Chronic Illness Research Articles

Multiple organ failure: What you need to know.

Multiple organ failure (MOF) remains a significant challenge for the acute care surgeon, often leading to poor patient outcomes. This comprehensive review explores the etiology, pathophysiology, clinical presentation, diagnosis, management strategies, prognosis, and prevention strategies associated with MOF and chronic critical illness. Understanding the intricate etiology and pathophysiology of MOF and chronic critical illness is essential for effectively managing these syndromes and developing targeted treatment strategies aimed at mitigating the underlying inflammatory, immune, and microvascular disturbances, in order to redirect patients onto a trajectory of recovery.

Prevalence of cyberbullying involvement and its association with clinical correlates among Chinese college students

BackgroundCyberbullying refers to a modern form of bullying that could be practiced electronically or on the Internet. This study conducted a cross-sectional survey to explore different types of cyberbullying involvement (CI) and the associations of CI with demographic characteristics and mental health problems among Chinese college students. MethodsA total sample of 18,578 Chinese college students were recruited (68.1 % female, mean age = 20.07 years) from October 17 to 29, 2023. All participants completed self-reported web-based questionnaires on demographic characteristics, CI, sleep disturbance, depression, anxiety, and suicidal ideation. ResultsMore than a quarter of participants (27.5 %) have been involved in cyberbullying: specifically speaking, 10.1 % cybervictims, 4.7 % cyberbullies, and 12.7 % both (cyberbully-victims). Males, younger age, left-behind experiences, individuals with poorer family economic status, adolescents with chronic physical illness, and those with family history of mental disorders are more likely to experience CI. Unlike participants without CI, cybervictims and cyberbully-victims reported a higher risk of sleep disturbance, depression, anxiety, and suicidal ideation. Cyberbullies also have a higher rate of sleep disturbance and depression than their peers who are not involved in cyberbullying. ConclusionOur findings indicate that CI is widespread among Chinese college students, and CI is associated with the high reported rates of a series of psychopathology. This study highlights the significance of implementing anti-cyberbullying interventions specifically targeted at college students. Furthermore, it underscores the importance of monitoring changes in students' mental health status throughout the intervention process.

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Peripheral artery disease is a considered as one of the major macrovascular complications in diabetes mellitus type 2. It is chronic arteriosclerotic illness that mainly affects the lower limbs and is presented as narrowed or blocked blood vessels. The prevalence increases with the age, it affects 15-20% of persons older than 70 years age, 10-15% of the general population. Smoking and high cholesterol levels increase the risk for PAD progression in large blood vessels such as legs, while diabetes increases the risk for PAD in small blood vessels such as the feet. Critical ischemia, its most severe form can lead to limb amputation and the patient’s death, and even its asymptomatic forms are associated with a high risk of cardiovascular morbidity and mortality. Approximately more than half of all patients are asymptomatic and preventive therapy reduces the risk of complications and death, so it’s important to recognize the subclinical forms in time and to control risk factors of disease. The risk factors that can be modified are tobacco use, hypertension, hyperlipidemia, diabetes mellitus, obesity and some of them cannot be modified such as age, sex or family medical history. Diabetes mellitus type 2 is considered as the most important risk factor for development of peripheral artery disease. The experts suggest that is necessary to establish an HBA1C therapeutic target below 8% in patient with DM and PAD.

