Summarising data and factors associated with COVID‑19 related conspiracy theories in the first year of the pandemic:a systematic review and narrative synthesis

Conspiracy theories can have particularly harmful effects by negatively shaping health-related behaviours. A significant number of COVID-19 specific conspiracy theories emerged in the immediate aftermath of the pandemic outbreak. The aim of this study was to systematically review the literature on conspiracy theories related to COVID-19 during the first year of the pandemic (2020), to identify their prevalence, their determinants and their public health consequences. A comprehensive literature search was carried out in PubMed and PsycINFO to detect all studies examining any conspiracy theory related to COVID-19 between January 1st 2020, and January 10th 2021. Forty-three studies were included with a total of 61,809 participants. Between 0.4 and 82.7% of participants agreed with at least one conspiracy belief. Certain sociodemographic factors (young age, female gender, being non-white, lower socioeconomic status), psychological aspects (pessimism, blaming others, anger) and other qualities (political conservatism, religiosity, mistrust in science and using social media as source of information) were associated with increased acceptance of conspiracy theories. Conspiracy beliefs led to harmful health-related behaviours and posed a serious public health threat. Large-scale collaborations between governments and healthcare organizations are needed to curb the spread of conspiracy theories and their adverse consequences

Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review

Objective: To provide a comprehensive review on the existing research and evi-dence regarding artificial intelligence (AI) applications in the assessment and management of urinary stone disease.Methods: A comprehensive literature review was performed using PubMed, Scopus, and Google Scholar databases to identify publications about innovative concepts or supporting applica-tions of AI in the improvement of every medical procedure relating to stone disease. The terms "endourology", "artificial intelligence", "machine learning", and "urolithiasis"were used for searching eligible reports, while review articles, articles referring to automated procedures without AI application, and editorial comments were excluded from the final set of publica-tions. The search was conducted from January 2000 to September 2023 and included manu-scripts in the English language.Results: A total of 69 studies were identified. The main subjects were related to the detection of urinary stones, the prediction of the outcome of conservative or operative management, the optimization of operative procedures, and the elucidation of the relation of urinary stone chemistry with various factors.Conclusion: AI represents a useful tool that provides urologists with numerous amenities, which explains the fact that it has gained ground in the pursuit of stone disease management perfection. The effectiveness of diagnosis and therapy can be increased by using it as an alter-native or adjunct to the already existing data. However, little is known concerning the poten-tial of this vast field. Electronic patient records, containing big data, offer AI the opportunity to develop and analyze more precise and efficient diagnostic and treatment algorithms. Never-theless, the existing applications are not generalizable in real-life practice, and high-quality studies are needed to establish the integration of AI in the management of urinary stone dis-ease.CNN ; CNN

Age and gender effects on the association of sleep insufficiency with hypertension among adults in Greece

Background: We aimed to investigate the relationship between sleep characteristics with hypertension using self-reported questionnaires. Material & methods: A total of 957 adults were classified into three groups (short [<6 h], normal [6-8 h] and long [>8 h] sleepers). Hypertension was defined as systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg or use of antihypertensive medication at the time of interview. Results: Overall prevalence of hypertension was 34.3%. Association between short sleep duration and hypertension that was age-specific, present only among younger and middle aged individuals and sparing the elderly, but not gender-specific, as no discrepancies existed between males and females in all age groups, was evident. Conclusion: This study promotes early pharmacological or cognitive behavioral interventions on sleep disturbances in order to reduce hypertension burden

Explainable Machine Learning in the Prediction of Depression

Background: Depression constitutes a major public health issue, being one of the leading causes of the burden of disease worldwide. The risk of depression is determined by both genetic and environmental factors. While genetic factors cannot be altered, the identification of potentially reversible environmental factors is crucial in order to try and limit the prevalence of depression. Aim: A cross-sectional, questionnaire-based study on a sample from the multicultural region of Thrace in northeast Greece was designed to assess the potential association of depression with several sociodemographic characteristics, lifestyle, and health status. The study employed four machine learning (ML) methods to assess depression: logistic regression (LR), support vector machine (SVM), XGBoost, and neural networks (NNs). These models were compared to identify the best-performing approach. Additionally, a genetic algorithm (GA) was utilized for feature selection and SHAP (SHapley Additive exPlanations) for interpreting the contributions of each employed feature. Results: The XGBoost classifier demonstrated the highest performance on the test dataset to predict depression with excellent accuracy (97.83%), with NNs a close second (accuracy, 97.02%). The XGBoost classifier utilized the 15 most significant risk factors identified by the GA algorithm. Additionally, the SHAP analysis revealed that anxiety, education level, alcohol consumption, and body mass index were the most influential predictors of depression. Conclusions: These findings provide valuable insights for the development of personalized public health interventions and clinical strategies, ultimately promoting improved mental well-being for individuals. Future research should expand datasets to enhance model accuracy, enabling early detection and personalized mental healthcare systems for better intervention. </p

Sleep insufficiency and incident diabetes mellitus among indigenous and minority populations in Greece

