bluuebunny/crossref_metadata_2025 huggingface dataset:
Mental Health Study and Psychological Factors Impacting the Behaviour Among College Students in India
Authors: Chhabda Dr. Parvindar Kaur , Sandilya Ranjit
Published: September 2024

Health risk behaviour, sometimes referred to as health impairing behaviour, is dangerous when it comes to children since it might have unfavourable consequences that last into adulthood. Although not entirely inherited, anxiety disorders can also result from the use of drugs, such as alcohol and caffeine, as well as the withdrawal from particular medications. They frequently occur in conjunction with other mental health issues, including actual depression, bipolar disorder, identity issues, and food issues. The phrase "nervousness" refers to four types of contacts that a person may experience: dissociative unease, physical tension, mental fear, and bodily symptoms. Feelings associated with unease range from mild anxiety to depressive bouts. While there are other psychological and therapeutic conditions that can mimic the signs of a tension disorder, this study outlines the elements that contribute to anxiety and how they impact students' mental health. The results and conclusions of the data collection process using a questionnaire were presented by the researcher. The researcher also talked about some inferences drawn from the participants' comments in addition to this.
Analytics of the Cost Effectiveness and Real-Time Health Risk Assessments for Pharmacy-Based Preventive Health Services
Authors: Sawlani Chandni , Sharma Pooja
Published: September 2024

More patient-centered care and participation in managing chronic illnesses are features of the modern pharmacist's task, which has evolved substantially in recent years. Still, the issue of whether or not pharmacists are cost-effective in diabetes care persists. Cost-effectiveness analyses (CEA) have emerged as a crucial tool when making informed decisions about healthcare delivery. Patients' present health status, past medical history (personal and family), and lifestyle variables influencing their health are all part of a health risk assessment (HRA). Hence, this study proposed a Cost-Effectiveness Analysis of Pharmacy-based Preventive Health Services (CEA-PBPHS) model for real-time health risk assessment. Nowadays, medical professionals place a greater emphasis on preventative health care. This research aims to examine the potential impact of risk assessment tools on males past due for a physical examination and evaluate the return on investment (ROI) for community pharmacists who provide this service for free. More cost-efficient or cost-saving than conventional treatment is pharmacist engagement in diabetes management due to better glucose control, higher patient compliances, and lower risks of medication-related issues. The experimental outcomes demonstrate that the suggested CEA-PBPHS model increases the health risk assessment ratio by 98.9%, the personalized health service ratio by 97.5% and the cost-effectiveness analysis ratio by 98.3% compared to other existing models.
Secure Healthcare Data Storage and Transmission: A Review of Current Technologies and Future Directions
Authors: Haval Abhijeet Madhukar , Afzal Md
Published: September 2024

The development of websites, applications, and the first social networks profoundly altered everyone's life and became the catalyst for advancement on a global scale. The days of immovable points, phones, and printing presses are long gone. But is everything really as perfect as it looks? Perhaps the most contentious thing in history is progress. We now have the freedom to express our ideas without fear, connect with individuals around the globe, and access a seemingly limitless amount of knowledge thanks to the Internet. But as time goes on, concerns about the cloudlessness of virtual existence become more and more prevalent; we have been captured by things that do not exist in reality. Apart from the well-known hazards like terrorism and global warming, the growth of the Internet has given rise to entirely unknown and novel perils that have infiltrated our life. We refer to this phenomena as "cybercrime". Any form of criminal activity carried out virtually is referred to as cybercrime. Ten to twenty years ago, this phenomena was known only to specialised specialists. IT industry, and it is currently a worldwide issue. Although everyone and the IT sector receive adequate security measures and equipment, cybercrime is nevertheless increasing at a very rapid pace in parallel. There are several security problems and cyberthreats in the modern world. With new technology emerging daily, we can predict major issues in the road.  In this work a Secure Healthcare Data Storage and Transmission in WAN area is discussed.
Pharmaceutical Care in Chronic Coronary Artery Disease Management
Authors: Jaiswal Vinay Kumar , Sahu Deepak Kumar
Published: September 2024

Individuals who suffer from Acute Coronary Artery Disease (CAD) frequently experience related issues, either because of the illness itself or as a side effect. Despite the existence of established criteria, Drug-Related Problems (DRPs) are more likely to arise, which impairs therapy outcomes and overburden patients. The purpose of this study is to assess clinical pharmacist-initiated medication optimisation in ACS patients. In order to optimise pharmacotherapy and the patient care process, a comprehensive clinical pharmacy service was created and deployed for the management of acute coronary syndrome (ACS-CPS). The service activities were prototyped under four primary themes. Our research showed the proactive role of clinical chemists in starting and offering services such as transition care, medication reconciliation, medication optimisation, and evidence-based drug information and interventions
Framework for Public Health Research and Addressing the Role of Law in Health Disparities
Authors: Kesharwani Samriddhi , Gidronia Sumant
Published: September 2024