A study of the crucial Role of Telehealth in Saudi Arabia's Nursing Care Changes

This research investigates how telehealth affects nursing care in Saudi Arabia, with particular attention to how it affects patient satisfaction, healthcare accessibility, and the management of chronic illnesses. The study used a mixed-methods approach to look at the experiences of 300 patients and 200 nurses in both urban and rural settings. It included both qualitative interviews and quantitative surveys. According to the findings, telehealth greatly improves accessibility by removing geographical barriers, and urban nurses use it at a somewhat higher rate than their rural colleagues. The majority of patient satisfaction ratings are positive, which is consistent with other research showing how telehealth can enhance patient experiences. According to the study, telemedicine interventions can effectively manage chronic diseases, including diabetes, as evidenced by a significant decrease in hospital visits and an improvement in medication adherence. Notwithstanding these advantages, considerable impediments were found to include technological hurdles including internet connectivity and digital literacy. The study's conclusions are in line with previous research, highlighting the necessity for continual advancements in technology and education while reiterating the role that telehealth has played in revolutionising healthcare delivery. All things considered, telehealth seems to be a useful instrument for improving nursing care, providing significant advantages and highlighting areas that require further development to reach its full potential in the Saudi healthcare system.

A study of the Effects of Physiotherapy on Knee Osteoarthritis

Osteoarthritis (OA) of the knee is a common chronic illness that causes pain and limited movement, greatly reducing quality of life. To manage knee OA, this randomised controlled trial evaluated the effectiveness of a comprehensive physiotherapy program that included exercise treatment, manual therapy, and patient education. One hundred individuals with moderate to severe osteoarthritis (OA) were randomised to be in one of two groups: the intervention group or the control group, which received conventional care. Supervised exercises, manual joint mobilisations, soft tissue manipulations, and education sessions on disease management and lifestyle adjustments were all part of the 12-week intervention. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) was used to measure pain and physical function as primary objectives. The Short Form-36 (SF-36) health survey was used to measure knee range of motion, muscle strength, and quality of life as secondary goals. The intervention group significantly outperformed the control group in terms of knee range of motion, muscle strength, and WOMAC pain and function scores (p < 0.001), according to the results. Furthermore, the intervention group's quality of life scores in the domains of pain and physical functioning were significantly higher. These results, which are in line with other research emphasizing the importance of exercise, manual treatment, and patient education in improving clinical outcomes, demonstrate the many advantages of a physiotherapy program in the effective management of knee OA. This study supports the integration of comprehensive physiotherapy into standard knee OA treatment protocols to improve patient well-being and functional capabilities. Future research should focus on optimizing these interventions for broader clinical application.

Optimized Tiny Machine Learning and Explainable AI for Trustable and Energy-Efficient Fog-Enabled Healthcare Decision Support System

The Internet of things (IoT)-based healthcare decision support system plays a crucial role in modern medicine, especially with the rise in chronic illnesses and an aging population necessitating continuous remote health monitoring. Current healthcare decision support systems struggle to deliver timely and accurate decisions with minimal latency due to limited real-time healthcare data and inefficient computational resources. There is a critical need for an optimized, energy-efficient machine learning model that reliably supports remote health monitoring within IoT and fog computing environments. Our study proposes an Optimized Tiny Machine Learning (TinyML) and Explainable AI (XAI) binary classification model for a trustable and energy-efficient healthcare decision support system, leveraging fog computing to optimize performance. The fog-based approach improves response times and enhances bandwidth usage, addressing critical needs such as reduced latency, higher bandwidth utilization, and decreased packet loss. To further improve efficiency, we incorporate the innovative mLZW data compression technique, significantly enhancing data communication efficiency and reducing response time to critical health alerts. However, limited real-time healthcare data records challenge machine learning classification performance. By implementing a TinyML algorithm, our system demonstrates superior performance to other machine learning models. The proposed optimized TinyML model achieves an impressive F1 score of 0.93 for health abnormalities detection, emphasizing its robustness and effectiveness. This paper highlights the potential of TinyML and XAI in delivering robust, trustworthy, and energy-aware healthcare solutions, making significant contributions toward effective remote health monitoring and decision support in fog-enabled IoT networks.Graphical abstract

Efficacy of Teleconsultation Versus Usual Care in Improving Quality of Life Among Geriatric Patients Aged 60 and Above: A Randomized Controlled Trial.

