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INTRODUCTION: There is growing evidence that implicit theories of smoking-whether smokers perceive smoking behavior as malleable or fixed-are significant predictors of quitting intentions. The present study aims to investigate the underlying mechanisms of implicit theories on smoking in predicting smokers' intentions to quit. METHODS: This was a cross-sectional study. We conducted multiple linear regression with quitting intentions as the dependent variable, implicit theories of smoking as the independent variable, and sociodemographic variables, quitting attempts in the past year, and whether receiving quitting advice in the past 12 months as the covariates. The mediating role of consideration of future consequences and self-efficacy in the relationship between ITS and quitting intentions was evaluated by mediation analyses. RESULTS: A total of 510 smokers were included in the final analyses. Smokers holding a higher incremental theory of smoking reported a higher likelihood of considering future consequences (ß = 0.289, p < 0.001) and a weaker possibility of considering immediate results (ß = -0.317, p < 0.001), which, in turn, enhanced their quitting self-efficacy and then led to stronger intentions to quit smoking (ß = 0.261, p < 0.001). CONCLUSIONS: The current study enriched our understanding of the underlying mechanisms that connect smokers' implicit theories of smoking and their likelihood of smoking cessation such that higher incremental theories of smoking predict stronger intention to quit smoking, and the effect was serially mediated by smokers' likelihood of considering future consequences of their behavior and their perceived self-efficacy for smoking cessation. IMPLICATIONS: This study indicated the mediating role of consideration of future consequences and self-efficacy for smoking cessation on the relationship between the implicit theories of smoking and quitting intentions. These two psychological factors and the pathways may be important points for understanding the model of implicit theories for smoking and improving the effectiveness of implicit theories-based intervention on smoking cessation.
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Background: The coronavirus disease 2019 (COVID-19) is a severe acute respiratory disease that poses a continuous threat to global public health. Many non-pharmacological interventions (NPIs) have been implemented to control the COVID-19 pandemic since the beginning. The aim of this study was to assess the impact of various NPIs on COVID-19 mortality during pre-vaccination and vaccination periods. Methods: The COVID-19 data used in this study comes from Our World in Data, we used the Oxford Strict Index (OSI) and its five combination interventions as independent variables. The COVID-19 mortality date (MRT) was defined as a date when daily rate of 0.02 COVID-19 deaths per 100,000 population in a country was reached, and the COVID-19 vaccination date (VRT) was defined as people vaccinated reaching 70%. Linear regression and random forest models were used to estimate the impact of various NPI implementation interventions during pre-vaccination and vaccination periods. The performance of models was assessed among others with Shapley Additive Explanations (SHAP) explaining the prediction capability of the model. Results: During the pre-vaccination period, the various NPIs had strong protective effect. When the COVID-19 MRT was reached, for every unit increase in OSI, the cumulative mortality as of June 30, 2020 decreased by 0.71 deaths per 100,000 people. Restrictions in travel (SHAP 1.68) and cancelation of public events and gatherings (1.37) had major reducing effect on COVID-19 mortality, while staying at home (0.26) and school and workplace closure (0.26) had less effect. Post vaccination period, the effects of NPI reduced significantly: cancelation of public events and gatherings (0.25), staying at home (0.22), restrictions in travel (0.14), and school and workplace closure (0.06). Conclusion: Continued efforts are still needed to promote vaccination to build sufficient immunity to COVID-19 in the population. Until herd immunity is achieved, NPI is still important for COVID-19 prevention and control. At the beginning of the COVID-19 pandemic, the stringency of NPI implementation had a significant negative association with COVID-19 mortality; however, this association was no longer significant after the vaccination rate reached 70%. As vaccination progresses, "cancelation of public events and gatherings" become more important for COVID-19 mortality.
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OBJECTIVES: The purpose of this study is to describe the situation of COVID-19 in European countries and to identify important factors related to prevention and control. METHODS: We obtained data from World Health Statistics 2020 and the Institute for Health Metrics and Evaluation (IHME). We calculated the Rt values of 51 countries in Europe under different prevention and control measures. We used lasso regression to screen factors associated with morbidity and mortality. For the selected variables, we used quantile regression to analyse the relevant influencing factors in countries with different levels of morbidity or mortality. RESULTS: The government has a great influence on the change in Rt value through prevention and control measures. The most important factors for personal and group prevention and control are the mobility index, testing, the closure of educational facilities, restrictions on large-scale gatherings, and commercial restrictions. The number of ICU beds and doctors in medical resources are also key factors. Basic sanitation facilities, such as the proportion of safe drinking water, also have an impact on the COVID-19 epidemic. CONCLUSIONS: We described the current status of COVID-19 in European countries. Our findings demonstrated key factors in individual and group prevention measures.
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COVID-19/prevención & control , Pandemias/prevención & control , SARS-CoV-2 , Número Básico de Reproducción/estadística & datos numéricos , COVID-19/epidemiología , COVID-19/mortalidad , Control de Enfermedades Transmisibles/métodos , Control de Enfermedades Transmisibles/estadística & datos numéricos , Europa (Continente)/epidemiología , Salud Global/estadística & datos numéricos , Humanos , Modelos Lineales , Pandemias/estadística & datos numéricosRESUMEN
BACKGROUND: To put COVID-19 patients into hospital timely, the clinical diagnosis had been implemented in Wuhan in the early epidemic. Here we compared the epidemiological characteristics of laboratory-confirmed and clinically diagnosed cases with COVID-19 in Wuhan. METHODS: Demographics, case severity and outcomes of 29,886 confirmed cases and 21,960 clinically diagnosed cases reported between December 2019 and February 24, 2020, were compared. The risk factors were estimated, and the effective reproduction number (Rt) of SARS-CoV-2 was also calculated. RESULTS: The age and occupation distribution of confirmed cases and clinically diagnosed cases were consistent, and their sex ratio were 1.0 and 0.9, respectively. The epidemic curve of clinical diagnosis cases was similar to that of confirmed cases, and the city centers had more cumulative cases and higher incidence density than suburbs in both of two groups. The proportion of severe and critical cases (21.5 % vs. 14.0 %, P < 0.0001) and case fatality rates (5.2 % vs. 1.2 %, P < 0.0001) of confirmed cases were all higher than those of clinically diagnosed cases. Risk factors for death we observed in both of two groups were older age, male, severe or critical cases. Rt showed the same trend in two groups, it dropped below 1.0 on February 6 among confirmed cases, and February 8 among clinically diagnosed cases. CONCLUSIONS: The demographic characteristics and spatiotemporal distributions of confirmed and clinically diagnosed cases are roughly similar, but the disease severity and clinical outcome of clinically diagnosed cases are better than those of confirmed cases. In cases when detection kits are insufficient during the early epidemic, the implementation of clinical diagnosis is necessary and effective.