Birmingham City University

Importance Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. Objective To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. Evidence Review We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. Findings In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572 000 deaths and 15.2 million DALYs), and stomach cancer (542 000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819 000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601 000 deaths and 17.4 million DALYs), TBL cancer (596 000 deaths and 12.6 million DALYs), and colorectal cancer (414 000 deaths and 8.3 million DALYs). Conclusions and Relevance The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care.

BACKGROUND: Explainability is one of the most heavily debated topics when it comes to the application of artificial intelligence (AI) in healthcare. Even though AI-driven systems have been shown to outperform humans in certain analytical tasks, the lack of explainability continues to spark criticism. Yet, explainability is not a purely technological issue, instead it invokes a host of medical, legal, ethical, and societal questions that require thorough exploration. This paper provides a comprehensive assessment of the role of explainability in medical AI and makes an ethical evaluation of what explainability means for the adoption of AI-driven tools into clinical practice. METHODS: Taking AI-based clinical decision support systems as a case in point, we adopted a multidisciplinary approach to analyze the relevance of explainability for medical AI from the technological, legal, medical, and patient perspectives. Drawing on the findings of this conceptual analysis, we then conducted an ethical assessment using the "Principles of Biomedical Ethics" by Beauchamp and Childress (autonomy, beneficence, nonmaleficence, and justice) as an analytical framework to determine the need for explainability in medical AI. RESULTS: Each of the domains highlights a different set of core considerations and values that are relevant for understanding the role of explainability in clinical practice. From the technological point of view, explainability has to be considered both in terms how it can be achieved and what is beneficial from a development perspective. When looking at the legal perspective we identified informed consent, certification and approval as medical devices, and liability as core touchpoints for explainability. Both the medical and patient perspectives emphasize the importance of considering the interplay between human actors and medical AI. We conclude that omitting explainability in clinical decision support systems poses a threat to core ethical values in medicine and may have detrimental consequences for individual and public health. CONCLUSIONS: To ensure that medical AI lives up to its promises, there is a need to sensitize developers, healthcare professionals, and legislators to the challenges and limitations of opaque algorithms in medical AI and to foster multidisciplinary collaboration moving forward.

IMPORTANCE: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). FINDINGS: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCE: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

In recent years focus-group interviews, as a means of qualitative data collection, have gained popularity amongst professionals within the health and social care arena. Despite this popularity, analysing qualitative data, particularly focus-group interviews, poses a challenge to most practitioner researchers. The present paper responds to the needs expressed by public health nutritionists, community dietitians and health development specialists following two training sessions organised collaboratively by the Health Development Agency, the Nutrition Society and the British Dietetic Association in 2003. The focus of the present paper is on the concepts and application of framework analysis, especially the use of Krueger's framework. It provides some practical steps for the analysis of individual data, as well as focus-group data using examples from the author's own research, in such a way as to assist the newcomer to qualitative research to engage with the methodology. Thus, it complements the papers by Draper (2004) and Fade (2004) that discuss in detail the complementary role of qualitative data in researching human behaviours, feelings and attitudes. Draper (2004) has provided theoretical and philosophical bases for qualitative data analysis. Fade (2004) has described interpretative phenomenology analysis as a method of analysing individual interview data. The present paper, using framework analysis concentrating on focus-group interviews, provides another approach to qualitative data analysis.

Importance: The increasing burden due to cancer and other noncommunicable diseases poses a threat to human development, which has resulted in global political commitments reflected in the Sustainable Development Goals as well as the World Health Organization (WHO) Global Action Plan on Non-Communicable Diseases. To determine if these commitments have resulted in improved cancer control, quantitative assessments of the cancer burden are required. Objective: To assess the burden for 29 cancer groups over time to provide a framework for policy discussion, resource allocation, and research focus. Evidence Review: Cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs) were evaluated for 195 countries and territories by age and sex using the Global Burden of Disease study estimation methods. Levels and trends were analyzed over time, as well as by the Sociodemographic Index (SDI). Changes in incident cases were categorized by changes due to epidemiological vs demographic transition. Findings: In 2016, there were 17.2 million cancer cases worldwide and 8.9 million deaths. Cancer cases increased by 28% between 2006 and 2016. The smallest increase was seen in high SDI countries. Globally, population aging contributed 17%; population growth, 12%; and changes in age-specific rates, -1% to this change. The most common incident cancer globally for men was prostate cancer (1.4 million cases). The leading cause of cancer deaths and DALYs was tracheal, bronchus, and lung cancer (1.2 million deaths and 25.4 million DALYs). For women, the most common incident cancer and the leading cause of cancer deaths and DALYs was breast cancer (1.7 million incident cases, 535 000 deaths, and 14.9 million DALYs). In 2016, cancer caused 213.2 million DALYs globally for both sexes combined. Between 2006 and 2016, the average annual age-standardized incidence rates for all cancers combined increased in 130 of 195 countries or territories, and the average annual age-standardized death rates decreased within that timeframe in 143 of 195 countries or territories. Conclusions and Relevance: Large disparities exist between countries in cancer incidence, deaths, and associated disability. Scaling up cancer prevention and ensuring universal access to cancer care are required for health equity and to fulfill the global commitments for noncommunicable disease and cancer control.