Introduction The geriatric population, aged 60 years and older, is rapidly growing worldwide. This demographic shift has led to a higher prevalence of chronic diseases, comorbidities, and functional impairments, placing immense pressure on healthcare systems. Teleconsultation, which uses telecommunication technologies to deliver healthcare services remotely, offers a potential solution. This study aimed to assess the efficacy of teleconsultation versus usual care in improving the quality of life among the geriatric population aged 60 years and older. Methods A parallel, randomized controlled trial with a 1:1 allocation ratio was conducted. Eligible participants, aged 60 and above, were recruited at the triage emergency department (ED) following a baseline eligibility assessment. Inclusion criteria included the ability to communicate in English or Hindi, possession of International Organization for Standardization (ISO-certified) instruments for self-monitoring, and willingness to comply with study procedures and provide written consent. Participants were randomly assigned to experimental and control arms using a computer-generated sequence, with allocation concealment achieved through sequentially numbered opaque sealed envelopes (SNOSEs), which were opened in front of participants after obtaining baseline data. A total of 2,000 participants (1,000 per arm) were enrolled and randomly assigned to either the teleconsultation or usual care group. Results In the teleconsultation group (n=1,000), 36.5% of participants (365) were female and 63.5% of participants (635) were male. Similarly, in the usual care group (n=1,000), 37.1% of participants (371) were female and 62.9% of participants (629) were male. The teleconsultation group significantly outperformed the usual care group in several domains pre-intervention, with higher mean scores in the physical health domain (11.16 vs. 10.96, P = 0.009), psychological domain (11.74 vs. 11.62, P = 0.020), and environment domain (12.44 vs. 12.26, P = 0.0001). No significant difference was observed in the social relationships domain (P = 0.452). The teleconsultation group significantly outperformed the usual care group in all domains post-intervention, with higher mean scores in the physical health domain (14.49 vs. 12.74), psychological domain (13.75 vs. 12.35), social relationships domain (14.05 vs. 12.90), and environment domain (13.91 vs. 12.94) (P < 0.001 for all). Conclusion These findings suggest that teleconsultation significantly improves the quality of life for elderly patients by providing a more accessible and convenient means of healthcare delivery and addressing the physical, emotional, and social challenges associated with chronic illnesses.

Mortality Risk Factors at Time on ED Admission in Elderly Patients with Infectious Diseases

Background: As elderly individuals often exhibit heightened vulnerability to infections due to factors such as compromised immune systems, chronic illnesses, and age-related physiological changes, understanding the characteristics and risk factors associated with infectious diseases in this population is crucial. The aim of the present study was to evaluate the characteristics of elderly patients with infectious disease in ED admission and to identify risk factors that influence in-hospital mortality. Material and Method: In this study, we enrolled 448 adult patients diagnosed with infectious diseases such as pneumonia, urinary tract infection, gastroenteritis, meningitis, and cellulitis. The participants were directly admitted to our Emergency Department (ED) from their homes or their relatives' residences between November 1, 2014, and May 31, 2015. We investigated patient’s vital signs, disease signs, source of infection, length of staying at hospital, length of staying at emergency service, mortality related scores, laboratory data, treatment and prognosis. Results and Conclusion: The rate of emergency care admissions with an infectious etiology was found as 17%. Average age of patients was 76±8 with 180 (40%) of them being female and 268 (60%) of them being male. Mortality rate was found as 23%. Cox regression analysis concluded that for 65 years or older patients, risk factors that effected mortality were; septic shock, cardiac disease and presence of malignancy, absence of COPD/Asthma, higher pCO2 and lower HCO3 at the time of admission to the emergency service. Calculating MEDS score and APACHE 2 score at admission to the emergency department and intensive care unit can facilitate early intervention, improving recovery prospects. Further research and clinical strategies may benefit from these identified predictors to improve the management and outcomes of elderly patients with infectious diseases in the ED.

Importance of Studying Non-Coding RNA in Children and Adolescents with Type 1 Diabetes.

