International Journal of Preventive Medicine and Health
EISSN : 2582-7588
Published by: Lattice Science Publication (LSP) (10.54105)
Total articles ≅ 10
Latest articles in this journal
Published: 30 May 2022
International Journal of Preventive Medicine and Health, Volume 2, pp 1-6; https://doi.org/10.54105/ijpmh.d1018.052422
The goal of this study is to estimate stature or height from lower-limbs in male-children from the Uttar Pradesh (UP) districts of Chandauli and Mirzapur (India). 501 children aged eight (8) to fourteen years (14) old volunteered to take part in the research during the school year 2014-2015, and data was collected using multistage random sampling. On the right-side of each participant, four anthropometric measurements were taken: height, trochanterion length (TL), tibiale-laterale length (TLL), and biepicondylar femur breadth (BFB) (ISAK recommendation). The data was analysed, and an attempt was made to create a regression model based on the link between stature (dependent variable) and TL, TLL, and BFB (estimates). At P<0.05, all culled estimates showed a significant correlation. To compare authentic and estimated stature, an independent t-test was used, and all three segments were obtained after that. The constructed regression models worked well for estimating stature, and the Trochanterion length is a very reliable predictor of stature. Because regression models for stature prediction from the above-mentioned body segments were used in this work, the findings could be beneficial in establishing biological profiles during forensic investigations and disaster victim identification
Published: 30 May 2022
International Journal of Preventive Medicine and Health, Volume 2, pp 7-14; https://doi.org/10.54105/ijpmh.d1019.052422
Kerala has seen a steep rise in the number of people affected by non-communicable diseases especially CVDs. There has also been an increase in the number of people being brought to the hospital emergency departments with acute coronary syndrome. With those facts in our minds, the research team wanted to assess the knowledge, attitude and practice on cardiovascular disease among the patients and bystanders visiting our tertiary care health centre in a rural part of Kerala. A cross sectional study was done using convenient sampling. An expert validated structured questionnaire was given to subjects after applying the exclusion criteria. A total of 354 people participated in the study with majority of males (56.5%). The questionnaire included questions regarding the knowledge regarding cardiovascular risk factors, knowledge regarding symptoms of acute coronary syndrome, attitude towards the risk factors and finally the practices carried out by them. The collected data was entered in Microsoft Excel and was analysed using SPSS version 20 software. After the analysis of the results, regarding questions related to knowledge, 77.4% subjects knew smoking is a risk factor for CVD. Most of the subjects knew that consuming fruits and vegetables regularly can prevent CVD. Regarding questions related to attitude, 65.8% agreed that regular exercise can prevent CVD. More than half of the subjects followed healthy lifestyle. There were statistically significant differences observed in knowledge level between sexes (males having a more mean knowledge score than females, p =0.001), age (age group of 20-30 having a high mean knowledge score than other age groups from 31-60, p< 0.001), education (graduates having a more mean knowledge score than those with primary and secondary education, p<0.001) and occupation (professionals having a high mean knowledge score compared to other fields of employment that we evaluated, p<0.001). More than half of the subjects were currently smoking (57.1%). This study revealed that the population had good knowledge and attitude regarding CVD risk factors. Yet, the number of smokers was still quite high. Development of better public information system is essential for the well-being of the society. Furthermore, despite having knowledge regarding certain factors, people showed less willingness to make lifestyle changes which also affected their practices. Hence, it is necessary to study KAP of the population at regular intervals to educate the people better and to aid in the planning of health promotion activities. This study proves that even though the people have good knowledge and attitude regarding CVD, the practices for prevention are not satisfactory. The researchers suggest that better health education campaigns regarding modifiable cardiovascular disease risk factors should be carried out among the public.
