Search results for: healthcare sectors

Authors: N. Al Khashan, H. Al Shammari, W. Al Bahli

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Patients who are eligible to receive treatment at the National Guard Health Affairs (NGHA), Saudi Arabia will typically have four medical record numbers (MRN), one in each of the geographical areas. More hospitals and primary healthcare facilities in other geographical areas will launch soon which means more MRNs. When patients own four MRNs, this will cause major drawbacks in patients’ quality of care such as creating new medical files in different regions for relocated patients and using referral system among regions. Consequently, the access to a patient’s medical record from other regions and the interoperability of health information between the four hospitals’ information system would be challenging. Thus, there is a need to unify medical records among these five facilities. As part of the effort to increase the quality of care, a new Hospital Information Systems (HIS) was implemented in all NGHA facilities by the end of 2016. NGHA’s plan is put to be aligned with the Saudi Arabian national transformation program 2020; whereby 70% citizens and residents of Saudi Arabia would have a unified medical record number that enables transactions between multiple Electronic Medical Records (EMRs) vendors. The aim of the study is to explore the plan, the challenges and barriers of unifying the 4 MRNs into one Enterprise Patient Identifier (EPI) in NGHA hospitals by December 2018. A descriptive study methodology was used. A journey map and a project plan are created to be followed by the project team to ensure a smooth implementation of the EPI. It includes the following: 1) Approved project charter, 2) Project management plan, 3) Change management plan, 4) Project milestone dates. Currently, the HIS is using the regional MRN. Therefore, the HIS and all integrated health care systems in all regions will need modification to move from MRN to EPI without interfering with patient care. For now, the NGHA have successfully implemented an EPI connected with the 4 MRNs that work in the back end in the systems’ database.

Keywords: consumer health, health informatics, hospital information system, universal medical record number

Procedia PDF Downloads 183

Authors: Khachen Kongpakwattana, Charungthai Dejthevaporn, Orapitchaya Krairit, Piyameth Dilokthornsakul, Devi Mohan, Nathorn Chaiyakunapruk

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Background: Although an increase in the burden of Alzheimer’s disease (AD) is evident worldwide, knowledge of costs and health-related quality of life (HR-QoL) associated with AD in Low- and Middle-Income Countries (LMICs) is still lacking. We, therefore, aimed to collect real-world cost and HR-QoL data, and investigate their associations with multiple disease-severity indicators among AD patients in Thailand. Methods: We recruited AD patients aged ≥ 60 years accompanied by their caregivers at a university-affiliated tertiary hospital. A one-time structured interview was conducted to collect disease-severity indicators, HR-QoL and caregiving information using standardized tools. The hospital’s database was used to retrieve healthcare resource utilization occurred over 6 months preceding the interview date. Costs were annualized and stratified based on cognitive status. Generalized linear models were employed to evaluate determinants of costs and HR-QoL. Results: Among 148 community-dwelling patients, average annual total societal costs of AD care were 8,014 US$ [95% Confidence Interval (95% CI): 7,295 US$ - 8,844 US$] per patient. Total costs of patients with severe stage (9,860 US$; 95% CI: 8,785 US$ - 11,328 US$) were almost twice as high as those of mild stage (5,524 US$; 95% CI: 4,649 US$ - 6,593 US$). The major cost driver was direct medical costs, particularly those incurred by AD prescriptions. Functional status was the strongest determinant for both total costs and patient’s HR-QoL (p-value < 0.001). Conclusions: Our real-world findings suggest the distinct major cost driver which results from expensive AD treatment, emphasizing the demand for country-specific cost evidence. Increases in cognitive and functional status are significantly associated with decreases in total costs of AD care and improvement on patient’s HR-QoL.

Keywords: Alzheimer's disease, associations, costs, disease-severity indicators, health-related quality of life

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Authors: Emma Avoyan

Abstract:

The safety standards for flood protection in the Netherlands have been revised recently. It is expected that all major flood-protection structures will have to be reinforced to meet the new standards. The Dutch Flood Protection Programme aims at accomplishing this task through innovative integrated projects such as construction of multi-functional flood defenses. In these projects, flood safety purposes will be combined with spatial planning, nature development, emergency management or other sectoral objectives. Therefore, implementation of dike reinforcement projects requires early involvement and collaboration between public and private sectors, different governmental actors and agencies. The development and implementation of such integrated projects has been an issue in Dutch flood risk management since long. Therefore, this article analyses how cross-sector collaboration within flood risk governance in the Netherlands has evolved over time, and how this development can be explained. The integrative framework for collaborative governance is applied as an analytical tool to map external factors framing possibilities as well as constraints for cross-sector collaboration in Dutch flood risk domain. Supported by an extensive document and literature analysis, the paper offers insights on how the system context and different drivers changing over time either promoted or hindered cross-sector collaboration between flood protection sector, urban development, nature conservation or any other sector involved in flood risk governance. The system context refers to the multi-layered and interrelated suite of conditions that influence the formation and performance of complex governance systems, such as collaborative governance regimes, whereas the drivers initiate and enable the overall process of collaboration. In addition, by applying a method of process tracing we identify a causal and chronological chain of events shaping cross-sectoral interaction in Dutch flood risk management. Our results indicate that in order to evaluate the performance of complex governance systems, it is important to firstly study the system context that shapes it. Clear understanding of the system conditions and drivers for collaboration gives insight into the possibilities of and constraints for effective performance of complex governance systems. The performance of the governance system is affected by the system conditions, while at the same time the governance system can also change the system conditions. Our results show that the sequence of changes within the system conditions and drivers over time affect how cross-sector interaction in Dutch flood risk governance system happens now. Moreover, we have traced the potential of this governance system to shape and change the system context.

Keywords: collaborative governance, cross-sector interaction, flood risk management, the Netherlands

