Healthcare Professionals Research Articles

Examining the Financial Literacy of Healthcare Professionals: A Research on a Provincial Health Directorate.

This research aimed to assess the financial literacy levels of healthcare professionals working at a Provincial Health Directorate and examine their relationships with various financial domains. The study utilized a cross-sectional online survey. The financial literacy scale was employed to assess the financial knowledge and compentencies of healthcare professionals, providing a structured evaluation of their understandig across various financial domains. Statistical analyses, including correlation analysis, independent samples t-test, and one-way ANOVA, were performed using SPSS-25 and R programs. A total of 240 participants took part, comprising 52.1% males and 47.9% females, aged between 20 and 65 years. Younger healthcare professionals (p=.017) and males (p=.001) demonstrated higher financial literacy levels. Significant correlations were found between financial literacy and domains such as investment instruments, debt and risk management, and personal finance management. Weak but positive relationships were observed between financial literacy and digital assets, indicating emerging trends in digital finance awareness. For instance, males exhibited higher proficiency in investment instruments and debt management, while younger professionals displayed higher knowledge in investment areas. The findings underscore the importance of targeted financial education for healthcare professionals, highlighting the need for sector-specific training programs. Enhanced financial literacy is essential for improving financial decision-making, ultimately benefiting both personal financial well-being and professional performance in the healthcare sector.

The impact of workplace violence on healthcare professionals’ quality of life: the mediating role of social support

The impact of workplace violence on healthcare professionals’ quality of life: the mediating role of social support

Older adult immigrants' experiences of being hospitalized: a qualitative study.

Access to equal health services is a key issue in most European countries. In the coming years, immigrants will constitute an increasing proportion of older adults in Europe, and their need for healthcare services will likely increase. Healthcare services must prepare for such encounters to make them equitable. Older immigrants' hospitalization experiences require elucidation. Their patient experiences can provide important knowledge when the healthcare system is working toward equal and equitable healthcare services. This study employed an exploratory qualitative design. Data were collected through narrative interviews with a purposive sample of eight older adult immigrants, aged 61-79 years. Patient narratives were analyzed using thematic analysis with a reflexive approach, as outlined by Braun and Clarke. The analysis created three themes that shed light on older adult immigrants' experiences as hospital patients. The themes conveyed experiences related to challenging involvement and interaction, notions of what an ideal patient should be like, and participants not feeling valued as a person. The findings indicate that communication between healthcare professionals and older adult immigrant patients is deficient: older immigrants in this study did not make their voices heard nor were they invited to participate by healthcare professionals. This contributes to limited involvement in assessment, treatment, and care. The older immigrants felt that they were not valued nor met as unique individuals. The findings indicate that health policy goals regarding patient participation and person-centered care are not met when older immigrants are patients. Consequently, the experiences of older adult immigrants in this study indicate that equal health services are at risk.

From Clinical to Non-clinical Outcomes in the Treatment of HIV: An Economic and Organizational Impact Assessment.

The aim of this study was to define the economic and organizational impacts related to a broader utilization of bictegravir/emtricitabine/alafenamide (BIC/FTC/TAF) in Italian clinical practice. A budget impact analysis-representing the evolution of the Italian National Healthcare Service (NHS) healthcare expenditure over 3years-was developed, considering the overall Italian population treated for human immunodeficiency virus (HIV). Model input variables were treatment history, therapeutic regimen, development of adverse events, achievement of an undetectable viral load and total direct healthcare costs. Besides the BIA, an organizational impact assessment was conducted to determine the impact on the use of healthcare resources, assessing the release of organizational hospital assets, focusing on the management of drug-related adverse events. Data were collected from scientific evidence, Italian national and regional legislations and healthcare professionals' reports. To verify the robustness of the economic and organizational impact assessment, sensitivity analyses were performed. Results demonstrate economic savings of about 26million euros in total health spending, assuming a higher penetration rate for BIC/FTC/TAF. This change in the current case mix would lead to a reduction in the specific costs related to adverse event management (0.9million euros; -2.09%) and in the medical management of patients (38million euros; -7.79%), with a positive impact on the achievement of virological control. From an organizational perspective, a wider use of BIC/FTC/TAF generates a reduction in the utilization of healthcare resources due to a decrease in adverse events and complications. The model estimated a 19.64% reduction in HIV-related inpatient days, which freed up healthcare professional time. Capable of improving both economic and organizational sustainability for the entire HIV care continuum, BIC/FTC/TAF is an efficient therapeutic strategy for people with HIV.

