Burnout and associated factors among nurses working in public hospitals of Harari region and Dire Dawa administration, eastern Ethiopia. A cross sectional study

Background Burnout is a syndrome of emotional exhaustion, low personal accomplishment and depersonalization experienced by a health professional and it is more common in nurses due to high workload and job stress that is mostly caused by working proximity to patients and taking care of them. Burnout compromises the provision of quality health care. Despite this, there is no information in Ethiopia on burnout among nurses in study area. Objectives To determine the magnitude of burnout and associated factors among nurses working in public hospitals of Harari regional state and Dire Dawa administration, eastern Ethiopia, February 1–29, 2020. Methods Institutional based quantitative cross-sectional study was employed from February 1–29 among 412 randomly selected nurses who have been working in hospitals for the last 6 months. Simple random sampling method was employed and data was collected by self-administered, standardized, reliable and valid, questionnaire (Maslachs Burnout Inventory- Human Services Survey). Data was entered into EpiData Version 3.1 and exported to statistical package for social science version 20 for analysis. All covariate with P-value less than 0.25 in bivariable analysis were candidate for multivariable analysis. Level of statistical significance was declared at p-value < 0.05. Results Among 412 nurses taking part in this study, 183(44.4%) of nurses with 95% CI, had experienced burnout. Married marital status [AOR:2.3,95%CI:(1.2–4.3)], poor current health status [AOR:4.8, 95% CI:(1.1–21.4)] and fair current health status [AOR:12, 95% CI:(4.5–32)], working greater than eight hour per-day[AOR:0.52, 95%CI:(0.29–0.92)], intention to leave a job [AOR:0.48,95%CI:(0.2–0.88), being working in emergency room [AOR:0.3,95%CI:(0.1–0.98)] and using a different medication related to work related health problems were factors associated with nurses’ burnout. Conclusion The nurses’ burnout in this study is high and it is attributed by marriage, perceiving health status as poor and fair, whereas, having the intention to leave job, being working in emergency room and using a medication in relation to work related health problems reduced risk of developing burnout. So, the concerned bodies should provide trainings which focus on stress copying mechanisms and assertiveness program.

A New Method for Friction Estimation in EMA Transmissions

The increasing interest for adopting electromechanical actuators (EMAs) on aircraft demands improved diagnostic and prognostic methodologies to be applied to such systems in order to guarantee acceptable levels of reliability and safety. While diagnostics methods and techniques can help prevent fault propagation and performance degradation, prognostic methods can be applied in tandem to reduce maintenance costs and increase overall safety by enabling predictive and condition-based maintenance schedules. In this work, a predictive approach for EMAs friction torque estimation is proposed. The algorithm is based on the reconstruction of the residual torque in mechanical transmissions. The quantity is then sampled and an artificial neural network (ANN) is used to obtain an estimation of the current health status of the transmission. Early results demonstrate that such an approach can predict the transmission health status with good accuracy.

Cancer Patients’ Willingness to Take COVID-19 Vaccination: A Nationwide Multicenter Survey in Korea

Considering the high morbidity and mortality of Coronavirus disease 2019 (COVID-19) in patients with malignancy, they are regarded as a priority for COVID-19 vaccination. However, general vaccine uptake rates among cancer patients are known to be lower than in their healthy counterparts. Thus, we aimed to investigate the attitude and acceptance rates for the COVID-19 vaccine in cancer patients and identify predictive factors for vaccination that could be modified to increase vaccine uptake rates, via a paper-based survey (58 items over six domains). A total of 1001 cancer patients participated in this nationwide, multicenter survey between February and April 2021. We observed that 61.8% of respondents were willing to receive the COVID-19 vaccine. Positive predictive factors found to be independently associated with vaccination were male gender, older age, obesity, previous influenza vaccination history, absence of cancer recurrence, time since cancer diagnosis over 5 years, and higher EuroQol Visual Analogue Scale scores. Along with the well-known factors that are positively correlated with vaccination, here, we report that patients’ disease status and current health status were also associated with their acceptance of the COVID-19 vaccination. Moreover, 91.2% of cancer patients were willing to be vaccinated if their attending physicians recommend it, indicating that almost 30% could change their decision upon physicians’ recommendation. Unlike other factors, which are unmodifiable, physicians’ recommendation is the single modifiable factor that could change patients’ behavior. In conclusion, we firstly report that Korean cancer patients’ acceptance rate of the COVID-19 vaccination was 61.8% and associated with disease status and current health status. Physicians should play a major role in aiding cancer patients’ decision-making concerning COVID-19 vaccines.

