Search results for: big health data

Authors: Danika Tynes

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Innovations in technology have implications for sustainable development in health and wellness. Remote monitoring is one innovation for which the evidence-base has grown to support its viability as a quality healthcare delivery adjunct. This research reviews global data on telehealth adoption, in particular, remote monitoring, and the conditions under which its success becomes more likely. System-level indicators were selected to represent four constructs of DoI theory (relative advantage, compatibility, complexity, and observability) and assessed against 5 types of Telehealth (Teleradiology, Teledermatology, Telepathology, Telepsychology, and Remote Monitoring) using ordinal logistic regression. Analyses include data from 84 countries, as extracted from the World Health Organization, World Bank, ICT (Information Communications Technology) Index, and HDI (Human Development Index) datasets. Analyses supported relative advantage and compatibility as the strongest influencers of remote monitoring adoption. Findings from this research may help focus on the allocation of resources, as a sustainability concern, through consideration of systems-level factors that may influence the success of remote monitoring adoption.

Keywords: remote monitoring, diffusion of innovation, telehealth, digital health

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Authors: Eduardo Costa

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Hospital strikes in the Portuguese National Health Service (NHS) are becoming increasingly frequent, raising concerns in what respects patient safety. In fact, data shows that mortality rates for patients admitted during strikes are up to 30% higher than for patients admitted in other days. This paper analyses the effects of hospital strikes on patients’ outcomes. Specifically, it analyzes the impact of different strikes (physicians, nurses and other health professionals), on in-hospital mortality rates, readmission rates and length of stay. The paper uses patient-level data containing all NHS hospital admissions in mainland Portugal from 2012 to 2017, together with a comprehensive strike dataset comprising over 250 strike days (19 physicians-strike days, 150 nurses-strike days and 50 other health professionals-strike days) from 135 different strikes. The paper uses a linear probability model and controls for hospital and regional characteristics, time trends, and changes in patients’ composition and diagnoses. Preliminary results suggest a 6-7% increase in in-hospital mortality rates for patients exposed to physicians’ strikes. The effect is smaller for patients exposed to nurses’ strikes (2-5%). Patients exposed to nurses strikes during their stay have, on average, higher 30-days urgent readmission rates (4%). Length of stay also seems to increase for patients exposed to any strike. Results – conditional on further testing, namely on non-linear models - suggest that hospital operations and service levels are partially disrupted during strikes.

Keywords: health sector strikes, in-hospital mortality rate, length of stay, readmission rate

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Authors: Billy Zou

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Statement of the Problem: The burden of mental illness and problem behaviors in adolescence has risen worldwide. While less than 50% of teens have access to traditional mental health care, more than 73% have smartphones. Internet-based interventions offer advantages such as cost-effectiveness, availability, and flexibility. Methodology & Theoretical Orientation: A literature review was done using a PubMed search with the words mental health app yielding 2113 results. 103 articles that met inclusion criteria were reviewed, and findings were then described and synthesized. Findings: 1. Computer-based CBT was found to be effective for OCD, depression, social phobia, and panic disorder. 2. Web-based psychoeducation reduced problem behavior and improved parental well-being. 3. There is limited evidence for mobile-phone-based apps, but preliminary results suggest computer-based interventions are transferrable to mobile apps. 4. Adherence to app-based treatment was correlated with impressions about the user interface Conclusion & Significance: There is evidence for the effectiveness of computer-based programs in filling the significant gaps that currently exist in mental health delivery in the United States and internationally. There is also potential and theoretical validity for mobile-based apps to do the same, though more data is needed.

Keywords: children's mental health, mental health app, child and adolecent psychiatry, digital therapy

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Authors: Junita Batubara

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Children with special needs, especially those with disability in mental, physical or social/emotional interactions, are marginalized. Many people still view them as troublesome, inconvenience, having learning difficulties, unproductive and burdensome to society. This study intends to investigate; how musical drama can develop the ability to control the coordination of mental functions; how musical dramas can assist children to work together; how musical dramas can assist to maintain the child's emotional and physical health; how musical dramas can improve children creativity. The objectives of the research are: To know whether musical drama can control the coordination of mental function of children; to know whether musical drama can improve communication ability and expression of children; to know whether musical drama can help children work with people around them; to find out if musical dramas can develop the child's emotional and physical health; to find out if musical drama can improve children's creativity. The study employed a qualitative research approach. Data was collecting by listening, observing in depth through public hearings that select the key informants who were teachers and principals, parents and children. The data obtained from each public hearing was then processed (reduced), conclusion drawing/verification, presentation of data (data display). Furthermore, the model obtained was implementing for musical performance, where the benefits of the show are: musical drama can improve language skills; musical dramas are capable of developing memory and storage of information; developing communication skills and express themselves; helping children work together; assisting emotional and physical health; enhancing creativity.