The Indian system of safeguarding an individual's health has a lengthy history. The commercialization of medications and the medical profession, along with the passage of time and advancements in science and technology, enhanced the duty of physicians and contributed to the daily rise in medical negligence lawsuits. The government has established a number of committees to examine public health-related issues, and these committees have produced a number of suggestions aimed at enhancing India's healthcare system. In India, the role that diverse organisations have played in promoting public participation in the participatory management of civil society in the health care system represents a paradigm shift. The world came to understand that one of every person's most basic necessities is their health. This suggested article makes the argument that laws can generally be used to address disparities in public health as well as the absence of appropriate legal guidelines for maintaining public health.
Electronic Systems for Environmental Public Health Monitoring and Exposure Assessment
Authors: Deshmukh Shailesh Madhavrao , Punam Sumit Ramswami
Published: September 2024

According to statistics, Alzheimer's is the fourth leading cause of mortality in the US and its annual death toll is steadily rising. Additionally, it has been seen to be developing moderately in Asian nations; by 2050, half of all Alzheimer sufferers would come from these countries. While there are currently no known medications that can entirely cure Alzheimer's, early detection of the disease can help doctors treat patients appropriately, extending their lives and improving their quality of life. A computerised detection system may be employed to help physicians identify Alzheimer's and to detect the disease early. Many CAD systems were created in the past, mostly for the benefit of public health, however the majority of them had poorer accuracy rates. Therefore, it is necessary to design an effective CAD system that can accurately anticipate the presence of AD. In this paper, a CAD system for accurately detecting if a patient has Alzheimer's disease or not was established. Medical professionals may now reliably and swiftly identify a wide range of diseases and ailments with the aid of computer algorithms, artificial intelligence, and medical imaging thanks to the rapidly expanding field of computer-aided diagnosis (CAD).
Manipulation Strategies in Interpersonal Relationships and Their Psychological Impact
Authors: Brichag Sylvia , Papusha Vladyslav , Kholokh Olena , Kuznietsov Marat , Danyliak Ruslana
Published: September 2024

Manipulation is a purposeful, conscious, organized psychological influence with the aim of using the personality of another person as a means of achieving one's own goals. The purpose of the article is to characterize the main strategies of manipulation in interpersonal relationships. A set of theoretical research methods was used: the conceptual and terminological analysis was used to determine the essence of the main concepts of the study, comparative and contrastive, which made it possible to analyze the periodicals and scientific-methodical publications on psychology, classification. The results identify the major components of the process of manipulative interaction and the main signs of manipulation in interpersonal relationships. The results showed that manipulators control their victims through positive reinforcement (praise, excessive apologies, gifts, attention), negative reinforcement (getting rid of the problem), unstable or partial reinforcement (fear, doubt), punishment (reproaches, shouting). The conclusions indicate that the psychological mechanisms of manipulative action ensure the effectiveness of the manipulator's psychological influence on the object of manipulation. The conclusions also summarize that the main manipulative techniques are organizational and procedural, logical and psychological, and personal. The prospect of further scientific research is an empirical study of the features of manipulative tendencies in interpersonal relations.
Spiritual Diabetes Self-Management Health Coaching Against Psychological Well-Being and Self-Management Compliance in Diabetes Mellitus Patients
Authors: Sari Ratna Yunita , Septianingrum Yurike , Faizah Imamatul , Rohmawati Riska , Muhith Abdul
Published: September 2024

Introduction: For patients with diabetes to keep being consistent with self-management, they should build their psychological well-being and feeling of direction in life through a progression of intricate and tedious errands. Aim: This examination looked to inspect the impacts of Spiritual Diabetes Self-Management Health Coaching on psychological health and self-management conduct. Methode: The study utilized a quasi-trial research design, using a basic irregular sampling method to decide the sample based on inclusion and exclusion rules. A sum of 126 respondents were remembered for the sample, with 63 respondents each in the intervention and control groups. Ryff's Psychological Well-Being (RPWB) and a Questionnaire on Compliance with Diabetes Self-Management (QCDSM) were the instruments utilized in this study. A t-test with p<0.5 was used in the statistical analysis. Results: The findings demonstrated that the normal psychological well-being in the intervention bunch was 174.22 both when the intervention, and the typical compliance with self-management was 47.56. Pre-and post-intervention averages for psychological well-being and self-management compliance in the control bunch were 144.62 and 19.32, respectively. A p-worth of 0.000 between spiritual diabetes self-management compliance and psychological well-being is uncovered by information analysis. Conclusion: Spiritual Guidelines for Overseeing Diabetes Patients with diabetes mellitus can profit from long-term health coaching to upgrade their psychological health and compliance with self-management.
Enhancing Public Healthcare Security: Integrating Cutting-Edge Technologies into Social Medical Systems
Authors: Chandrakar Ekta , Dahiya Aman
Published: September 2024