Understanding needs and expectations of heart failure patients and their caregivers regarding digital health - the PASSION-HF project

Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): INTERREG-NWE Background/Introduction Current heart failure (HF) healthcare provision is not sufficient. Due to demographic changes and subsequent increases in comorbidities, along with unequal distribution of medical care in rural areas, alternative approaches need be sought. The use of eHealth applications has potential to enable patients to become more self-sufficient. The "PASSION-HF" project aims to develop an interactive decision-making system – a virtual doctor – that provides solutions based on current guidelines and artificial intelligence. Patient independence is maximized through 24/7 access to personalized HF-management. Furthermore, the application defines decision points, where medical professionals need to be included. Purpose To understand needs and expectations of HF patients and their informal caregivers in regard to a virtual doctor. Methods We conducted an exploratory mixed-methods study within the Netherlands, UK, Ireland and Germany. Semi-structured qualitative interviews were supplemented by a standardized questionnaire. The interviews focused on i) acceptance and motivation to use a virtual doctor and ii) experience and perception of current health care provision. The interviews were analysed using the content analysis according to Mayring (2010) with the help of "ATLAS.TI" software. Additional information about the role of informal caregivers, technology acceptance and decision-making processes was collected via questionnaires. Results A total of 49 patients and 33 informal caregivers were interviewed. Most patients were male (76%), aged between 60 and 69 years (43%). Three key themes were identified in regard to an interactive decision-making system: 1) Reassurance, because patients felt uncertain about their condition and their symptoms, they had a strong desire for an application that could monitor their health 24/7, was able to spot deteriorations, before they occured and gave them instant feedback about their current health status; 2) Personalized advice, e.g. patients wanted the virtual doctor to adapt medication, sport activities and food recommendations to their current health status; and 3) Transparency, e.g. patients wanted to know, where the recommendations are coming from and justifications for management modifications. Interview findings also identified that the HF-nurses play a significant role in the care and management of the condition. Across all countries with HF-nurses, they were the primary point of contact, when patients had any HF related concerns. Conclusion The findings provide valuable information for the development and implementation of eHealth solutions. Patients want reassurance, independently of the availability of healthcare services, combined with personalized advice regarding day-to-day management of their HF. For the next step, we are planning a multicentre clinical trial to test the prototype of the application. Here all decisions are examined by a clinical committee and benefits are evaluated.

An Overview of Multi Agent System for Sports and Healthcare Industry

Players more often engage in excessive physical activities during exercise session as well as in the game session because results of the games highly depend over the performance of participants that can be degraded due to various factors current health status, injury history, exercise types and duration, training and game experience. A Multi agent System can analyze all these factors and the overall performance of the participants can be improved using feedback. In this paper, the role of the Artificial Intelligence, Expert System, Machine/Deep Learning/Neural Networks in the sports and healthcare industry will be explored.

Simulation of epidemic models with generally distributed sojourn times

Epidemic models are used to analyze the progression or outcome of an epidemic under different control policies like vaccinations, quarantines, lockdowns, use of face-masks, pharmaceutical interventions, etc. When these models accurately represent real-life situations, they may become an important tool in the decision-making process. Among these models, compartmental models are very popular and assume individuals move along a series of compartments that describe their current health status. Nevertheless, these models are mostly Markovian, that is, the time in each compartment follows an exponential distribution. Here, we introduce a novel approach to simulate general stochastic epidemic models that accepts any distribution for the sojourn times.

