Level Of Risk Research Articles

Health equity via inclusive communications: self-censorship of marginalized health needs in qualitative research

ABSTRACT Based on a multi-phase study conducted on the World Health Organization’s (WHO) age-friendly cities program, healthy-cities program, and global sustainable-cities initiatives, this paper assesses how older adults – particularly those living with chronic health conditions and disabilities – discuss mobility challenges in qualitative research. Initial results indicate that demobilizing levels of travel cost and travel risk are implied, with older adults refraining from direct discussion. Reflective analysis is performed on marginalized older adults’ conceptual associations, ideologies, and response to social norms, to identify sources of pressure which may lead to downplaying or self-censorship on transport disadvantage. Results highlight that inequalities may arise from both the built environment and how research trainees communicate in research. Despite literature which suggests severe impacts of transport disadvantage, older adults may face difficulties in voicing their needs when research trainees adhere to the following social norms. First, physical access and feasibility may be minimized as mere matters of convenience to the able-bodied individual; second, overcoming transportation barriers may be seen as based on one’s effort – as opposed to the disabling effects of the built environment; third, health and fitness in general may be also associated with one’s effort, and increasingly also to one’s commitment to environmental-sustainability; fourth, older adults may feel pressure to align perspectives with more privileged stakeholders, or with the general public; fifth, money and income may be delegitimized as apt research topics, regardless of how inability to overcome travel costs may impact daily-wellbeing. Implications for educating future gerontology-research trainees conclude the study.

Volatile organic compounds and cancer risk assessment in an intensive care unit.

Changes caused by air-cleaning devices in the amounts of volatile organic compounds in an intensive care unit were monitored in the study. The cancer risk and hazard index were calculated. The measurements were made for one month at isolated room and two different points and times in the intensive care unit. According to the sampling program, the air-cleaning devices were turned off in weeks 1 and 4 and turned on in weeks 2 and 3. Volatile organic compounds were collected by active sampling. Samples were analyzed by a thermal desorber coupled to a gas chromatography-mass spectrometry instrument with selective ion monitoring. The results showed that the concentrations of benzene, toluene, and o-xylene decreased by about 70% after the air-cleaning devices were installed. The cancer risk assessment for naphthalene was recorded at the highest level of cancer risk (Class A). The hazard index value of naphthalene was recorded at the harmful level when air-cleaning devices were not installed. The concentrations of benzene (p = 0.01), toluene (p = 0.02), ethylbenzene (p = 0.02), styrene (p = 0.01), and m, p-xylene (p = 0.04) before the air-cleaning devices were installed were significantly different from those recorded when the air-cleaning devices were turned on.

Exposure Effects of Environmentally Relevant Concentrations of the Tricyclic Antidepressant Amitriptyline in Early Life Stage Zebrafish.

Antidepressants are one of the most globally prescribed classes of pharmaceuticals, and drug target conservation across phyla means that nontarget organisms may be at risk from the effects of exposure. Here, we address the knowledge gap for the effects of chronic exposure (28 days) to the tricyclic antidepressant amitriptyline (AMI) on fish, including for concentrations with environmental relevance, using zebrafish (Danio rerio) as our experimental model. AMI was found to bioconcentrate in zebrafish, was readily transformed to its major active metabolite nortriptyline, and induced a pharmacological effect (downregulation of the gene encoding the serotonin transporter; slc6a4a) at environmentally relevant concentrations (0.03 μg/L and above). Exposures to AMI at higher concentrations accelerated the hatch rate and reduced locomotor activity, the latter of which was abolished after a 14 day period of depuration. The lack of any response on the features of physiology and behavior we measured at concentrations found in the environment would indicate that AMI poses a relatively low level of risk to fish populations. The pseudopersistence and likely presence of multiple drugs acting via the same mechanism of action, however, together with a global trend for increased prescription rates, mean that this risk may be underestimated using current ecotoxicological assessment paradigms.