This paper addresses the nature of the concept of quality in relation to higher education. It analyses ways of thinking about quality, considers their relevance to higher education, explores their interrelationships and examines their philosophical and political underpinnings. The relative nature of quality is examined. First, quality means different things to different people. Second, quality is relative to ‘processes’ or ‘outcomes’. The widely differing conceptualisations of quality are grouped into five discrete but interrelated categories. Quality can be viewed as exception, as perfection, as fitness for purpose, as value for money and as transformative. Determining criteria for assessing quality in higher education requires an understanding of different conceptions of quality that inform the preferences of stakeholders.

Abstract Chest X-ray is the first imaging technique that plays an important role in the diagnosis of COVID-19 disease. Due to the high availability of large-scale annotated image datasets, great success has been achieved using convolutional neural networks ( CNN s) for image recognition and classification. However, due to the limited availability of annotated medical images, the classification of medical images remains the biggest challenge in medical diagnosis. Thanks to transfer learning, an effective mechanism that can provide a promising solution by transferring knowledge from generic object recognition tasks to domain-specific tasks. In this paper, we validate and a deep CNN , called Decompose, Transfer, and Compose ( DeTraC ), for the classification of COVID-19 chest X-ray images. DeTraC can deal with any irregularities in the image dataset by investigating its class boundaries using a class decomposition mechanism. The experimental results showed the capability of DeTraC in the detection of COVID-19 cases from a comprehensive image dataset collected from several hospitals around the world. High accuracy of 93.1% (with a sensitivity of 100%) was achieved by DeTraC in the detection of COVID-19 X-ray images from normal, and severe acute respiratory syndrome cases.

Imitation learning techniques aim to mimic human behavior in a given task. An agent (a learning machine) is trained to perform a task from demonstrations by learning a mapping between observations and actions. The idea of teaching by imitation has been around for many years; however, the field is gaining attention recently due to advances in computing and sensing as well as rising demand for intelligent applications. The paradigm of learning by imitation is gaining popularity because it facilitates teaching complex tasks with minimal expert knowledge of the tasks. Generic imitation learning methods could potentially reduce the problem of teaching a task to that of providing demonstrations, without the need for explicit programming or designing reward functions specific to the task. Modern sensors are able to collect and transmit high volumes of data rapidly, and processors with high computational power allow fast processing that maps the sensory data to actions in a timely manner. This opens the door for many potential AI applications that require real-time perception and reaction such as humanoid robots, self-driving vehicles, human computer interaction, and computer games, to name a few. However, specialized algorithms are needed to effectively and robustly learn models as learning by imitation poses its own set of challenges. In this article, we survey imitation learning methods and present design options in different steps of the learning process. We introduce a background and motivation for the field as well as highlight challenges specific to the imitation problem. Methods for designing and evaluating imitation learning tasks are categorized and reviewed. Special attention is given to learning methods in robotics and games as these domains are the most popular in the literature and provide a wide array of problems and methodologies. We extensively discuss combining imitation learning approaches using different sources and methods, as well as incorporating other motion learning methods to enhance imitation. We also discuss the potential impact on industry, present major applications, and highlight current and future research directions.

