Climate change knowledge influences attitude to mitigation via efficacy beliefs

Theories proposing climate change apathy is explained by inadequate knowledge do not account for why many informed and concerned Americans fail to act. While correlations between knowledge, efficacy for climate change, and attitude to mitigation have been observed, few studies have examined efficacy for climate change as a mediator. This study aimed to investigate the influence of specific climate change knowledge on attitude to mitigation via efficacy beliefs. A cross-sectional survey of 205 US adults recruited from Amazon's Mechanical Turk assessed participants’ climate change knowledge, efficacy for climate change, and attitude to mitigation. Indirect effects of self-efficacy for climate change were observed in three mediation models, suggesting efficacy for climate change explains some of the relationship between specific climate change knowledge and attitude to mitigation. The findings suggest risk communication can motivate pro-environmental attitudes with interventions that deliver information about climate change and develop efficacy for mitigation behavior.     

Predicting System Usage from Intention and Past Use: Scale Issues in the Predictors

The objective of this study is to provide insights into how the predictive power for computer‐recorded system usage can be improved. Based on 386 responses from actual users of an information system, we examine the predictive power for system usage according to the scales of the predictors used, namely, intention and past use. First, we show that the predictive power of intention can be significantly improved with the choice of an appropriate measure. However, even the desirable intention measure failed to explain two‐thirds of the variance in system usage. Second, the results show that past use as measured by computer‐recorded log data can significantly enhance our ability to predict system usage. Finally, when both intention and past use are controlled for, the explained variance in system usage is shown to vary widely from 20% to 73%, depending on the predictors' scales. Overall, our findings suggest that an accurate prediction of system usage requires a more rigorous approach than that often applied in information systems research.     

Vaccine clinical trials with dynamic borrowing of historical controls: Two retrospective studies

Traditional vaccine efficacy trials usually use fixed designs with fairly large sample sizes. Recruiting a large number of subjects requires longer time and higher costs. Furthermore, vaccine developers are more than ever facing the need to accelerate vaccine development to fulfill the public's medical needs. A possible approach to accelerate development is to use the method of dynamic borrowing of historical controls in clinical trials. In this paper, we evaluate the feasibility and the performance of this approach in vaccine development by retrospectively analyzing two real vaccine studies: a relatively small immunological trial (typical early phase study) and a large vaccine efficacy trial (typical Phase 3 study) assessing prophylactic human papillomavirus vaccine. Results are promising, particularly for early development immunological studies, where the adaptive design is feasible, and control of type I error is less relevant.     

私力救济的法理分析

本文在法理学层面上论述了救济理论中的私力救济 ,对私力救济的概念做了界定 ,概括了它的构成要件 ,进而对之进行价值分析 ,认为私力救济的主要价值是正义、效率和秩序。