Comorbidities and use of health services in people with diabetes mellitus according to risk levels by adjusted morbidity groups

BackgroundPeople with diabetes mellitus frequently have other comorbidities and involve greater use of primary and hospital care services. The aim of this study was to describe the comorbidities and use of primary and hospital care services of people with diabetes according to their risk level by adjusted morbidity groups (AMG) and to analyse the factors associated with the utilisation of these services.MethodsCross-sectional study. People with diabetes were identified within the population of patients with chronic conditions of an urban health care centre by the AMG stratification tool integrated into the primary health care electronic clinical record of the Community of Madrid. Sociodemographic, functional, clinical characteristics and annual health care services utilisation variables were collected. Univariate, bivariate and Poisson regression analyses were performed.ResultsA total of 1,063 people with diabetes were identified, representing 10.8% of patients with chronic conditions within the health centre. A total of 51.4% were female, the mean age was 70 years, 94.4% had multimorbidity. According to their risk level, 17.8% were high-risk, 40.6% were medium-risk and 41.6% were low-risk. The most prevalent comorbidities were hypertension (70%), dyslipidaemia (67%) and obesity (32.4%). Almost 50% were polymedicated. Regarding health services utilisation, 94% were users of primary care, and 59.3% were users of hospital care. Among the main factors associated with the utilisation of both primary and hospital care services were AMG risk level and complexity index. In primary care, utilisation was also associated with the need for primary caregivers, palliative care and comorbidities such as chronic heart failure and polymedication, while in hospital care, utilisation was also associated with comorbidities such as cancer, chronic obstructive pulmonary disease or depression.ConclusionsPeople with diabetes were older, with important needs for care, many associated comorbidities and polypharmacy that increased in parallel with the patient’s risk level and complexity. The utilisation of primary and hospital care services was very high, being more frequent in primary care. Health services utilization were principally associated with functional factors related to the need of care and with clinical factors such as AMG medium and high-risk level, more complexity index, some serious comorbidities and polymedication.

Cost and time risk factors in construction projects in the Dominican Republic

The building sector is very dynamic and complex, so construction works are surrounded by uncertainties. The deficiencies of this sector are mainly related to poor project planning and management, resulting in losses because of missed deadlines, cost overruns, reworks, and unsatisfied clients. For a project to be successful, all the parties involved should work together to effectively manage the risks that could emerge in the project life cycle. This research defines and establishes a classification of the factors causing cost and time deviations in construction projects in the Dominican Republic. For this purpose, the most common factors are compiled, and their risk levels are determined by using the data obtained in a survey in which professionals from the building sector participated. The indexes marked by the participants show that the serious risk factors are design variations and the variations made by clients, a tight project schedule and the preparation of bid offers, deficiencies in the work planning and schedule, the lack of skilled labour, and work performance errors.

Do firms with environmental, social, and governance reputational risk take into account board gender diversity? An analysis on a global scale

AbstractObjectiveThis article studies whether a firm's environmental, social, and governance (ESG) reputational risk influences board gender diversity. Besides, we are also interested in the moderating role of gender equality and country development level toward the relationship between reputational risk and board gender diversity.MethodUsing a comprehensive sample of firms from 52 countries between 2007 and 2019, we employ multiple regression with fixed effects. Our findings remain robust when using alternative measures of variables and addressing endogeneity concerns by employing a two‐stage systems generalized method of moments estimation and an instrumental variable approach.ResultsCompanies with high levels of ESG reputational risk tend to add more women directors to resolve these problems. Furthermore, the empirical results point out that the positive impact of ESG reputational risk on board gender diversity is more pronounced for countries with a higher degree of gender equality or developed countries.ConclusionsOverall, our study is the first international study to link ESG reputational risk via media channels to board gender diversity.

Research on Coupling Effect Measurement and Coupling Risk Simulation of Green Building Construction Safety Risk Factors

The construction of green buildings is an important direction for the transformation and development of the construction industry, but it is beset with problems such as a lack of construction experience, immature new technologies, and unstable material properties; these issues bring risks to the construction stage of green buildings, and the coupling of uncertain risk factors in the construction process of green buildings may lead to unfavorable results. The purpose of this study is to explore the coupling degree of green building construction safety risk factors and the changing trend in their coupling combinations at the system risk level. First, the risk factor index system was defined by reading the literature and gathering expert opinions, and the coupling degree between risk factors was measured using an improved coupling degree model. Then, a system dynamics model was established to simulate and analyze the coupling effects among the risk factors and determine the combinations with the greatest influence. The results show that the risk probability is proportional to the risk coupling value, the human–environment coupling value is the largest, and the material equipment–management coupling value is the smallest. The human–environment system simulation shows that reducing the coupling value of system factors will promote a decrease in the total level of system risk. According to the research conclusions, measures to prevent risk coupling are proposed, which offer theoretical references for green building practitioners carrying out risk management; these measures hold a certain guiding significance for the risk control and future development of green buildings.

