South Eastern European Journal of Public Health (SEEJPH - Universität Bielefeld)
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Employing PLS-SEM Analysis to Examine the Mediation Role of Artificial Intelligence in Physician Experience. An Empirical Study of the Effect of the Medical Smartwatch on Physician Satisfaction
Full text linkObjective: The rapid advancements in the Internet of Things (IoT) have allowed end users to enjoy restriction-free access to information. One of the notable developments in IoT is the introduction of wearable technologies, such as smartwatches. The growing popularity of wearable technology has made it possible for users to receive health and fitness data regardless of time or place. This study aims to examine the mediation role of artificial intelligence in physician experience toward using the medical smartwatch, particularly examining the effect of the medical smartwatch on physician satisfaction.Methods: This study utilized a deductive research approach employing a cross-sectional design. Data was collected through online questionnaires from healthcare providers, particularly physicians in the United Arab Emirates (UAE). The Structural Equation Modelling analysis (SEM) was employed to evaluate the theoretical and final path models. This study further assessed the theoretical model using the Partial Least Squares (PLS) as it offers concurrent analysis for evaluating the structural model and enhancing result accuracy.Results: Artificial Intelligence (AI) experience significantly influenced physicians’ satisfaction. Additionally, the study provided supporting, satisfying evidence for the mediating effects of AI experience.Conclusion: The study provided supporting evidence for the mediating effects of AI experience on physicians’ satisfaction. This study bridges the gap in the literature regarding the absence of studies examining physicians’ perceptions of medical smartwatch usage in the medical domain by providing a profound understanding of physicians’ satisfaction and perceptions regarding smartwatch usage in the UAE.This study bridges the gap in the literature regarding the absence of studies examining physicians’ perceptions of medical smartwatch usage by providing a profound understanding of physicians’ satisfaction and perceptions regarding smartwatch usage in the UAE
Clinical Profile Of Congenital Eye Abnormalities In Children Aged 0-5 Years And Their Correlation With Demographic Factors
Full text linkBackground: Congenital eye abnormalities encompass a wide range of structural and functional defects present at birth, contributing significantly to childhood visual impairment and blindness. Understanding their clinical profile and demographic associations is essential for early detection and prevention. Aim of the study: To evaluate the clinical spectrum of congenital eye abnormalities in children aged 0-5 years and analyze their correlation with demographic factors. Methods: This hospital-based observational study was conducted over one year in Bangladesh. Eighty-two pediatric patients presenting with congenital ocular anomalies were included. Data on clinical features, antenatal history, and demographic variables were collected using a structured questionnaire. Comprehensive ophthalmologic examinations were performed, and findings were analyzed using SPSS v26.0. Result: Children aged 4-5 years constituted the largest group (56.10%), with a male predominance (64.63%). The most common presenting symptom was decreased ocular vision (18.29%), followed by watering of eyes (13.41%). Congenital cataract was the most prevalent anomaly (46.74%), followed by coloboma of the iris and choroid (33.62%), and anophthalmos (19.68%). Bilateral involvement was more frequent than unilateral presentation. Conclusion: Congenital cataract, coloboma, and whole globe anomalies are the predominant ocular abnormalities in early childhood. Timely screening and intervention strategies are essential to minimize long-term visual disability, especially in resource-limited settings
Personalized Patient Care Through AI-Driven Segmentation Predictive Modelling Thyroid Disease Detection Using Machine Learning
Full text linkThe thyroid gland is the crucial organ in the human body, secreting two hormones that help to regulate the human body’s metabolism. Thyroid disease is a severe medical complaint that could be developed by high Thyroid Stimulating Hormone (TSH) levels or an infection in the thyroid tissues. Hypothyroidism and hyperthyroidism are two critical conditions caused by insufficient thyroid hormone production and excessive thyroid hormone production, respectively. Deep learning models can be used to precisely process the data generated from different medical sectors and to build a model to predict several dis- eases. In this paper, we use different machine-learning algorithms to predict hypothyroidism and hyperthyroidism. Moreover, we identified the most significant features, which can be used to detect thyroid diseases more precisely. After completing the pre-processing and feature selection steps, we applied our modified and original data to several classification models to predict thyroids. We found Random Forest (RF) is giving the maximum evaluation score in all sectors in our dataset, and Naive Bayes is performing very poorly. Moreover, selecting the feature by using the feature importance method RF provides the best accuracy of 91.42%, precision of 92%, recall of 92% and F1-score of 92%. Further, by analyzing the characteristics and behavior of the dataset, we identified the most important features (TSH, T3, TT4, and FTI) of the dataset. In terms of accuracy and other performance evaluation criteria, this study could advocate the use of effective classifiers and features backed by machine learning algorithms to detect and diagnose thyroid disease. Finally, we did some explain ability analysis of our best classifier to understand the internal black-box of our machine learning model and datasets. This study could further pave the way for the researcher as well as healthcare professionals to analyze thyroid disease in real time applications
A Comparative Analysis Of Social And Economic Development Indicators In India And Bhutan