Self-reported symptoms in a cohort of rheumatoid arthritis and lupus erythematosus during the COVID-19 quarantine period

Background. During the first three months of the COVID-19 pandemic in the Philippines, there was a supply shortage of hydroxychloroquine and methotrexate. This problem with medication access and the life changes resulting from the COVID-19 pandemic may predispose patients with rheumatoid arthritis (RA) or lupus erythematosus (LE) to disease flares.Objective. This study aims to investigate self-reported symptoms of disease flares among patients with rheumatoid arthritis or lupus erythematosus during the COVID-19 pandemic.Methods. A total of 512 completed online surveys from patients with LE or RA were collected. The gathered data included sociodemographic characteristics, self-reported physical symptoms, health service utilization, and availability of hydroxychloroquine and methotrexate.Results. Seventy-nine percent of respondents had lupus, while 21% had RA. One-third of the cohort had contact with their attending physician during the two-month quarantine period prior to the survey. Eighty-two percent were on hydroxychloroquine and 23.4% were on methotrexate; but 68.6% and 65%, respectively, of those prescribed had irregular intake of these medicines due to unavailability. The current health status was reported as good by 66.2%; 24% had no symptoms during the two-week period prior to the survey. The most common symptoms experienced were joint pain (67.4%), muscle pain (46.3%), headache (35.4%), and skin rash (25.4%). Five percent had a combination of these four most common symptoms. There was a higher proportion of patients with irregular supply of hydroxychloroquine with joint pains (54.9% versus 41.7%, p=0.012) and rash (24.7% versus 9.8%, p<0.001, Table 3).Conclusion. In our cohort of RA or LE, the majority reported at least one symptom that may indicate disease flare. There were more patients with joint pains or rash among those with irregular supply of hydroxychloroquine.

MIPT JACKET (Mentally Illed Patient Tracking)

In health care, IOT as a key player that furnishes better healthcare facilities to the affected, doctors and hospitals as well at anytime and anywhere. The proposed system consists of various medical devices such as sensors and mobile based application which communicates via network connected devices. These devices will monitor and record patients’ health data and various medical information. Different types of sensors are used like Temperature Sensor, Seizure Sensor, GPS Sensor, GSM Sensor and Pulse Sensor. The proposed paper will provide instant information about the patient’s current health status and full medical information in case any medical emergency arises both to the family members and the hospital. The collected information will predict patient’s chronic disorders or other diseases such as heart attacks in preliminary stage itself using the data mining techniques. MIPT Jacket technology provides greater visibility into every patient’s safe zone and improves patient’s safety by identifying the gaps in internal hospital processes and recovering them. Instant medical help will be provided to patient in non – safe zone also via sensors.

Rotary machine vibration monitoring and smart balance correction

During the rotary machine operation process, seemingly small amounts of abnormal vibration can often cause serious damage to the machinery over time and even increase the risk of accidents. Although professional vibration engineers can determine the current health status of a machine by interpreting the vibration spectrum information and predicting which components will fail, if even ordinary operators can send feedback regarding the vibration signals reaching the human–machine interface through a system when an abnormality is detected in the machine, the abnormality can be made known and processed in time. This can prevent the magnified impact of rotary inertia, thereby lowering the risk of major damage and the failure of machinery and equipment, as well as effectively saving on equipment maintenance costs. This study mainly adopted LabVIEW and Arduino IDE to develop a control program and human–machine monitoring interface. As the initial experiment on rotary machine vibration monitoring and smart balance correction, the measurement system setup in this study was applied to determine vibration abnormality as well as to carry out continuous online automatic balance correction. Experimental verification was carried out using active correction and smart correction. In terms of active online balance correction, the amplitude correction rate was 96%, the double-frequency correction rate was 102.9%, and the correction process was performed in 5 min. In terms of smart balance correction, the amplitude correction rate was 103.8%, the double-frequency correction rate was 103.3%, and the correction process was performed in 3 min. Through feedback signaling, the operator can effectively learn the current health status of the mechanical equipment from the human–machine interface.