Objective: To investigate the potential association between sleep pathology and diabetes mellitus (DM) using self-reported questionnaires. Material and Methods: 957 adults aged between 19 and 86 years old were enrolled in this cross-sectional study. Multistage stratified cluster sampling was used and subjects were classified into three groups [short (8h) sleep duration]. Individuals were classified as diabetics if they responded positively to the questions: “Have you ever been told that you are diabetic or have high blood sugar by a health professional?” or “Are you on antidiabetic medication?”. Sleep quality, utilizing Epworth sleepiness scale, Athens insomnia scale, Pittsburgh sleep quality index and Berlin questionnaire, was also examined. Results: DM prevalence was higher among expatriated and Muslim Greeks (23.1% and 18.7%, respectively) compared to indigenous Greek Christians (4.4%). DM prevalence was significantly associated with short sleep duration (aOR=2.82, p<0.001), excessive daytime sleepiness (aOR=2.09, p=0.019) and poor sleep quality (aOR=2.56, p<0.001), while its relation with insomnia (aOR=1.63, p=0.065) and risk for obstructive sleep apnea (aOR=1.53, p=0.080) were of marginal statistical significance. Conclusion: This study indicates an association between sleep quantity, quality and DM and supports early pharmacological and cognitive behavioral interventions on sleep disturbances in order to reduce the burden of DM with increased focus on minority population needs

Association between sleep insufficiency and dyslipidemia: a cross-sectional study among Greek adults in the primary care setting

Objective: To investigate the potential association between sleep insufficiency and dyslipidemia (DL) in the primary care setting using self-reported questionnaires. Material and Methods: 957 adults aged between 19 and 86 years old from the rural area of Thrace, Greece were enrolled in this cross-sectional study. Multistage stratifed cluster sampling was used and the subjects were classifed into three groups according to sleep duration [short (8h) sleep duration]. DL was defined by a positive response to the question “Have you ever been told by a doctor or health professional that your blood cholesterol or triglyceride levels were high?”, or if they were currently taking antilipidemic agents. Sleep quality, utilizing Epworth sleepiness scale, Athens insomnia scale, Pittsburgh sleep quality index and Berlin questionnaire, was also examined. Results: DL prevalence was significantly associated with short sleep duration (aOR=2.18, p<0.001) and insomnia (aOR=1.43, p=0.050), while its relation with poor sleep quality (aOR=1.31, p=0.094) and risk for obstructive sleep apnea (aOR=1.32, p=0.097) were of marginal statistical significance. Concerning insomnia subtypes, DL was significantly associated with difficulties maintaining sleep (aOR=2.99, p<0.001) and early morning awakenings (aOR=1.38, p=0.050), but not difficulties initiating sleep (aOR=1.18, p=0.328). Conclusion: This study reveals an association between sleep pathology and DL. Thus, early pharmacological and cognitive or behavioral interventions that improve sleep are deemed necessary in order to decrease DL burden

A large‐scale meta‐analytic atlas of mental health problems prevalence during the COVID‐19 early pandemic

The COVID-19 pandemic and related restrictions can impact mental health. In order to quantify the mental health burden of COVID-19 pandemic, we conducted a systematic review and meta- analysis, searching World Health Organization COVID-19/PsycInfo/PubMed databases (09/29/2020), including observational studies reporting on mental health outcomes in any population affected by COVID-19. Primary outcomes were the prevalence of anxiety, depression, stress, sleep problems, post-traumatic symptoms. Sensitivity analyses were conducted on severe mental health problems, in high-quality studies, and in representative samples. Subgroup analyses were conducted stratified by age, sex, country income level, and COVID-19 infection status. One-hundred-seventy-three studies from February-July 2020 were included (n=502,261, median sample=948, age=34.4 years, females=63%). Ninety-one percent were cross-sectional studies, and 18.5%/57.2% were of high/moderate quality. Highest prevalence emerged for post-traumatic symptoms in COVID-19 infected people (94%), followed by behavioural problems in those with prior mental disorders (77%), fear in healthcare workers (71%), anxiety in caregivers/family members of people with COVID-19 (42%), general health/social contact/passive coping style in the general population (38%), depression in those with prior somatic disorders (37%), and fear in other-than-healthcare workers (29%). Females and people with COVID-19 infection had higher rates of almost all outcomes; college students/young adults of anxiety, depression, sleep problems, suicidal ideation; adults of fear and post-traumatic symptoms. Anxiety, depression, and post- traumatic symptoms were more prevalent in low-/middle-income countries, sleep problems in high-income countries. The COVID-19 pandemic adversely impacts mental health in unique manners across population subgroups. Our results inform tailored preventive strategies and interventions to mitigate current, future, and transgenerational adverse mental health of the COVID-19 pandemic

Oncology during the COVID-19 pandemic: challenges, dilemmas and the psychosocial impact on cancer patients.

COVID-19 has caused unprecedented societal turmoil, triggering a rapid, still ongoing, transformation of healthcare provision on a global level. In this new landscape, it is highly important to acknowledge the challenges this pandemic poses on the care of the particularly vulnerable cancer patients and the subsequent psychosocial impact on them. We have outlined our clinical experience in managing patients with gastrointestinal, hematological, gynaecological, dermatological, neurological, thyroid, lung and paediatric cancers in the COVID-19 era and have reviewed the emerging literature around barriers to care of oncology patients and how this crisis affects them. Moreover, evolving treatment strategies and novel ways of addressing the needs of oncology patients in the new context of the pandemic are discussed