Notes

COVID-19 vaccine hesitancy in older adults along with ms in the usa: A new follow-up review in the original vaccine rollout throughout 2021.
tandalone learning tool or one that could be combined with other training formats.
These findings indicate that the MOOC was successful in targeting learners from LMICs, in strengthening their IR knowledge and contributing to their ability to apply it in their professional practice. The utility of MOOCs for providing IR training to learners in LMICs, where implementation challenges are encountered often, makes this platform an ideal standalone learning tool or one that could be combined with other training formats.
Coronary plaque vulnerability prediction is difficult because plaque vulnerability is non-trivial to quantify, clinically available medical image modality is not enough to quantify thin cap thickness, prediction methods with high accuracies still need to be developed, and gold-standard data to validate vulnerability prediction are often not available. Patient follow-up intravascular ultrasound (IVUS), optical coherence tomography (OCT) and angiography data were acquired to construct 3D fluid-structure interaction (FSI) coronary models and four machine-learning methods were compared to identify optimal method to predict future plaque vulnerability.

Baseline and 10-month follow-up in vivo IVUS and OCT coronary plaque data were acquired from two arteries of one patient using IRB approved protocols with informed consent obtained. IVUS and OCT-based FSI models were constructed to obtain plaque wall stress/strain and wall shear stress. Forty-five slices were selected as machine learning sample database for vulnal-factor predictor achieved an AUC 0.836. Using random forest for predicting MPVI change, minimum cap thickness was the optimal single-factor predictor with AUC 0.785 and the AUC of optimal combinational-factor predictor achieved 0.847.

This feasibility study demonstrated that machine learning methods could be used to accurately predict plaque vulnerability change based on morphological and biomechanical factors from multi-modality image-based FSI models. Large-scale studies are needed to verify our findings.
This feasibility study demonstrated that machine learning methods could be used to accurately predict plaque vulnerability change based on morphological and biomechanical factors from multi-modality image-based FSI models. Large-scale studies are needed to verify our findings.Very few studies have been concerned with assessing the prevalence of burnout and depressive symptoms, especially during an infectious outbreak on non-frontline health care workers, such as a psychiatrist. In such instances, the role of psychiatrists and other mental health providers as a source of psychological support to the public and frontline workers is indispensable and valuable. This study aims to assess the prevalence of burnout and depressive symptoms, and their correlation, during the COVID-19 pandemic among psychiatry residents in Saudi Arabia. A total of 121 out of 150 psychiatry residents in Saudi Arabia completed the Maslach Burnout Inventory and Patient's Health Questionnaire for the assessment of burnout and depressive symptoms. Burnout symptoms were found in 27.3%, and another 27.3% reported having depression symptoms. In addition, 16.5% reported having both burnout and depressive symptoms, with a significant relationship between them. Participants in the first 2 years of training and having a history of receiving mental health treatment in the past 2 years were at higher risk. The need is urgent to increase investment in mental health services and to construct a plan to reduce this risk of burnout and depression among psychiatrists by developing preventative strategies to prevent burnout and promote wellness is more important than ever.
Aging is the major risk factor for most human cancers. We aim to develop and validate a reliable aging-related gene pair signature (ARGPs) to predict the prognosis of gastric cancer (GC) patients.

The mRNA expression data and clinical information were obtained from two public databases, The Cancer Genome Atlas (TCGA) dataset, and Gene Expression Omnibus (GEO) dataset, respectively. The best prognostic signature was established using Cox regression analysis (univariate and least absolute shrinkage and selection operator). The optimal cut-off value to distinguish between high- and low-risk patients was found by time-dependent receiver operating characteristic (ROC). The prognostic ability of the ARGPS was evaluated by a log-rank test and a Cox proportional hazards regression model.

The 24 ARGPs were constructed for GC prognosis. Using the optimal cut-off value - 0.270, all patients were stratified into high risk and low risk. In both TCGA and GEO cohorts, the results of Kaplan-Meier analysis showed that tict the prognostic outcome of GC patients.
Our study has developed a robust prognostic signature that can accurately predict the prognostic outcome of GC patients.The COVID-19 pandemic has affected people's physical and mental health. Quarantine and other lockdown measures have altered people's daily lives; levels of anxiety, depression, substance use, self-harm and suicide ideation have increased. This commentary assesses how international governments, agencies and organisations are responding to the challenge of the mental health impact of COVID-19 with the aim of informing the ongoing policy and service responses needed in the immediate and longer term. It identifies some of the key themes emerging from the literature, recognises at-risk populations and highlights opportunities for innovation within mental health services, focusing on the published academic literature, international health ministry websites and other relevant international organisations beyond the United Kingdom and Ireland. COVID-19 has challenged, and may have permanently changed, mental health services. It has highlighted and exacerbated pre-existing pressures and inequities. Many decision-makers consider this an opportunity to transform mental health care, and tackling the social determinants of mental health and engaging in prevention will be a necessary part of such transformation. Better data collection, modelling and sharing will enhance policy and service development. The crisis provides opportunities to build on positive innovations the adaptability and flexibility of community-based care; drawing on lived experience in the design, development and monitoring of services; interagency collaboration; accelerating digital healthcare; and connecting physical and mental health.
Accounting for the co-occurrence of multiple environmental influences is a more accurate reflection of population exposure than considering isolated influences, aiding in understanding the complex interactions between environments, behaviour and health. This study examines how environmental 'goods' such as green spaces and environmental 'bads' such as alcohol outlets co-occur to develop a nationwide area-level healthy location index (HLI) for New Zealand.