To reduce the negative effects of digitization, normative advice in international human rights legislation incorporates digital health into ethical and human rights frameworks. The use of digital health technology for universal health coverage (UHC) is acknowledged to have benefits, but its implementation must be based on respect for human rights, equity, and ethics, as well as upholding norms of acceptable quality, safety, and morality. The WHA acknowledged the necessity to use digital health technologies in the wake of the COVID-19 pandemic in 2020, but stressed that in doing so, they must "pay particular attention to digital inclusion, patient empowerment, data privacy and security, legal and ethical issues, and the protection of personal data." This paper's goal is to critically assess the proposed legislative framework and policy that regulate digital health technologies in India, as well as the implementation of digital health.
Finding the Link Between Cyberbullying and Suicidal Behavior Among School Going Adolescents
Authors: K Gokul , D Dr Gokul , D Dr Keerthana , B Dr Nisha
Published: September 2024

Background: Studies have shown that cyberbullying or online bullying has increased the risk of suicidal thoughts and suicidal behaviours. Although suicide or suicidal behaviours are not directly related to cyberbullying it can be said that cyberbullying increases depression rates and feelings of isolation which end up in suicidal calls. This research aims to understand the nexus between cyberbullying and suicidal behaviour. Methods and materials: A self-administered and anonymous online questionnaire was used to survey 410 higher secondary school adolescents aged 16 to 18 and the data analysis has been carried out by statistical analysis with the help of IBM-SPSS software of version 22.  Results: The findings of the results have revealed that cyberbullying was more prevalent among the respondents than cyber victimization. There was a small fraction of the population that said that they had undergone suicidal behaviour due to cyberbullying. Between text messaging and multimedia messaging, the best platform for cyberbullying was multimedia messaging. The reason behind this was its usage around the world, its popularity, and its ease. Teenagers over the age of 17 years have reported the highest percentage share for suicide rates and most of them were female. Conclusion: It can be concluded that cyber bullying is a threat to those girls who is currently studying in 11th standard and or age 17 years whose parents are separated or not living together.
Computer Vision Application for Effective Flood Forecasting in Public Health Systems
Authors: Jaleel Uruj , Lalmawipuii R
Published: September 2024

Among the natural disasters, floods are considered as one of the most devastating since they can damage infrastructures, force people leave their homes, and negatively impact the public health. The training of the model seems to be computationally intensive and could prove an interruption where computational resources are a limited commodity. In this paper, we present the Greylag goose driven redefined Long Short-Term Memory (GG-RLSTM) model to be implemented by public health systems in effective flood forecasting. Thus, adapting behavioural patterns in Greylag geese, GG-RLSTM enhances the theoretical structure of LSTM and increases its capability to capture complex relations in the flood processes. From the Kaggle dataset, we gathered meteorological evidence, and geographical features. The results from the experiments indicate that effectiveness of the proposed GG-RLSTM model is higher than the other conventional methods in terms of accuracy (89%), precision (88%), recall (87%), and f1-score (90%). Due to the effectiveness of the model and its applicability in various situations, public health systems can likely adopt it and commence preventive flood measures.
Application of Wearable Electronics Sensors for Public Health Monitoring and Disease Prevention
Authors: Pillai Anu G , Kewte Shital
Published: September 2024

Each component of contemporary technology depends on sensors. Improved and more advanced sensors have the potential to advance technological advancements and ultimately contribute to a better quality of life for humans. Adopting more modern materials, designs, and sensing mechanism types is crucial to the development of sensors. Wearable sensors can be used to monitor several aspects of human gait by placing them on the hip, knee, wrist, and foot, among other parts of the body. Measurements of public health, including body temperature, heart rate, pulse oxygenation, respiration rate, blood pressure, blood glucose, ECG signal, and disease prevention, can be made with these sensors. Numerous recent studies have taken into consideration wearable sensor-based systems. With an emphasis on monitoring human physiological indicators, the research work aimed to demonstrate new sensor utilisation in the development of wearable devices for biomonitoring applications.
Evaluating the Impact of Universal Health Coverage Policies on Population Health Outcomes Using Big Data Analytics for Comprehensive Policy Assessment
Authors: Bhaskar Rajeev Kumar , Kumaraswamy Balasubramaniam
Published: September 2024

