybrid and in-person learning modalities, indicating that hybrid learning modalities may not reduce the risk of respiratory disease transmission.

[The measurement of risks of health damage under provision of primary medical sanitary care].

The organization and implementation of quality management system in medical organization based on internal quality control and safety of medical activities, permits to implement continuous improvement of organization functioning, to eliminate errors or undesirable occurrences as well as to prevent causes of premature mortality and to contribute into increasing of indicator of life expectancy.The implementation of risk-oriented approach in management of medical organization within the framework of internal quality control and safety of medical activities is actual and necessary condition in accordance with adopted regulatory legal acts. Currently, in the healthcare system there are no developed and approved methods of developing infrastructure of risk management in medical organization. The purpose of the study: to apply the FMEA analysis and Pareto diagram technologies to quantify and rank risks of health harm in development of organizational and managerial decision-making. The sociological method was applied to identify violations in provision of medical care, including their frequency and possible risks. The FMEA analysis was implemented to each undesirable occurrence (risk), considering frequency of its occurrence. The priority number of risk (PMR) is calculated and risk register is compiled. The Pareto diagram construction technology made it possible to assess significance and to build risk matrix.

Human health risk identification of petrochemical sites based on extreme gradient boosting.

Petrochemical industry is a key industry of soil pollution, which presents great effects on human health and the ecological environment. It is of great significance to achieve rapid, economic and efficient health risk identification for petrochemical industry in China. In this work, an efficient method was developed based on extreme gradient boosting (XGBoost) algorithm for human health risk identification, which is different from the traditional health risk assessment with complicated procedures. In this methodology, an index system of 13 indicators was established from the perspective of "sources - pathways - receptors" for risk identification. The 10-fold cross validation was used to assess the generalization performance, and the accuracy, precision and recall were employed to evaluate the performance of the algorithms. Wilcoxon signed-rank test was conducted to analyze the differences between XGBoost and other models for statistical support. The results showed that XGBoost significantly presented a better performance for health risk identification over multilayer perceptron neural network with error backpropagation training (BPNN), support vector machine (SVM), gradient boosting decision tree (GBDT) and light gradient boosting machine (LightGBM), with an accuracy of 0.783. The most important features contributing to the risk identification were determined with the sequence of site location (in the industrial zone or not), site planning and production period. Great attention should be given to the petrochemical sites that are not located in the industrial zone with long production period and sensitive receptors in the health risk identification. This method has important reference significance for relevant departments to carry out soil contamination screening and health risk assessment of petrochemical sites.

Identifying women at risk of weight gain after a breast cancer diagnosis: Results from a cohort of Australian women.

ISSUES ADDRESSED: This study aimed to identify risk factors associated with weight gain post a diagnosis of breast cancer in a cohort of Australian women. METHODS: In this retrospective clinical audit, objectively measured weight, age and menopause status, treatment type/s, grade, stage, oestrogen receptor and progesterone receptor (PR) status were extracted for 73 breast cancer patients from an ongoing breast cancer treatment quality assurance project. Weight gain or loss was classified as a body mass increase or decrease of ≥5% of weight at diagnosis. RESULTS: When compared to weight at diagnosis, 57% of patients maintained, 22% gained, and 21% lost weight at 24 months post-diagnosis. Factors associated with weight gain were a diagnosis of grade II (P < .001) or grade III (P < .001) compared to grade I breast cancer, and refusal of radiotherapy (P < .001). Factors associated with weight loss were being postmenopausal compared to premenopausal (P = .033), PR positive compared to PR negative (P < .001), refusal of chemotherapy (P < .001) and radiotherapy recommended (P < .001). CONCLUSIONS: The maintenance of weight in a majority of women in this cohort is a novel finding. Early identification of women at risk of weight gain post a breast cancer diagnosis can assist health professionals identify, and therefore assisting patients in the prevention and management of weight gain and associated sequela. Investigating the weight-related communications between a patient and specialist, their access to allied health professionals and social support may assist in understanding the overall positive changes in this cohort.

Decision support analysis for risk identification and control of patients affected by COVID-19 based on Bayesian Networks.