BACKGROUND: For more than three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has provided a framework to quantify health loss due to diseases, injuries, and associated risk factors. This paper presents GBD 2023 findings on disease and injury burden and risk-attributable health loss, offering a global audit of the state of world health to inform public health priorities. This work captures the evolving landscape of health metrics across age groups, sexes, and locations, while reflecting on the remaining post-COVID-19 challenges to achieving our collective global health ambitions. METHODS: The GBD 2023 combined analysis estimated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 375 diseases and injuries, and risk-attributable burden associated with 88 modifiable risk factors. Of the more than 310 000 total data sources used for all GBD 2023 (about 30% of which were new to this estimation round), more than 120 000 sources were used for estimation of disease and injury burden and 59 000 for risk factor estimation, and included vital registration systems, surveys, disease registries, and published scientific literature. Data were analysed using previously established modelling approaches, such as disease modelling meta-regression version 2.1 (DisMod-MR 2.1) and comparative risk assessment methods. Diseases and injuries were categorised into four levels on the basis of the established GBD cause hierarchy, as were risk factors using the GBD risk hierarchy. Estimates stratified by age, sex, location, and year from 1990 to 2023 were focused on disease-specific time trends over the 2010-23 period and presented as counts (to three significant figures) and age-standardised rates per 100 000 person-years (to one decimal place). For each measure, 95% uncertainty intervals [UIs] were calculated with the 2·5th and 97·5th percentile ordered values from a 250-draw distribution. FINDINGS: Total numbers of global DALYs grew 6·1% (95% UI 4·0-8·1), from 2·64 billion (2·46-2·86) in 2010 to 2·80 billion (2·57-3·08) in 2023, but age-standardised DALY rates, which account for population growth and ageing, decreased by 12·6% (11·0-14·1), revealing large long-term health improvements. Non-communicable diseases (NCDs) contributed 1·45 billion (1·31-1·61) global DALYs in 2010, increasing to 1·80 billion (1·63-2·03) in 2023, alongside a concurrent 4·1% (1·9-6·3) reduction in age-standardised rates. Based on DALY counts, the leading level 3 NCDs in 2023 were ischaemic heart disease (193 million [176-209] DALYs), stroke (157 million [141-172]), and diabetes (90·2 million [75·2-107]), with the largest increases in age-standardised rates since 2010 occurring for anxiety disorders (62·8% [34·0-107·5]), depressive disorders (26·3% [11·6-42·9]), and diabetes (14·9% [7·5-25·6]). Remarkable health gains were made for communicable, maternal, neonatal, and nutritional (CMNN) diseases, with DALYs falling from 874 million (837-917) in 2010 to 681 million (642-736) in 2023, and a 25·8% (22·6-28·7) reduction in age-standardised DALY rates. During the COVID-19 pandemic, DALYs due to CMNN diseases rose but returned to pre-pandemic levels by 2023. From 2010 to 2023, decreases in age-standardised rates for CMNN diseases were led by rate decreases of 49·1% (32·7-61·0) for diarrhoeal diseases, 42·9% (38·0-48·0) for HIV/AIDS, and 42·2% (23·6-56·6) for tuberculosis. Neonatal disorders and lower respiratory infections remained the leading level 3 CMNN causes globally in 2023, although both showed notable rate decreases from 2010, declining by 16·5% (10·6-22·0) and 24·8% (7·4-36·7), respectively. Injury-related age-standardised DALY rates decreased by 15·6% (10·7-19·8) over the same period. Differences in burden due to NCDs, CMNN diseases, and injuries persisted across age, sex, time, and location. Based on our risk analysis, nearly 50% (1·27 billion [1·18-1·38]) of the roughly 2·80 billion total global DALYs in 2023 were attributable to the 88 risk factors analysed in GBD. Globally, the five level 3 risk factors contributing the highest proportion of risk-attributable DALYs were high systolic blood pressure (SBP), particulate matter pollution, high fasting plasma glucose (FPG), smoking, and low birthweight and short gestation-with high SBP accounting for 8·4% (6·9-10·0) of total DALYs. Of the three overarching level 1 GBD risk factor categories-behavioural, metabolic, and environmental and occupational-risk-attributable DALYs rose between 2010 and 2023 only for metabolic risks, increasing by 30·7% (24·8-37·3); however, age-standardised DALY rates attributable to metabolic risks decreased by 6·7% (2·0-11·0) over the same period. For all but three of the 25 leading level 3 risk factors, age-standardised rates dropped between 2010 and 2023-eg, declining by 54·4% (38·7-65·3) for unsafe sanitation, 50·5% (33·3-63·1) for unsafe water source, and 45·2% (25·6-72·0) for no access to handwashing facility, and by 44·9% (37·3-53·5) for child growth failure. The three leading level 3 risk factors for which age-standardised attributable DALY rates rose were high BMI (10·5% [0·1 to 20·9]), drug use (8·4% [2·6 to 15·3]), and high FPG (6·2% [-2·7 to 15·6]; non-significant). INTERPRETATION: Our findings underscore the complex and dynamic nature of global health challenges. Since 2010, there have been large decreases in burden due to CMNN diseases and many environmental and behavioural risk factors, juxtaposed with sizeable increases in DALYs attributable to metabolic risk factors and NCDs in growing and ageing populations. This long-observed consequence of the global epidemiological transition was only temporarily interrupted by the COVID-19 pandemic. The substantially decreasing CMNN disease burden, despite the 2008 global financial crisis and pandemic-related disruptions, is one of the greatest collective public health successes known. However, these achievements are at risk of being reversed due to major cuts to development assistance for health globally, the effects of which will hit low-income countries with high burden the hardest. Without sustained investment in evidence-based interventions and policies, progress could stall or reverse, leading to widespread human costs and geopolitical instability. Moreover, the rising NCD burden necessitates intensified efforts to mitigate exposure to leading risk factors-eg, air pollution, smoking, and metabolic risks, such as high SBP, BMI, and FPG-including policies that promote food security, healthier diets, physical activity, and equitable and expanded access to potential treatments, such as GLP-1 receptor agonists. Decisive, coordinated action is needed to address long-standing yet growing health challenges, including depressive and anxiety disorders. Yet this can be only part of the solution. Our response to the NCD syndemic-the complex interaction of multiple health risks, social determinants, and systemic challenges-will define the future landscape of global health. To ensure human wellbeing, economic stability, and social equity, global action to sustain and advance health gains must prioritise reducing disparities by addressing socioeconomic and demographic determinants, ensuring equitable health-care access, tackling malnutrition, strengthening health systems, and improving vaccination coverage. We live in times of great opportunity. FUNDING: Gates Foundation and Bloomberg Philanthropies.