Procedia PDF Downloads 116

Authors: N. Perko, N. Kavran, M. Bukljas, I. Berbic

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This paper is a result of implemented research on proposed introduced methodology for nautical ports capacity planning by introducing a multi-criteria approach of defined criteria and impacts at the Adriatic Sea. The purpose was analysing the determinants -characteristics of infrastructure and services of nautical ports capacity allocated, especially nowadays due to COVID-19 pandemic, as crucial for the successful operation of nautical ports. Giving the importance of the defined priorities for short-term and long-term planning is essential not only in terms of the development of nautical tourism but also in terms of developing the maritime system, but unfortunately, this is not always carried out. Evaluation of the use of resources should follow from a detailed analysis of all aspects of resources bearing in mind that nautical tourism used resources in a sustainable manner and generate effects in the tourism and maritime sectors. Consequently, the identified multiplier effect of nautical tourism, which should be defined and quantified in detail, should be one of the major competitive products on the Croatian Adriatic and the Mediterranean. Research of nautical tourism is necessary to quantify the effects and required planning system development. In the future, the greatest threat to the long-term sustainable development of nautical tourism can be its further uncontrolled or unlimited and undirected development, especially under pressure markedly higher demand than supply for new moorings in the Mediterranean. Results of this implemented research are applicable to nautical ports management and decision-makers of maritime transport system development. This paper will present implemented research and obtained result-developed methodology for nautical port capacity planning -port capacity planning multi-criteria decision-making. A proposed methodological approach of multi-criteria capacity planning includes four criteria (spatial - transport, cost - infrastructure, ecological and organizational criteria, and additional services). The importance of the criteria and sub-criteria is evaluated and carried out as the basis for sensitivity analysis of the importance of the criteria and sub-criteria. Based on the analysis of the identified and quantified importance of certain criteria and sub-criteria, as well as sensitivity analysis and analysis of changes of the quantified importance, scientific and applicable results will be presented. These obtained results have practical applicability by management of nautical ports in the planning of increasing capacity and further development and for the adaptation of existing nautical ports. Obtained research is applicable and replicable in other seas, and results are especially important and useful in this COVID-19 pandemic challenging maritime development framework.

Keywords: Adriatic Sea, capacity, infrastructures, maritime system, methodology, nautical ports, nautical tourism, service

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Authors: Nilay Balkan

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Introductory statement: The purpose of this study is to understand how small business owners develop social media marketing competency, the challenges they encounter in doing so, and establish the social media training needs of such businesses. These challenges impact the extent to which small business owners build effective social media knowledge and, in turn, impact their ability to implement effective social media marketing into their business practices. This means small businesses are not fully able to benefit from social media, such as benefits to customer relationship management or increasing brand image, which would support the overall business operations for these businesses. This research is part one of a two-phased study. The first phase aims to establish the challenges small business owners face in building social media marketing competency and their specific training needs. Phase two will then focus in more depth on the barriers and challenges emerging from phase one. Summary of Methodology: Interviews with ten small business owners were conducted from various sectors, including fitness, tourism, food, and drinks. These businesses were located in the central belt of Scotland, which is an area with the highest population and business density in Scotland. These interviews were in-depth and semi-structured, with the purpose of being investigative and understanding the phenomena from the lived experience of the small business owners. A purposive sampling was used, where small business owners fulfilling certain criteria were approached to take part in the interviews. Key findings: The study found four ways in which small business owners develop their social media competency (informal methods, formal methods, learning through a network, and experimenting) and the various challenges they face with these methods. Further, the study established four barriers impacting the development of social media marketing competency among the interviewed small business owners. In doing so, preliminary support needs have also emerged. Concluding statement: The contribution of this study is to understand the challenges small business owners face when learning how to use social media for business purposes and identifying their training needs. This understanding can help the development of specific and tailored support. In addition, specific and tailored training can support small businesses in building competency. This supports small businesses to progress to the next stage of their development, which could be to further their digital transformation or grow their business. The insights from this study can be used to support business competitiveness and support small businesses to become more resilient. Moreover, small businesses and entrepreneurs share some similar characteristics, such as limited resources and conflicting priorities, and the findings of this study may be able to support entrepreneurs in their social media marketing strategies as well.

Keywords: small business, marketing theory and applications, social media marketing, strategic management, digital competency, digitalisation, marketing research and strategy, entrepreneurship

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Authors: Nikhil A. Gavhane, Sachin Shah, Ishant S. Mahajan, Pawan D. Bahekar

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Introduction: Millions of people are affected with dengue fever every year, which drives up healthcare expenses in many low-income countries. Organ failure and other serious symptoms may result. Another worldwide public health problem is sickle cell anaemia, which is most prevalent in Africa, the Caribbean, and Europe. Dengue epidemics have reportedly occurred in locations with a high frequency of sickle cell disease, compounding the health problems in these areas. Aims and Objectives: This study examines dengue infection in sickle cell disease-afflicted pre-schoolers. Method:This Retrospective cohort study examined paediatric patients. Young people with sickle cell disease (SCD), dengue infection, and a control group without SCD or dengue were studied. Data on demographics, SCD consequences, medical treatments, and laboratory findings were gathered to analyse the influence of SCD on dengue severity and clinical outcomes, classified as severe or non-severe by the 2009 WHO classification. Using fever or admission symptoms, the research estimated acute illness duration. Result: Table 1 compares haemoglobin genotype-based dengue episode features in SS, SC, and controls. Table 2 shows that severe dengue cases are older, have longer admission delays, and have particular symptoms. Table 3's multivariate analysis indicates SS genotype's high connection with severe dengue, multiorgan failure, and acute pulmonary problems. Table 4 relates severe dengue to greater white blood cell counts, anaemia, liver enzymes, and reduced lactate dehydrogenase. Conclusion: This study is valuable but confined to hospitalised dengue patients with sickle cell illness. Small cohorts limit comparisons. Further study is needed since findings contradict predictions.

Keywords: dengue, chills, headache, severe myalgia, vomiting, nausea, prostration

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Authors: James Ladzekpo

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Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

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Authors: Ouassila Bekkal Brikci Benhabib, Zahia Boucherit Otmani, Kebir Boucherit, A. Seghir

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The establishment of intravenous catheters in hospitalized patient is an act common in many clinical situations. These therapeutic tools, from their insertion in the body, represent gateways including fungal germs prone. The latter can generate the growth of biofilms, which can be the cause of fungal infection. Faced with this problem, we conducted a study at the University Hospital of Tlemcen in the neurosurgery unit and aims to isolate and identify Candida yeasts from intravenous catheters. Then test their ability to form biofilms. Materials and methods: 256 patient hospitalized in surgery of the hospital in west Algeria were submitted to this study. All samples were taken from peripheral venous catheters implanted for 72 hours or more days. A total of 31 isolates of Candida species were isolated. MIC and SMIC are determined at 80% inhibition by the test XTT tetrazolium measured at 490 nm. The final concentrations of antifungal agent being between 0.03 and 16 mg / ml for amphotericin B and from 0.015 to 8 mg / mL caspofungin. Results: 31 Candida species isolates from catheters including 14 Candida albicans and 17 Candida non albicans . 21 strains of all the isolates were able to form biofilms. In their form of Planktonic cells, all isolates are 100% susceptible to antifungal agents tested. However, in their state of biofilms, more isolates have become tolerant to the tested antifungals. Conclusion: Candida yeasts isolated from intravascular catheters are considered an important virulence factor in the pathogenesis of infections. Their involvement in catheter-related infections can be disastrous for their potential to generate biofilms. They survive high concentrations of antifungal where treatment failure. Pending the development of a therapeutic approach antibiofilm related to catheters, their mastery is going through: -The risk of infection prevention based on the training and awareness of medical staff, -Strict hygiene and maximum asepsis, and -The choice of material limiting microbial colonization.