Universal Health Coverage (UHC) aims to eliminate financial barriers to care which is important for everyone’s affordability. Thus, it is helpful to study how UHC affects population health outcomes and where it may be headed in the future. Big Data Analytics provides good tools for scrutinizing those principles and their results on a huge scale. Communities differ in terms of their health outcomes; and health systems are complex. This paper tries to address these among other issues by integrating big data sets that are diverse and analysing them together. As an innovative way of examining universal health coverage initiatives’ impact on populations, researchers propose the Comprehensive Analysis of Fragmented Health Systems (CA-FHS). CA-FHS uses Big Data Analytics to compile and analyse information from many different sources thereby giving an exhaustive breakdown of health outcomes by demography as well as geographic area. This would allow trends or patterns not seen using conventional evaluation tools to be discovered. It encompasses public health, policy-making, as well as healthcare management concerns. In this way, the method may bring out the strengths and weaknesses inherent in the healthcare system such that policies are recommended for change while resource allocation is done for bettering UHC-related consequences internationally. It will enable the evaluation of long-term effects resulting from these projects so that they can meet their goals eventually. The process will involve creating hypothetical policy scenarios and then assessing how these would affect population’s historical health outcomes through use of historical data simulation techniques; thus providing input into potential policy choices at federal level concerning evidence-based recommendations towards achieving improvement in health status.
Big Data Analytics Based Data Driven Public Health Care System For Heart Disease Detection
Authors: Rahman Dr. F , Lalnunthari
Published: September 2024

Everyone should be more conscious of their lifestyle choices in order to live a healthy life. This can be done by following appropriate eating plans, being aware of healthcare issues, and knowing how to maintain good health. The health sector produces enormous amounts of electronic data every second in the present digital era, making it extremely difficult to store and manage the data using traditional software and technology. Additionally, the impending data is generated in varied forms, such as semi-structured, unstructured, and/or structured. The rate at which data are evolving and their abundance necessitate an overwhelming amount of health care data. Thus, it appears that health-related data can be handled using big data. This study demonstrates how quickly things are evolving, resulting in the creation of several approaches and continuous research into fixes for issues that crop up in a range of industries.
Design of Iot-Enabled Early Warning System For Health Disease Diagnosis
Authors: Nandy Manish , Ramesh Hajare Hirendra
Published: September 2024

Hospitals employ early warning systems as a scoring tool to evaluate a patient's health by periodically taking their vital signs. The EWS has the advantage of lowering medical costs, mortality rates, and irregular record-keeping, all of which improve patient diagnosis and prognosis. Vital signs are a reflection of a patient's health condition and are assigned a sub-score in EWS based on the degree of deviation from the value when compared to a healthy individual. Next, the sum of all subscores is used to estimate the overall score. EWS built on the Internet of Things (IoT) has changed dramatically in the last few decades. It has the power to drastically change the way that healthcare is delivered. The timely provision of healthcare services is increasingly dependent on the vital signs monitoring system. The paradigm has changed from computer-based electronic recording to traditional manual recording. In rural and isolated places without access to basic medical facilities, required infrastructure, or licensed medical professionals, IoT-based EWS is critical to the provision of healthcare services. The design of healthcare, real-time vital sign monitoring, remote health monitoring, and the interpretation of numerous vital signs for the prediction of health status and abnormality detection are the main areas of attention for this research.
Developing Innovative Secured Protocol For M Health Application In Wireless Body Area Networks
Authors: Soni Palvi , Tandan Gajendra
Published: September 2024

In today's technologically advanced society, cell phones and related devices are essential for managing peoples' individual demands. This is a smart device that determines and regulates how we use our free time, communicate, shop, and engage with the outside world. It still requires a lot of fixes to be effective and strong. The development of tiny devices, or sensors, gave mHEALTH greater adaptability and a fresh perspective. The majority of currently available mobile applications are widely accessible by users, who can use them to take vital signs and evaluate their own physical state. In an effort to increase public acceptability, some mobile companies have developed health applications for smartphones. People use these programs to monitor changes in bodily parameters such as body temperature, heart rate, blood pressure, and pulse rate in order to assess their physical conditions. Using the MSE-BAN architecture, this study has created a stable mHEALTH architecture. The scheduling plan for the study project was created by taking the importance of the essential signals into account. The public health care system that has been suggested can shorten hospital stays and enable clinical staff to continuously monitor patients.
Effective Patient Scheduling For Public Health Events Based On Deep Reinforcement Learning
Authors: Kumar Dr. Sanjay , Sharma Priti
Published: September 2024