Abstract This article differentiates between descriptive and explanatory factors to develop a typology and a theory of stakeholder and public engagement. The typology describes different types of public and stakeholder engagement, and the theory comprises four factors that explain much of the variation in outcomes (for the natural environment and/or for participants) between different types of engagement. First, we use a narrative literature search to develop a new typology of stakeholder and public engagement based on agency (who initiates and leads engagement) and mode of engagement (from communication to coproduction). We then propose a theory to explain the variation in outcomes from different types of engagement: (1) a number of socioeconomic, cultural, and institutional contextual factors influence the outcomes of engagement; (2) there are a number of process design factors that can increase the likelihood that engagement leads to desired outcomes, across a wide range of sociocultural, political, economic, and biophysical contexts; (3) the effectiveness of engagement is significantly influenced by power dynamics, the values of participants, and their epistemologies, that is, the way they construct knowledge and which types of knowledge they consider valid; and (4) engagement processes work differently and can lead to different outcomes when they operate over different spatial and temporal scales. We use the theoretical framework to provide practical guidance for those designing engagement processes, arguing that a theoretically informed approach to stakeholder and public engagement has the potential to markedly improve the outcomes of environmental decision‐making processes.

The analytic hierarchy process (AHP) has gained increasing attention in construction management (CM) domain as a technique to analyse complex situations and make sound decisions. However, AHP per se or its potential applications on CM problems are ill-defined within extant literature. The present paper reviews 77 AHP-based papers published in eight selected peer-reviewed CM journals from 2004 to 2014 to better define and delineate AHP application areas and decision-making problems solved within CM. The findings indicated that risk management and sustainable construction were the most popular AHP application areas in CM. It was also revealed that AHP (1) is flexible and can be used as a stand-alone tool or in conjunction with other tools to resolve construction decision-making problems; and (2) is widely used in Asia. In addition, the most prominent justifications for using AHP were found to be small sample size, high level of consistency, simplicity and availability of user-friendly software. This paper provides a useful reference for researchers and practitioners interested in the application of AHP in CM. Future research is needed to compare and contrast between AHP and other multicriteria decision-making methods; such work could reveal which techniques provide optimized solutions under various decision-making scenarios.