Type 1 diabetes (T1D) mellitus is a chronic illness in children and teens, with rising global incidence rates. It stems from an autoimmune attack on pancreatic β cells, leading to insufficient insulin production. Genetic susceptibility and environmental triggers initiate this process. Early detection is possible by identifying multiple autoantibodies, which aids in predicting future T1D development. A new staging system highlights T1D's onset with islet autoimmunity rather than symptoms. Family members of T1D patients face a significantly increased risk of T1D. Italy recently passed a law mandating national T1D screening for pediatric populations. Measurements of β cell function continue to be essential in assessing efficacy, and different models have been proposed, but more appropriate biomarkers are mandatory for both progression studies before the onset of diabetes and during therapeutic monitoring. Biomarkers like microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) play key roles in T1D pathogenesis by regulating gene expression. Understanding their roles offers insights into T1D mechanisms and potential therapeutic targets. In this review, we summarized recent progress in the roles of some non-coding RNAs (ncRNAs) in the pathogenesis of T1D, with particular attention to miRNAs, lncRNAs, and circRNAs.

The Impact of Wearable Devices on Public Health Outcomes in The Treatment of Chronic Diseases Through Continuous Physiological Monitoring

Chronic illnesses contribute to elevated levels of disability and death. The active involvement of patients in the treatment of chronic diseases is a crucial element of healthcare systems that are focused on chronic diseases. Wearable devices provide real-time health information focused on the patient, enabling them to make informed decisions about self-management. Although wearables are believed to offer advantages in enhancing the self-management of chronic illnesses, their impact on healthcare outcomes still needs to be well comprehended. This study sought to investigate the effect of wearables on healthcare results in adults with chronic conditions by conducting a comprehensive analysis of existing evidence for physiological monitoring. A narrative systematic literature review was performed by searching six databases for randomized and observational research published from January 2018 to July 2023. These studies focused on utilizing a wearable intervention in a group of individuals with chronic diseases to evaluate its effect on a predetermined end measure. The outcomes were defined as any impact on patient or practitioner experience, cost-effectiveness, or healthcare outcomes resulting from the wearable intervention. The findings from the research included in the analysis were gathered according to 6 main themes, which were used as the foundation for a qualitative summary. This research adhered to the requirements outlined in the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) declaration.

A Hybrid Segmentation Algorithm for Rheumatoid Arthritis Diagnosis Using X-ray Images

Rheumatoid Arthritis (RA) is a chronic autoimmune illness that occurs in the joints, resulting in inflammation, pain, and stiffness. X-ray examination is one of the most common diagnostic procedures for RA, but manual X-ray image analysis has limitations because it is a time-consuming procedure and is prone to errors. A specific algorithm aims to a lay stable and accurate segmenting of carpal bones from hand bone images, which is vitally important for identifying rheumatoid arthritis. The algorithm demonstrates several stages, starting with Carpal bone Region of Interest (CROI) specification, dynamic thresholding, and Gray Level Co-occurrence Matrix (GLCM) application for texture analysis. To get the clear edges of the image, the component is first converted to the greyscale function and thresholding is carried out to separate the hand from the background. The pad region is identified to obtain the contours of it, and the CROI is defined by the bounding box of the largest contour. The threshold value used in the CROI method is given a dynamic feature that can separate the carpal bones from the surrounding tissue. Then the GLCM texture analysis is carried out, calculating the number of pixel neighbors, with the specific intensity and neighbor relations of the pixels. The resulting feature matrix is then employed to extract features such as contrast and energy, which are later used to categorize the images of the affected carpal bone into inflamed and normal. The proposed technique is tested on a rheumatoid arthritis image dataset, and the results show its contribution to diagnosis of the disease. The algorithm efficiently divides carpal bones and extracts the signature parameters that are critical for correct classification of the inflammation in the cartilage images.