Full text linkThe friendship between India and Bhutan is not a new one. Apart from sharing a common boundary, the two nations share a history of rich culture and heritage. There exists friendly relation between Bhutan and India as per bilateral treaty of 1949. Both India and Bhutan being one of the founder members of the SAARC, they try to promote meaningful bilateral and multi- lateral trade relations. The friendly relations between the two countries have been going on since long and are strengthening further with the passage of time. However, the two countries differ in their outlook towards growth and development in the modern times. India is doing well as far as attracting foreign investment is concerned but Bhutan is strengthening its culture, working towards a healthy, happy and a clean environment. They believe that without happiness, moral and ethical values economic growth is just a number and wouldn’t last long. Their approach to development is a more balanced one. Instead of the 3 P’s of India (Public Private Partnership) their focus is on People Progress and Participation. What needs to be learnt from one another are ways of economic achievements which are concentrating on societal, moral and ethical values and how important in today’s time is the need to take preserve the rich roots of one’s own culture. Going by the strategic location of these two countries, good governance is required to achieve social and economic goals domestically and to achieve the growth targets in this era of increased globalization and privatization. Research Methodology: The trading history of the two nations is compared based on secondary data collected from the Embassy of India, in Thimpu, Bhutan. The indicators used for understanding the growth aspect of the two nations, are GNI Per Capita, HDI and GNH. The source used for the same would be World Bank Data reports for the year 2014-15. The other sources for making comparisons based on social factors are The SAARC Reports, 2013& the UNDP Human Development Reports, 2016.The data taken from the World Happiness Report, 2017, will be studied and analysis of the reasons behind the social and economic indicators will be put forth
Role Of Intrinsic Foot Muscles Strengthening Exercise In Reducing Pain Of Plantar Fasciitis
Full text linkBackground: Plantar fasciitis is a prevalent cause of heel pain, often resulting from inflammation and microtears in the plantar fascia due to biomechanical imbalances, overuse, or decreased intrinsic foot muscle strength. While traditional treatments include rest, anti-inflammatory medications, and orthotics, recurrence and chronic symptoms remain significant challenges. Emerging evidence suggests that strengthening intrinsic foot muscles may offer a conservative and sustainable management strategy. Objective: This study aimed to evaluate the role of intrinsic foot muscle strengthening exercises in reducing pain and improving foot function among patients with plantar fasciitis. Methods: A quasi-experimental study was conducted among 30 adults clinically diagnosed with plantar fasciitis at Department of Physical Medicine and Rehabilitation, Bangabandhu Sheikh Mujib Medical University (BSMMU), Bangladesh, between July 2018 and June 2019. Participants underwent a structured 4 to 6-week exercise regimen that included toe curls, marble pickups, short foot, and doming exercises. Pain intensity and foot function were assessed using the Visual Analog Scale (VAS) and Foot Function Index (FFI), respectively, before and after the intervention. Data were analyzed using paired t-tests, with significance set at p < 0.05. Results: Participants showed significant improvements following the intervention. The mean VAS score decreased from 7.2 ± 1.1 to 3.6 ± 1.2 (p < 0.001), indicating substantial pain reduction. Similarly, total FFI scores improved from 68.5 ± 9.3 to 42.3 ± 10.2 (p < 0.001), with notable reductions across all subscales—pain, disability, and activity limitation. High adherence (90%) and absence of adverse events highlighted the safety and feasibility of the intervention. Conclusion: Intrinsic foot muscle strengthening exercises significantly reduced pain and improved foot function in patients with plantar fasciitis. Given their effectiveness, safety, and accessibility, these exercises can be incorporated into conservative treatment protocols to enhance clinical outcomes and reduce dependency on pharmacologic or surgical interventions
Effects Of Back School On Chronic Nonspecific Low Back Pain In Adolescents
Full text linkBackground: Low back pain (LBP) is a common condition among adolescents, with significant implications for their health and quality of life. This study aimed to assess the prevalence of LBP and examine its associations with age, Body Mass Index (BMI), backpack weight, and posture in adolescent students. Methods: A cross-sectional study was conducted with 60 adolescent students aged 14-17 years from local schools in Dhaka, Bangladesh. Data were collected through self-reported questionnaires and physical assessments to determine the prevalence of LBP and identify risk factors. Participants were categorized based on age, BMI, backpack weight, and posture type. Descriptive statistics and Chi-square tests were used for analysis, with a p-value of <0.05 considered statistically significant. Results: The prevalence of LBP was found to be 78.3%, with the highest incidence observed in 15-year-olds (50%) and underweight adolescents (50%). A significant association was found between LBP and heavier backpack weight, with 33.3% of students in the 2.001–3.00 kg category reporting pain. Posture type was also a significant factor, with sitting posture (41.7%) being most strongly associated with LBP. Statistical analysis revealed significant associations between age, BMI, backpack weight, and posture type with the prevalence of LBP (p<0.05). Conclusions: The study highlights the high prevalence of LBP among adolescents, particularly in relation to age, BMI, backpack weight, and posture. These findings suggest that interventions such as Back School programs, aimed at promoting proper posture and reducing backpack weight, could help prevent and manage LBP in this age group. Further longitudinal studies are recommended to explore the long-term effects of these factors on adolescent back health
Harnessing Clinical Data To Improve Healthcare Efficiency
Full text linkIn recent years, healthcare systems worldwide have faced immense pressure to enhance efficiency and provide better patient outcomes while reducing costs. One of the key solutions lies in the ability to harness clinical data for improved decision-making, resource allocation, and treatment outcomes. Clinical data, such as patient records, diagnostic results, and treatment histories, offers valuable insights into the effectiveness of healthcare interventions. This research explores how clinical data can be leveraged through advanced analytics, machine learning algorithms, and data integration techniques to optimize healthcare delivery. By using real-world data, the study aims to enhance decision-making processes and provide a foundation for predictive modeling in clinical settings. The paper presents various tools, methodologies, and challenges in utilizing clinical data, as well as their potential to improve healthcare efficiency. The research further discusses the importance of data-driven approaches in enhancing operational efficiency and patient outcomes. Results suggest that integrating clinical data across platforms and applying analytics leads to better resource allocation, reduces patient wait times, and enables more personalized care pathways. The study’s findings provide valuable insights for policymakers, healthcare practitioners, and technology developers interested in optimizing healthcare systems through data-driven approaches