BACKGROUND Endometriosis is a chronic condition affecting between 2 and 17% of women of reproductive age. Common symptoms are chronic pelvic pain, fatigue, congestive dysmenorrhoea, heavy menstrual bleeding and deep dyspareunia. Studies have demonstrated the considerable negative impact of this condition on women's quality of life (QoL), especially in the domains of pain and psychosocial functioning. The impact of endometriosis is likely to be exacerbated by the absence of an obvious cause and the likelihood of chronic, recurring symptoms. The aims of this paper are to review the current body of knowledge on the social and psychological impact of endometriosis on women's lives; to provide insights into women's experience of endometriosis; to provide a critical commentary on the current state of knowledge and to make recommendations for future psycho-social research. METHODS The review draws on a method of critical narrative synthesis to discuss a heterogeneous range of both quantitative and qualitative studies from several disciplines. This included a systematic search, a structured process for selecting and collecting data and a systematic thematic analysis of results. RESULTS A total of 42 papers were included in the review; 23 used quantitative methods, 16 used qualitative methods and 3 were mixed methods studies. The majority of papers came from just four countries: UK (10), Australia (8), Brazil (6) and the USA (5). Key categories of impact identified in the thematic analysis were diagnostic delay and uncertainty; 'QoL' and everyday activities; intimate relationships; planning for and having children; education and work; mental health and emotional wellbeing and medical management and self-management. CONCLUSIONS Endometriosis has a significant social and psychological impact on the lives of women across several domains. Many studies have methodological limitations and there are significant gaps in the literature especially in relation to a consideration of the impact on partners and children. We recommend additional prospective and longitudinal research utilizing mixed methods approaches and endometriosis-specific instruments to explore the impact of endometriosis in more diverse populations and settings. Furthermore, there is an urgent need to develop and evaluate interventions for supporting women and partners living with this chronic and often debilitating condition.

The upcoming fifth generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated artificial intelligence (AI) operations. However, fully intelligent network orchestration and management for providing innovative services will only be realized in Beyond 5G (B5G) networks. To this end, we envisage that the sixth generation (6G) of wireless networks will be driven by on-demand self-reconfiguration to ensure a many-fold increase in the network performance and service types. The increasingly stringent performance requirements of emerging networks may finally trigger the deployment of some interesting new technologies, such as large intelligent surfaces, electromagnetic-orbital angular momentum, visible light communications, and cell-free communications, to name a few. Our vision for 6G is a massively connected complex network capable of rapidly responding to the users' service calls through real-time learning of the network state as described by the network edge (e.g., base-station locations and cache contents), air interface (e.g., radio spectrum and propagation channel), and the user-side (e.g., battery-life and locations). The multi-state, multi-dimensional nature of the network state, requiring the real-time knowledge, can be viewed as a quantum uncertainty problem. In this regard, the emerging paradigms of machine learning (ML), quantum computing (QC), and quantum ML (QML) and their synergies with communication networks can be considered as core 6G enablers. Considering these potentials, starting with the 5G target services and enabling technologies, we provide a comprehensive review of the related state of the art in the domains of ML (including deep learning), QC, and QML and identify their potential benefits, issues, and use cases for their applications in the B5G networks. Subsequently, we propose a novel QC-assisted and QML-based framework for 6G communication networks while articulating its challenges and potential enabling technologies at the network infrastructure, network edge, air interface, and user end. Finally, some promising future research directions for the quantum- and QML-assisted B5G networks are identified and discussed.

Older people and COVID-19: Isolation, risk and ageismInternationally, health authorities and governments are warning older people that they are at a higher risk of more serious and possible fatal illness associated with COVID-19.Mortality data from Oxford COVID-19 Evidence Service (25/3/20) indicate a risk of mortality of 3.6% for people in their 60s, which increases to 8.0% and 14.8% for people in their 70s and over 80s.Therefore, the global recommendation for older populations includes social isolation, which involves staying at home and avoiding contact with other people, possibly for an extended period of time, currently estimated to be between three and four months.Older populations in this current O RCI D

Social valuation of ecosystem services and public policy alternatives is one of the greatest challenges facing ecological economists today. Frameworks for valuing nature increasingly include shared/social values as a distinct category of values. However, the nature of shared/social values, as well as their relationship to other values, has not yet been clearly established and empirical evidence about the importance of shared/social values for valuation of ecosystem services is lacking. To help address these theoretical and empirical limitations, this paper outlines a framework of shared/social values across five dimensions: value concept, provider, intention, scale, and elicitation process. Along these dimensions we identify seven main, non-mutually exclusive types of shared values: transcendental, cultural/societal, communal, group, deliberated and other-regarding values, and value to society. Using a case study of a recent controversial policy on forest ownership in England, we conceptualise the dynamic interplay between shared/social and individual values. The way in which social value is assessed in neoclassical economics is discussed and critiqued, followed by consideration of the relation between shared/social values and Total Economic Value, and a review of deliberative and non-monetary methods for assessing shared/social values. We conclude with a discussion of the importance of shared/social values for decision-making.

