..

Журнал исследований и разработок в области медицинского образования

Отправить рукопись arrow_forward arrow_forward ..

Объем 9, Проблема 4 (2021)

Обзорная статья

Parental support systems during end-of-life care of their newborns

Keren-Happuch Twumasiwaa Boateng, Vida Nyagre Yakong, Nicholas L. Yombei

Background: The progress made in neonatal intensive care delivery worldwide has resulted in optimal health outcomes of neonates, however, newborns and infants still die. The infants and newborns who die, majority of them die in Neonatal Intensive Care Units (NICU). The experiences of many parents following a poor prognosis of their newborns requiring end of life care suggest that parents usually need support from health care professionals who render direct services to their child, however, the extent and nature of this support is perceivably unknown. Purpose: The purpose of this study was therefore to explore parents’ lived experiences of support at NICU in Tamale Teaching Hospital (TTH). Methodology: Using an exploratory descriptive design, a semi-structured interview guide was used to collect data. Ethical approval was sought from TTH ethics review committee which is the final authority to give approval for the data collection. Purposive and convenience sampling was used to select eight (8) parents to inform the study. The participating parents completed an informed consent form prior to their participation in an interview. The results were analyzed using thematic analysis. Key findings: Effective communication and the provision of continuous, concise and complete information about child’s condition were important to parents during the end-of-life care (EoLC) of their newborns in the NICU; Parental support in terms of information and communication, emotional, psychological and spiritual support, as shared decision-making are essential for quality EoLC at the TTH. Recommendations: Accommodation should be provided for parents of babies on NICU admission. Support groups should be formed to assist parents of babies receiving EoLC.

Обзорная статья

Social Support System and its Influence on Maternal Experiences, Tamale Central Hospital

Keren Happuch Twumasiwaa Boateng

Hospitalization of neonates in NICUs may subject mothers to shock and depression as a result of giving birth to babies who have low birth weight or premature babies and hence very fragile. This type of hospitalization disrupts the family process and subjects the parents of these babies to a state of crisis and disarray. These challenges range from social, economic, physiological and psychological in nature. There are no support groups for mothers with preterm babies to share their pain, experiences or interact with other mothers with similar problems. Over all, the problems of preterm babies may be in the increase yet not satisfactorily documented in the Ghanaian context. This study seeks to explore the social support system and its influence on maternal experiences. The study used exploratory descriptive design. The Study was conducted in the Tamale Metropolis, specifically targeting women with preterm babies undergoing treatment at the Tamale Central Hospital. The purposive sampling technique was used to recruit participants for the study. A semi-structured interview guide was used to conduct face-to-face interviews with participants. The tape-recorded interviews were then transcribed verbatim and analyzed manually with the content analysis approach. The results were analyzed using thematic analysis. The findings of the study demonstrated that when the participants were provided with information on how to care and were also shown how to provide the caring activities, they developed confidence in taking care of their preterm baby. Support from staff, other mothers in the neonatal unit and the participants’ families assisted them to cope and promoted bonding. Management should support all neonatal intensive care facilities with adequate equipment and logistics to facilitate newborn care which will help limit the stay of hospitalized preterm babies in the neonatal intensive care units.

Обзорная статья

Maternal Iron Folate Supplement Delivery during Pregnancy in a Developing Country: Scoping Review

Kebreab Paulos, Dereje Haile, Adisu Yeshambel, Tigst Bekele

Background: It has been notified that ordinary consumption of dietary supplements containing iron or a combination of iron and folic acid for the duration of being pregnant improves maternal health and being pregnant results. Iron deficiency is the prevalent usual nutrient deficiency and the most common reason of anemia global. Because of the elevated iron necessities for the duration of being pregnant, iron deficiency can cause maternal anemia and decreased new child iron stores. Methods: Scoping assessment of maternal complement applications distribution strategies in low-earnings country such as Bangladesh, Ethiopia, India, Kenya, and Nepal are examined. A systematic search became executed in six databases; CINAHL (Cumulative Index to Nursing & Allied Health), MEDLINE, Web of Science, PubMed, and Scopus, and FSTA (Food Science and Technology) Results: A systematic search performed in six databases yielded a total of 526 un-duplicated results; (CINAHL: 42, Medline: 112, Web of Science: 77, PubMed: 90, Scopus: 179, FSTA: 10, and additional records: 16). Results after duplicates were removed (n=318), these results were screened, and relevant studies based on the research question identified and selected (n=10). The 10 full-text articles were assessed for eligibility and 5 of these studies were excluded for not meeting the scoping review criteria. Data was extracted and charted from the five remaining studies. The findings were collated and summarized. two modes of delivery were identified: 1. CommunityBased Distribution for Routine Iron/Folic Acid Supplementation in Pregnancy; and 2. pregnant women who received iron folate supplements from health centers/local centers; Conclusions: Barriers in delivering maternal supplements included lack of trained professional volunteers, limited support and guidance provided to volunteers, and a high cost of equipment, supplies, and buildings. Pregnant women in developing countries faced many obstacles in accessing maternal supplement programs including poverty, rural isolation, limited transportation, low social status, traditional, cultural, and religious practices. Strategies required to improve program delivery involved an earlier invitation to prenatal supplements, increase in partnerships, a focus on adolescent girls’ health, increase in training and incentives for volunteers, and self-help groups focused on prenatal education and counseling services.