Analytics of the Cost Effectiveness and Real-Time Health Risk Assessments for Pharmacy-Based Preventive Health Services

More patient-centered care and participation in managing chronic illnesses are features of the modern pharmacist's task, which has evolved substantially in recent years. Still, the issue of whether or not pharmacists are cost-effective in diabetes care persists. Cost-effectiveness analyses (CEA) have emerged as a crucial tool when making informed decisions about healthcare delivery. Patients' present health status, past medical history (personal and family), and lifestyle variables influencing their health are all part of a health risk assessment (HRA). Hence, this study proposed a Cost-Effectiveness Analysis of Pharmacy-based Preventive Health Services (CEA-PBPHS) model for real-time health risk assessment. Nowadays, medical professionals place a greater emphasis on preventative health care. This research aims to examine the potential impact of risk assessment tools on males past due for a physical examination and evaluate the return on investment (ROI) for community pharmacists who provide this service for free. More cost-efficient or cost-saving than conventional treatment is pharmacist engagement in diabetes management due to better glucose control, higher patient compliances, and lower risks of medication-related issues. The experimental outcomes demonstrate that the suggested CEA-PBPHS model increases the health risk assessment ratio by 98.9%, the personalized health service ratio by 97.5% and the cost-effectiveness analysis ratio by 98.3% compared to other existing models.

Respiratory Syncytial Virus Infections in Pediatric Intensive Care: Association of Sociodemographic Data and Clinical Outcomes with Viral and Bacterial Co-infections.

The aim of the study was to evaluate respiratory syncytial virus (RSV) infections in cases followed in the pediatric intensive care unit (PICU). The study was designed as a prospective cohort in 6 PICUs. There were 3 groups: only RSV (+), RSV (v+) who were positive for another viral agent(s) in addition to RSV, and RSV (b+) who were positive for a bacterial agent(s) in addition to RSV. A total of 119 cases were included in the study, 67 (56.3%) of whom were male. The RSV (+) group had a lower pH compared to the other groups and a higher rate of acute bronc hiolitis/bronchitis diagnoses compared to the RSV (v+) group. The RSV (v+) group had higher bicarbonate levels, higher creatinine levels, longer hospital stays, and higher Pediatric Risk of Mortality-3 scores (PRISM-3) compared to the RSV (+) group. Cases with RSV (b+) were younger and also had lower body weight compared to the other groups. Furthermore, the RSV (b+) group had higher C-reactive protein and Procalcitonin (PCT) levels and higher rates of High Flow Nasal Cannula-Oxygen Therapy (HFNC-OT) use. Multiple linear regression analysis revealed that PRISM-3 score, PCT levels, Pediatric Acute Respiratory Distress Syndrome diagnoses, inhaled steroid use, chronic illness status, and heart rate on admission were associated with the length of stay in the PICU. High flow nasal cannula-oxygen therapy continues to be the most frequently preferred respiratory support method in RSV infections. Viral infections accompanying RSV can increase the severity of the disease.

Prevalence and Risk Factors of Psychiatric Symptoms among Type 2 Diabetes Mellitus Patients in South India: A Cross-Sectional Study.

Background: Type 2 diabetes mellitus poses a momentous challenge when accompanied by psychiatric symptoms like depression, anxiety, and stress, adding to the complaint's threat. Research on these factors in patients with uncontrolled chronic illnesses in India, particularly in Tamil Nadu, is limited. Hence, this study aims to determine the prevalence and risk factors of these psychiatric symptoms among Type 2 diabetes patients.  Methods: A cross-sectional study was conducted in Alpha Hospital and Research Center in Madurai, South India, from April 2020 to March 2021, enrolling 614 participants (307 with Type 2 diabetes mellitus and 307 general population). Data were collected using Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale and Perceived Stress Scale. The IBM SPSS version 23 was used for statistical analysis.  Results: Two-thirds of youth women with type 2 diabetes have higher fasting blood sugar levels than men when compared to general population. 82.61% of patients with uncontrolled diabetes developed severe stress, surpassing those with well-controlled and pre-diabetes. Severe depression is most prevalent among patients with neuropathic foot ulcers (54.76%) and nephropathy (61.54%). Predominant mental health risk factors include being single, high school education, poor glycemic control, comorbid hypertension, and family history. Interestingly, lifestyle factors like alcohol use and smoking positively impact mental health outcomes.  Conclusion: This study shows the intricate connection between Type 2 diabetes and mental health problems in Madurai, emphasizing the necessity for a multidisciplinary strategy to enhance outcomes and reduce financial burden. Future research in nursing has to focus on implementing and assessing therapies aimed at reducing patients' stress, anxiety and depression.