Published: 30 March 2022
International Journal of Preventive Medicine and Health, Volume 2, pp 1-7; https://doi.org/10.54105/ijpmh.c1017.032322
In this era of economic challenges health care consumers’ desire quality of care that comes with value and satisfaction. This cross-sectional descriptive study assessed maternal satisfaction with the quality of antenatal care rendered by midwives at a tertiary health institution in the Southeast Nigeria. Three objectives guided the researchers in achieving the purpose of the study. Sample of 171 respondents was drawn from a population of 301 pregnant women using Taro Yameni formula for sample size calculation. Validated investigators’ structured questionnaire with reliability index of 0.70 was used for data collection. Data generated from the study were analyzed through descriptive statistics using SPSS Version 21 IBM. Findings from the study revealed that the pregnant women attending Antenatal clinic at the state tertiary health institution are satisfied with the quality of physical and psychological care rendered by the midwives in the institution. Outstanding in their satisfaction were evidenced in their contentment with blood pressure monitoring (43.4%), weight monitoring (40.9%), directives on family planning (47.4%), reassurance by midwives (40.9%), and confidentiality of privileged information (42.7%). They saw the spacious nature of the ANC care arena as a satisfier too. Greater number of the women (77.8%) believes that they derived their satisfaction of care from the availability of essential drugs and necessary equipment. Finally in order to improve satisfaction with antenatal care, organizational aspects of antenatal care such as reducing waiting times and increasing accessibility to drugs and equipments need to be improved. The researchers recommended that the hospital management should recruit more midwives to reduce the work load on those working at the ANC unit and also provide comfortable environment for the pregnant women attending the ANC.
Published: 10 November 2021
International Journal of Preventive Medicine and Health, Volume 1, pp 5-10; https://doi.org/10.54105/ijpmh.e1013.111521
India is quickly becoming one of the most popular tourist destinations in the world. The rise of India as a tourist destination can be attributed to a number of factors. The growth of medical tourism in India is one of the reasons examined in this paper. Healthcare tourism is when people from all over the world fly to another country to receive medical, dental, and surgical treatment when exploring, vacationing, and completely immersing themselves in the attractions of the countries they are visiting. In the medical tourism industry, India is one of the most popular destinations. Medical tourism is experiencing rapid growth in India. Medical tourists cross foreign boundaries in search of medical care. Medical tourism has developed to become a multibillion-dollar industry. It is important to remember that the primary goal of medical tourists is to provide high-quality medical care at an affordable cost. When compared to other developing countries in the world, India has emerged as the most sought-after destination for medical tourists due to the availability of world-class doctors at affordable prices. In addition, India has a wide range of tourist destinations. It has tremendous potential for creating jobs and earning large sums of foreign currency. The paper ends with policy recommendations for advancing the rapidly growing medical tourism industry.
Published: 10 November 2021
International Journal of Preventive Medicine and Health, Volume 1, pp 1-4; https://doi.org/10.54105/ijpmh.c1008.111521
This research paper focusses on the recent impact of Covid-19 on the G20 countries on basis of the number of cases and the number of deaths in several aspects. This paper also provides a brief history of the previously occurred pandemics and epidemics. A statistical analysis was conducted for 19 countries of the G20 assembly and presented in the paper. This topic was chosen in interest of recent events of the Covid-19 pandemic and its extensive effect on the world at large. The dataset consisting of records from nineteen countries was chosen as a part of the analysis. Apart from being involved in the G20 summit, these countries are looked upon by other countries of the world due to their economic and overall development. Further, past history of some pandemics and epidemics were taken into study.
Published: 10 September 2021
International Journal of Preventive Medicine and Health, Volume 1, pp 1-5; https://doi.org/10.54105/ijpmh.b1005.091421
Robotic and advanced technology rehabilitation is useful for people with difficulties and deficits in arm and hand movements, walking problems and balance disorders. Robotic technologies are being introduced in the rehabilitation field to support the activity of specialists, doctors and physiotherapists; the future and the challenge of rehabilitation lies precisely in the development of robotics. Robot assists the therapist in administering the most appropriate motor therapy with precision and repeatability modulates the difficulty of the exercise. It allows repetitive task-oriented activities with augmentative feedback capable of inducing brain plasticity. It acquires quantitative information on movement and evaluates the services performed he first, “Arm and Hand”, is used to help the opening and closing movements of the hand. After entering it by hand and forearm, gently guides the patient’s shoulder and elbow movements to reach and grasp objects. “Wrist”, on the other hand, interacts with the movements of the wrist and integrates functionally with the “Hand” module.
Published: 10 July 2021
International Journal of Preventive Medicine and Health, Volume 1, pp 1-4; https://doi.org/10.54105/ijpmh.c1010.071321
Kidney diseases are increasing day by day among people. It is becoming a major health issue around the world. Not maintaining proper food habits and drinking less amount of water are one of the major reasons that contribute this condition. With this, it has become necessary to build up a system to foresee Chronic Kidney Diseases precisely. Here, we have proposed an approach for real time kidney disease prediction. Our aim is to find the best and efficient machine learning (ML) application that can effectively recognize and predict the condition of chronic kidney disease. We have used the data from UCI machine learning repository. In this work, five important machine learning classification techniques were considered for predicting chronic kidney disease which are KNN, Logistic Regression, Random Forest Classifier, SVM and Decision Tree Classifier. In this process, the data has been divided into two sections. In one section train dataset got trained and another section got evaluated by test dataset. The analysis results show that Decision Tree Classifier and Logistic Regression algorithms achieved highest performance than the other classifiers, obtaining the accuracy of 98.75% followed by random Forest, which stands at 97.5%.