Nationwide data were collected, processed, and geocoded on a comprehensive range of environmental exposures. Health-constraining 'bads' were represented by (i) fast-food outlets, (ii) takeaway outlets, (iii) dairy outlets and convenience stores, (iv) alcohol outlets, (v) and gaming venues. Health-promoting 'goods' were represented by (i) green spaces, (ii) blue spaces, (iii) physical activity facilities, (iv) fruit and vegetable outlets, and (v) supermarkets. The HLI was developed based on ranked access to environmental domains. The HLI was then used to his study further reinforce the need to embrace the multidimensional nature of neighbourhood and place not only when designing health-promoting places, but also when studying the effect of existing built environments on population health.
COVID-19 has an inevitable burden on public health, potentially widening the gender gap in healthcare and the economy. We aimed to assess gender-based desparities during COVID-19 in Jordan in terms of health indices, mental well-being and economic burden.

A nationally representative sample of 1300 participants ≥18 years living in Jordan were selected using stratified random sampling. Data were collected via telephone interviews in this cross-sectional study. Chi-square was used to test age and gender differences according to demographics, economic burden, and health indices (access to healthcare, health insurance, antenatal and reproductive services). A multivariable logistic regression analysis was used to estimate the beta-coefficient (β) and 95% confidence interval (CI) of factors correlated with mental well-being, assessed by patients' health questionnaire 4 (PHQ-4).

656 (50.5%) men and 644 (49.5%) women completed the interview. Three-fourths of the participants had health insurance during the COVIDonomy.
Our results showed no gender differences in healthcare coverage or access during the COVID-19 crisis generally. Women in Jordan are experiencing worse outcomes in terms of mental well-being and economic burden. Policymakers should give priority to women's mental health and antenatal and reproductive services. Financial security should be addressed in all Jordanian COVID-19 national plans because the crisis appears widening the gender gap in the economy.
Nutrition labels show potential in increasing healthy food and beverage purchases, but their effectiveness seems to depend on the type of label, the targeted food category and the setting, and evidence on their impact in real-world settings is limited. The aim of this study was to evaluate the effectiveness of an industry-designed on-shelf sugar label on the sales of beverages with no, low, medium and high sugar content implemented within a real-world supermarket.

In week 17 of 2019, on-shelf sugar labels were implemented by a Dutch supermarket chain. Non-alcoholic beverages were classified using a traffic-light labeling system and included the beverage categories "green" for sugar free (< 1.25 g/250 ml), "blue" for low sugar (1.25-6.24 g/250 ml), "yellow" for medium sugar (6.25-13.5 g/250 ml) and "amber" for high sugar (> 13.5 g/250 ml). Store-level data on beverage sales and revenue from 41 randomly selected supermarkets for 13 weeks pre-implementation and 21 weeks post-implementation were used foificantly decrease unhealthy beverage sales or significantly increase healthier beverage sales. Nutrition labeling initiatives combined with complementary strategies, such as pricing strategies or other healthy food nudging approaches, should be considered to promote healthier beverage purchases.
The implementation of an on-shelf sugar labeling system did not significantly decrease unhealthy beverage sales or significantly increase healthier beverage sales. EGFR inhibitor Nutrition labeling initiatives combined with complementary strategies, such as pricing strategies or other healthy food nudging approaches, should be considered to promote healthier beverage purchases.
The persistent fragmentation of home healthcare reflects inadequate coordination between care providers. Still, while factors at the system (e.g., regulations) and organisational (e.g., work environment) levels crucially influence homecare organisation, coordination and ultimately quality, knowledge of these factors and their relationships in homecare settings remains limited.

This study has three aims [1] to explore how system-level regulations lead to disparities between homecare agencies' structures, processes and work environments; [2] to explore how system- and organisation-level factors affect agency-level homecare coordination; and [3] to explore how agency-level care coordination is related to patient-level quality of care.

This study focuses on a national multi-center cross-sectional survey in Swiss homecare settings. It will target 100 homecare agencies, their employees and clients for recruitment, with data collection period planned from January to June 2021. We will assess regulations and financing mechanisms (via public records), agency characteristics (via agency questionnaire data) and homecare employees' working environments and coordination activities, as well as staff- and patient-level perceptions of coordination and quality of care (via questionnaires for homecare employees, clients and informal caregivers).
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