Amidst the current worldwide pandemic of the novel coronavirus, there are still issues about the efficient allocation of emergency supplies and shortcomings in recovery protocols. To enhance individuals' health and overall welfare, it is imperative to enhance and refine the emergency patient scheduling framework for health emergencies while upholding the idea of a society with an inherent future for humanity. The paper proposed an Efficient Patient Scheduling for Public Health Emergencies (EPS-PHE) using Multiagent Reinforcement Learning (MRL). Originally intended to solve the PHE and improve EPS, the technology was conceived as a distributed multiagent system. MRL has proposed a decentralized incentive system evaluation technique for the EPS-PHE input. An incentive type called a Direct Incentive (DI) is used to show the relationships between individuals or details about two closely connected events. The quality of data transmission in EPS-PHE or the efficacy of the emergency network is measured using a Collective Incentive (CI). Simulation research has shown the value of the Deep Learning (DL) - MRL approach in EPS-PHE framework optimization.
Exploration of Workaholic Characteristics of Married Women in Healthcare sector during Pandemic situations
Authors: Praveenadevi D. , Manimegalai V. , P Sreelatha , Bamini J , Kaushal Ashish Kumar , Fufa Gamachu
Published: September 2024

Women in professional and family life are facing lot of challenges where they are struggling to manage their work pressure and family responsibilities. In healthcare sectors, the employees especially the nurses have to carry out shift work and have to perform morning, evening and night shifts. It is analysed and proved by many analysts that mostly the women from middleclass family life are subject to such work-life challenges in particular the women nurses especially during pandemic situations. This study focuses on Workaholism which is an extreme work force that leads to the disregard of others’ welfare and harmful effects faced by the women nurses especially who are married. In this aspect, the research was conducted to examine the workaholic characteristics of married women especially the nursing professionals during the pandemic period. The study was conducted by collecting data from women nurses from South part of India and the sample size derived for the study is 200. The findings reveal that Continuous thoughts of Work Involvement, Accepts Extra Work Time, Task Oriented, Compensation based on Work Performance and   No Botheration about Work life Balance are the major workaholic characteristics of women nurses especially who are married.
Exploring Postponing Career Decisions of Indonesian Vocational Students from Biopsychososial Dimension: A Path Analysis
Authors: Kurniawan Nanda Alfan , Hidayah Nur , Akbar Sa’dun , Ramli M. , Ngussa Baraka Manjale , Fitriyah Fifi Khoirul , Hanafi Husni
Published: September 2024

Career decisions encourage students to get opportunities in various career path after graduating. Procrastination in career decision-making made the chance reducted by the time their hanging decision. In wider effect, this impacts the national level of educated unemployment. Multiple factors can be a potential source of procrastination in career decisions. Exploring these factor should be considering the biopsychosocial dimension as genetic and behavior, psychological development, and social-cultural interact on the decision making process. This research aims to examine the influence and relationship between parental expectations and personal career aspirations of vocational school students in the postponing of career decisions, which is mediated by students' dependency and compromise skills. The research method uses quantitative with a non-experimental design. The data analysis technique uses path analysis. The research subjects were 450 vocational school students in East Java, Indonesia. The research results show that parental expectations mediated by dependency positively affect postponing career decision. Students' compromise skills negatively affect postponing career decision. Furthermore, personal career aspirations have a negative direct and indirect effect on the students' postponing career decisions, which is mediated by this research variable. The research results recommend that demographic and cultural exploration be carried out to compare research results comprehensively.
Health Care Strategy and its Impact on Quality of Health Services in India
Authors: Ghate Atul Dattatraya , Ahmed Mariyam
Published: September 2024

The health care industry operates in a very dynamic environment, particularly in the modern era. The introduction of technology has led to a significant advancement in the medical area. The entire environment in which the medical industry today functions has changed as a result of this infusion. Modern medical technology used to treat patients improves the reputation of the hospital. Technology is employed in the hospital's management as well as in its treatment. Hospital operations can be managed more effectively and successfully with the use of automation solutions. Modern technology is available at private hospitals, and it has been seamlessly incorporated into the medical industry. The private sector has always been at the forefront of implementing cutting-edge medical technologies and providing patients with top-notch care. This survey revealed a similar trend, with the private sector coming in first, then trust-run hospitals, and finally private clinics. Public hospitals in India have taken note of this aspect as well and are actively putting plans into place to introduce the necessary technology for hospital management and treatment.
Optimizing Telemedicine for Public Health: Novel Machine Learning-Driven Blood Pressure Evaluation Model
Authors: Biswas Debarghya , Tiwari Ankita
Published: September 2024

As a form of asynchronous interaction between patients and doctors through electronic technology to provide distant clinical solutions, telemedicine seems not to deliver sufficient and accurate means of predicting and evaluating public health indicators outside conventional health settings like BP. In this investigation, we have used a new fish migration optimized cat boost technique named fish migration optimized cat boost (FMO+CB) for predicting blood pressure rates with the help of the physiological data collected from human subjects by the Electrical Impedance Myography (EIMO) apparatus. To further enhance the prediction performance of BP, the FMO technique and the CB method are incorporated. An analysis of the FMO approach shows that it is used to select the correct parameters to avoid overlearning. Evaluation of the prediction result of BP using various criteria such as MAE =3.06, MSE =50.04, and MAPE =3.03 are tested using the proposed approach through a Python platform. The experimental results prove the fact that the FMO+CB methodology has better prediction accuracy compared to the other methods.
The Mindfulness-Based on Spiritual Intervention on Psychological Well-Being and Blood Sugar Levels in Type 2 Diabetes Mellitus Patients
Authors: Rohmawati Riska , Faizah Imamatul , Sari Ratna Yunita , Hasina Siti Nur , Muhith Abdul , Wijayanti Lono , Kartini Yanis
Published: September 2024