Keywords: children Down syndrome, music, drama script, performance

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Authors: Julio Albuja, David Zaldumbide

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Data analysis is an important step before taking a decision about money. The aim of this work is to analyze the factors that influence the final price of the houses through data mining algorithms. To our best knowledge, previous work was researched just to compare results. Furthermore, before using the data of the data set, the Z-Transformation were used to standardize the data in the same range. Hence, the data was classified into two groups to visualize them in a readability format. A decision tree was built, and graphical data is displayed where clearly is easy to see the results and the factors' influence in these graphics. The definitions of these methods are described, as well as the descriptions of the results. Finally, conclusions and recommendations are presented related to the released results that our research showed making it easier to apply these algorithms using a customized data set.

Keywords: algorithms, data, decision tree, transformation

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Authors: Haruna Modibbo Usman, Mustapha Muktar, Nasiru Inuwa

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This paper examined the long run relationship between health outcomes and economic growth in Nigeria from 1961 to 2012. Using annual time series data, Augmented Dickey-Fuller (ADF) test is conducted to check the stochastic properties of the variables. Also, the long run relationship among the variables is confirmed based on Johansen Multivariate Cointegration approach whereas the long run and short run dynamics are observed using Vector Error Correction Mechanism (VECM). In addition, VEC Granger causality test is employed to examine the direction of causality among the variables. On the whole, the results obtained revealed the existence of a long run relationship between health outcomes and economic growth in Nigeria and that both life expectancy and crude death rate as measures of health are found to have a long run negative and statistically significant impact on the economic growth over the study period. This is further buttressed by the results of Granger causality test which indicated the existence of unidirectional causality running from life expectancy and crude death rate to economic growth. The study therefore, calls for governments at various levels to create preconditions for health improvements in Nigeria in order to boost the level of health outcomes.

Keywords: cointegration, economic growth, Granger causality, health outcomes, VECM

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Authors: Meng Qing Feng, Otsile Morake

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Background: Successful implementation of the COVID-19 vaccination ensures the prevention of virus infection. Postponement and refusal of the vaccination will threaten public health, which is now common among the general public across the world. In addition, an acceptance of the COVID-19 vaccine appears as a decisive factor in controlling the COVID-19 pandemic. Purpose: This study's objective is to explore the factors influencing the public intention to be vaccinated (ITBV). Design/methodology/approach: The web-based survey included socio-demographics and questions related to the theory of planned behavior (TPB) and the health belief model (HBM). An online survey was administered using Google Form to collect data from participants of Botswana. The sample included 339 participants, half-half of the participants were female. Data analysis was run using the Statistical Package for the Social Sciences (SPSS). Findings: The study results highlight that perceived severity, perceived barriers, health motivation, and attitude have a positive and significant effect on ITBV, while perceived susceptibility, benefits, subjective norms, and perceived behavior control do not affect ITBV. Among all of the predictors, perceived barriers have the most significant influence on ITBV. Conclusion: Theoretically, this research stated that both HBM and TPB are effective in predicting and explaining the general public ITBV. Practically, this study offers insights to the government and health departments to arrange and launch health awareness programs and provide a better guide to vaccination so that doubts about vaccine confidence and the level of uncertainty can be decreased.

Keywords: COVID-19, Omicron, intention to be COVID-19 vaccine, health behavior model, theory of planned behavior, Botswana

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Authors: Nadia Fatima Zahra Malki

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Quality is one of the most important modern management patterns that organizations seek to achieve in all areas and sectors in order to meet the needs and desires of customers and to remain and continuity, as they constitute a competitive advantage for the organization. and among the most prominent organizations that must be available on the quality factor are health organizations as they relate to the most valuable component of production. It is a person, and his health, and any error in it threatens his life and may lead to death, so she must provide health services of high quality to achieve the highest degree of satisfaction for the patient. This research aims to study the quality of health services and the extent of their impact on patient satisfaction, and this is through an applied study that relied on measuring the level of quality of health services in the university hospital center of Algeria and the extent of their impact on patient satisfaction according to the dimensions of the quality of health services, and we reached a conclusion that the determinants of the quality of health services It affects patient satisfaction, which necessitates developing health services according to patients' requirements and improving their quality to obtain patient satisfaction.