Risk of drug-induced angioedema: a pharmacovigilance study of FDA adverse event reporting system database

ObjectiveThe purpose of this study is to explore and analyze the FDA Adverse Event Reporting System (FAERS) database to identify drug adverse reaction signals associated with angioedema. The findings aim to provide valuable insights for clinical drug safety considerations.MethodsThe Open Vigil 2.1 data platform was utilized to collect adverse event reports related to angioedema from the first quarter of 2004 to the fourth quarter of 2023. The reporting odds ratio (ROR) and proportional reporting ratio (PRR) were employed as disproportionality measures to detect adverse reaction signals Sof drugs associated with angioedema.ResultsA total of 38,921 reports were retrieved, with the majority being reported by healthcare professionals. The analysis included predominantly adult patients (≥18 years of age), with slightly higher representation of females compared to males. Among the top 30 drugs associated with the occurrence of angioedema, 24 drugs showed positive signals in the risk analysis. Based on the individual drug reporting odds ratio (95% confidence interval) as a measure of risk signal strength, the top five drugs are as follows: lisinopril [ROR (95% CI): 46.43 (42.59–50.62)], enalapril [ROR (95% CI): 43.51 (39.88–47.46)], perindopril [ROR (95% CI): 31.17 (27.5–35.32)], alteplase [ROR (95% CI): 29.3 (26.95–31.85)], ramipril [ROR (95% CI): 20.93 (19.66–22.28)]. After categorizing the drugs, the strongest positive signal was observed in the antithrombotic agents [ROR (95% CI): 22.53 (21.16–23.99)], following that, cardiovascular drugs [ROR (95% CI): 9.17 (8.87–9.48)], antibiotics [ROR (95% CI): 6.42 (5.91–6.96)], immunosuppressors [ROR (95% CI): 5.95 (5.55–6.39)], anti-inflammatory analgesics [ROR (95% CI): 4.65 (4.45–4.86)], antiallergic drugs [ROR (95% CI): 4.47 (3.99–5)], antiasthmatics [ROR (95% CI): 2.49 (2.14–2.89)], blood sugar control drugs [ROR (95% CI): 1.65 (1.38–1.97)], and digestive system drugs [ROR (95% CI): 1.59 (1.45–1.74)] exhibited progressively decreasing ROR values.ConclusionMany medications are associated with a high risk of angioedema. These medications play a crucial and potentially preventable role in controlling the occurrence of angioedema. It is essential to consider the risk level of drug-induced angioedema in clinical practice to optimize medication therapy.

Understanding the Biomechanics of Musculoskeletal Injuries in High-Risk Environmental Conditions

The present study examines the biomechanics of musculoskeletal injuries in high-risk environmental conditions by thoroughly analyzing diverse data sources and employing various methodologies. This study utilizes motion analysis, force sensor measurements, computer simulations, and biomechanical testing to examine the various factors contributing to musculoskeletal injuries. The analysis of motion indicates that specific tests, namely varus test, impose considerably greater biomechanical stress, thereby emphasizing their susceptibility to causing injuries. The force sensor data reveals that pressure mapping system is responsible for exerting the highest force, raising concerns regarding its potential impact on the risk of injury. According to computer simulations, various injury risks are associated with different conditions, with load carriage exhibiting the highest risk. The analysis of joint stability during biomechanical testing reveals discrepancies in joint stability levels across different tasks. Outliers within the dataset highlight tasks that exhibit notable concerns regarding joint stability. Moreover, supplementary motion analysis data about various task variants, such as Sulcus sign and vasus stress test unveils distinct variations that lead to heightened levels of biomechanical stress. The discoveries mentioned above offer valuable perspectives on the biomechanical foundations of musculoskeletal injuries in environments with elevated risk levels. The aforementioned findings emphasize the necessity of implementing focused interventions, enhancing equipment design, and implementing heightened safety measures to reduce the risks of injury effectively. The present study establishes a fundamental basis for subsequent research endeavors and proposes approaches designed to safeguard the welfare of individuals operating in demanding contexts.

A STUDY OF INVESTOR’S ATTITUDE TOWARDS MUTUAL FUNDS AS AN INVESTMENT OPTION

Mutual fund as an investment avenue provides a platform to the investor who does not want to take high risk on their hard-earned investment. In India, mutual fund industry is growing rapidly and this industry has emerged as an important segment of the financial market of India, especially in channelizing and mobilizing the savings of millions of individuals into the investment in equity and debt instruments. Mutual fund investment is less risky than investing directly in stocks and is therefore a safer option for risk averse investors. A competent fund manager should analyse investor behaviour, perception, and attitude and understand their needs and expectations to gear up the performance to meet investor expectations and requirements. Also, the mutual fund industry today is one of the most preferred investment options of all over the world. It plays a crucial role in the economic development of a country. Mutual fund active involvement can be seen by their dominant presence in the money market as well as the capital market. They are also found very active in the stock market by way of ensuring stability as a supplier of large funds through steady absorption of floating stocks. Investors invest directly in individual securities or indirectly through a financial intermediary. Study intends to identify the usage of schemes and level of risk on the basis of their income level. The findings of the study indicate that the majority of the selected respondents have used open ended schemes with moderate risk.