Published: 10 May 2021
International Journal of Preventive Medicine and Health, Volume 1, pp 5-7; https://doi.org/10.54105/ijpmh.b1003.051221
Healthcare Informatics plays a very important role for manipulating data. In the healthcare discoveries, pattern recognition is important for the prediction of depression, aggression, pain and severe disease diagnostics. In , the real innovation that has affected and organized human services is cloud computing, which empowers whenever anyplace access to the information put away in a cloud. The mobile devices are continuously observing patients that move around a networked healthcare environment. In traditional healthcare diagnostic system, we depend upon expensive tests and machineries which increase the expenditure of healthcare. It is dire need to reduce the aggregate cost of regular or usual diagnostics incorporates high cost of hospitalization. These expenses can be limited or disposed of with the assistance of remote patient monitoring gadget, a healthcare IoT product. Remote monitoring of person’s health gadget includes the observing of a person from an alternate area. This dispenses the requirement for driving to clinic and to being hospitalized for less severe circumstances. This research will explore the depression monitoring system by detecting the facial expression using suitable soft computing algorithm. We may use different algorithms such as CNN and Multilayer Perceptron to get the best result. On the basis of classification it detects the class of disease. For this purpose, the primary dataset from various facial expressions of a patient will be collected, filtered and apply to classification algorithm to train the model.
Published: 10 May 2021
International Journal of Preventive Medicine and Health, Volume 1, pp 1-4; https://doi.org/10.54105/ijpmh.b1002.051221
Heart diseases are one of the most challenging problems faced by the Health Care sectors all over the world. These diseases are very basic now a days. With the expanding count of deaths because of heart illnesses, the necessity to build up a system to foresee heart ailments precisely. The work in this paper focuses on finding the best Machine Learning algorithm for identification of heart diseases. Our study compares the precision of three well known classification algorithms, Decision Tree and Naïve Bayes, Random Forest for the prediction of heart disease by making the use of dataset provided by Kaggle. We utilized various characteristics which relate with this heart diseases well, to find the better algorithm for prediction. The result of this study indicates that the Random Forest algorithm is the most efficient algorithm for prediction of heart disease with accuracy score of 97.17%.
Published: 10 November 2020
International Journal of Preventive Medicine and Health, Volume 1, pp 1-7; https://doi.org/10.54105/ijpmh.a2005.111120
Covid-19 pandemic has changed the routines of families all over the world. From March 2020 up to today, Italian families are still struggling for adaptation. Parents of children and adolescents with a clinical diagnosis are more at risk for parental burnout, depression, and anxiety, and they are now experiencing restrictions in many services families relied on. Home-based and hospital-based interventions based on the Play Specialist’s approach have been limited due to anti-covid norms. Internationally, Play Specialist intervention has been empirically demonstrated effective in diminishing children’s negative emotions in relation to medical procedures and in increasing adaptation and compliance towards medical settings. Plus, Play Specialist’s intervention indirect effect on parental wellbeing is still unexplored. In Italy, differently from UK and USA, the Play Specialist intervention is not certified in the health-care system yet. The present study tests the effects on parental psychosocial health of a telematic adaptation of the Play Specialist approach (TPS), conducted in the post-lockdown months in Italy. Two groups of parents (N=33, Mean age=43.36, SD=9.81, Female= 66% receiving the TPS intervention, and N=33 Mean age=41.84, SD=6.15, Female=78% controls) of children in clinical conditions are compared. Parental burnout, anxiety, stress, depression, social support, and parental perception of children’s emotional problems have been measured via self-report questionnaires. Analysis of covariance reveals that the TPS group is less stressed, perceives higher social support, lower parental burnout (i.e., emotional distancing, contrast with other/previous Self, fed-up feeling), lower emotional and behavioural child’s problems than the control group. These findings are addressed at encouraging both research and practice around the Play Specialist’s intervention beyond the hospital-context.