Keywords: health service, health quality, quality determinants, patient satisfaction

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Authors: K. Y. S. Putri, Heri Fathurahman, Yuki Surisita, Widi Sagita, Kiki Dwi Arviani

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Society needs the assistance of academics in understanding and being skilled in health communication literacy. Information technology runs very fast while health communication literacy skills in getting health communication information during the pandemic are not as fast as the development of information technology. The research question is whether there is an influence of health communication on information technology in health information during the pandemic in Indonesia. The purpose of the study is to find out the influence of health communication on information technology in health information during the pandemic in Indonesia. The concepts of health communication literacy and information technology are used this study. Previous research is in support of this study. Quantitative research methods by disseminating questionnaires in this study. The validity and reliability test of this study is positive, so it can proceed to the next statistical analysis. Descriptive results of variable health communication literacy are of positive value in all dimensions. All dimensions of information technology are of positive value. Statistical tests of the influence of health communication literacy on information technology are of great value. Discussion of both variables in the influence of health communication literacy and high-value information technology because health communication literacy has a high effect in information technology. Respondents to this study have high information technology skills. So that health communication literacy in obtaining health information during the 2019-2022 pandemic is needed. Research advice is that academics are still very much needed by the community in the development of society during the pandemic.

Keywords: health information, health information needs, literacy health communication, information technology

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Authors: Daniel Walker, Adam Qureshi, David Marchant, Alex Bahrami Balani

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The present study aimed to assess the impact of concussion and physical pain on depression and health-related quality of life. Depressive symptoms were assessed using the Center for Epidemiological Studies' Depression Scale, and scores of health-related quality of life were measured by health-related quality of life short form-12. Data analysis of 67 participants (concussed 32 vs. 35 non-concussed) revealed that (i) 52% were displaying depressive symptoms (concussed 30% vs. non-concussed 22%) (ii) concussion had a significant effect on depressive symptoms when controlling for pain but no effect on the quality of life scores when controlling the same variable (iii) pain had a significant effect on depressive symptoms and quality of life. With this, both concussion and physical pain seem to have a negative impact on mental health; however, individuals may only recognise a reduction in quality of life with increased physical pain, hence a deterioration in mental well-being could be disregarded as a factor of health-related quality of life.

Keywords: depression, quality of life, concussion, physical pain

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Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi

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This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control

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Authors: Deinzel R. Uezono, Vivien Fe F. Fadrilan-Camacho, Bianca Margarita L. Medina, Antonio Domingo R. Reario, Trisha M. Salcedo, Luke Wesley P. Borromeo

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The environment of health care workers is considered one of the most hazardous settings due to the nature of their work. In developing countries especially, the Philippines, this continues to be overlooked in terms of programs and services on occupational health and safety (OHS). One possible reason for this is the existing information gap on OHS which limits data comparability and impairs effective monitoring and assessment of interventions. To address this gap, there is a need to determine the current conditions of Filipino health care workers in their workplace. This descriptive cross-sectional study assessed the occupational health and safety conditions of health care workers in barangay health centers in a selected city in Metro Manila, Philippines by: (1) determining the hazards present in the workplace; (2) determining the most common self-reported medical problems; and (3) describing the elements of an OHS system based on the six building blocks of health system. Assessment was done through walkthrough survey, self-administered questionnaire, and key informant interview. Data analysis was done using Epi Info 7 and NVivo 11. Results revealed different health hazards present in the workplace particularly biological hazards (exposure to sick patients and infectious specimens), physical hazards (inadequate space and/or lighting), chemical hazards (toxic reagents and flammable chemicals), and ergonomic hazards (activities requiring repetitive motion and awkward posture). Additionally, safety hazards (improper capping of syringe and lack of fire safety provisions) were also observed. Meanwhile, the most commonly self-reported chronic diseases among health care workers (N=336) were hypertension (20.24%, n=68) and diabetes (12.50%, n=42). Top commonly self-reported symptoms were colds (66.07%, n=222), coughs (63.10%, n=212), headache (55.65%, n=187), and muscle pain (50.60%, n=170) while other diseases were influenza (16.96%, n=57) and UTI (15.48%, n=52). In terms of the elements of the OHS system, a general policy on occupational health and safety was found to be lacking and in effect, an absence of health and safety committee overseeing the implementing and monitoring of the policy. No separate budget specific for OHS programs and services was also found to be a limitation. As a result, no OHS personnel and trainings/seminar were identified. No established information system for OHS was in place. In conclusion, health and safety hazards were observed to be present across the barangay health centers visited in a selected city in Metro Manila. Medical conditions identified as most commonly self-reported were hypertension and diabetes for chronic diseases; colds, coughs, headache, and muscle pain for medical symptoms; and influenza and UTI for other diseases. As for the elements of the occupational health and safety system, there was a lack in the general components of the six building blocks of the health system.