Blood sugar levels are influenced by psychological well-being, which is affected by diabetics who go from being healthy to sick. This study examined the effect of spiritually situated mindfulness interventions on the psychological health and blood sugar levels of individuals with type 2 diabetes mellitus. Method: A quasi-explore different avenues regarding an untreated benchmark group and ward pre-and post-test samples was the research strategy utilized. All type 2 DM patients at the Surabaya Islamic Hospital Outpatient Clinic made up the study's populace. Using a basic random sampling strategy, 130 samples in totally were selected based on the inclusion and exclusion rules. Also, the sample was split fifty, with 60 respondents each in the control and treatment groups. The Glucometer and the Ryff Psychological Well-Being Scale were the instruments utilized in this investigation. Matched sample t-test and independent sample t-test data analysis. Result: The results showed that the psychological well-being of the intervention bunch was 147.68 before the intervention and 171.32 after it. The mean blood sugar level in the gathering before the intervention was executed was 302.64, however after it was carried out, it was 189.11. In addition, the mean blood sugar levels in the benchmark group were 289.21 and 283.87 when the intervention, and the mean psychological well-being levels were 146.84 and 146.02, respectively. Furthermore, the data analysis demonstrated a negative relationship between type 2 diabetes patients' blood sugar levels and psychological well-being and mindfullnes based on spiritual intervention (p = 0.00). Discuss: Individuals with type 2 diabetes can encounter improvements in their psychological well-being by lowering their blood sugar levels through the often used mindfullnes based on spiritual intervention.
Analysing The Breast Cancer Awareness Of Public Health Care Management In India
Authors: Shrivastava Dr. Vivek , Sandilya Ranjit
Published: September 2024

One of the most prevalent types of cancer impacting women worldwide is breast cancer. Breast cancer in women is a significant global public health issue because of its high rate of morbidity and mortality as well as its substantial social and financial costs. The number of new cases and fatalities from breast cancer is rising year, contributing to the disease's growing global burden. In India, breast cancer ranks second in terms of cancer-related fatalities among women and is the most common cancer. However, the percentage is undoubtedly higher in America, where one in eight people get this potentially fatal cancer. According to the Population Based Cancer Registry of India, between 25% and 31% of all malignancies in women in urban areas (such as Mumbai, Delhi, Chennai, Ahmadabad, Bangalore, Bhopal, etc.) are breast cancers. Although the rise in breast cancer cases is mostly reported in large cities, it is very likely that many cases go unreported in rural areas. The average age at which breast cancer is diagnosed has dropped from 50–70 years to 30–50 years. Millions of people can be assisted in lowering the risk of breast cancer by receiving the right information and treatment under the direction of professionals. Therefore, this study aims to investigate practitioners' opinions regarding the implementation of the awareness model in the health sector as well as the public's perspective of the models for women suffering breast cancer.
Empowerment of Augmented Reality (AR) for Patient Education and Engagement: Medication Adherence Programs' Impact on Public Health Outcomes
Authors: Yadav Kamlesh Kumar , Kirit Dhablia Dharmesh
Published: September 2024

The entire effectiveness of pharmacological treatment depends on patients taking their medications as prescribed. Patient education is a vital component of the endeavours to enhance adherence to medications. However, many people still fail to take their prescription pills as prescribed. In addition to having access to healthcare, those who follow their doctors' orders greatly improve their chances of a positive outcome. The unfortunate reality is that many people do not take their medications as prescribed, which has led to deteriorating health, higher healthcare costs, and more overall costs. Hence, this paper presents the Smart Augmented Reality-based Patient Medication Adherence Program (SAR-PMAP) model for effective patient education and engaging medication. The augmented reality spectacles help those with trouble keeping track of their medication, and the model encourages patients to take their prescriptions as prescribed. Users may easily go to their homes with the aid of the navigation functions, and patients with impaired eyesight can benefit from the audio option that gives out the date and time. Given all this data, the Medication Coach Intelligent Agent (MCIA) takes the lead in making comprehensive decisions so patients can get autonomous, individualized, and unobtrusive treatments.
Integration Of Fuzzy Logic And Deep Learning For Medical Image Analysis In Neuroimaging
Authors: Jayasutha D. , Divakar TVS , Selvam P.M.Sithar , Ambethkar M Raja , Vigneshkumar P. , Kumar Sunil
Published: September 2024