Keywords: candida, biofilm, hospital, infection, amphotericin B, caspofungin

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Authors: Maria Karidakis, Barbara Kelly

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The challenges precipitated by the advent of COVID-19 have brought to the fore the task governments and key stakeholders are faced with; ensuring public health communication is readily accessible to vulnerable populations. COVID-19 has presented challenges for the provision and reception of timely, accessible, and accurate health information pertaining to vaccine health messaging to Aboriginal and Torres Strait Islander peoples. The aim of this qualitative study was to explore strategies used by Aboriginal-led organisations to improve communication about COVID-19 and vaccination for their communities and to explore how these mediation and outreach strategies were received by community members. We interviewed 6 Aboriginal-led organisations and 15 community members from several states across Australian, and these interviews were analysed thematically. The findings suggest that effective public health communication is enhanced when aFirst nations-led response defines the governance that happens in First Nations communities. Pro-active and self-determining Aboriginal leadership and decision-making helps drive the response to counter a growing trend towards vaccine hesitancy. Other strategies include establishing partnerships with government departments and relevant non-governmental organisations to ensure services are implemented and culturally appropriate. The outcomes of this research will afford policymakers, stakeholders in healthcare, and cultural mediators the capacity to identify strengths and potential problems associated with pandemic health information and to subsequently implement creative and culturally specific solutions that go beyond the provision of written documentation via translation or interpreting. It will also enable governing bodies to adjust multilingual polices and to adopt mediation strategies that will improve information delivery and intercultural services on a national and international level.

Keywords: intercultural communication, qualitative, public health communication, COVID-19, pandemic, mediated communication, first nations people

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Authors: Stefanache Stefania, Ioana R. Podina

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Background: Embodied Conversational Agents (ECAs) are revolutionizing education and healthcare by offering cost-effective, adaptable, and portable solutions. Research on the Uncanny Valley effect (UVE) involves various embodied agents, including ECAs. Achieving the optimal level of anthropomorphism, no consensus on how to overcome the uncanniness problem. Objectives: This systematic review aims to identify the user characteristics, agent features, and context factors that influence the UVE. Additionally, this review provides recommendations for creating effective ECAs and conducting proper experimental studies. Methods: We conducted a systematic review following the PRISMA 2020 guidelines. We included quantitative, peer-reviewed studies that examined human-ECA interaction. We identified 17,122 relevant records from ACM Digital Library, IEE Explore, Scopus, ProQuest, and Web of Science. The quality of the predictors, mediators, and moderators adheres to the guidelines set by prior systematic reviews. Results: Based on the included studies, it can be concluded that females and younger people perceive the ECA as more attractive. However, inconsistent findings exist in the literature. ECAs characterized by extraversion, emotional stability, and agreeableness are considered more attractive. Facial expressions also play a role in the UVE, with some studies indicating that ECAs with more facial expressions are considered more attractive, although this effect is not consistent across all studies. Few studies have explored contextual factors, but they are nonetheless crucial. The interaction scenario and exposure time are important circumstances in human-ECA interaction. Conclusions: The findings highlight a growing interest in ECAs, which have seen significant developments in recent years. Given this evolving landscape, investigating the risk of the UVE can be a promising line of research.

Keywords: human-computer interaction, uncanny valley effect, embodied conversational agent, systematic review

Procedia PDF Downloads 57

Authors: Ana Mafalda Silva, Rebeca Fontes, Ana Paula Vaz, Carla Carreira, Ana Corte-Real

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Decades of research on the topic of interpersonal violence against minors highlight five main conclusions: 1) it causes harmful effects on children's development and health; 2) it is prevalent; 3) it violates children's rights; 4) it can be prevented and 5) parents are the main aggressors. The child abuse scenario is identified through clinical observation, administrative data and self-reports. The most used instruments are self-reports; however, there are no valid and reliable self-report instruments for minors, which consist of a retrospective interpretation of the situation by the victim already in her adult phase and/or by her parents. Clinical observation and collection of information, namely from the orofacial region, are essential in the early identification of these situations. The management of medical data, such as personal data, must comply with the General Data Protection Regulation (GDPR), in Europe, and with the General Law of Data Protection (LGPD), in Brazil. This review aims to answer the question: In a situation of medical assistance to minors, in the suspicion of interpersonal violence, due to mistreatment, is it necessary for the guardians to provide consent in the registration and sharing of personal data, namely medical ones. A scoping review was carried out based on a search by the Web of Science and Pubmed search engines. Four papers and two documents from the grey literature were selected. As found, the process of identifying and signaling child abuse by the health professional, and the necessary early intervention in defense of the minor as a victim of abuse, comply with the guidelines expressed in the GDPR and LGPD. This way, the notification in maltreatment scenarios by health professionals should be a priority and there shouldn’t be the fear or anxiety of legal repercussions that stands in the way of collecting and treating the data necessary for the signaling procedure that safeguards and promotes the welfare of children living with abuse.

Keywords: child abuse, disease notifications, ethics, healthcare assistance

Procedia PDF Downloads 84

Authors: Richard Ren

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Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 107

Authors: Van Truong Pham

Abstract:

Background: Self-management was described as a potential strategy for blood pressure control in patients with hypertension. However, the effects of self-management interventions on blood pressure, self-efficacy, medication adherence, and body mass index (BMI) in older adults with hypertension have not been systematically evaluated. We evaluated the effects of self-management interventions on systolic blood pressure (SBP) and diastolic blood pressure (DBP), self-efficacy, medication adherence, and BMI in hypertensive older adults. Methods: We followed the recommended guidelines of preferred reporting items for systematic reviews and meta-analyses. Searches in electronic databases including CINAHL, Cochrane Library, Embase, Ovid-Medline, PubMed, Scopus, Web of Science, and other sources were performed to include all relevant studies up to April 2019. Studies selection, data extraction, and quality assessment were performed by two reviewers independently. We summarized intervention effects as Hedges' g values and 95% confidence intervals (CI) using a random-effects model. Data were analyzed using Comprehensive Meta-Analysis software 2.0. Results: Twelve randomized controlled trials met our inclusion criteria. The results revealed that self-management interventions significantly improved blood pressure control, self-efficacy, medication adherence, whereas the effect of self-management on BMI was not significant in older adult patients with hypertension. The following Hedges' g (effect size) values were obtained: SBP, -0.34 (95% CI, -0.51 to -0.17, p < 0.001); DBP, -0.18 (95% CI, -0.30 to -0.05, p < 0.001); self-efficacy, 0.93 (95%CI, 0.50 to 1.36, p < 0.001); medication adherence, 1.72 (95%CI, 0.44 to 3.00, p=0.008); and BMI, -0.57 (95%CI, -1.62 to 0.48, p = 0.286). Conclusions: Self-management interventions significantly improved blood pressure control, self-efficacy, and medication adherence. However, the effects of self-management on obesity control were not supported by the evidence. Healthcare providers should implement self-management interventions to strengthen patients' role in managing their health care.