HUMAN HEALTH AND IMPORTANCE OF NUTRITION

In addition to maintaining normal physical processes, nutrition also promotes growth and development and lowers the risk of chronic illnesses. It is necessary for optimum health and vigour that we get a diet rich in essential nutrients and well-balanced. Nutritious food can enhance physical and mental potential. Macro-nutrients and micro-nutrients are the two main categories of nutrients found in a diet. Diet is an important contributor to human health, and public health bodies are issuing guidelines aimed at favouring healthy food choices. Low food intake and infections are the immediate causes of malnutrition. Many countries struggle with malnutrition or caloric deficits, while others encounter difficulties with caloric overconsumption and micronutrient deficiencies. A multitude of factors contribute to this global problem. Considering the health challenges facing our world population, the need is clear for continually improving recommendations and strategies to promote human health. The purpose of this study was to provide information on the functions of different nutrients, the conditions caused by their deficiency, the components of a healthy diet, and the complications of different types of malnutrition. A lot of research is being done, and new findings are published every day to increase our knowledge about food and nutrition and to find ways to apply this knowledge in choosing the right foods to eat so that our body is well nourished and healthy. For the maintenance of health and growth and to develop greater resistance against infections, one must consume balanced food that contains all the nutrients in the correct proportion.

Evaluation of patient's quality of counselling in the context of diabetes treatment by community pharmacists for Public Health

Providing Patient Counseling (PC) may be beneficial in enhancing disease treatment results, especially for chronic illnesses like Diabetes Mellitus (DbM), which is prevalent in underdeveloped countries. This research aims to examine the counseling and contentment levels of patients who visit diabetes clinics in Community Pharmacies (CP), intending to contribute to the field of Public Health (PH). This research aimed to evaluate the efficacy of PC services offered to individuals with DbM. In this cross-sectional research, a patient simulation technique was used with an organized survey of 560 CPs chosen to offer primary healthcare. The survey has been split into three sections: demographics, PC methods used during prescription collection, and satisfaction assessment of the services rendered. The results revealed that PC was offered for taking medication among patients with type 1 DbM, but it was lacking for patients with type 2 DbM. Patients were provided with insufficient counseling on the potential adverse effects and the need to adopt a healthier lifestyle. The degree of satisfaction was a mere 20.2%, suggesting that there may be a deficiency in PC services. The investigation has shown inadequate PC procedures and low levels of contentment in the services offered by CP to patients with DbM. Given the rising occurrence of DbM and the presence of other medical conditions, it is crucial to provide PCs with DbM.

Analysis of Pharmaceutical Sciences and Public Health Applications

Growing in frequency in both rural and urban parts of India, growing percentage of people at risk of diabetes, Indian population's genetic susceptibility to diabetes risk factors related to the environment, Globalisation causing a decline in physical exercise Some of the challenges that the disease poses in India are low patient awareness of hypertension, undiagnosed hypertension due to a variety of factors such as low healthcare facilities and economic status, inadequate disease control, and an increasing incidence of complications related to hypertension. Although there are solutions, the healthcare team will need to work in tandem with the clinician who is battling the illness on an individual basis. This will prevent the patient from receiving the proper care, the clinician from being able to listen to the patient's problems and find solutions, the patient from receiving the psychological support they need for a chronic illness, and the nation from suffering from economic hardship after the patient's illness. The purpose of this study was to identify the services provided by pharmaceutical care and evaluate the barriers to pharmaceutical care in various settings in order to provide relevant recommendations.