In the context of the outbreak of coronavirus disease (COVID-19), this paper proposes an innovative and systematic decision support model based on Bayesian networks (BNs) to identify and control the risk of COVID-19 patients spreading the virus, which requires the following three steps. First, by consulting the related literature and combining this with expert knowledge, we identify and classify the characteristics (risk factors) of COVID-19 and obtain a conceptual framework for COVID-19 Risk Assessment Bayesian Networks (CRABNs). Second, data on COVID-19 patients with expert scoring results on patient risk levels were collected from hospitals in Hubei Province of China and are used as the training set, and the structure and parameters of the CRABNs model are obtained through machine learning. Finally, we propose two indicators, namely, Model Bias and Model Accuracy, and use the remaining data to verify the feasibility and effectiveness of the CRABNs model to ensure that there are no significant differences between the predicted results of the model and the actual results provided by experts who have relevant experience in treating COVID-19. At the same time, we compared the CRABNs model with the support vector machine (SVM), random forest (RF), and k-nearest neighbour (KNN) models through four indicators: accuracy, sensitivity, specificity, and F-score. The results suggest the reliability of the model and show that it has promising application potential. The proposed model can be used globally by doctors in hospitals as a decision support tool to improve the accuracy of assessing the severity of COVID-19 symptoms in patients. Furthermore, with the further improvement of the model in the future, it can be used for risk assessments in the field of epidemics.

Problematic Behaviors and Predicting Online Risk Behaviors in High School Students.

Adolescent behavior now occurs offline and online. Frequently studied and treated independently, the relationship between offline problem behaviors and online risk taking is not well understood. This study asked whether there are any problematic behaviors predictive of online risk taking by high school students. Using a 2009 dataset of 2,077 high school students grades 9-12, five areas of offline problematic behaviors were examined: Academic problems, anxiety, behavioral wrongdoing, bullying, and social-emotional. Nine binary results were classified as online risk: Sexting, online harassment (perpetrating and experiencing), visiting sex sites, talking about sex, receiving sexual pictures, meeting offline, anything sexual happened, feeling nervous or uncomfortable. Behavioral wrongdoing (fighting, school suspension, trouble with police, theft), emerged as a significant predictor appearing in all nine models, followed by bullying experience (bully or victim) in six models. Identifying common problem behaviors that predict online risk taking are key components in developing strategies to promote adolescent health and well-being.

Feasibility of an Online, Interactive Body Mass Index Parental Notification Letter (e-BMI).

School-based body mass index (BMI) screening is required in 50% of states with parent notification letters distributed among 11 of those states. Additional research is needed to effectively communicate screening results to parents. We conducted a pilot investigation of parent acceptability of an electronic, interactive BMI parental notification letter (e-BMI) along with the feasibility of implementing an e-BMI letter in the school setting. In addition, we assessed parental attitudes and practices regarding their child's weight-related behaviors. Electronic letter distribution and parent receipt were consistent with traditional paper letter mailings; however, we did not observe any significant behavioral impacts with either letter format. Parents reported interest in wellness programming offered by the school, a potential opportunity for schools to engage families in healthful practices. Additional research is needed to understand the impact of e-BMI letters and accompanying web-based resources specifically for parents of students with overweight or obesity.

Exploring Screening Practices for Child Sexual Abuse in School Settings: An Integrative Review.

Child sexual abuse (CSA) is a pervasive public health problem. If left undetected, CSA can result in immediate and long-term health problems, which can be mitigated through early identification. Schools are an ideal environment to implement screening measures, and school nurses (SN) are uniquely poised to intervene and respond early. The aim of this review was to systematically examine and synthesize the international evidence related to screening for early identification of CSA in schools. Themes emerging from the analysis were SN behaviors relative to screening, potential instruments or approaches for screening, and SN and school professionals' beliefs about CSA screening practices. This review found little evidence that CSA screening is occurring in schools. However, SNs are aware that screening falls within their scope of practice and many SNs feel they should be screening for it. A constant proactive approach by SNs is necessary to improve early identification and subsequent intervention.

The Role of Nursing in the School Setting to Lead Efforts to Impact Child Trafficking: An Integrative Review.

Registered professional and advanced practice nurses in the school setting, as a specialized practice entity, are leaders in implementation of evidence-based practice, skilled coordinators of care, advocates for students, and experts in designing systems assisting individuals and communities to reach full potential. Child trafficking (CT) is an emerging public health threat impacting safety and well-being of students present in the school setting. This literature review identified four themes in five studies: (1) training impacts nurses' knowledge, awareness, and attitudes; (2) school nursing is underrepresented in training, education, prevention, response, and research; (3) lack of collaboration exists between school staff and school nurses; and (4) formal education and length of experience impact levels of interventions school nurses are able to provide. School nurses are opportunely situated to intervene as advocates for vulnerable children to develop a coordinated, effective response to CT risk factors, mitigating risk and fostering resiliency with systems-based change.