Keywords: self-management, meta-analysis, blood pressure control, self-efficacy, medication adherence, body mass index

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Authors: Eric Lee G. Escobedo-Wu, Nidhi Rohatgi, Fouzel Dhebar

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It is challenging for patients to navigate through healthcare systems after-hours. This leads to delays in care, patient/provider dissatisfaction, inappropriate resource utilization, readmissions, and higher costs. It is important to provide patients and providers with effective clinical decision-making tools to allow seamless connectivity and coordinated care. In August 2015, patient-centric Stanford Health Care established Clinical Advice Services (CAS) to provide clinical decision support after-hours. CAS is founded on key Lean principles: Value stream mapping, empathy mapping, waste walk, takt time calculations, standard work, plan-do-check-act cycles, and active daily management. At CAS, Clinical Assistants take the initial call and manage all non-clinical calls (e.g., appointments, directions, general information). If the patient has a clinical symptom, the CAS nurses take the call and utilize standardized clinical algorithms to triage the patient to home, clinic, urgent care, emergency department, or 911. Nurses may also contact the on-call physician based on the clinical algorithm for further direction and consultation. Since August 2015, CAS has managed 228,990 calls from 26 clinical specialties. Reporting is built into the electronic health record for analysis and data collection. 65.3% of the after-hours calls are clinically related. Average clinical algorithm adherence rate has been 92%. An average of 9% of calls was escalated by CAS nurses to the physician on call. An average of 5% of patients was triaged to the Emergency Department by CAS. Key learnings indicate that a seamless connectivity vision, cascading, multidisciplinary ownership of the problem, and synergistic enterprise improvements have contributed to this success while striving for continuous improvement.

Keywords: after hours phone calls, clinical advice services, nurse triage, Stanford Health Care

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Authors: Rashmi Uchil, A. H. Sequeira

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Post-liberalization era in India has seen an unprecedented growth of mergers, both domestic as well as cross-border deals. Indian organizations have slowly begun appreciating this inorganic method of growth. However, all is not well as is evidenced in the lowering value creation of organizations after mergers. Several studies have identified that organizational culture is one of the key factors that affects the success of mergers. But very few studies have been attempted in this realm in India. The current study attempts to identify the factors in the organizational culture variable that may be unique to India. It also focuses on the difference in the impact of organizational culture on merger of organizations in the manufacturing and service sectors in India. The study uses a mixed research approach. An exploratory research approach is adopted to identify the variables that constitute organizational culture specifically in the Indian scenario. A few hypotheses were developed from the identified variables and tested to arrive at the Grounded Theory. The Grounded Theory approach used in the study, attempts to integrate the variables related to organizational culture. Descriptive approach is used to validate the developed grounded theory with a new empirical data set and thus test the relationship between the organizational culture variables and the success of mergers. Empirical data is captured from merged organizations situated in major cities of India. These organizations represent significant proportions of the total number of organizations which have adopted mergers. The mix of industries included software, banking, manufacturing, pharmaceutical and financial services. Mixed sampling approach was adopted for this study. The first phase of sampling was conducted using the probability method of stratified random sampling. The study further used the non-probability method of judgmental sampling. Adequate sample size was identified for the study which represents the top, middle and junior management levels of the organizations that had adopted mergers. Validity and reliability of the research instrument was ensured with appropriate tests. Statistical tools like regression analysis, correlation analysis and factor analysis were used for data analysis. The results of the study revealed a strong relationship between organizational culture and its impact on the success of mergers. The study also revealed that the results were unique to the extent that they highlighted a marked difference in the manner of internalization of change of organizational culture after merger by the organizations in the manufacturing sector. Further, the study reveals that the organizations in the service sector internalized the changes at a slower rate. The study also portrays the industries in the manufacturing sector as more proactive and can contribute to a change in the perception of the said organizations.

Keywords: manufacturing industries, mergers, organizational culture, service industries

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Authors: Jared Cheves, Amanda DeChent, Joyce Pan

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Total knee replacements (TKAs) are one of the most common but painful surgical procedures performed in the United States. Currently, the gold standard for postoperative pain management is the utilization of opioids. However, in the wake of the opioid epidemic, the healthcare system is attempting to reduce opioid consumption by trialing innovative opioid sparing analgesic techniques such as continuous peripheral nerve blocks (CPNB) and continuous periarticular infiltration (CPAI). The alleviation of pain, particularly during the first 72 hours postoperatively, is of utmost importance due to its association with delayed recovery, impaired rehabilitation, immunosuppression, the development of chronic pain, the development of rebound pain, and decreased patient satisfaction. While both CPNB and CPAI are being used today, there is limited evidence comparing the two to the current standard of care or to each other. An extensive literature review was performed to explore the safety profiles and effectiveness of CPNB and CPAI in reducing reported pain scores and decreasing opioid consumption. The literature revealed the usage of CPNB contributed to lower pain scores and decreased opioid use when compared to opioid-only control groups. Additionally, CPAI did not improve pain scores or decrease opioid consumption when combined with a multimodal analgesic (MMA) regimen. When comparing CPNB and CPAI to each other, neither unanimously lowered pain scores to a greater degree, but the literature indicates that CPNB decreased opioid consumption more than CPAI. More research is needed to further cement the efficacy of CPNB and CPAI as standard components of MMA in TKA procedures. In addition, future research can also focus on novel catheter-free applications to reduce the complications of continuous catheter analgesics.

Keywords: total knee arthroplasty, continuous peripheral nerve blocks, continuous periarticular infiltration, opioid, multimodal analgesia

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Authors: Diamant Irene, Dar Tamar

