Highlights The COVID-19 pandemic had significant mental health impacts on the population of Kuwait. Unemployment, uncertainty, distress, increasing deaths and lockdown measures contribute to the burden. From our experience risk factors include; female, smoker, past psychiatric history, increased social media use. Availability of psychological support and mental health awareness reduces the burden.
Although the approved COVID-19 vaccines have proven to be safe and effective, multiple beliefs and misconceptions still exist influencing the vaccine uptake rates around the world. The multifaceted complex phenomenon of vaccine hesitancy could jeopardize the efforts to overcome this pandemic. The aim of this study is to identify the prevalence and examine the factors associated with vaccine hesitancy in Kuwait. This is a web-based cross-sectional study conducted in Kuwait from March 2021 until April 2021, during the second wave of the COVID-19 pandemic. Our questionnaire examined basic demographic information, attitudes towards the COVID-19 vaccines as well as reasons for and against accepting the vaccine. Out of the 2345 responders, the majority are fully convinced to take the vaccine (83%) and the rate of vaccine hesitancy is 17%. Vaccine hesitancy is higher among non-healthcare workers, those previously positive for the COVID-19 virus, and those against vaccines in general. Vaccine hesitancy could jeopardize the efforts to overcome this pandemic; therefore, intensifying nationwide education and dismissal of falsified information is an essential step towards addressing vaccine hesitancy.
Background Surgical residency often poses a challenge to residents, with long working hours and a stressful work environment. Surgical residents are at an increased risk of burnout and depression. Such mental health burdens could go so far as to affect treatment outcomes. Aim To assess the prevalence and risk factors for depression and burnout among residents across surgical specialties in Kuwait. Materials and methods An online questionnaire was sent to the residents enrolled to the surgical residency programs in Kuwait, from the period of January 2020–February 2020. Variables collected included; age, gender, marital status, smoking history, exercise, specialty, year of training, on-call frequency, assessment of burnout (using the abbreviated Maslach Burnout Inventory (aMBI)) and assessment of depressive symptoms (using the Patient Health Questionnaire-9 (PHQ-9) score). Results A total of 85 surgical residents between the age of 20 and 40 years responded. Most (64.7%) were male and 35.3% female. More than half were married (51.8%) and 41.2% were single. The majority of the residents were in general surgery (43.5%), with the least being in otolaryngology (7.1%) and neurosurgery (5.9%). The prevalence of depressive symptoms was 55.3%, and 51.8% had a high overall burnout score. Conclusion Addressing burnout at all stages during residency training is paramount in improving standard of care as well as increasing the wellness of residents.
Purpose The quality of consumer-oriented health information on the web has been defined and evaluated in several studies. Usually it is based on evaluation criteria identified by the researchers and, so far, there is no agreed standard for the quality indicators to use. Based on such indicators, tools have been developed to evaluate the quality of web information. The HONcode is one of such tools. The purpose of this paper is to investigate the influence of web document features on their quality, using HONcode as ground truth, with the aim of finding whether it is possible to predict the quality of a document using its characteristics. Design/methodology/approach The present work uses a set of health documents and analyzes how their characteristics (e.g. web domain, last update, type, mention of places of treatment and prevention strategies) are associated with their quality. Based on these features, statistical models are built which predict whether health-related web documents have certification-level quality. Multivariate analysis is performed, using classification to estimate the probability of a document having quality given its characteristics. This approach tells us which predictors are important. Three types of full and reduced logistic regression models are built and evaluated. The first one includes every feature, without any exclusion, the second one disregards the Utilization Review Accreditation Commission variable, due to it being a quality indicator, and the third one excludes the variables related to the HONcode principles, which might also be indicators of quality. The reduced models were built with the aim to see whether they reach similar results with a smaller number of features. Findings The prediction models have high accuracy, even without including the characteristics of Health on the Net code principles in the models. The most informative prediction model considers characteristics that can be assessed automatically (e.g. split content, type, process of revision and place of treatment). It has an accuracy of 89 percent. Originality/value This paper proposes models that automatically predict whether a document has quality or not. Some of the used features (e.g. prevention, prognosis or treatment) have not yet been explicitly considered in this context. The findings of the present study may be used by search engines to promote high-quality documents. This will improve health information retrieval and may contribute to reduce the problems caused by inaccurate information.
Background To date, multiple scoring systems have been utilised in predicting outcomes in burn patients. The aim of this study is to determine the accuracy of three established scoring systems used for burn patients admitted to the intensive care unit and to determine the risk factors associated with poor outcomes. Methods A total of 211 patients who were admitted to the ICBU in a tertiary care centre in Kuwait from January 2017 to December 2019 were analysed retrospectively. Data were collected using patient medical records. The FLAMES, BOBI and revised Baux scores were calculated, and the survivor and non-survivor scores of patients were analysed to determine the sensitivity, specificity and Area Under the Receiver Operating Characteristics (AUROC) of the different scoring modalities. Results The majority of the analysed population were male patients (165/211) and the most common mechanism of burns was flame burns (166/211). Most of the patients admitted to the ICBU survived (188/211). Female gender was associated with a higher mortality rate, whilst inhalational injury and co-morbidities were not associated with a higher mortality rate. The revised Baux score had a sensitivity value of 96% and 90% specificity. The BOBI score had a sensitivity of 91% and 76% specificity. The FLAMES score had a sensitivity of 96% and the highest specificity of 99%. All 3 scores had AUC values exceeding 90%. Conclusion Statistically, FLAMES score had the highest accuracy of predicting outcomes in burn patients, however all three scores demonstrated acceptable predictive rates when it comes to practical application, permitting the use of either one of the studied scores with satisfactory prognostic outcomes.
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