A Dynamic Spatiotemporal Understanding of Changes in Social Vulnerability to Wildfires at Local Scale

Research on wildfires and social vulnerability has gained significant importance due to the increasing frequency and severity of wildfires around the world. This study investigates the dynamic changes in social vulnerability to wildfires over a decade in Idaho, USA, utilizing GIS-based tools and a quasi-experimental design. We assess the evolving nature of social vulnerability at a local scale, emphasizing both spatial and temporal dynamics. Initially, we identified social vulnerability trends in relation to varying levels of wildfire risk. The research then employs propensity score matching to contrast areas affected by wildfires in 2012 with similar non-affected regions, thereby quantifying the short-term shifts in social vulnerability post-wildfires. The results indicate that regions with a high wildfire risk may display elevated vulnerability, characterized by an increase in unemployment rates and a reduction in high-income households. These findings tentatively demonstrate the compounded effect of wildfires on already vulnerable populations, highlighting the critical need for targeted interventions. Ultimately, this study underscores the importance of integrating dynamic social vulnerability assessments into wildfire management and planning, aiming to enhance community resilience and equitable resource distribution in the face of escalating wildfire threats.

A new risk level identification model for aviation safety

The aviation safety reporting system (ASRS) data, which are accident investigation reports issued by the national transportation safety board (NTSB), are often used for aviation risk level identification modeling. However, ASRS data suffer from sample imbalance and inaccurate encoding of textual information. To address these issues, this paper proposes a novel risk identification model. Initially, the pre-trained sentence bidirectional encoder representations from transformers (SBERT) model is fine-tuned using the textual information in the ASRS data, improving the accuracy of the text encoding. Subsequently, a generative adversarial network (GAN) is employed to generate samples for underrepresented categories in the ASRS data, thereby addressing the sample imbalance problem. Finally, a bayesian optimization algorithm is integrated to automatically search for the hyperparameters of the risk identification model, further enhancing the model's performance in risk level identification. Experimental results demonstrate that not only does the SBERT fine-tuning substantially improve the accuracy of text information encoding, but both data augmentation and automatic hyperparameter search also significantly contribute to the performance improvement of the risk level recognition model.

Enhancing Environmental Sustainability: Risk Assessment and Management Strategies for Urban Light Pollution

Light pollution imposes significant and far-reaching adverse effects on human society, necessitating its stringent regulation. However, intervention policies could be customized to suit the unique characteristics of each region, taking into account local conditions. To address this challenge, we have developed a comprehensive light pollution risk assessment model using a combination of objective and subjective weighting methods, including analytic hierarchy process (AHP), independent weighting method (IWM), entropy weight method (EWM), coefficient of variation (CV), criteria importance through intercriteria correlation (CRITIC), and principal component analysis (PCA). This model facilitates a systematic evaluation of light pollution risk levels across diverse regions in China. Subsequently, we have proposed intervention policies targeting light pollution risk reduction and assessed their efficacy using the synthetic control method. Our findings reveal elevated light pollution risk levels in coastal and mountainous regions with heightened concentrations closer to urban centers. Strategies focused on enhancing lighting hardware, optimizing lighting schedules, and upgrading light sources demonstrated the impact on reducing light pollution risk levels (LPRL). This study not only lays a solid theoretical foundation for assessing urban light pollution risks but furnishes empirical evidence to aid relevant authorities in formulating effective light pollution control strategies.