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Burnout, conceptualized within the framework of stress research, is to a large extent a result of a threat on resources of time or a feeling of time shortage. In reaction to numerous tasks, deadlines, high output, management of different duties encompassing work-home conflicts, many individuals experience ‘time pressure’. Time pressure is characterized as the perception of a lack of available time in relation to the amount of workload. It can be a result of local objective constraints, but it can also be a chronic attribute in coping with life. As such, time pressure is associated in the literature with general stress experience and can therefore be a direct, contributory burnout factor. The present study examines the relation of chronic time pressure – feeling of time shortage and of being rushed, with another central aspect in subjective temporal experience - time perspective. Time perspective is a stable personal disposition, capturing the extent to which people subjectively remember the past, live the present and\or anticipate the future. Based on Hobfoll’s Conservation of Resources Theory, it was hypothesized that individuals with chronic time pressure would experience a permanent threat on their time resources resulting in relatively increased burnout. In addition, it was hypothesized that different time perspective profiles, based on Zimbardo’s typology of five dimensions – Past Positive, Past Negative, Present Hedonistic, Present Fatalistic, and Future, would be related to different magnitudes of chronic time pressure and of burnout. We expected that individuals with ‘Past Negative’ or ‘Present Fatalist’ time perspectives would experience more burnout, with chronic time pressure being a moderator variable. Conversely, individuals with a ‘Present Hedonistic’ - with little concern with the future consequences of actions, would experience less chronic time pressure and less burnout. Another temporal experience angle examined in this study is the difference between the actual distribution of time (as in a typical day) versus desired distribution of time (such as would have been distributed optimally during a day). It was hypothesized that there would be a positive correlation between the gap between these time distributions and chronic time pressure and burnout. Data was collected through an online self-reporting survey distributed on social networks, with 240 participants (aged 21-65) recruited through convenience and snowball sampling methods from various organizational sectors. The results of the present study support the hypotheses and constitute a basis for future debate regarding the elements of burnout in the modern work environment, with an emphasis on subjective temporal experience. Our findings point to the importance of chronic and stable temporal experiences, as time pressure and time perspective, in occupational experience. The findings are also discussed with a view to the development of practical methods of burnout prevention.

Keywords: conservation of resources, burnout, time pressure, time perspective

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Authors: John Ahluwalia

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As an affluent first-world nation, Canada took swift and comprehensive action during the outbreak of the SARS-CoV-2 (COVID-19) pandemic compared to other countries in the same socio-economic cohort. The United States has stumbled to overcome obstacles most developed nations have faced, which has led to significantly more per capita cases and deaths. The initial outbreaks of COVID-19 occurred in the US and Canada within days of each other and posed similar potentially catastrophic threats to public health, the economy, and governmental stability. On a macro level, events that take place in the US have a direct impact on Canada. For example, both countries tend to enter and exit economic recessions at approximately the same time, they are each other’s largest trading partners, and their currencies are inexorably linked. Why is it that Canada has not shared the same fate as the US (and many other nations) that have realized much worse outcomes relative to the COVID-19 pandemic? Variables intrinsic to Canada’s national infrastructure have been instrumental in the country’s efforts to flatten the curve of COVID-19 cases and deaths. Canada’s coordinated multi-level governmental effort has allowed it to create and enforce policies related to COVID-19 at both the national and provincial levels. Canada’s policy of universal healthcare is another variable. Health care and public health measures are enforced on a provincial level, and it is within each province’s jurisdiction to dictate standards for public safety based on scientific evidence. Rather than introducing confusion and the possibility of competition for resources such as PPE and vaccines, Canada’s multi-level chain of government authority has provided consistent policies supporting national public health and local delivery of medical care. This paper will demonstrate that the coordinated efforts on provincial and federal levels have been the linchpin in Canada’s relative success in containing the deadly spread of the COVID-19 virus.

Keywords: COVID-19, Canada, GIS, temporal analysis, ESRI

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Authors: Pesaru Vigneshwar Reddy, Parvathaneni Pavan

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Green organic chemistry which is the latest and one of the most researched topics now-a- days has been in demand since 1990’s. Majority of the research in green organic chemistry chemicals are some of the important starting materials for greater number of major chemical industries. The production of organic chemicals has raw materials (or) reagents for other application is major sector of manufacturing polymers, pharmaceuticals, pesticides, paints, artificial fibers, food additives etc. organic synthesis on a large scale compound to the labratory scale, involves the use of energy, basic chemical ingredients from the petro chemical sectors, catalyst and after the end of the reaction, seperation, purification, storage, packing distribution etc. During these processes there are many problems of health and safety for workers in addition to the environmental problems caused there by use and deposition as waste. Green chemistry with its 12 principles would like to see changes in conventional way that were used for decades to make synthetic organic chemical and the use of less toxic starting materials. Green chemistry would like to increase the efficiency of synthetic methods, to use less toxic solvents, reduce the stage of synthetic routes and minimize waste as far as practically possible. In this way, organic synthesis will be part of the effort for sustainable development Green chemistry is also interested for research and alternatives innovations on many practical aspects of organic synthesis in the university and research labaratory of institutions. By changing the methodologies of organic synthesis, health and safety will be advanced in the small scale laboratory level but also will be extended to the industrial large scale production a process through new techniques. The three key developments in green chemistry include the use of super critical carbondioxide as green solvent, aqueous hydrogen peroxide as an oxidising agent and use of hydrogen in asymmetric synthesis. It also focuses on replacing traditional methods of heating with that of modern methods of heating like microwaves traditions, so that carbon foot print should reduces as far as possible. Another beneficiary of this green chemistry is that it will reduce environmental pollution through the use of less toxic reagents, minimizing of waste and more bio-degradable biproducts. In this present paper some of the basic principles, approaches, and early achievements of green chemistry has a branch of chemistry that studies the laws of passing of chemical reactions is also considered, with the summarization of green chemistry principles. A discussion about E-factor, old and new synthesis of ibuprofen, microwave techniques, and some of the recent advancements also considered.

Keywords: energy, e-factor, carbon foot print, micro-wave, sono-chemistry, advancement

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Authors: Elissar Mansour, Emily Chen, Tracee Fernandez, Mariam Basheti, Christopher Gordon, Bandana Saini

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Sleep is an essential process for the maintenance of several neurobiological processes such as memory consolidation, mood, and metabolic processes. It is known that sleep patterns vary with age and is affected by multiple factors. While non-pharmacological strategies are generally considered first-line, sedatives are excessively used in the older population. This study aimed to explore the management of sleep in residential aged care facilities (RACFs) by nurse professionals and to identify the key factors that impact provision of optimal sleep health care. An inductive thematic qualitative research method was employed to analyse the data collected from semi-structured interviews with registered nurses working in RACF. Seventeen interviews were conducted, and the data yielded three themes: 1) the nurses’ observations and knowledge of sleep health, 2) the strategies employed in RACF for the management of sleep disturbances, 3) the organizational barriers to evidence-based sleep health management. Nurse participants reported the use of both non-pharmacological and pharmacological interventions. Sedatives were commonly prescribed due to their fast action and accessibility despite the guidelines indicating their use in later stages. Although benzodiazepines are known for their many side effects, such as drowsiness and oversedation, temazepam was the most commonly administered drug. Sleep in RACF was affected by several factors such as aging and comorbidities (e.g., dementia, pain, anxiety). However, the were also many modifiable factors that negatively impacted sleep management in RACF. These include staffing ratios, nursing duties, medication side effects, and lack of training and involvement of allied health professionals. This study highlighted the importance of involving a multidisciplinary team and the urge to develop guidelines and training programs for healthcare professionals to improve sleep health management in RACF.