Keywords: health hazards, occupational health and safety, occupational health and safety system, safety hazards

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Authors: Mengdi Zhang, Zhenji Gao, Ning Kang, Rongmei Liu

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Management and application of geological big data is an important part of China's national big data strategy. With the implementation of a national big data strategy, geological big data management becomes more and more critical. At present, there are still a lot of technology barriers as well as cognition chaos in many aspects of geological big data management and application, such as data sharing, intellectual property protection, and application technology. Therefore, it’s a key task to make better use of new technologies for deeper delving and wider application of geological big data. In this paper, we briefly introduce the basic principle of blockchain technology at the beginning and then make an analysis of the application dilemma of geological data. Based on the current analysis, we bring forward some feasible patterns and scenarios for the blockchain application in geological big data and put forward serval suggestions for future work in geological big data management.

Keywords: blockchain, intellectual property protection, geological data, big data management

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Authors: E. Bennion, A. Acharya, S. Barnes, D. Ferrell, S. Luckett-Cole, G. Mower, J. Nelson, Y. Nguyen

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Objective: This study aimed to evaluate the validity of a firearm injury query in the Early Notification of Community-based Epidemics syndromic surveillance system. Syndromic surveillance data are used at the Utah Department of Health for early detection of and rapid response to unusually high rates of violence and injury, among other health outcomes. The query of interest was defined by the Centers for Disease Control and Prevention and used chief complaint and discharge diagnosis codes to capture initial emergency department encounters for firearm injury of all intents. Design: Two epidemiologists manually reviewed electronic health records of emergency department visits captured by the query from April-May 2020, compared results, and sent conflicting determinations to two arbiters. Results: Of the 85 unique records captured, 67 were deemed probable, 19 were ruled out, and two were undetermined, resulting in a positive predictive value of 75.3%. Common reasons for false positives included non-initial encounters and misleading keywords. Conclusion: Improving the validity of syndromic surveillance data would better inform outbreak response decisions made by state and local health departments. The firearm injury definition could be refined to exclude non-initial encounters by negating words such as “last month,” “last week,” and “aftercare”; and to exclude non-firearm injury by negating words such as “pellet gun,” “air gun,” “nail gun,” “bullet bike,” and “exit wound” when a firearm is not mentioned.

Keywords: evaluation, health information system, firearm injury, syndromic surveillance

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Authors: Herawati Tri Siswati, Nurhidayat Ana Sıdık Fatimah

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The Indonesia Basic Health Research, 2013 showed that prevalence of stunting of 6–12 children years old was 35,6%, wasting was 12,2% and obesiy was 9,2%. The Indonesian Goverment have School Health Program, held in coordination, plans, directing and responsible, developing and implement health student. However, it's implementation still under expected, while Indonesian Ministry of Health has initiated the School Health Program acceleration. This aimed is to know the influencing of training to knowledge and skill of elementary school teacher about measurement and assesment nutrirional status children. The research is quasy experimental with pre-post design, in Sleman disctrict, Yogyakarta province, Indonesia, 2015. Subject was all of elementary school teacher’s who responsible in School Health Program in Gamping sub-district, Sleman, Yogyakarta, i.e. 32 persons. The independent variable is training, while the dependent variable are teacher’s klowledge and skill on measurement and assesment nutrirional status children. The data was analized by t-test. The result showed that the knowledge score before training is 31,6±9,7 and after 56,4±12,6, with an increase 24,8±15,7, and p=0.00. The skill score before training is 46,6±11,1 and after 61,7±13, with an increase 15,2±14,2, p = 0.00. Training can increase the teacher’s klowledge and skill on measurement and assesment nutrirional status.

Keywords: training, school health program, nutritional status, children.

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Authors: Antonio Lopez-Villegas, Daniel Catalan-Matamoros, Remedios Lopez-Liria

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Objectives: The purpose of this study was to analyze clinical data, health-related quality of life (HRQoL) and functional capacity of patients using a telemonitoring follow-up system (TM) compared to patients followed-up through standard outpatient visits (HM) 5 years after the implantation of a pacemaker. Methods: This is a controlled, non-randomised, nonblinded clinical trial, with data collection carried out at 5 years after the pacemakers implant. The study was developed at Hospital de Poniente (Almeria, Spain), between October 2012 and November 2013. The same clinical outcomes were analyzed in both follow-up groups. Health-Related Quality of Life and Functional Capacity was assessed through EuroQol-5D (EQ-5D) questionnaire and Duke Activity Status Index (DASI) respectively. Sociodemographic characteristics and clinical data were also analyzed. Results: 5 years after pacemaker implant, 55 of 82 initial patients finished the study. Users with pacemakers were assigned to either a conventional follow-up group at hospital (HM=34, 50 initials) or a telemonitoring system group (TM=21, 32 initials). No significant differences were found between both groups according to sociodemographic characteristics, clinical data, Health-Related Quality of Life and Functional Capacity according to medical record and EQ5D and DASI questionnaires. In addition, conventional follow-up visits to hospital were reduced in 44,84% (p < 0,001) in the telemonitoring group in relation to hospital monitoring group. Conclusion: Results obtained in this study suggest that the telemonitoring of users with pacemakers is an equivalent option to conventional follow-up at hospital, in terms of Health-Related Quality of Life and Functional Capacity. Furthermore, it allows for the early detection of cardiovascular and pacemakers-related problem events and significantly reduces the number of in-hospital visits. Trial registration: ClinicalTrials.gov NCT02234245. The PONIENTE study has been funded by the General Secretariat for Research, Development and Innovation, Regional Government of Andalusia (Spain), project reference number PI/0256/2017, under the research call 'Development and Innovation Projects in the Field of Biomedicine and Health Sciences', 2017.