Обзорная статья

Machine Learning in Public Health: A Review of the Problems and Challenges

MD Asadullah, Mamunar Rashid, Priyanka Basu, Md Murad Hossain

In recent years Machine learning that has been used for disease diagnosis and prediction in public healthcare sector. It plays an essential role in healthcare and is rapidly being applied to education. It is one of the driving forces in science and technology, but the emergence of big data involves paradigm shifts in the implementation of machine learning techniques from traditional methods. Computers are now well equipped to diagnose many health issues with the availability of large health care datasets and progressions in machine learning techniques. Several machine learning techniques have been used by researchers in public health. Several of these methods, including Support Vector Machines (SVM), Decision Trees (DT), Naïve Bayes (NB), Random Forest (RF) and K-Nearest Neighbors (KNN), are widely used in predictive model design research, resulting in effective and accurate decision-making. The predictive models discussed here are based on different supervised ML techniques as well as various input characteristics and data samples. Therefore, the predictive models can be used to support healthcare professionals and patients globally to improve public health as well as global health. Finally we provide some basic problems and challenges which face the researcher in public health.

Обзорная статья

Amyloid Beta as a Drug Target for the Treatment of Alzheimeraes disease

MD Asadullah, Mamunar Rashid, Priyanka Basu, Md Murad Hossain

In recent years Machine learning that has been used for disease diagnosis and prediction in public healthcare sector. It plays an essential role in healthcare and is rapidly being applied to education. It is one of the driving forces in science and technology, but the emergence of big data involves paradigm shifts in the implementation of machine learning techniques from traditional methods. Computers are now well equipped to diagnose many health issues with the availability of large health care datasets and progressions in machine learning techniques. Several machine learning techniques have been used by researchers in public health. Several of these methods, including Support Vector Machines (SVM), Decision Trees (DT), Naïve Bayes (NB), Random Forest (RF) and K-Nearest Neighbors (KNN), are widely used in predictive model design research, resulting in effective and accurate decision-making. The predictive models discussed here are based on different supervised ML techniques as well as various input characteristics and data samples. Therefore, the predictive models can be used to support healthcare professionals and patients globally to improve public health as well as global health. Finally we provide some basic problems and challenges which face the researcher in public health.

Мини-обзорная статья

Mental Health during COVID -19

Kaur Raman Deep*

Any global disaster whether natural or man- made leads to several severe physical and psychological concerns. Presently one of such concern 
which is influencing the cognitive well -being of the whole world is COVID -19. Started with few unexplained cases of pneumonia in 
Wuhan, China, COVID-19, novel coronavirus disease was declared pandemic by WHO in Jan’2020. To date (April 29th, 2020), over 
3018681 confirmed cases and 207973 deaths attributable to this disease have been reported as per WHO situation report.

исследовательская статья

Impact of Covid-19 Pandemic Lockdown on Social and Mental Health of Residence of Ondo State, Nigeria

Olasunkanmi Adeleke, Adegboro JS

Background: COVID-19 is an outbreak of global pandemic disease which is causing fears and concerns among many people, with a significant
influence on the social and mental well-being of every individuals. Considering the relevance of all the above factors, it was aimed to
investigate the impact of COVID-19 pandemic lockdown on social and mental health of residence of Ondo State, Nigeria.
Methods: The descriptive survey type research design was used in this study. Using probability sampling technique, data were obtained
through administration of questionnaire on 648 married couples with children in Ondo State. Data collected were analysed using
inferential statistics