How consumer trust affects the adoption of e-healthcare products on mobile apps: an analysis of perceived usefulness, time, and price

Purpose E-healthcare has gained importance, particularly in emerging economies, because of its ability to provide health-care products and services while minimizing contact with the external world, which was particularly relevant during the COVID-19 pandemic. Despite its advantages, consumers seem hesitant to use mobile apps to access such services. Previous research has found that perceived usefulness, time consumption and price significantly impact consumer willingness to purchase e-healthcare products on mobile apps. This study aims to investigate the role of consumer trust in the willingness to purchase e-healthcare products on mobile apps while controlling for the effects of perceived usefulness, time consumption and price. Design/methodology/approach Data have been collected using non-probability judgmental and snowball sampling techniques from five major cities in India. After the data cleaning process, 238 questionnaires were used for data analysis in this study. The authors used confirmatory factor analysis to validate all the constructs and subsequently used the hierarchical regression technique to conduct this study. Findings The study’s findings show that consumer trust is the most crucial factor for predicting a willingness to purchase e-healthcare products through mobile apps, despite several other variables that also have a positive impact. These findings present important practical implications for mobile app developers, health-care professionals and lawmakers to further enhance the adoption of e-healthcare products on mobile apps. Research limitations/implications The research was conducted by considering primarily young adults (those between the ages of 20 and 45 – above) and targeted five cities in India. This highlights a limitation in the research, as small groups of the intended audience were included (mainly young people). Originality/value This study considers perceived usefulness, time and price, in addition to trust, to predict consumer willingness to purchase. Its findings can be valuable in the fields of consumer behavior, health care and technology, especially in emerging markets.

The Discourse Surrounding Polycystic Ovary Syndrome on TikTok: A Social Media Analysis

Background/Objectives: Individuals are turning increasingly towards online resources, such as TikTok, to educate themselves on their medical conditions. Polycystic ovary syndrome (PCOS) is a prominent example, as women report dissatisfaction with the diagnosis process and treatment options. This study aims to provide a content analysis of the quality of PCOS health information on TikTok. Methods: A total of 325 TikTok videos were screened. Pertinent data, including likes, comments, shares, and views, along with video content concerning symptoms, interventions, and provider interactions were analyzed. Two reviewers independently used a modified DISCERN criteria to assess the quality of information for each video. A logistic regression was also utilized to model the probability of healthcare professionals creating educational videos. Results: A total of 238 videos met the eligibility criteria for analysis. Videos had a median of 468,400 views (Q1 = 146,400, Q3 = 1,100,000) and 18,000 likes (Q1 = 5631, Q3 = 65,100). The mean modified DISCERN scores were 3.6 ± 0.9 for physicians (n = 23), 2.0 ± 1.1 for non-physician healthcare providers (n = 52), and 1.0 ± 0.2 for non-healthcare professionals (n = 141) (p < 0.001). Healthcare professionals were 10.9 times more likely to create educational videos in comparison to non-healthcare professionals (p < 0.001). Conclusions: TikTok videos related to PCOS attract considerable engagement but provide low-quality information. Most videos were made by non-healthcare professionals, who discussed treatment options with limited or no research. Healthcare providers should be aware of the impacts on patients’ preconceived notions and help to improve patient education.