Driving risk identification of urban arterial and collector roads based on multi-scale data

Urban arterial and collector roads, while interconnected within the urban transportation network, serve distinct purposes, leading to different driving risk profiles. Investigating these differences using advanced methods is of paramount significance. This study aims to achieve this by primarily collecting and processing relevant vehicle trajectory data alongside driver-vehicle–road-environment data. A comprehensive risk assessment matrix is constructed to assess driving risks, incorporating multiple conflict and traffic flow indicators with statistically temporal stability. The Entropy weight-TOPSIS method and the K-means algorithm are employed to determine the risk scores and levels of the target arterial and collector roads. Using risk levels as the outcome variables and multi-scale features as the explanatory variables, random parameters models with heterogeneity in means and variances are developed to identify the determinants of driving risks at different levels. Likelihood ratio tests and comparisons of out-of-sample and within-sample prediction are conducted. Results reveal significant statistical differences in the risk profiles between arterial and collector roads. The marginal effects of significant parameters are then calculated separately for arterial and collector roads, indicating that several factors have different impacts on the probability of risk levels for arterial and collector roads, such as the number of movable elements in road landscape pictures, the standard deviation of the vehicle’s lateral acceleration, the average standard deviation of speed for all vehicles on the road segment, and the number of one-way lanes on the road segment. Some practical implications are provided based on the findings. Future research can be implemented by expanding the collected data to different regions and cities over longer periods.

Evaluation of the impact of bundled nursing strategies on the prevention of venous thromboembolism in patients with cerebral hemorrhage.

To investigate the effectiveness and value of bundled nursing strategies for venous thromboembolism prevention in nonsurgical patients with cerebral hemorrhage, 200 patients who underwent treatment for cerebral hemorrhage in our hospital from January 2023 to July 2023 were chosen as the study subjects. Patients were divided into control group and experimental group according to different treatment methods. For patients in the control group, regular care was used, while for patients in the observation group, bundled care was used for intervention. This study used a venous thromboembolism risk factor assessment form to assess the probability of patients suffering from venous thromboembolism. It used the incidence of venous thromboembolism, disease cognition level, coagulation function, fibrinolysis, changes in blood routine, exercise ability, improvement in quality of life, and patient satisfaction with nursing mode as detection indicators to obtain the changes in various indicator values and patient satisfaction scores under different nursing interventions. Prior to nursing intervention, the significant statistical differences did not exist (P > .05) between the control group and the observation group in terms of general information, number of venous thromboembolism risk levels, degree of disease cognition, coagulation function, blood routine, exercise ability, quality of life, and fibrinolysis indicators. After a period of nursing intervention, the significant statistical difference existed (P < .05) between the control group and the observation group in terms of general information, number of venous thromboembolism risk levels, degree of disease cognition, coagulation function, blood routine, exercise ability, quality of life, and fibrinolysis indicators. In the patient satisfaction score, the satisfaction scores of male and female patients with general care were 0.865 and 0.878, respectively, and the satisfaction scores for bundled care were 0.942 and 0.965, respectively. In conclusion, bundled care can better improve the coagulation status and blood routine indexes of nonsurgical patients with cerebral hemorrhage compared with ordinary care, thus contributing to better prevention of venous thromboembolism in nonsurgical patients with cerebral hemorrhage.

Seismic Risk Assessment and Analysis of Influencing Factors in the Sichuan–Yunnan Region

Investigating the distribution characteristics of earthquake disaster risks in the Sichuan–Yunnan region is of great importance for enhancing government emergency response capabilities and achieving sustainable regional development. This study, based on disaster systems theory, constructs a seismic risk evaluation index system for the Sichuan–Yunnan region and employs the entropy method to determine the comprehensive risk index for earthquake disasters across 37 prefecture-level cities. The findings reveal the following: (1) High-risk areas for disaster-causing factors are located in the Hengduan Mountain region and the North–South Mountain Range Valley Region; medium-risk areas are distributed along the northwestern edge of the Sichuan Basin; low-risk areas are situated in the eastern part of the Sichuan Basin and the Yunnan Plateau. (2) High-risk disaster-prone environments are found in the Hengduan Mountain region; medium-risk areas are present on the Yunnan Plateau and the western part of the North–South Mountain Range Valley Region; low-risk areas are in the Sichuan Basin. (3) High-vulnerability areas include the central Sichuan Basin and Kunming on the Yunnan Plateau; medium-vulnerability areas are located in the eastern and western parts of the Sichuan Basin; low-vulnerability areas are in the less developed parts of the Yunnan Plateau, the North–South Mountain Range Valley Region, and the Hengduan Mountain region. (4) High-risk seismic disaster areas are concentrated in the developed regions of the Sichuan Basin and the Yunnan Plateau; medium-risk areas are concentrated in the western part of the North–South Mountain Range Valley Region; low-risk areas are sporadically distributed in the eastern parts of the Sichuan–Yunnan region. (5) The vulnerability of the population, economy, and lifeline systems significantly explain the variation in seismic risk levels, all exceeding 0.70; the synergistic effects of disaster-causing factor danger, disaster-prone environment stability, and disaster-prone environment sensitivity are the most pronounced, with explanatory power exceeding 0.85 after factor interaction.