исследовательская статья

Understanding about Contraceptive Devices among the Unmarried Adolescence

Bishnu Sapkota

Reproductive health is an essential and important factor of human life for which adolescence needs to have knowledge about it. This will help
them to plan for their family after marriage and in their future it even helpful to aware about the use of temporary and permanently contraceptive
method and devices. It is significant for male and female of different level of education through which they learn about the situation of
using contraceptive devices of different age groups of unmarried adolescence. It is necessary to have knowledge of reproductive
process and contraceptive devices. Our society still can’t talk about contraceptive devices and method as well as reproductive process in the
family setting and member of own family due to our culture. It is not good for talking in front of adolescence child. After gaining the
knowledge of reproductive health and its process, it is easy to minimize when the problem occurs in the time of reproduction process

Полная исследовательская работа

Perception of Patient and Visitors on Noise Pollution in Hospitals and Need of the Real Time Noise Monitoring System

Jagruti Patil

Background: Various studies have found that noise is rising in hospitals since the 1960's and it’s consistent. Hospitals should have the quietest environment. WHO rules on Community noise expresses that noise in the emergency clinics during night ought not to surpass 40 dinside. And during the day and evening the guideline value indoors is 30 dB (A). Noise has many negative impacts physiologically and psychologically not only on patients but on staff too. Still many hospitals have noise more than recommended limits. It has found that patients recover faster in good acoustic conditions as compared to bad acoustic conditions. And it can help to increase the HCAHPS score of the hospitals. To reduce the noise there is need to adopt various technologies which can monitor the noise and reduce it.

Methodology: To understand the perception of patients and visitors on noise in the hospital and the need of the real time noise monitoring system, a qualitative survey was conducted. The responses we got are from various regions of India. Also, a thorough study of the previous on the same topic was done to analyse the topic better.

Result: Despite WHO guidelines on noise for the hospitals, our study shows that noise in the hospitals are still rising and it’s exceeding the recommended limit. Patient’s sleep got hampered during hospital stay, they got irritated due to noise. And it resulted in low patient satisfaction.

Conclusion: Noise does not only impact the patient’s health, but also it leads to low patient satisfaction and negative perception towards the hospitals. People want hospitals to take necessary actions to reduce the noise like real time noise monitoring systems. By focusing on increasing patient satisfaction score, hospitals can achieve revenue goals.

исследовательская статья

Assesement of covid-19 seroprevalence and predictors among symptom suspected quarantined individual in North West Ethiopia. Institutional-based survey of recorded reviewed

Fassikaw Kebede, Tsehay Kebede, Birhanu Kebede

Novel coronavirus 2019 (COVID-19) is a worldwide spreading pandemic respiratory disease caused by a positive single strand (RNA) virus. The assiduous and persistent endeavored efforts for effective tackling of the COVID-19 pandemic remain futile and ineffectual. This study aims to assess COVID-19 seroprevalence and associated risk factors among symptom suspected quarantined individual in North West Ethiopia.

Methods: Institutional-based survey of COVID-19 symptoms suspected quarantined individuals from 21 Aprils- 30 December 2020. The collected data were edited and enter into EPI-DATA 3.1 version, then export to STATA/R-14 (SE) software for analysis. Bi-variables logistic regression was used for candidate variables transfer to multivariable logistic regression at P-value<0.25. Adjusted odds ratio with its 95% (CI) was used to declared statically significant variables at p-value<0.05. 

Results: Of total 4233 quarantined individuals who received the SARS-CoV-2 IgG antibody test, 4230/99.78% were interviewed with a 99.82% response rate. The overall seroprevalence of COVID-19 symptom suspected quarantined individuals in North West Ethiopia was found 5.11: 95% CI (4.4--5.87). The overall knowledge and practice of prevention towards COVID-19 infection on isolated individuals were found 86.17% (95%CI: 85.1--87.2) and 62.82%; 95%CI: 60.75--63.8), respectively. The risks of developing COVID-19 infection among quarantined groups who had poor knowledge and poor practice were 1.49 (AOR=1.49 95%CI: 1.13--2.2, P< 0.027), and 2.9 (AOR=2.9; 95%CI: 2.2--3.9; P<0.01) times increased.

Conclusion: The seroprevalence of the quarantined population is high as compared with previously reported. The majority of the respondents know how to prevent themselves from the COVID-19, but changing this prevention knowledge into the practice of tackling is great hiatus.

Индексировано в

arrow_upward arrow_upward