Semantic Segmentation Based on Geometric Calibration Using AI and AR in Health Care

In the medical field, medical imaging is essential for precise diagnosis, treatment planning, and condition monitoring. The goal of this work is to improve the field of healthcare imaging by investigating the complementary applications of augmented reality (AR) and artificial intelligence (AI) in semantic segmentation. More precise identification and delineation of anatomical structures and abnormalities in medical images is made possible by AI-driven semantic segmentation, opening the door to more precise diagnosis and treatment plans. Modern AI algorithms are employed in the suggested methodology to perform semantic segmentation in a variety of medical imaging modalities, including ultrasound, CT, and MRI scans. The detection of anomalies such as tumours, irregularities in organs, and neurological disorders is made easier by these algorithms. The foundation for integrating augmented reality technologies into the healthcare ecosystem is provided by the segmented medical images. AR enhances the interaction and visualization of segmented medical data in the context of healthcare. Real-time augmented reality overlays help surgeons by improving surgical navigation and precision. Additionally, AR apps help with medical education by offering professionals and students alike an immersive learning environment. AR provides interactive visualizations to help patients understand their medical conditions when they are going for therapy and rehabilitation. The difficulties in integrating these technologies in the healthcare industry are discussed in this paper, with a focus on the significance of data privacy, regulatory compliance, and easy integration with current healthcare systems. The successful deployment of AI technologies necessitates interdisciplinary collaboration among AI developers, healthcare professionals, and AR specialists to ensure compliance with ethical, legal, and clinical standards mandated in the healthcare domain. The proposed Segmentation mask is redefined with geometric calibration and used with U-Net for image segmentation. The segmentation is experimented on Cityscapes and PASCAL VOC 2012 datasets. The experimental results show that proposed semantic segmentation based on geometric calibration yields more accuracy than its counterparts.

Maternal heart failure: state-of-the-art review.

Pregnancy is a period of substantial changes to the body's normal physiology, and the failure to adapt to these changes can lead to life-threatening pathology, particularly involving the cardiovascular system. In comparison to pre-pregnancy physiology, pregnant women have increased blood volume and physical demands which exert increased stress on the heart. This is important to consider in women with and without previously diagnosed cardiovascular disease, as the physiologic changes during pregnancy and postpartum can lead to sudden decompensation. The management of heart failure is particularly important as it remains the most common cardiovascular complication during pregnancy and is associated with substantial maternal and fetal morbidity and mortality. This is especially true in patients with pre-existing heart failure, who should receive counseling before conception and in certain cases be advised against pregnancy. For these reasons, healthcare professionals must be well-versed in the different strategies of diagnosis, management, treatment, and monitoring. This review will outline the pathophysiology, diagnostics, management, and general approach to heart failure in pregnant patients.

Abstract 4147627: A Pharmacovigilance Study of Bempedoic Acid: Balancing Risks and Benefits

Introduction: Bempedoic acid has been approved by FDA since Feb 2020 as an adjunct to maximally tolerated statin therapy for the reduction of LDL-C, specifically in individuals afflicted by atherosclerotic cardiovascular disease (ASCVD) and heterozygous familial hypercholesterolemia (HeFH). Bempedoic acid is also a viable alternative for patients intolerant to statins. Most recently, it has been approved to use for primary prevention of hyperlipidemia, alone or in combination with a statin. It is important to study its side effect profile as it is anticipated to be used more frequentlynin the future. Methods: We explored reported adverse events (AEs) of bempedoic acid using FDA Adverse Event Reporting System (FAERS). A total of 1202 adverse effects were reported until March 31, 2024. 69.97% AEs were reported by healthcare professionals (HCPs), which were further analyzed. AEs were analyzed in men (32.53%) vs women (53.24%) and in three age groups of 18-64, 65-85, and >85 years. Results: A total of 586 (48.7%) events were serious adverse effects. Most common side effects were myalgia which included muscle pain, extremity pain and muscle spasm (25.04%), arthralgia including back pain and bone pain (18.47%), nausea (6.6%), headache(5.5%), gout (4.4%). Among the patients with adverse effects, 4.75% had cardiac side effects which included atrial fibrillation (12%), palpitation (29%), angina pectoris (18%), Myocardial Infarction (5%). Discussion: A thorough understanding of bempedoic acid's complex pharmacology empowers healthcare professionals to tailor treatment plans based on individual patient requirements. This enables informed decision-making in prescribing, optimizing dosage regimens, and mitigating potential adverse reactions. Most studies have been relatively short term in order to confirm the long term side effect profile. It would be beneficial to be cautious in using this medication for patients with above mentioned clinical conditions like myalgia, arthralgia, gout, rhabdomyolysis, atrial fibrillation, angina pectoris. Conclusion: Long term pharmacovigilance is needed to assess the safety profile of bempedoic acid over extended use. With the current increasing use of bempedoic acid, there is a need for more data on safety profiles. In future, further randomized trials are required to better assess the safety profile.