Keywords: registered nurses, residential aged care facilities, sedative use, sleep

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Authors: Nelson Kimeli Kemboi Yego, Juma Kasozi, Joseph Nkruzinza, Francis Kipkogei

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The study investigated the low uptake of health insurance in Kenya despite efforts to achieve universal health coverage through various health insurance schemes. Unsupervised machine learning techniques were employed to identify patterns in health insurance uptake based on sociodemographic factors among Kenyan households. The aim was to identify key demographic groups that are underinsured and to provide insights for the development of effective policies and outreach programs. Using the 2021 FinAccess Survey, the study clustered Kenyan households based on their health insurance uptake and sociodemographic features to reveal patterns in health insurance uptake across the country. The effectiveness of k-prototypes clustering, hierarchical clustering, and agglomerative hierarchical clustering in clustering based on sociodemographic factors was compared. The k-prototypes approach was found to be the most effective at uncovering distinct and well-separated clusters in the Kenyan sociodemographic data related to health insurance uptake based on silhouette, Calinski-Harabasz, Davies-Bouldin, and Rand indices. Hence, it was utilized in uncovering the patterns in uptake. The results of the analysis indicate that inclusivity in health insurance is greatly related to affordability. The findings suggest that targeted policy interventions and outreach programs are necessary to increase health insurance uptake in Kenya, with the ultimate goal of achieving universal health coverage. The study provides important insights for policymakers and stakeholders in the health insurance sector to address the low uptake of health insurance and to ensure that healthcare services are accessible and affordable to all Kenyans, regardless of their socio-demographic status. The study highlights the potential of unsupervised machine learning techniques to provide insights into complex health policy issues and improve decision-making in the health sector.

Keywords: health insurance, unsupervised learning, clustering algorithms, machine learning

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Authors: Biniam Seifu Debelo, Bheema Lingaiah Thamineni, Hanumesh Kumar Dasari, Ahmed Ali Dawud

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Background: One of the most frequent neurological conditions in newborns is neonatal seizures, which may indicate severe neurological dysfunction. They may be caused by a broad range of problems with the central nervous system during or after pregnancy, infections, brain injuries, and/or other health conditions. These seizures may have very subtle or very modest clinical indications because patterns like oscillatory (spike) trains begin with relatively low amplitude and gradually increase over time. This becomes very challenging and erroneous if clinical observation is the primary basis for identifying newborn seizures. Objectives: In this study, a diagnosis system using deep convolutional neural networks is proposed to determine and classify the severity level of neonatal seizures using multichannel neonatal EEG data. Methods: Clinical multichannel EEG datasets were compiled using datasets from publicly accessible online sources. Various preprocessing steps were taken, including converting 2D time series data to equivalent waveform pictures. The proposed models underwent training, and their performance was evaluated. Results: The proposed CNN was used to perform binary classification with an accuracy of 92.6%, F1-score of 92.7%, specificity of 92.8%, and precision of 92.6%. To detect newborn seizures, this model is utilized. Using the proposed CNN model, multiclassification was performed with accuracy rates of 88.6%, specificity rates of 92.18%, F1-score rates of 85.61%, and precision rates of 88.9%. A multiclassification model is used to classify the severity level of neonatal seizures. The results demonstrated that the suggested strategy can assist medical professionals in making accurate diagnoses close to healthcare institutions. Conclusion: The developed system was capable of detecting neonatal seizures and has the potential to be used as a decision-making tool in resource-limited areas with a scarcity of expert neurologists.

Keywords: CNN, multichannel EEG, neonatal seizure, severity identification

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Authors: Mudrika Singhal

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The research paper is basically about how the genetically modified organisms evolved and their significance in today’s world. It also highlights about the various pros and cons of the genetically modified organisms and the progress of India in this field. A genetically modified organism is the one whose genetic material has been altered using genetic engineering techniques. They have a wide range of uses such as transgenic plants, genetically modified mammals such as mouse and also in insects and aquatic life. Their use is rooted back to the time around 12,000 B.C. when humans domesticated plants and animals. At that humans used genetically modified organisms produced by the procedure of selective breeding and not by genetic engineering techniques. Selective breeding is the procedure in which selective traits are bred in plants and animals and then are domesticated. Domestication of wild plants into a suitable cultigen is a well known example of this technique. GMOs have uses in varied fields ranging from biological and medical research, production of pharmaceutical drugs to agricultural fields. The first organisms to be genetically modified were the microbes because of their simpler genetics. At present the genetically modified protein insulin is used to treat diabetes. In the case of plants transgenic plants, genetically modified crops and cisgenic plants are the examples of genetic modification. In the case of mammals, transgenic animals such as mice, rats etc. serve various purposes such as researching human diseases, improvement in animal health etc. Now coming upon the pros and cons related to the genetically modified organisms, pros include crops with higher yield, less growth time and more predictable in comparison to traditional breeding. Cons include that they are dangerous to mammals such as rats, these products contain protein which would trigger allergic reactions. In India presently, group of GMOs include GM microorganisms, transgenic crops and animals. There are varied applications in the field of healthcare and agriculture. In the nutshell, the research paper is about the progress in the field of genetic modification, taking along the effects in today’s world.

Keywords: applications, mammals, transgenic, engineering and technology

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Authors: Noor Hasmini Abd Ghani

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Brand resonance is among of new focused strategy that getting more attention in nowadays by larger companies for their long-term market survival. The brand resonance emphasizing of two main characteristics that are intensity and activity able to generate psychology bond and enduring relationship between a brand and consumer. This strong attachment relationship has represented brand resonance with the concept of consumer brand relationship (CBR) that exhibit competitive advantage for long-term market survival. The main consideration toward this brand resonance approach is not only in the context of larger companies but also can be adapted in Small and Medium Enterprises (SMEs) as well. The SMEs have been recognized as vital pillar to the world economy in both developed and emergence countries are undeniable due to their economic growth contributions, such as opportunity for employment, wealth creation, and poverty reduction. In particular, the facts that SMEs in Malaysia are pivotal to the well-being of the Malaysian economy and society are clearly justified, where the SMEs competent in provided jobs to 66% of the workforce and contributed 40% to the GDP. As regards to it several sectors, the SMEs service category that covers the Food & Beverage (F&B) sector is one of the high-potential industries in Malaysia. For that reasons, SMEs strong brand or brand equity is vital to be developed for their long-term market survival. However, there’s still less appropriate strategies in develop their brand equity. The difficulties have never been so evident until Covid-19 swept across the globe from 2020. Since the pandemic began, more than 150,000 SMEs in Malaysia have shut down, leaving more than 1.2 million people jobless. Otherwise, as the SMEs are the pillar of any economy for the countries in the world, and with negative effect of COVID-19 toward their economic growth, thus, their protection has become important more than ever. Therefore, focusing on strategy that able to develop SMEs strong brand is compulsory. Hence, this is where the strategy of brand resonance is introduced in this study. Mainly, this study aims to investigate the impact of CBR as a predictor and mediator in the context of social media marketing (SMM) activities toward SMEs e-brand equity (or strong brand) building. The study employed the quantitative research design concerning on electronic survey method with the valid response rate of 300 respondents. Interestingly, the result revealed the importance role of CBR either as predictor or mediator in the context of SMEs SMM as well as brand equity development. Further, the study provided several theoretical and practical implications that can benefit the SMEs in enhancing their strategic marketing decision.