BACKGROUND: Timely and comprehensive analyses of causes of death stratified by age, sex, and location are essential for shaping effective health policies aimed at reducing global mortality. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides cause-specific mortality estimates measured in counts, rates, and years of life lost (YLLs). GBD 2023 aimed to enhance our understanding of the relationship between age and cause of death by quantifying the probability of dying before age 70 years (70q0) and the mean age at death by cause and sex. This study enables comparisons of the impact of causes of death over time, offering a deeper understanding of how these causes affect global populations. METHODS: GBD 2023 produced estimates for 292 causes of death disaggregated by age-sex-location-year in 204 countries and territories and 660 subnational locations for each year from 1990 until 2023. We used a modelling tool developed for GBD, the Cause of Death Ensemble model (CODEm), to estimate cause-specific death rates for most causes. We computed YLLs as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. Probability of death was calculated as the chance of dying from a given cause in a specific age period, for a specific population. Mean age at death was calculated by first assigning the midpoint age of each age group for every death, followed by computing the mean of all midpoint ages across all deaths attributed to a given cause. We used GBD death estimates to calculate the observed mean age at death and to model the expected mean age across causes, sexes, years, and locations. The expected mean age reflects the expected mean age at death for individuals within a population, based on global mortality rates and the population's age structure. Comparatively, the observed mean age represents the actual mean age at death, influenced by all factors unique to a location-specific population, including its age structure. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 250-draw distribution for each metric. Findings are reported as counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2023 include a correction for the misclassification of deaths due to COVID-19, updates to the method used to estimate COVID-19, and updates to the CODEm modelling framework. This analysis used 55 761 data sources, including vital registration and verbal autopsy data as well as data from surveys, censuses, surveillance systems, and cancer registries, among others. For GBD 2023, there were 312 new country-years of vital registration cause-of-death data, 3 country-years of surveillance data, 51 country-years of verbal autopsy data, and 144 country-years of other data types that were added to those used in previous GBD rounds. FINDINGS: The initial years of the COVID-19 pandemic caused shifts in long-standing rankings of the leading causes of global deaths: it ranked as the number one age-standardised cause of death at Level 3 of the GBD cause classification hierarchy in 2021. By 2023, COVID-19 dropped to the 20th place among the leading global causes, returning the rankings of the leading two causes to those typical across the time series (ie, ischaemic heart disease and stroke). While ischaemic heart disease and stroke persist as leading causes of death, there has been progress in reducing their age-standardised mortality rates globally. Four other leading causes have also shown large declines in global age-standardised mortality rates across the study period: diarrhoeal diseases, tuberculosis, stomach cancer, and measles. Other causes of death showed disparate patterns between sexes, notably for deaths from conflict and terrorism in some locations. A large reduction in age-standardised rates of YLLs occurred for neonatal disorders. Despite this, neonatal disorders remained the leading cause of global YLLs over the period studied, except in 2021, when COVID-19 was temporarily the leading cause. Compared to 1990, there has been a considerable reduction in total YLLs in many vaccine-preventable diseases, most notably diphtheria, pertussis, tetanus, and measles. In addition, this study quantified the mean age at death for all-cause mortality and cause-specific mortality and found noticeable variation by sex and location. The global all-cause mean age at death increased from 46·8 years (95% UI 46·6-47·0) in 1990 to 63·4 years (63·1-63·7) in 2023. For males, mean age increased from 45·4 years (45·1-45·7) to 61·2 years (60·7-61·6), and for females it increased from 48·5 years (48·1-48·8) to 65·9 years (65·5-66·3), from 1990 to 2023. The highest all-cause mean age at death in 2023 was found in the high-income super-region, where the mean age for females reached 80·9 years (80·9-81·0) and for males 74·8 years (74·8-74·9). By comparison, the lowest all-cause mean age at death occurred in sub-Saharan Africa, where it was 38·0 years (37·5-38·4) for females and 35·6 years (35·2-35·9) for males in 2023. Lastly, our study found that all-cause 70q0 decreased across each GBD super-region and region from 2000 to 2023, although with large variability between them. For females, we found that 70q0 notably increased from drug use disorders and conflict and terrorism. Leading causes that increased 70q0 for males also included drug use disorders, as well as diabetes. In sub-Saharan Africa, there was an increase in 70q0 for many non-communicable diseases (NCDs). Additionally, the mean age at death from NCDs was lower than the expected mean age at death for this super-region. By comparison, there was an increase in 70q0 for drug use disorders in the high-income super-region, which also had an observed mean age at death lower than the expected value. INTERPRETATION: We examined global mortality patterns over the past three decades, highlighting-with enhanced estimation methods-the impacts of major events such as the COVID-19 pandemic, in addition to broader trends such as increasing NCDs in low-income regions that reflect ongoing shifts in the global epidemiological transition. This study also delves into premature mortality patterns, exploring the interplay between age and causes of death and deepening our understanding of where targeted resources could be applied to further reduce preventable sources of mortality. We provide essential insights into global and regional health disparities, identifying locations in need of targeted interventions to address both communicable and non-communicable diseases. There is an ever-present need for strengthened health-care systems that are resilient to future pandemics and the shifting burden of disease, particularly among ageing populations in regions with high mortality rates. Robust estimates of causes of death are increasingly essential to inform health priorities and guide efforts toward achieving global health equity. The need for global collaboration to reduce preventable mortality is more important than ever, as shifting burdens of disease are affecting all nations, albeit at different paces and scales. FUNDING: Gates Foundation.