Health-related quality of life among pediatric patients with acute lymphoblastic leukemia: An exploratory cross-sectional study.

Improved survival rates broadened the pediatric oncology focus to include health-related quality of life (HRQoL). This cross-sectional study aimed to examine HRQoL by treatment phase and disease risk level in pediatric patients with B-cell acute lymphoblastic leukemia (B-ALL), including those in early survivorship. A subset of data from a larger prospective cohort study was analyzed. Data were collected from 73 patients (73 parent reports and 28 self-reports). Parent proxy and self-report PROMIS measures assessed HRQoL across treatment phases (early intensive, maintenance, and off treatment) and disease risk groups (standard vs high). Analyses assessed the relationship between parent proxy and patient self-reports and the differences in HRQoL among treatment phases and risk groups. Parent proxy reports generally indicated worse fatigue, pain interference, and mobility compared with patient self-reports. Self-reports in the early intensive treatment group suggested worse depressive symptoms, fatigue, mobility, and upper extremity function compared with those in later phases. Parent proxy reports showed worse fatigue and depressive symptoms in early intensive treatment group relative to those in later phases. Patient self-reports in the maintenance group demonstrated the best peer relationships scores. Parent proxy reports in the high-risk group reported significantly higher depressive symptoms and fatigue compared with the standard-risk group. Differences in HRQoL suggest targets for further assessment and intervention. The early treatment and immediate post-survivorship periods may represent particularly critical time points. Longitudinal studies with larger and diverse samples should further explore HRQoL trajectories in this population.

Prediction of maternal health risk levels based on multiple machine learning algorithms

Prediction of maternal health risk levels based on multiple machine learning algorithms

A new two-stage emergency material distribution framework for urban rainstorm and flood disasters to promote the SDGs

Under the coupled effects of climate change and urbanization, urban rainstorm and flood has become more frequent and intense. The effect of the flood disasters emergency response has a direct impact on the success or failure of the rescue. Emergency material distribution is one of the most critical steps in the emergency response phase and is crucial to achieve the Sustainable Development Goals (SDGs). This study proposes a two-stage emergency material distribution framework for urban rainstorm and flood disasters. The entropy weight method and technique for order preference by similarity to ideal solution (EWM-TOPSIS) was adopted to incorporate the difference in relief-demand urgency into the emergency material distribution principle. The mathematical model was established by minimizing emergency travel time, inequity and social costs (logistic costs and deprivation costs) as objective functions. The gamultiobj algorithm was used to solve the model. The proposed framework is further applied in Xi'an city of China. The results showed that the affected sites were categorized into disaster risk levels I, II and III. The Pareto solution set was obtained by optimizing each conflicting objective. The emergency material distribution plan was selected from the Pareto solution set based on the actual situation. In the plan, the flood disasters emergency travel time totaled 6.48 h, the inequity totaled 3.69, and the total social costs reached 226,584 CNY. The proposed framework is more consistent with the needs of the actual rescue by comparing the four models generated plans. Decision-makers should not only consider minimizing dispatch time and social costs, but also the trade-off between equity and prioritization of distribution. This study helps to provide new ideas for sustainable urban development and emergency management. Urban rainstorm and flood disasters change with the changing environment dynamically, and it is difficult to collect dynamic disaster information on the affected sites. Thus our further study will focus on improving the prediction accuracy of dynamic urban rainstorm and flood disasters.

Promoting risky play: Insights from the Outside Play Lab

Promoting risky play: Insights from the Outside Play Lab Mariana Brussoni, founder of the Outside Play Lab at The University of British Columbia, is a pioneer in promoting the benefits of risky play for children. Her research emphasizes the importance of allowing children to engage in outdoor activities that involve a certain level of risk, arguing that this type of play is crucial for their overall development. In this exclusive interview, Mariana Brussoni from the Outside Play Lab shares her insights on risky play and childhood development. Mariana Brussoni shared her journey from being a developmental psychologist to focusing on injury prevention. Her transition was driven by the need to address children’s safety comprehensively. She explained, “In public health and injury prevention, it’s very typical that they use a very siloed approach thinking only about preventing injuries. Whereas as a developmental psychologist, I think about the child as a whole and what they need to thrive.” The Outside Play Lab seeks to strike a balance between safety and the developmental needs of children, promoting a holistic approach to injury prevention.