Asian Pacific Journal of Health Sciences
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An Online Study of MBBS Student Performance in Internal Assessment of a Pre-clinical Department during the COVID-19 Pandemic
Get PDFBackground: The COVID-19 pandemic has had a significant impact on medical education. As the crisis persists, it is critical to develop valid and reliable assessment methodologies. Aims: The aims of this study were to determine the impact of competency-based medical education (“COMPETENCY-BASED MEDICAL EDUCATION”) implemented online in the biochemistry department during the pandemic on the results of online internal assessments. Materials and Methods: After receiving institutional clearance in 6 months, this pilot study was done on 150 1st-year MBBS students at IQ City Medical College and Hospital, Durgapur. In 6 months, two internal assessments have to be completed online. Multiple choice questions, short answer type questions, orals, and spots were divided into four compartments during our internal evaluation sessions, which were held 3 times a month. A survey was conducted to gather data pertaining to student stress levels during offline and online examinations. Statistical analysis: The data were analyzed using the paired t-test. Reliability of data was checked using Cronbach’s alpha. Results: Participants ranked Expected Offline Examination Stress Risk higher (M = 4.7200, Standard deviation [SD] = 1.58906) as opposed to the Expected Online Examination Stress Risk (3.6800, SD = 1.53841), a statistically significant mean increases of 1.04000, and 95% confidence interval (CI) [0.81192, 1.26808], t (149) = 9.010, P < 0.001. In case of perceived risks, participants ranked Perceived Offline Examination Stress Risk higher (M = 4.7600, SD = 1.64533) as opposed to the Perceived Online Examination Stress Risk (M =3.6867, SD = 1.63081), a statistically significant mean increases of 1.07333, 95% CI [0.83098, 1.31568], t (149) = 8.751, P < 0.001. Conclusions: According to the findings of this study, students expect and perceive online examination stress risk to be lower than that of offline examinations. The research also revealed that students were able to score higher in online tests than in offline exams, implying that the department of biochemistry may conduct internal assessments as well as implement “COMPETENCY-BASED MEDICAL EDUCATION” online
Awareness and Attitudes toward COVID-19 Pandemic among Elderly Population of West Bengal
Get PDFBackground: COVID-19 has emerged as a pandemic and it has had unprecedented negative impact on elderly population. A lack of awareness and poor understanding of the disease may result in rapid transmission of the disease. This study aimed to investigate the awareness and attitude toward COVID-19 among elderly population in West Bengal, India. Methods: This cross-sectional study was conducted with the help of an online questionnaire and sent to elderly population of West Bengal. The study comprised a series of questions regarding demography, family composition, awareness, attitudes, and practices as precautionary measures from COVID-19. Results: A total of 212 elderly respondents participated in this study comprising 55.66% of males and 44.34% are females. Overall 75.58 ± 3.21 respondents showed good knowledge and awareness about COVID-19. Avoiding social gathering (84.43%), preference to stay in home (76.89%), and wearing mask (74.06%) were the most common preventive measures taken by respondents that were followed using sanitizing (58.96%) and avoiding traveling (24.64%). Significantly more educated and employed respondents showed more considerable knowledge of the disease awareness. Conclusion: The study respondents showed adequate basic knowledge and awareness of COVID-19. There is a strong need to implement periodic educational interventions and training programs on infection control practices
Temporal Study of Physicochemical Characteristics and Qualitative Plankton Diversity of a River Kosi, a Tributary of West Ramganga in Reference to the Habitat of Garra gotyla gotyla
Get PDFThe river, Kosi originates from the western slope of the Kaushani range and flows (mountains of Almora, Nainital and Udham Singh Nagar) in the southern direction and joins the river, Western Ramganga at tarai region. Along with the total catchment area of 3,420 sq.km., river Kosi covers a distance of 240 km. The present study determines the habitat at of Garra gotyla, physicochemical parameters of water and plankton diversity of river Kosi from January 2019 to December 2019. During the study, various physicochemical parameters such as air temperature, water temperature, pH, dissolved oxygen, dissolved free carbon dioxide, electrical conductivity, velocity, transparency, total dissolved solids, and total alkalinity were analyzed. The biological study was focused on the qualitative assessment of phytoplankton and zooplankton diversity. A total of 34 species of phytoplankton as well as 13 species of zooplankton were recorded during the present study and among phytoplankton, the dominant group was the members of the class- Bacillariophyceae
Identification and Prioritization of Black Spots in Hilly Road Segment Using Accident Severity Index Method