Negotiating the Past: The making of memory In South Africa Get access Negotiating the Past: The making of memory In South Africa, edited by Sarah Nuttall and Carli Coetzee. Cape Town: Oxford University Press Southern Africa, 1998. xii+300pp. £14.99 paperback. ISBN 0-19-571503-9. DOMINIC HEAD DOMINIC HEAD University of Central England Search for other works by this author on: Oxford Academic Google Scholar African Affairs, Volume 98, Issue 391, April 1999, Pages 277–278, https://doi.org/10.1093/oxfordjournals.afraf.a008028 Published: 01 April 1999

In the 2000s, online games became popular, while studies of Internet gaming addiction emerged, outlining the negative consequences of excessive gaming, its prevalence, and associated risk factors. The establishment of specialized treatment centers in South-East Asia, the US, and Europe reflects the growing need for professional help. It is argued that only by understanding the appeal of Internet gaming, its context, and neurobiologic correlates can the phenomenon of Internet gaming addiction be understood comprehensively. The aim of this review is to provide an insight into current perspectives on Internet gaming addiction using a holistic approach, taking into consideration the mass appeal of online games, the context of Internet gaming addiction, and associated neuroimaging findings, as well as the current diagnostic framework adopted by the American Psychiatric Association. The cited research indicates that the individual's context is a significant factor that marks the dividing line between excessive gaming and gaming addiction, and the game context can gain particular importance for players, depending on their life situation and gaming preferences. Moreover, the cultural context is significant because it embeds the gamer in a community with shared beliefs and practices, endowing their gaming with particular meaning. The cited neuroimaging studies indicate that Internet gaming addiction shares similarities with other addictions, including substance dependence, at the molecular, neurocircuitry, and behavioral levels. The findings provide support for the current perspective of understanding Internet gaming addiction from a disease framework. The benefits of an Internet gaming addiction diagnosis include reliability across research, destigmatization of individuals, development of efficacious treatments, and the creation of an incentive for public health care and insurance providers. The holistic approach adopted here not only highlights empirical research that evidences neurobiologic correlates of Internet gaming addiction and the establishment of a preliminary diagnosis, but also emphasizes the necessity of an indepth understanding of the meaning, context, and practices associated with gaming.

The Internet of Things (IoT) is essential in innovative applications such as smart cities, smart homes, education, healthcare, transportation, and defense operations. IoT applications are particularly beneficial for providing healthcare because they enable secure and real-time remote patient monitoring to improve the quality of people's lives. This review paper explores the latest trends in healthcare-monitoring systems by implementing the role of the IoT. The work discusses the benefits of IoT-based healthcare systems with regard to their significance, and the benefits of IoT healthcare. We provide a systematic review on recent studies of IoT-based healthcare-monitoring systems through literature review. The literature review compares various systems' effectiveness, efficiency, data protection, privacy, security, and monitoring. The paper also explores wireless- and wearable-sensor-based IoT monitoring systems and provides a classification of healthcare-monitoring sensors. We also elaborate, in detail, on the challenges and open issues regarding healthcare security and privacy, and QoS. Finally, suggestions and recommendations for IoT healthcare applications are laid down at the end of the study along with future directions related to various recent technology trends.