Input from magnetic resonance imaging (MRI) scans is used by contemporary deep learning algorithms to assess changes in brain structure. Over the past several years, a variety of deep learning techniques have gained popularity for their application in the process of feature learning and the enhancement of the responsiveness of systems for learning. We are able to apply a deep learning classifier to identify structural changes in the brain and express the spatial information in this study. This is made possible by integrating the transfer learning model with a fuzzy convolutional neural network (CNN) that performed 3D convolutions at earlier levels. Through the utilisation of ResNet and 2D fuzzy convolutional layers, the model makes use of MCI, which is more often referred to as AD, in order to enhance class separability. To facilitate binary classification in the study, the suggested model is trained and evaluated over a collection of sagittal, coronal, or transverse MRI slices. This is done in order to facilitate the job. An approach known as 5-fold cross-valuation is utilised in this research project in order to investigate the accuracy that was achieved via the use of classification issues during testing and training. In terms of accuracy, the suggested technique achieves a rate of 99%, which is higher than both existing methods and methods that do not use ResNet and 2D Fuzzy convolutional layers. This is according to the data obtained from simulations.
Medication Adherence and Health Outcomes: A Public Health Perspective
Authors: Singh Chiranjeev , Jaiswal Harish
Published: September 2024

Medicine is a two-edged sword: while it can treat a patient's illness, when applied carelessly, it also has the potential to do more harm than good. Ensuring that patients receive appropriate medication for their clinical condition at the appropriate time, by the appropriate channel, and in the appropriate doses should be the top priority for any healthcare system. Polypharmacy can be helpful because numerous morbidities are common, but it can also have unintended harmful effects. The co-morbidity-polypharmacy score uses the patient's physiological age rather than their chronological age to predict how their therapy will turn out. Any departure from the medication's intended therapeutic impact may be regarded as a drug-related issue. The purpose of this study was to examine the effects of clinical pharmacist interventions on drug-related issues in prescriptions for polypharmacy as well as the cost-benefit analysis of clinical pharmacy services. The particular goals were to recognise and address drug-related issues, find out how well health care providers received clinical pharmacist interventions, analyse the cost-benefit of clinical pharmacy services, and create and suggest a clinical pharmacists intervention form to standardise and record drug-related issues.
Prime Components Influencing the Foreigners Towards the Medical Tourism in India –A Factorial Approach
Authors: Praveenadevi D. , Varun T. , Arulini K. , Kumar Sunil , R.Jaazieliah Ms. , Vijayalakshmi R.
Published: September 2024

The prevalent of universal corporate sectors and government initiatives in India have enhanced the service sector venture in recent years. To draw more medical tourists, the Indian government and the medical sector have substantially spent in enhancing the Indian healthcare abroad. However, it's also crucial to consider the traits of the patients who select India for their medical care. Medical Tourism in India has peculiar traits and special abilities, specialized services and platforms, expertise and well-equipped hospitals and medical staff, a culturally rich region, cutting-edge facilities, supportive individuals, and overall warmth and hospitality. Previous studies focus on the problems faced by the tourists, study in other nations and how people choose their destinations for treatments especially Americans’. With a sample of 600 respondents, the data is directly observed at the hospitals from the international patients in the six states of Kerala, Tamil Nadu, Andhra Pradesh, Telangana, Karnataka and Pondicherry. In order to produce a unique dataset that may be utilized to address more inquiries about India's tourism in general, the study compiles data from also the other secondary sources. To study and predict patients' intentions to return to India and their loyalty, it is and to frame the hypothesis assess their opinions of the various facilities and services provided during medical tourism. Factorial analysis, a multivariate statistical technique, has been used to analyze the data and identify the top ten factors motivating the tourists to India. The current study throws light to identify the key areas on which hospitals should concentrate in order to promote medical tourism in the current, cut throat climate.
Public Health Management: Innovative Facility Arrangement Framework Towards Emergency Relief
Authors: Soni Dr. Sandeep , Maurya Dr. Shyam
Published: September 2024

The better public health organizations are contingent on the healthier distribution of earthquake relief facilities when there is an immediate seismic event. Choosing the perfect site for these emergency relief centers that would suitably integrate cities is a challenging task. Heuristic calculations are practical methods for resolving these kinds of complex optimization problems. This study's objective is to develop a novel method for allocating parcels to assistance facilities and figuring out where they should be placed: swarm-tuned war strategy optimization (SWSO). The SWSO method syndicates the investigative efficiency of the WSO strategy with Particle Swarm Optimization (PSO) to solve the complex elements of this task by humanizing directional skills. Using GIS, possible sites were designated, and letters were brought utilizing a suggested SWSO method that reduced the quantity of trip. The method exceeded present approaches in terms of meeting cumulatively the achievement of emergency managers and public health managers in providing disaster relief and, eventually, maximizing people's seismic resilience.
Uncovering Oral Health Concerns: Exploring Dental Anxiety within Transgender Community: A Systematic Review
Authors: Resident Dr.Logesh Sidhu, Senior , M.D.S Dr.K.Kasthuri Priya, , Resident Dr Kaviashika, Senior , Resident Dr.Angeline Hephzibah.P, Senior , Dr.M.Senthil, M.D.S  , Resident Dr.Akhil  M.D.S., Senior
Published: September 2024