Counseling Gen Alpha: Pandemic's Impact on Developmental and Mental Health

The covid- 19 pandemic has had a widespread impact on global health. Many studies have discussed its effect on various populations and continue to study measures to work on them. The upcoming research has a limited focus on Generation Alpha: individuals born after 2010 who have been exposed to these adverse effects from their formative years: the digital age, social isolation, and environmental stressors. It has left a significant impression on their developmental milestones and mental health for which the healthcare professionals and parents are not fully equipped with. This review paper aims to discuss how the flexible and adaptive nature of counseling can employ strategies to help overcome these problems and assist in the ‘digital pandemic’ that is here to stay. The review method will analyze existing literature using citation tracking, conference proceedings, internet search engines, and primarily through open peer-reviewed electronic databases like PubMed, Research Gate, and ScienceDirect.. The results and implications of the study will be highlighted in the full paper.

Assessment of e-cigarette dependence and influencing factors among Palestinian young adults: a cross-sectional study.

E-cigarette use is a growing public health concern, especially because of the potential health risks it poses. This study focuses on assessing e-cigarette dependence and the factors associated with it among Palestinian young adults. A cross-sectional survey was conducted from January to May 2023 among university students in the West Bank. A self-administered questionnaire was used to collect demographic data, knowledge, and attitudes regarding e-cigarettes. E-cigarette dependence was assessed using the Penn State Electronic Cigarette Dependence Index. The study included 386 university students who used e-cigarettes. Many of them started using e-cigarettes at a young age, and 54.7% were dual users of e-cigarettes and traditional tobacco. High levels of dependence were reported in 11.4% of participants, and moderate dependence in 28.8%. Several factors were identified through multivariate linear regression as significantly associated with e-cigarette dependence: a higher monthly allowance (β = 0.116, 95% CI: 0.128- 1.124, p = .014), having a father who uses tobacco (β = 0.095, 95% CI: 0.030- 1.638, p = .042), having a close friend who smokes traditional cigarettes (β = 0.095, 95% CI: 0.019- 1.667, p = .045), using e-cigarettes in areas where traditional smoking is prohibited (β = 0.175, 95% CI: 0.689-2.330, p < .001), using e-cigarettes to quit other forms of tobacco (β = 0.134, 95% CI: 0.434-2.314, p = .004), and a more negative attitude score (β = - 0.210, 95% CI: - 0.285- - 0.112, p < .001). The study revealed high levels of e-cigarettes dependence among the participants among young adults, with associated variables such as monthly allowance, attitudes, and age of e-cigarette initiation. Policymakers, educators, and healthcare professionals should collaborate to address e-cigarette dependence among young adults, taking into consideration social, environmental, and socioeconomic factors.

Effort, Lever, and Fulcrum Failures in the Development of Trendelenburg Sign and Gait: A Physiotherapist’s Insight

This short review explores how failures related to the fulcrum, lever, and effort of the hip joint contribute to the development of a positive Trendelenburg sign and gait. It highlights the anatomy and biomechanics of the hip joint, emphasising its function as a first-class lever essential for lower limb activities such as walking. The review discusses how various pathologies affecting the hip joint’s lever arm, fulcrum, and effort can lead to instability and compensatory gait patterns. By understanding the biomechanical principles and anatomical structures involved, healthcare professionals can devise effective interventions aimed at restoring normal hip function and improving patient outcomes.