INTRODUCTION: In recent years, the use of portfolios as learning and assessment tools has become more widespread across the range of health professions. Whilst a growing body of literature has accompanied these trends, there is no clear collated summary of the evidence for the educational effects of the use of portfolios in undergraduate education. This systematic review is the result of our work to provide such a summary. METHODS: We developed a protocol based on the recommendations of the Best Evidence Medical Education (BEME) collaboration. Citations retrieved by electronic searches of 10 databases were assessed against pre-defined inclusion/exclusion criteria by two independent reviewers and full texts of potentially relevant articles were obtained. Studies were identified for inclusion in the review by examination of full text articles by two independent reviewers. At all stages, discrepancies were resolved by consensus. Data relating to characteristics of the student population, intervention, outcome measures, student design and outcomes were collected using a piloted data extraction form. Each study was assessed against 11 quality indicators designed to provide information about how well it was designed and conducted; and against the Kirkpatrick hierarchy as modified for educational settings. Comparisons between different groups were carried out using the Kruskal-Wallis test (non-parametric ANOVA) or the Mann-Whitney U test as appropriate. RESULTS: Electronic searches yielded 2,348 citations. A further 23 citations were obtained by hand searching of reference lists. About 554 full articles were retrieved and assessed against our inclusion criteria. Of the 69 studies included in our review, 18 were from medicine, 32 from nursing and 19 from other allied health professions, including dentistry, physiotherapy and radiography. In all professional groups, portfolios were used mainly in the clinical setting, completion was compulsory, reflection required and assessment (either formative, summative or a combination of both) the norm. Three studies used electronic portfolios. Whilst many studies used a combination of data collection methods, over half of all included studies used questionnaires, a third used focus group interviews and another third used direct assessment of portfolios. Most studies assessed student or tutor perceptions of the effect of the use of portfolios on their learning. Five studies used a comparative design, one of which was a randomized controlled trial. Studies were most likely to meet the quality indicators relating to appropriateness of study subjects, clarity of research question and completeness of data. However, in many studies, methods were not reported in sufficient detail to allow a judgement to be made. About 19 of the 69 included studies (27%) met seven or more quality indicators. Across all professions, such 'higher quality' studies were more likely to have been published recently. The median 'quality score' (number of indicators met) rose from two for studies published in 2000 or earlier to seven for studies published in 2005 or later. Significant differences were observed between the quality scores for studies published in or before 2000 and those published between 2001 and 2004 (p = 0.027), those published in or before 2000 and those published in 2005 or later (p = 0.002) and between all studies (p = 0.004). Similar trends were seen in all professional groups. About 59 (85%) of the included studies were assessed at level 1 of the modified Kirkpatrick hierarchy (i.e. 'participation' effects, including 'post hoc' evaluations of student perceptions of the effects of keeping a portfolio on their learning). About 9 (13%) of the studies reported direct measurement of changes in student skills or attitudes and one study reported a change in student behaviour. The main effects of portfolio use identified by the included studies were: Improvement in student knowledge and understanding (28 studies, six at Kirkpatrick level 2 or above), greater self-awareness and encouragement to reflection (44 studies, seven at Kirkpatrick level 2 or above) and the ability to learn independently (10 studies, one at Kirkpatrick level 2). The findings of higher quality studies also identified benefits in these areas. They reported improved student knowledge and understanding, particularly the ability to integrate theory with practice, although a correlation with improved scores in other assessments was not always apparent. Greater self-awareness and engagement in reflection were also noted, although some studies questioned the quality of the reflection undertaken. Higher quality studies also suggest that use of portfolios improves feedback to students and gives tutors a greater awareness of students' needs, may help students to cope with uncertain or emotionally demanding situations and prepares students for postgraduate settings in which reflective practice is required. Time commitment required to collate a portfolio was the major drawback identified. In two of the studies, this was found to detract from other clinical learning. CONCLUSIONS: At present, the strength and extent of the evidence base for the educational effects of portfolios in the undergraduate setting is limited. However, there is evidence of an improving trend in the quality of reported studies. 'Higher quality' papers identify improvements in knowledge and understanding, increased self-awareness and engagement in reflection and improved student-tutor relationships as the main benefits of portfolio use. However, they also suggest that whilst portfolios encourage students to engage in reflection, the quality of those reflections cannot be assumed and that the time commitment required for portfolio completion may detract from other learning or deter students from engaging with the process unless required to do so by the demands of assessment. Further work is needed to strengthen the evidence base for portfolio use, particularly comparative studies which observe changes in student knowledge and abilities directly, rather than reporting on their perceptions once a portfolio has been completed.