57 research outputs found
Determinants of Propranolol’s Selective Effect on Loss Aversion
Research on emotion and decision making has suggested that arousal mediates risky decisions, but several distinct and often confounded processes drive such choices. We used econometric modeling to separate and quantify the unique contributions of loss aversion, risk attitudes, and choice consistency to risky decision making. We administered the beta-blocker propranolol in a double-blind, placebo-controlled within-subjects study, targeting the neurohormonal basis of physiological arousal. Matching our intervention’s pharmacological specificity with a quantitative model delineating decision-making components allowed us to identify the causal relationships between arousal and decision making that do and do not exist. Propranolol selectively reduced loss aversion in a baseline- and dose-dependent manner (i.e., as a function of initial loss aversion and body mass index), and did not affect risk attitudes or choice consistency. These findings provide evidence for a specific, modulatory, and causal relationship between precise components of emotion and risky decision making
Variability in the analysis of a single neuroimaging dataset by many teams
Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed
Variability in the analysis of a single neuroimaging dataset by many teams
Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed
Perceptions of physician leadership in Botswana
Background. Physician leadership is essential for the strengthening of health systems, especially in underserved settings such as sub-Saharan Africa. To be effective, leaders must be perceived as such by their community. It is unknown how perceptions of physician leadership in Botswana compare with those of the Canadian Medical Education Directives for Specialists (CanMEDS) Physician Competency Framework, which is used to shape the training of Botswana’s future physicians.Objective. To examine if the perceived competencies of physician leadership in Botswana are specifically named in the CanMEDS Framework and thereby inform Botswana’s graduate medical education.Methods. We conducted focus groups discussions with nurses, interns, medical officers and specialists at Princess Marina Hospital and Nyangabgwe Referral Hospital. Key questions focused on describing the qualities of physician leadership. For data analysis we used inductive content coding and comparison with the CanMEDS frameworks.Results. Forty-eight clinicians participated and 111 unique codes were assigned to 503 comments. Eighty-four per cent of comments corresponded to the CanMEDS 2005 competencies; many were captured within the competencies of the medical expert (13.0%), communicator (17.8%), collaborator (15.6%), scholar (14.9%) and professional (31.3%) roles. About 5% of comments mapped to the draft CanMEDS 2015 update, and 11.5% were not specifically described in either version of CanMEDS, including charisma and decisiveness.Conclusion. The CanMEDS frameworks specifically address most of the competencies perceived as important for physician leadership in Botswana. Additional perceptions were identified that may require the attention of existing and aspiring physician leaders and their teachers to ensure they attain and maintain their effectiveness as leaders
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Functional benefits of predator species diversity depend on prey identity
1. Determining the functional significance of species diversity in natural enemy assemblages is a key step towards prediction of the likely impact of biodiversity loss on natural pest control processes. While the biological control literature contains examples in which increased natural enemy diversity hinders pest control, other studies have highlighted mechanisms where pest suppression is promoted by increased enemy diversity. 2. This study aimed to test whether increased predator species diversity results in higher rates of predation on two key, but contrasting, insect pest species commonly found in the rice ecosystems of south-east Asia. 3. Glasshouse experiments were undertaken in which four life stages of a planthopper (Nilaparvata lugens) and a moth (Marasmia patnalis) were caged with single or three-species combinations of generalist predators. 4. Generally, predation rates of the three-species assemblages exceeded expectation when attacking M. patnalis, but not when attacking N. lugens. In addition, a positive effect of increased predator species richness on overall predation rate was found with M. patnalis but not with N. lugens. 5. The results are consistent with theoretical predictions that morphological and behavioural differentiation among prey life stages promotes functional complementarity among predator species. This indicates that emergent species diversity effects in natural enemy assemblages are context dependent; they depend not only on the characteristics of the predators species, but on the identity of the species on which they prey
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