A UTILIZAÇÃO DO PRÉ TREINO E SUA RELAÇÃO COM O AUMENTO DA ANSIEDADE: UMA REVISÃO BIBLIOGRÁFICA

The use of pre-workout supplements is common among those seeking to optimize athletic performance. These products, which often contain stimulants like caffeine, taurine, and tyrosine, are designed to increase energy, endurance, and concentration but may also be associated with increased anxiety. This study aimed to analyze the relationship between the use of pre-workout supplements and the increase in anxiety, considering their pharmacological actions. Specific objectives included identifying the main ingredients found in pre-workout supplements, discussing clinical aspects related to anxiety, and pointing out the mechanisms of action of stimulants that may trigger anxious symptoms. The research followed PRISMA guidelines, examining relevant articles published in the last eight years in databases such as PubMed and SCIELO, resulting in the analysis of 13 studies. The main identified ingredients include caffeine, beta-alanine, branched-chain amino acids, arginine, and L-Dopa. Caffeine is particularly notable for its stimulating effects and potential to increase anxiety. The mechanisms of action of stimulants can elevate the release of neurotransmitters that induce alertness but also contribute to anxiety symptoms, such as nervousness and restlessness. The combination of multiple ingredients can lead to complex interactions, where ergogenic benefits are counterbalanced by adverse effects, such as increased heart rate. An informed approach, guided by healthcare professionals, is essential to optimize results without compromising mental and physical health.

A real−world pharmacovigilance study of FDA Adverse Event Reporting System events for pralsetinib

BackgroundPralsetinib, a selective oral inhibitor of rearranged during transfection (RET) fusion proteins and oncogenic RET mutants, has shown significant efficacy in treating RET fusion-positive non-small cell lung cancer and thyroid cancer. However, since pralsetinib was approved in the United States in September 2020, there have been limited reports of post-marketing adverse events (AEs). In this study, we aimed to analyze the AE signals with pralsetinib on the basis of the United States Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) to provide instructions in clinical practice.MethodsAll AE reports were obtained from the FAERS database from the first quarter (Q3) of 2020 to the second quarter (Q2) of 2024. Various signal quantification techniques were used for analysis, including reporting odds ratios, proportional reporting ratios, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker (MGPS)-based empirical Bayesian geometric mean.ResultsOut of 8,341,673 case reports in the FAERS database, 1,064 reports of pralsetinib as the “primary suspected (PS)” AEs were recorded, covering 26 system organ classes and 256 preferred terms. Of the reports, 62.5% were from consumers rather than healthcare professionals. The most common systems were general disorders and administration site conditions (n = 704), investigations (n = 516), and gastrointestinal disorders (n = 405). A total of 95 significant disproportionality preferred terms (PTs) conformed to the four algorithms simultaneously. AEs that ranked the top three at the PT level were hypertension (n = 80), asthenia (n = 79), and anemia (n = 65). Of the 95 PTs with significant disproportionation, unexpected significant AEs such as increased blood calcitonin, increased myocardial necrosis marker, and bacterial cystitis were observed, which were not mentioned in the drug’s instructions. The median onset time of pralsetinib-associated AEs was 41 days [interquartile range (IQR) 14–86 days]. The majority of the AEs occurred in 30 days (42.86%).ConclusionOur pharmacovigilance analysis of real-world data from the FEARS database revealed the safety signals and potential risks of pralsetinib usage. These results can provide valuable evidence for further clinical application of pralsetinib and are important in enhancing clinical medication safety.