Dental fear and anxiety (DFA) have substantial implications for oral health, often resulting in the avoidance of dental care and negative consequences. Despite facing unique health challenges and discrimination, there is a lack of research on the prevalence of DFA among transgender individuals. This paper seeks to synthesize evidence regarding the prevalence of DFA within this population. We searched multiple databases, including PubMed, Google Scholar, Cochrane Database, Web of Science, and LILACS, for studies published up to May 2024. We included observational studies, cross-sectional studies, surveys, and cohort studies that provided data on DFA prevalence among transgender individuals. Eligible studies were screened, and data extraction was performed according to predefined criteria. The risk of bias was evaluated using the ROBINS-E tool, while the level of evidence and quality were assessed following the Oxford Centre for Evidence-Based Medicine guidelines. Among the 20 studies assessed for eligibility, only 2 met the inclusion criteria and were thus included in the review. These studies reported varying prevalence rates of DFA among transgender individuals, with both exhibiting a moderate risk of bias. However, the quality of evidence was deemed low due to the limited number of studies and their observational nature. The available evidence indicates that transgender individuals experience notable levels of dental fear and anxiety, which contribute to disparities in accessing oral health care and achieving positive outcomes. This review underscores the imperative for further high-quality research to comprehensively understand and address the oral health needs of transgender individuals, ensuring equitable and effective dental care.
Advanced Tuberculosis Detection System for Preserving Public Health
Authors: Mishra Dr. Nidhi , Shivaji Ghorpade Bipin
Published: September 2024

Tuberculosis is a major public health threat that requires efficient and early detection technologies. Challenges associated with real-world implementation include information variability, model availability, and operations in different clinical circumstances. In this paper, we introduce a Crow Search Driven Tuned Logistic Regression (CS-TLR) tuberculosis identification system to sustain early identification of the disease and increase the levels of diagnostic accuracy to help sustain public health. The model attempts to enhance the overall prediction performance of logistic regression by optimizing its parameters by using CSA's optimization capability. We gathered the Kaggle dataset with a variety of clinical and demographic characteristics of tuberculosis patients. We evaluate the performance of the suggested method employing standard parameters including AUC (90.5%), precision (89.9%), recall (90.1%), and F1-score (89.7%). The findings suggest that it could be an important public health surveillance tool by enabling early diagnosis and treatment of TB.
Analyzing The Influential Factors of Psychological Health and Employee Performance in Public Health
Authors: Jaleel Dr. Uruj , Fatma Eram
Published: September 2024

The purpose of this study was to identify the degree to which industry employee’s performance and psychological health within the public health sector are impacted by their workplace, work stress, and burnout. This research employs a quantitative methodology. The samples employed in this study were employees of Industry, which comprised 42 individuals. A questionnaire is used to collect data, which is then analyzed using the SPSS software. We explained the entire process of ensuring the credibility of the data that was collected from the individuals through the questionnaires. According to the findings of this study, it was established that burnout, work stress, and workplace factors influence EP. The evaluation highlights the need of some polices and promising strategies to improve the mental and overall public health. This study also emphasized the need to deal with psychological problems at workplace in order to have healthier and more positive workers.
Big Data Analytics Challenges and Opportunities in Heart Disease Recognition: Novel Dimensionality Reduction with Classification Approach
Authors: Sinha Dr. Anupa , Kumar Yalakala Dinesh
Published: September 2024

Due to the current technological growth, a number of strategies have been developed, and more are being developed to eliminate problems that arise in many fields. Big Data techniques are employed to effectively stored health data due to the continual and massive volume of data created by the human body. Furthermore, the most important procedure is the classification of health data since it must be carried out precisely in order to diagnose cardiac disease early. The database images are various in size to reduce the dimension the Modified Principal Component Analysis (MPCA) Algorithm is used. the proposed MPCA algorithm is act as a feature selection model to pick features. One of the best and most effective techniques for classifying medical data is the Modified Deep Convolutional Neural Network (MDCNN). It has been shown to work for a variety of hospitalized patients. Consequently, the simulation results show that this proposal enhances classification accuracy in experimental research for the detection of heart ailment.  Hence, the proposed method leads to an efficient usage of the resources and cost reduction. This approach assists the physician in taking suitable decision for giving a better treatment at right moment.