Keywords: cardiovascular diseases, health-related quality of life, pacemakers follow-up, remote monitoring, telemedicine

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Authors: Jia-Jin He, Tzu-Yuan Stessa Chao

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It is generally accepted that community residents with abundant open space have better health status on average, and thus more and more cities around the world began their pursuit of the greatest possible amount of green space within urban areas through urban planning approach. Nevertheless, only a few studies managed to provide empirical evidence regarding the actual relationship between 'providing' green space and 'improving' human health at city level. There is also lack of evidence of direct positive improvement of health by increasing the amount of green space. For urban planning professional, it is important to understand citizens’ usage behaviour towards green space as a critical evidence for future planning and design strategies. There is a research need to further investigate the amount of green space, user behaviour of green spaces and the health outcome of urban dwellers. To this end, we would like to find out other important factors for urban dwellers’ usage behaviours of green spaces. 'Average green spaces per person' is one of the National well-being Indicators in Taiwan as in many other countries. Through our preliminary research, we collected and analyzed the official data of planned open space coverages, average life expectancy, exercise frequency and obesity ratio in all cities of Taiwan. The study result indicates an interesting finding that Kaohsiung city, the second largest city in Taiwan, tells a completely different story. Citizens in Kaosiung city have more open spaces than any other city through urban planning, yet have relatively unhealthy condition in contrary. Whether it pointed out that the amount of the open spaces per person has would not direct to the health outcome. Therefore, the pre-established view which states that open spaces must have positive effects on human health should be examined more prudently. Hence, this paper intends to explore the relationship between user behaviour of open spaces and citizens’ health conditions by critically analyzing past related literature and collecting selective data from government health database in 2015. We also take Kaohsiung city, as a case study area to conduct statistical analysis first followed by questionnaire survey to gain a better understanding. Finally, we aim to feedback our findings to the current planning system in Taiwan for better health promotion urbanized areas.

Keywords: open spaces, urban planning systems, healthy cities, health outcomes

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Authors: David P. Horton, Gary Lynch-Wood

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Western populations are aging, prone to various lifestyle health problems, and increasing their demand for health and social care services. This demand has created enormous fiscal and regulatory challenges. In response, government institutions have deployed strategies of behavior modification to encourage people to exercise greater personal responsibility over their health and care needs (i.e., welfare responsibilisation). Policy strategies are underpinned by the assumption that people if properly supported, will make better health and lifestyle selections. Not only does this absolve governments of the responsibility for meeting all health and care needs, but it also enables government institutions to assert fiscal control over welfare spending. Looking at the regulation of health and social care in the UK, the authors identify and outline a suite of regulatory tools that are designed to extract and manage the resources of health and social care services users and to encourage them to make (‘better’) use of these resources. This is important for our understanding of how health and social care regulation is responding to ongoing social and economic challenges. It is also important because there has been a failure to systematically examine the relevance of resources for regulation, which is surprising given that resources are crucial to how and whether regulation succeeds or fails. In particular, drawing from the regulatory welfare state concept, the authors analyse the key legal and regulatory changes and mechanisms that have been introduced since the 2008 financial crisis, focusing on critical measures such as the Health and Social Care Act and regulations introduced under the National Health Service Act. The authors show how three types of user resources (i.e., tangible, labor, and data) are being used to assert fiscal control and increase welfare responsibilisation. Amongst other things, the paper concludes that service users have become more than rule followers and targets of behavioral modification; rather, they are producers of resources that regulatory systems have come to rely on.