An approach to reduce inhaler errors using Donabedian's triad

Inhaler errors inversely affect the outcome of respiratory diseases. Inhaler devices, such as the metered-dose inhalers (MDI) and dry powder inhalers (DPI), are commonly used in treating respiratory diseases like asthma and chronic obstructive pulmonary disease (COPD), and incorrect use of these devices can result in suboptimal treatment outcomes, increased probabilities of hospitalizations or admissions, and poorer quality of life. Patient related factors to inhaler errors include age, cognitive and physical abilities, education, language barriers, and preferences. Device-related factors such as inhaler design and operational complexity can also lead to errors. Finally, factors related to healthcare professionals (HCP) such as competency, level of knowledge in disease and inhaler device and availability to educate patients, can play a role in inhaler error. Quality management is a potential solution to this problem. Quality improvement strategies towards addressing inhaler misuse can increase patient satisfaction and improve patient outcomes. Donabedian's triad, which includes structure, process, and outcome can be utilized in developing a framework for reducing inhaler errors. Institutional solutions are more towards the structural and process changes in the triad, such as HCP training, checklists on training efficacy, provision of action plans, and availability of staff to educate and train patients. Patient-centered solutions focus more on process and outcome domains, such as improvement in lung functions, patient education, re-assessment and re-education of inhaler techniques, and adherence to treatment regimen. By focusing on structural and process domains, the quality of care can be enhanced, resulting in improved outcomes.

Does financing for private maternity services improve birth experiences in Poland? A mixed-methods study of the Babies Born Better Survey.

Women in Poland, despite having access to publicly-funded medical care during pregnancy, childbirth and the postpartum period, frequently use private care. Women's experience and satisfaction with childbirth have been considered one of the key indicators of the quality of care. In this study we explore whether and how paying for private childbirth services affects women's experiences and satisfaction with care. The qualitative portion seeks to understand how individual women construct meaning around their childbirth experiences, including their relationships with healthcare personnel, medical interventions, birth environment, and professionalism. This mixed-methods study is based on data from 951 online questionnaires completed by women who gave birth between June 2017 and June 2022, in Poland. This study is part of the international Babies Born Better Survey project. The project used simultaneous quantitative and qualitative data collection, it was exploratory with equivalent status of qualitative and quantitative data. Quantitative data were analyzed descriptively and chi-squared tests were conducted to compare women who used private and public care. Qualitative data were analyzed using inductive thematic analysis. The quantitative and qualitative results were integrated, in accordance with the chosen mixed-methods design. There were no major differences in sociodemographic characteristics (except living standards), health status and satisfaction with labor between women who paid for private services during childbirth and those who used only publicly-funded care. For both groups of women, healthcare personnel and their behavior were the most frequently mentioned aspect shaping childbirth experiences. Other important aspects were: medical interventions, birth environment, and staff professionalism. Although accessing private perinatal services care did not provide women with care consistent with their expectations, women put a lot of trust into private services as a means to receive more attentive care. Further research investigating the interplay between private and public services is needed to explore the question how private services may impact the care women receive and why women put so much trust in these services.

Developing a Statewide Strategic Plan for Prevention, Early Identification, and Treatment of Psychosis.

Access to evidence-based programs that address early psychosis is a substantial public health concern. The authors describe the community-engaged, data-driven process that informed the development of the Massachusetts Strategic Plan for Early Psychosis, an effort to identify actionable priorities to build a system of prevention and care that responds to the needs of individuals who experience psychosis and their caregivers. A multiphase, mixed-methods approach was used to gather knowledge from young adults experiencing early psychosis and their caregivers, including two symposia with diverse stakeholders. Six overarching goals were identified, each with possible action steps and stigma reduction strategies: connecting and supporting individuals who experience psychosis and their families, promoting early identification of and intervention for psychosis through community education, providing specialized support to key community members, providing specialized support to medical and behavioral health care professionals, supporting specialized treatment teams in the delivery of evidence-based care, and developing a statewide system of psychosis services. Next steps for and operationalization of the statewide strategic plan for psychosis in Massachusetts will require a population health approach that engages the community through intersectoral and multisectoral strategies.