Get PDFIntroduction: Road traffic accidents (RTA) will become the third-largest contributor to the global burden of diseases after the ischemic heart diseases and depression. The place where the traffic accident percentages are higher is called as black spot location. The most common assumption for a black spot location is that, there should be any road environmental or geometric issues resulting in the repetition of accidents. Methodology: Our study was conducted in two districts of the Northern Region of India (Uttarakhand). The data were collected on various factors such as weather, accident type, severity levels, and road geometry such as number of curves, segment length, Annual Average Daily Traffic. Results: The present study was an attempt to find out the black spots and to measure the accident severity index (ASI) of the identified black spots in the areas of Dehradun and Haridwar. For each location the ASI was calculated and the Rankings were allotted to the black spots so as to find the severity of the black spots. Conclusion: The present study also suggests that the RTA should be taken under consideration as per the accident severity rather than the frequency of the accidents
Artificial Intelligence Based Automatic Speech Emotion and Drunkenness Detection Using Convolutional Neural Network Voice Segment Dropout Optimizer
Get PDFSpeech recognition is far from an easy task, because of the unique nature of the human emotional text and a speech recognition model must strike a balance between being accurate. It should be accurate and sufficient enough to cause a broad group of datasets to separate and prevent errors. The models of the states created using artificial intelligence: Positive, sadly angry, and likely to fall are the easy ways to find the drunkenness or non-drunkenness. By building on the previous methods of emotional detection, drunkenness data set experiences can accurately identify these states. The solution development goal is to evaluate in real time because of the different voice recognition from consumers. It is reported to give the user an idea of what emotion they are experiencing or whether they are stumbling, if an assistant detects a drunk person, it will alert him or her about or making large online data extracted drunk information. If the model proves reliable, it can be used in voice-activated, the artificial intelligence (AI) is characterized by a lack of social or situational awareness of the person with it interacts to active on first stage. The second stage to direct on support Artificial Intelligence and Convolutional Neural Network Voice Segment Dropout Optimizer (CNN-VSDO) algorithm is a system that maintains the issues mentioned above that minimize the risk of overlapping. The convolutional neural network for classification employs filters to features from the spectrogram. This approach is used in personal assistant systems to provide the highest and most suitable of AI-human interaction and more appropriate state-based interactions between AI and humans
Lung Infection Detection using Progressive UNet Architecture
Get PDFThe fragmentation of medical images of tissue anomalies in organs or the blood vascular system is critical for any computerized diagnostic system. Nevertheless, automated segmentation in medical image analysis is complex since it requires in-depth information about the target organ architecture. This paper presents UNet, an end-to-end deep learning segmentation technique for early recognition of COVID. The proposed UNet model is progressive and capable of diagnosing different lung infection types along with COVID-19 infection. For this, computed tomography images are considered. The XGBoost classifier is integrated with UNet for feature classification in this model. The result analysis was performed on different convolution neural network models, that is, ResNet50, Inception, ResNet101, ResNet152, DenseNet, and UNet. These models were implemented on MATLAB using the deep neural network toolbox. From the result, it has been noticed that Inception achieved a minimum accuracy of 85.2%, and UNet achieved 99% of accuracy. It has been observed that UNet achieved approx. 16% of improvement over the inception model
Use of Chatbot for Addressing Adolescent’s Queries on Sexual and Reproductive Health-related Issues – Findings from a Field Implementation in Madhya Pradesh, India
Get PDFAs per the Census of 2011, adolescent and young people (10–24 years of age) constitute around 30% of the India’s population. Young people face number of challenges in accessing information on sexual and reproductive health (SRH) due to associated taboos. To address these challenges, an initiative was launched to provide life skill-based education to the adolescent across 120 villages in two districts of Madhya Pradesh. After the program implementation for a year, it was observed that adolescents were not comfortable during the SRH sessions. Hence, after discussion with adolescents a chatbot was designed and launched. The chatbot had access to more than 9000 question and answers including audio and video materials. After 6 months, a brief assessment was undertaken with 2047 adolescent (boys - 1186 and girls - 861) to assess its relevance and usefulness. The concept of chatbot was appreciated by 93% of the respondents and they prefer it instead of having face-to-face conversation with counselor or health-care providers. About 90% respondents appreciated the fact that it is easily accessible, 87% respondents appreciated that it has comprehensive information and 86% respondents found chat messages appropriate. About 24% respondents were worried that as their family members may see their chats. About 38% respondents also expressed the need of making it multilingual and support some regional languages. Chatbot can be very powerful medium to address adolescent’s queries on SRH-related issues as it is easily accessible, and adolescent feel more comfortable. At the same time, it needs to be backed with quality service provision