Keywords: health care, regulation, resources, social care

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Authors: Denis Özdemir, Max Senges

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There are many examples of AI-supported apps for better health and wellbeing. Generally, these applications help people to achieve their goals based on scientific research and input data. Still, they do not always explain how those three are related, e.g. by making implicit assumptions about goals that hold for many but not for all. We present a seven-step method for designing health and wellbeing AIs considering goal setting, measurable results, real-time indicators, analytics, visual representations, communication, and feedback. It can help engineers as guidance in developing apps, recommendation algorithms, and interfaces that support humans in their decision-making without patronization. To illustrate the method, we create a recommender AI for tiny wellbeing habits and run a small case study, including a survey. From the results, we infer how people perceive the relationship between them and the AI and to what extent it helps them to achieve their goals. We review our seven-step engineering method and suggest modifications for the next iteration.

Keywords: recommender systems, natural language processing, health apps, engineering methods

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Authors: Namrata Mishra

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Health of a person plays a vital role in the collective health of his community and hence the well-being of the society as a whole. But, in today’s fast paced technology driven world, health issues are increasingly being associated with human behaviors – their lifestyle. Social networks have tremendous impact on the health behavior of individuals. Many researchers have used social network analysis to understand human behavior that implicates their social and economic environments. It would be interesting to use a similar analysis to understand human behaviors that have health implications. This paper focuses on concepts of those behavioural analyses that have health implications using social networks analysis and provides possible algorithmic approaches. The results of these approaches can be used by the governing authorities for rolling out health plans, benefits and take preventive measures, while the pharmaceutical companies can target specific markets, helping health insurance companies to better model their insurance plans.

Keywords: breadth first search, directed graph, health behaviors, social network analysis

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Authors: Elaine Wong

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This research protocol aims to explore and justify the need for nutrition and physical activity intervention to improve health outcomes among SME (Small Medium Enterprise) employees. It was found that the worksite is an ideal and convenient setting for employees to take charge of their health thru active participation in health programmes since they spent a great deal of time at their workplace. This study will examine the impact of both general or/and targeted health interventions in both SME and non-SME companies utilizing the Workplace Health Promotion (WHP) grant over a 12 months period and assessed the improvement in chronic health disease outcomes in Singapore. Random sampling of both non-SME and SME companies will be conducted to undergo health intervention and statistical packages such as Statistical Package for Social Science (SPSS) 25 will be used to examine the impact of both general and targeted interventions on employees who participate and those who do not participate in the intervention and their effects on blood glucose (BG), blood lipid, blood pressure (BP), body mass index (BMI), and body fat percentage. Using focus groups and interviews, the data results will be transcribed to investigate enablers and barriers to workplace health intervention revealed by employees and WHP coordinators that could explain the variation in the health screening results across the organisations. Dietary habits and physical activity levels of the employees participating and not participating in the intervention will be collected before and after intervention to assess any changes in their lifestyle practices. It makes economic sense to study the impact of these interventions on health screening outcomes across various organizations that are existing grant recipients to justify the sustainability of these programmes by the local government. Healthcare policy makers and employers can then tailor appropriate and relevant programmes to manage these escalating chronic health disease conditions which is integral to the competitiveness and productivity of the nation’s workforce.

Keywords: chronic diseases, health screening, nutrition and fitness intervention , workplace health

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Authors: Henry Venter, Murali Thyloth, Alceu Casseb

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Historically, mental and substance use disorders were not a global health priority. Since the 1993 World Development Report, the importance of the contribution of mental health and substance abuse on the relative global burden associated with disease morbidity has been recognized with 300 million people worldwide suffering from depression alone. This led to an international effort to improve the mental health of populations around the world. Despite these efforts some countries remain at the top of the list of countries with the highest rate of mental illness. Important research questions were asked: Would there be commonalities regarding mental health between these countries; would there be common factors leading to the high prevalence of mental illness; and how prepared are these countries with mental health delivery? Findings from this research can aid organizations and institutions preparing mental health service providers to focus training and preparation to address specific needs revealed by the study. Methods: Researchers decided to compare three distinctly different countries at the top of the list of countries with the highest rate of mental illness, the USA, India and Brazil, situated on three different continents with different economies and lifestyles. Data were collected using archival research methodology, reviewing records and findings of international and national health and mental health studies to subtract and compare data and findings. Results: The findings indicated that India is the most depressed country in the world, followed by the USA (and China) with Brazil in Latin America with the greatest number of depressed individuals. By 2020 roughly 20% of India, acountry of over one billion citizens, will suffer from some form of mental illnees, yet there are less than 4,000 experts available. In the USA 164.8 million people were substance abusers and an estimate of 47.6 million adults, 18 or older, had any mental illness in 2018. That means that about one in five adults in the USA experiences some form of mental illness each year, but only 41% of those affected received mental health care or services in the past year. Brazil has the greatest number of depressed individuals, in Latin America. Adults living in Sao Paulo megacity has prevalence of mental disorders at greater levels than similar surveys conducted in other areas of the world with more than one million adults with serious impairment levels. Discussion: The results show that, despite the vast socioeconomic differences between the three countries, there are correlations regarding mental health prevalence and difficulty to provide adequate services including a lack of awareness of how serious mental illness is, stigma for seeking mental illness, with comorbidity a common phenomenon, and a lack of partnership between different levels of service providers, which weakens mental health service delivery. The findings also indicate that mental health training institutions have a monumental task to prepare personnel to address the future mental health needs in each of the countries compared, which will constitute the next phase of the research.