Keywords: SME brand equity, SME social media marketing, SME consumer brand relationship, SME brand resonance

Procedia PDF Downloads 51

Authors: F. Fatoye, C. E. Mbada, T. Gebrye, A. O. Ogunsola, C. Fatoye, O. Oyewole

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Musculoskeletal disorders (MSDs) such as low back pain (LBP), cervical spondylosis (CSPD), sprain, osteoarthritis (OA), and post immobilization stiffness (PIS) have a major impact on individuals, health systems and society in terms of morbidity, long-term disability, and economics. This study estimated the direct and indirect costs of common MSDs in Osun State, Nigeria. A review of medical charts for adult patients attending Physiotherapy Outpatient Clinic at the Obafemi Awolowo University Teaching Hospitals Complex, Osun State, Nigeria between 2009 and 2018 was carried out. The occupational class of the patients was determined using the International Labour Classification (ILO). The direct and indirect costs were estimated using a cost-of-illness approach. Physiotherapy related health resource use, and costs of the common MSDs, including consultation fee, total fee charge per session, costs of consumables were estimated. Data were summarised using descriptive statistics mean and standard deviation (SD). Overall, 1582 (Male = 47.5%, Female = 52.5%) patients with MSDs population with a mean age of 47.8 ± 25.7 years participated in this study. The mean (SD) direct costs estimate for LBP, CSPD, PIS, sprain, OA, and other conditions were $18.35 ($17.33), $34.76 ($17.33), $32.13 ($28.37), $35.14 ($44.16), $37.19 ($41.68), and $15.74 ($13.96), respectively. The mean (SD) indirect costs estimate of LBP, CSPD, PIS, sprain, OA, and other MSD conditions were $73.42 ($43.54), $140.57 ($69.31), $128.52 ($113.46), sprain $140.57 ($69.31), $148.77 ($166.71), and $62.98 ($55.84), respectively. Musculoskeletal disorders contribute a substantial economic burden to individuals with the condition and society. The unacceptable economic loss of MSDs should be reduced using appropriate strategies. Further research is required to determine the clinical and cost effectiveness of strategies to improve health outcomes of patients with MSDs. The findings of the present study may assist health policy and decision makers to understand the economic burden of MSDs and facilitate efficient allocation of healthcare resources to alleviate the burden associated with these conditions in Nigeria.

Keywords: economic burden, low back pain, musculoskeletal disorders, real-world

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Authors: Mahadehe Hassan

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In most countries manufacturing, trading and distribution of gasoline and diesel fuels belongs to the most important sectors of national economy. For Bangladesh, a robust, well-functioning, secure and smartly managed national fuel distribution chain is an essential precondition for achieving Government top priorities in development and modernization of transportation infrastructure, protection of national environment and population health as well as, very importantly, securing due tax revenue for the State Budget. Bangladesh is a developing country with complex fuel supply network, high fuel taxes incidence and – till now - limited possibilities in application of modern, automated technologies for Government national fuel market control. Such environment allows dishonest physical and legal persons and organized criminals to build and profit from illegal fuel distribution schemes and fuel illicit trade. As a result, the market transparency and the country attractiveness for foreign investments, law-abiding economic operators, national consumers, State Budget and the Government ability to finance development projects, and the country at large suffer significantly. Research shows that over 50% of retail petrol stations in major agglomerations of Bangladesh sell adulterated fuels and/or cheat customers on the real volume of the fuel pumped into their vehicles. Other forms of detected fuel illicit trade practices include misdeclaration of fuel quantitative and qualitative parameters during internal transit and selling of non-declared and smuggled fuels. The aim of the study is to recommend the implementation of a National Fuel Distribution Integrity Program (FDIP) in Bangladesh to address and resolve fuel adulteration and illicit trade problems. The program should be customized according to the specific needs of the country and implemented in partnership with providers of advanced technologies. FDIP should enable and further enhance capacity of respective Bangladesh Government authorities in identification and elimination of all forms of fuel illicit trade swiftly and resolutely. FDIP high-technology, IT and automation systems and secure infrastructures should be aimed at the following areas (1) fuel adulteration, misdeclaration and non-declaration; (2) fuel quality and; (3) fuel volume manipulation at retail level. Furthermore, overall concept of FDIP delivery and its interaction with the reporting and management systems used by the Government shall be aligned with and support objectives of the Vision 2041 and Smart Bangladesh Government programs.

Keywords: fuel adulteration, octane, kerosene, diesel, petrol, pollution, carbon emissions

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Authors: Alvin Uchenna Ugwu

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The United Nation’s 2030 agenda and Global Action Programme (GAP) for implementation of the Sustainable Development Goals (SDGs), has mandated all sectors in the societies, including education, to develop strategies towards actualizing sustainability in all facets of the society, by the year 2030. Education is no doubt a key tool for social change. However, educational institutions in most African nations need a paradigmatic shift to strike a balance between policies (curricular) and practices, with regards to Education for Sustainable Development (ESD). The paradigm shift in this regard is described as whole-institution/school approach. The whole institution approaches advocate action-focused ESD. In other words, ESD policy and curriculum makers, formal and non-formal education institutions, need to ‘practice what they preach’. This paper is developed from an ongoing study carried out by the author and guided by two research questions: -What are the views of intermediate phase science and technology preservice teachers on the ESD content included in the science and technology modules? -What challenges or enable intermediate phase science and technology pre-service teachers to learn about ESD in science and technology modules? The study drew from the views and experiences of preservice science teachers, learning about ESD in a university’s college of education in South Africa. Using qualitative case study research design, the research data were generated via questionnaires and focus group discussions. Analysis of generated data indicates that universities and institutions of higher learning need to demonstrate practical involvement while implementing ESD in societies, rather than just standing as knowledge media. Findings of the study further suggest that natural sciences and technology courses in teacher education programmes and other institutions of higher learning, should be perceived as key transformative tools in shaping the consciousness of students towards integrating and fostering ESD in developing countries such as South Africa. Thus, this paper seeks to promote ‘Whole Institution Involvement’ in teacher education colleges in South Africa, as a measure of improving ESD in higher education settings. The paper suggests that in order to achieve ESD in higher education settings and beyond, policies and practices should be reexamined beyond rhetoric and buzzwords. The paper further argues that implementation of ESD is largely influenced by context, hence two different contexts should be examined empirically.