Usefulness of Gastropanel for Validation of Efficacy of Drugs from Traditional Systems of Medicine in Functional Dyspepsia
Get PDFGastropanel, serological ELISA test comprising of stomach biomarkers; serum pepsinogen I, pepsinogen II, gastrin-17, and Helicobacter pylori antibody depicts clearly the morphological and functional status of stomach mucosa in patients suffering from dyspepsia. Although the traditional system of medicine is a huge resource of efficient formulations useful in gastrointestinal disorders such as functional dyspepsia, lack of robust scientific evidence, and qualitative/subjective parameters like symptom scores do not suffice the need for the same. This study was thus planned to assess usefulness of gastropanel tests to validate efficacy of Avipattikar choorna, well-known antacid remedy in functional dyspepsia. A. choorna was given to patients of dyspeptic disorders following which gastropanel was performed pre- and post-treatment. The gastropanel findings obtained, prior and post-interventions were compared using Wilcoxon MPSR test and a level of P < 0.05 was considered for statistical significance. It was observed that although symptom scores showed improvement in all patients after treatment, change in pre- and post-values of gastropanel was seen only in few patients. Gastropanel could differentiate between true responders and non-responders, identification of which was difficult merely with symptom scores. Another highlight was that A. choorna proved more effective in H. pylori IgG positive cases. Gastropanel may be used as an effective tool to understand and validate the efficacy of traditional medicines in functional dyspepsia and gastric disorders along with its effect on stomach physiology and acid regulation. Need for employment of quantitative/objective parameters for traditional system drugs validation is also highlighted
A Case Study on Breathing Rehabilitation in a 32-year-old Male with Dysfunctional Breathing
Get PDFDespite having a significant impact on the personal, psychological, and social dimensions of a person’s health, health professionals’ emphasis on the epidemiological, pathological, and physiological basis of the dysfunctional breathing, therefore, fails to provide patients with an appropriate treatment. Given the multifarious and psychophysiological nature of dysfunctional breathing, a holistic and multidimensional management would seem the most appropriate way to manage such a prevalent condition This case study presents a holistic approach to comprehensively manage dysfunctional breathing. That being the case, interventions for four key domains — biochemical aspects, biomechanical aspects, psychosocial aspects, and respiratory symptoms — were provided. It was obvious from the outcome findings that dysfunctional breathing can only be successfully understood by relating it to the person’s life experiences including their, beliefs, values, emotions, influences, and social relations
Exploring the Role of Social Connectedness and Health Anxiety in Predicting Psychological Well-being
Get PDFBackground: Due to COVID-19 pandemic, social distancing was taken as one of the precautionary measure in India. Uncertainty about signs and symptoms, modes of transmission, and lack of definite treatment of COVID-19 have put the mental health of people in India at risk. This study was carried out to explore the role of connectedness, affiliation, and companionship factors of social connectedness and health anxiety in predicting psychological well-being and its components. Method: This study was carried out on 317 Indian adults recruited through convenience sampling method during July 2020 to November 2020. Hypotheses were tested using linear regression methods. Results: Companionship predicted 1.9% and 7.7% of variance in autonomy and environmental mastery, respectively. Affiliation predicted 6.7% variance in personal growth. Connectedness and companionship explained 26.8% variance of positive relationships with others and 16.1% of self-acceptance. Health anxiety predicted 6.3%, 6.8, 6.7%, 8.3%, and 9% variance of autonomy, environmental mastery, personal growth, positive relationship with others, and self-acceptance, respectively. Conclusion: “Connectedness” and “companionship” were the significant predictors of “positive relationships with others” and “self-acceptance.” “Companionship” predicted “autonomy” and “environmental mastery,” whereas “personal growth” was predicted by “affiliation.” Health anxiety predicted all domains of psychological well-being except purpose of life