Keywords: mental health epidemiology, mental health disorder, mental health prevalence, mental health treatment

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Authors: Tamanna Jethava, Rahul Joshi

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Frequent Item sets play an essential role in many data Mining tasks that try to find interesting patterns from the database. Typically it refers to a set of items that frequently appear together in transaction dataset. There are several mining algorithm being used for frequent item set mining, yet most do not scale to the type of data we presented with today, so called “BIG DATA”. Big Data is a collection of large data sets. Our approach is to work on the frequent item set mining over the large dataset with scalable and speedy way. Big Data basically works with Map Reduce along with HDFS is used to find out frequent item sets from Big Data on large cluster. This paper focuses on using pre-processing & mining algorithm as hybrid approach for big data over Hadoop platform.

Keywords: frequent item set mining, big data, Hadoop, MapReduce

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Authors: Tebeu Pierre Marie

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Introduction: WHO defines community participation as a process in which the local population, take responsibility in planning for their health, participates in the strategy’s development for implementation and accessibility to physical, moral and social well-being. For the purpose of dealing with health, the community participation is made through the organization called health Centre committee leader (HCCL/COSA) for Integrated health Center and District hospital committee leaser (HDCL/COGES) for District Hospital. Little is known about the effective participation of the community in health related activities in Ignié-Ngabé-Mayama health district. Objective: This study aimed at assessing the involvement of community in the health system running at the Ignié-Ngabé-Mayama health district. Methods: This was a qualitative cross-sectional study conducted in the Ignié-Ngabé-Mayama health district from 15 December 2020 to 30 April 2021. The study population consisted of 10 HCCL and one District hospital committee leaser (DHCL). Data were collected using a pretested questionnaire and validated by the investigating team. The variables of interest were; effective existence of HCCL/DHCL, their involvement HCCL/DHCL in health related activities, their financing management, planning of activities and leadership. Results: A total of 11 participants were interviewed, including 10 HCCL and 1 DHCL. The Sex-Ratio was 9/11; with primary level 6/11 and were mostly farmers 6/11. Analyzing the involvement of the HDCL/DHCL in health promotion and preventive activities; this was effective only for two of them (2/11). Analyzing the barriers for their involvement, the leaders reported the lack of financial support by the state, lack NGO support. Additionally, they reported to have been very active when there was Performance Based Founding Project in the District. Conclusion: Only two of the (HDCL/HCCL) out of 11 were really functioning. Reported barriers to their running were: lack of state/NGOs support and ending of PBF Project. There is a need to organize a tripartite forum including stats, NGOs and Community for boosting the community participation in health related activities in Ignié-Ngabé-Mayama health district.

Keywords: health district committee, health Centre committee, community participation, Brazzaville, Congo

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Authors: W. Rowan, Y. O’Connor, L. Lynch, C. Heavin

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Situation Awareness can offer the potential for conscious dynamic reflection. In an era of online health data sharing, it is becoming increasingly important that users of health social networks (HSNs) have the information necessary to make informed decisions as part of the registration process and in the provision of eConsent. This research aims to leverage an adapted Situation Awareness (SA) model to explore users’ decision making processes in the provision of eConsent. A HSN platform was used to investigate these behaviours. A mixed methods approach was taken. This involved the observation of registration behaviours followed by a questionnaire and focus group/s. Early results suggest that users are apt to automatically accept eConsent, and only later consider the long-term implications of sharing their personal health information. Further steps are required to continue developing knowledge and understanding of this important eConsent process. The next step in this research will be to develop a set of guidelines for the improved presentation of eConsent on the HSN platform.

Keywords: eConsent, health social network, mixed methods, situation awareness

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Authors: Bishoy Abouelsoud Saad Amin

Abstract:

This paper examines the use of computer and its related health hazard among computer users in South-Western zone of Nigeria. Two hundred and eighteen (218) computer users constituted the population used to evaluate association between posture, extensive computer use and related health hazard. The instruments for the study are a questionnaire on demographics, lifestyle, body features and work ability index while mean rating, standard deviation and t test were used for data analysis. Identified health related hazard include damages to the eyesight, bad posture, arthritis, musculoskeletal disorders, headache, stress and so on. The results showed that factors such as work demand, posture, closeness to computer screen and excessive working hours on computers constitute health hazards in both old and young computer users of various gender. It is therefore recommended that total number of hours spent with computer should be monitored and controlled.