Risk Assessment and Diagnosis Code Prediction from Electronic Health Records (EHR) using deep learning

Knowledge in the medical field is often expressed by distinct and subjective norms. Much research and development efforts have focused on using deep learning algorithms to predict the likelihood of illnesses from EHR in recent years. When it comes to risk prediction, deep learning-based techniques outperform more conventional machine learning models. But nothing in the literature fully accounts for what doctors already know, such as the connections between illnesses and their risk factors. This research examines the use of Multi-layer Perceptron models for the categorisation of diagnoses in electronic health records. The raw data and a modified version of the EHR dataset are used to train two MLPs with distinct topologies. For comparative purposes, a Random Forest is used as a baseline. To phenotype patients using their electronic health records, we provide a deep learning method. Predictive modelling of chronic illnesses is the particular scenario used to verify the suggested model on a real-world EHR data warehouse. Many deep learning applications on EHRs have been effective, and there is still a lot of potential to be realised. It has been discovered that deep learning models can learn from the limited EHR dataset, but not to a level where they outperform the baseline model.

The risk perception of COVID-19 and vaccine uptake among patients with chronic illnesses at a tertiary health facility in Nigeria.

This study assessed the risk perception of COVID-19 and the uptake of the COVID-19 vaccine among patients with chronic illnesses in a tertiary health facility. A hospital-based cross-sectional study. The outpatient clinics in a tertiary health facility in Ilorin, North-Central Nigeria. Patients with chronic diseases attending outpatient clinics in UITH, Ilorin from November- December 2022, excluding patients under 18 years of age, using simple random sampling by balloting for outpatient clinics, proportional allocation for participants from each clinic, and systematic sampling method for eligible respondents. Risk perception of COVID-19 and vaccine uptake among patients with chronic illnesses in Nigeria. Respondents believed that older people were most at risk of COVID-19. Over two-thirds, 278 (69.5%) of the respondents had received the COVID-19 vaccine. Fear of the unknown (36.0%) and fear of side effects 30 (24.6%) were the most common reasons for not taking the vaccine. Those married were more likely to have received at least one dose of the vaccine (p=0.007). COVID-19 risk perception and COVID-19 vaccine uptake were relatively above average. Fear of the unknown and side effects were significant reasons for not taking the vaccines. None declared.

Care Burden and Psychological Resilience of Mothers Accompanying Their Children with Chronic Illnesses Hospitalized in Pediatric Wards

Abstract Background: Psychological resilience plays a pivotal role in managing the caregiving burden experienced by mothers of hospitalized young children with chronic illnesses. The resilience of these mothers is not only critical for their own mental health but also for the well-being and development of their child. Aim: This study aimed to assess the care burden, psychological resilience, and associated factors of mothers with hospitalized children aged 0-2 years who have chronic diseases. Materials and Methods: The participants included 134 mothers of hospitalized children. Data were gathered utilizing a personal information form, the Zarit Burden Interview, and the Brief Resilience Scale. Results: Working mothers with a bachelor’s degree had higher Zarit Burden Interview scores than non-working mothers. Mothers of children with epilepsy and neurological diseases had higher Zarit Burden Interview scores than those with other chronic diseases. Mothers receiving instrumental and spiritual support had significantly higher Brief Resilience Scale scores. Discussion: Among mothers who accompany their children with a chronic illness diagnosis in the hospital, those who are university graduates, employed, or have children diagnosed with epilepsy and neurological diseases are particularly at risk in terms of the burden of care and psychological resilience. Conclusion: Physicians and especially pediatric nurses can enhance the psychological resilience of these mothers identified as a risk group in this study and alleviate their care burden by providing instrumental and moral support in the clinical setting. The support given to these accompanying mothers can contribute more significantly to the child's quality of life and care.