Keywords: education for sustainable development, higher education institutions, pre-service science teachers, qualitative case study research, whole institution involvement

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Authors: Kushal Patel, Manasa Dittakavi, Cyrus Falsafi, Gretchen Lovett

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Rural America has seen a surge in opioid addiction rates and overdose deaths in recent years, becoming a significant public health crisis. This may be due to a variety of factors, such as lack of access to healthcare or other economic and social factors that can contribute to addiction such as poverty, unemployment, and social isolation. As the opioid epidemic has disproportionately affected rural communities, pregnant women in these areas may be highly susceptible and face additional difficulties in facing the appropriate care they need. Opioid use disorder has many negative effects on prenatal infants. These include changes in their microbiome, mental health, neurodevelopment and cognition. These can affect how the child performs in various activities in life and how they interact with others. It has been demonstrated that using cognitive behavioral therapy improves not just pain-related results but also mobility, quality of life, disability, and mood outcomes. This indicates that cognitive behavioral therapy (CBT) may be a useful therapeutic strategy for enhancing general health and wellbeing in people with opioid use problems. In terms of treating psychiatric diseases, CBT carries fewer dangers than opioids. One study that illustrates the potential for CBT to promote a reduction in opioid use disorder used self-reported drug use patterns 6 months prior to and during their pregnancy. At the beginning of the study, participants reported an average of 3.78 drug or alcohol use days in the previous 28 days, which decreased to 1.63 days after treatment. The study also found a decrease in depression scores, as measured by IDS scores, from 23.9 to 17.1 at the end of treatment. These and other results show that CBT can have meaningful impacts on pregnant women in Rural America who struggle with an opioid use disorder. This project has been approved by the West Virginia School of Osteopathic Medicine- Office of Research and Sponsored Programs and deemed non-research scholarly work.

Keywords: appalachia, CBT, opiods, pregnancy

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Authors: Fernando Araujo, Sandra Cardoso, Fátima Fonseca, Sandra Cavaca

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A debureaucratization strategy for the Portuguese Health Service was assumed by the Executive Board of the SNS, in deep articulation with the Shared Services of the Ministry of Health. Two of the main dimensions were focused on sick leaves (SL), that transform primary health care (PHC) in administrative institutions, limiting access to patients. The self-declaration of illness (SDI) project, through the National Health Service Contact Centre (SNS24), began on May 1, 2023, and has already resulted in the issuance of more than 300,000 SDI without the need to allocate resources from the National Health Service (NHS). This political decision allows each citizen, in a maximum 2 times/year, and 3 days each time, if ill, through their own responsibility, report their health condition in a dematerialized way, and by this way justified the absence to work, although by Portuguese law in these first three days, there is no payment of salary. Using a digital approach, it is now feasible without the need to go to the PHC and occupy the time of the PHC only to obtain an SL. Through this measure, bureaucracy has been reduced, and the system has been focused on users, improving the lives of citizens and reducing the administrative burden on PHC, which now has more consultation times for users who need it. The second initiative, which began on March 1, 2024, allows the SL to be issued in emergency departments (ED) of public hospitals and in the health institutions of the social and private sectors. This project is intended to allow the user who has suffered a situation of acute urgent illness and who has been observed in an ED of a public hospital or in a private or social entity no longer need to go to PHC only to apply for the respective SL. Since March 1, 54,453 SLs have been issued, 242 in private or social sector institutions and 6,918 in public hospitals, of which 134 were in ED and 47,292 in PHC. This approach has proven to be technically robust, allows immediate resolution of problems and differentiates the performance of doctors. However, it is important to continue to qualify the proper functioning of the ED, preventing non-urgent users from going there only to obtain SL. Thus, in order to make better use of existing resources, it was operationalizing this extension of its issuance in a balanced way, allowing SL to be issued in the ED of hospitals only to critically ill patients or patients referred by INEM, SNS24, or PHC. In both cases, an intense public campaign was implemented to explain the way it works and the benefits for patients. In satisfaction surveys, more than 95% of patients and doctors were satisfied with the solutions, asking for extensions to other areas. The administrative simplification agenda of the NHS continues its effective development. For the success of this debureaucratization agenda, the key factors are effective communication and the ability to reach patients and health professionals in order to increase health literacy and the correct use of NHS.

Keywords: debureaucratization strategy, self-declaration of illness, sick leaves, SNS24

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Authors: Obaidul Fattah Tanvir, Zinat Ara Afroze

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Community living adjacent to forests and Protected Areas, especially in South Asian countries, have a common practice in extracting resources for their living and livelihoods. This extraction of resources, because the way it is done, destroys the biophysical features of the area. Deforestation, wildlife poaching, illegal logging, unauthorized hill cutting etc. are some of the serious issues of concern for the sustainability of the natural resources that has a direct impact on environment and climate as a whole. To ensure community involvement in conservation initiatives of the state, community based forest management, commonly known as Comanagement, has been in practice in 6 South Asian countries. These are -India, Nepal, Sri Lanka, Pakistan, Bhutan and Bangladesh. Involving community in forestry management was initiated first in Bangladesh in 1979 and reached as an effective co-management approach through a several paradigm shifts. This idea of Comanagement has been institutionalized through a Government Order (GO) by the Ministry of Environment and Forests, Government of Bangladesh on November 23, 2009. This GO clearly defines the structure and functions of Co-management and its different bodies. Bangladesh Forest Department has been working in association with community to conserve and manage the Forests and Protected areas of Bangladesh following this legal document. Demographically young people constitute the largest segment of population in Bangladesh. This group, if properly sensitized, can produce valuable impacts on the conservation initiatives, both by community and government. This study traced the major factors that motivate community youths to work effectively with different tiers of comanagement organizations in conservation of forests and Protected Areas of Bangladesh. For the purpose of this study, 3 FGDs were conducted with 30 youths from the community living around the Protected Areas of Cox’s bazar, South East corner of Bangladesh, who are actively involved in Co-management organizations. KII were conducted with 5 key officials of Forest Department stationed at Cox’s Bazar. 2 FGDs were conducted with the representatives of 7 Co-management organizations working in Cox’s Bazar region and approaches of different community outreach activities conducted for forest conservation by 3 private organizations and Projects have been reviewed. Also secondary literatures were reviewed for the history and evolution of Co-management in Bangladesh and six South Asian countries. This study found that innovative community outreach activities that are financed by public and private sectors involving youths and community as a whole have played a pivotal role in conservation of forests and Protected Areas of the region. This approach can be replicated in other regions of Bangladesh as well as other countries of South Asia where Co-Management exists in practice.

Keywords: community, co-management, conservation, forests, protected areas, youth

Procedia PDF Downloads 259