Keywords: computer game, metaphor, middle school students, virtual environments computer auditing, risk, measures to prevent, information management computer-related health hazard, musculoskeletal disorders, computer usage, work ability index

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Authors: Joseph K. A. Johnson

Abstract:

Hypertension affects 20 percent of the people within the ages 55 upward in Ghana. Of these, almost one-third are unaware of their condition. Also at the age of 55, more men turned to have hypertension than women. After that age, the condition becomes more prevalent with women. Hypertension is significantly more common in African Americans of both sexes than the racial or ethnic groups. This study was conducted to determine the causes of high blood pressure in Ashanti Region, Ghana. The study employed One Hundred and Seventy (170) respondents. The sample population for the study was all the available respondents at the time of the data collection. The research was conducted using primary data where convenience sampling was used to locate the respondents. A set of questionnaire were used to gather the data for the study. The gathered data was analysed using principal component analysis. The study revealed that, personal description, lifestyle behavior and risk awareness as some of the causes of high blood pressure in Ashanti Region. The study therefore recommend that people must be advice to see to their personal characteristics that may contribute to high blood pressure such as controlling of their temper and how to react perfectly to stressful situations. They must be educated on the factors that may increase the level of their blood pressure such as the essence of seeing a medical doctor before taking in any drug. People must also be made known by the public health officers to those lifestyles behaviour such as smoking and drinking of alcohol which are major contributors of high blood pressure.

Keywords: high blood pressure, principal component analysis, hypertension, public health

Procedia PDF Downloads 473

Authors: Allmin Susaiyah, Aki Härmä, Milan Petković

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Automatic generation of insights from data using insight mining systems (IMS) is useful in many applications, such as personal health tracking, patient monitoring, and business process management. Existing IMS face challenges in controlling insight extraction, scaling to large databases, and generalising to unseen domains. In this work, we propose a hybrid approach consisting of rule-based and neural components for generating insights from data while overcoming the aforementioned challenges. Firstly, a rule-based data 2CNL component is used to extract statistically significant insights from data and represent them in a controlled natural language (CNL). Secondly, a BERTSum-based CNL2NL component is used to convert these CNLs into natural language texts. We improve the model using task-specific and domain-specific fine-tuning. Our approach has been evaluated using statistical techniques and standard evaluation metrics. We overcame the aforementioned challenges and observed significant improvement with domain-specific fine-tuning.

Keywords: data mining, insight mining, natural language generation, pre-trained language models

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Authors: Akiode Ayobami, Akiode Akinsewa, Odeku Mojisola, Salako Busola, Odutolu Omobola, Nuhu Khadija

Abstract:

Purpose: Evidence exists that family planning use can contribute to reduction in infant and maternal mortality in any country. Despite these benefits, contraceptive use in Nigeria still remains very low, only 10% among married women. Understanding factors that predict contraceptive use is very important in order to improve the situation. In this paper, we analysed data from the 2013 Nigerian Demographic and Health Survey (NDHS) to better understand predictors of contraceptive use in Nigeria. The use of logistics regression and other traditional models in this type of situation is not appropriate as they do not account for social structure influence brought about by the hierarchical nature of the data on response variable. We therefore used multilevel modelling to explore the determinants of contraceptive use in order to account for the significant variation in modern contraceptive use by socio-demographic, and other proximate variables across the different Nigerian states. Method: This data has a two-level hierarchical structure. We considered the data of 26, 403 married women of reproductive age at level 1 and nested them within the 36 states and the Federal Capital Territory, Abuja at level 2. We modelled use of modern contraceptive against demographic variables, being told about FP at health facility, heard of FP on TV, Magazine or radio, husband desire for more children nested within the state. Results: Our results showed that the independent variables in the model were significant predictors of modern contraceptive use. The estimated variance component for the null model, random intercept, and random slope models were significant (p=0.00), indicating that the variation in contraceptive use across the Nigerian states is significant, and needs to be accounted for in order to accurately determine the predictors of contraceptive use, hence the data is best fitted by the multilevel model. Only being told about family planning at the health facility and religion have a significant random effect, implying that their predictability of contraceptive use varies across the states. Conclusion and Recommendation: Results showed that providing FP information at the health facility and religion needs to be considered when programming to improve contraceptive use at the state levels.

Keywords: multilevel modelling, family planning, predictors, Nigeria

Procedia PDF Downloads 407

Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

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Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: data mining, data analysis, prediction, optimization, building operational performance

Procedia PDF Downloads 838