Interprofessional Team Training

Background: Interprofessional team training (IPTT) prepares students from health care professions for team-based care. Evaluating different learning environments to inform decisions about delivery format is timely and important. Purpose: To compare in-person and online IPTT learner outcomes. Method: Undergraduate and graduate students (n = 866) from 11 professions participated. Using retrospective pre-/post-methodology, 20 item Interprofessional Collaboration Competency Attainment Survey (ICCAS) scores were compared, and qualitative responses analyzed. Results: Mean ICCAS scores improved for in-person and online delivery (P &lt; .0001) with large effect sizes (Cohen’s D = 0.94-1.86). In-person delivery resulted in greatest improvement (P = .038), offset by online logistical benefits. Qualitative themes highlighted impact on learning, importance of facilitator competence, and setting expectations. Conclusion: IPTT achieved learning consistent with competency development. Advantages from in-person delivery should be weighed against online logistical advantages.

Predictive Modeling and Early Detection of Parkinson's Disease Using Machine Learning

Parkinson's disease is a progressive neurodegenerative disorder that impacts millions of citizens in the USA, mainly targeting the motor system and causing debilitating symptoms such as rigidity, tremors, and bradykinesia. The diagnosis of Parkinson's disease is presently heavily dependent on clinical evaluations and neurological examinations, targeting the detection of motor dysfunction. The principal aim of this study was to use machine learning as a means for early detection and prediction of Parkinson's disease. The dataset utilized for this study was the Parkinson’s Disease Dataset, retrieved from the UCI Machine Learning Repository, which included comprehensive biomedical voice measurements from a cohort of individuals, 23 of whom are diagnosed with Parkinson’s disease and 8 who are healthy controls. This dataset included a set of features extracted from voice recordings. These include parameters like fundamental frequency (pitch), amplitude variation, jitter, shimmer, and several phonation-related measures known to reflect early vocal impairments associated with the disease in question. This research project deployed three credible and proven algorithms, namely, logistic regression, random forest, and the Support Vector Machines. Besides, this study employed a combination of metrics, including accuracy, precision, recall, F1-score, and ROC-AUC, which are more holistic toward the model performance. According to the metric performance results of the three models, several key insights were drawn into the early detection of Parkinson's Disease. Particularly, it was clear that the Random Forest model had superior accuracy and was the most reliable in classifying positive cases and healthy patients, which could be that this model turned out to be most reliable in an early detection setting. In that respect, predictive modeling in Parkinson's Disease is a capability frontier that has the potential to make much difference in clinical decision-making. Supported by Machine Learning algorithms, clinicians can trace the minute patterns in patient data, which are not easily visible through any other diagnostic means. In such cases, early detection of Parkinson's Disorder with vocal biomarkers or motor assessment may afford healthcare professionals opportunities for early interventions that might retard the disease process.

Knowledge and Attitude on Neonatal Resuscitation Among Nursing Students: A Cross-Sectional Study.

This study assesses nursing students' knowledge and attitudes toward neonatal resuscitation. This cross-sectional study was conducted at a nursing college in June 2024. Participants were selected through purposive sampling. Data on knowledge and attitudes toward neonatal resuscitation were collected using self-administered web-based questionnaires. Statistical analyses were used to examine the comparisons, correlations, and predictors, including t-tests, ANOVA, Pearson correlation tests, and binomial logistic regression. Statistical analyses showed that 45.2% of nursing students had moderate knowledge, 39% had good knowledge, and all exhibited positive attitudes. BSc nursing students, those with prior neonatal resuscitation training, and those who had witnessed or performed resuscitation had significantly higher knowledge (p ≤.001). III-year Diploma students, those aged 22-23, and students with 6-10 days of NICU/labor room posting also had higher knowledge (p ≤ .001, p ≤ .005). Additionally, BSc students and those with prior training displayed significantly more positive attitudes (p ≤ .001). A moderate positive correlation was found between knowledge and attitude, with key predictors being labor room posting duration for knowledge and exam marks for attitude. This study highlights the need for improved neonatal resuscitation education and training of nursing students to improve outcomes and reduce mortality rates among newborns. To ensure effective newborn care, educational programs can be designed to target specific areas such as clinical exposure and resuscitation training. Comprehensive training initiatives aligned with international guidelines are vital for developing proficient neonatal resuscitation practices. Such proactive approaches can help build a cohort of competent healthcare professionals who can deliver timely and effective interventions, thereby ensuring the well-being of newborns.