Multiple Sclerosis (MS) is an immune-mediated, neuroinflammatory disease of the central nervous system and in industrialised countries the most common cause of progressive neurological disability in working age persons. However, there is significant between-subject heterogeneity in disease activity and response to treatment. Currently, the ability to predict at diagnosis who will have a benign, intermediate, or aggressive disease course is very limited. There is therefore a need for integrated predictive tools to inform individualised treatment decision making. FutureMS is a nationally-representative, prospective observation cohort study comprising 440 participants with a new diagnosis of relapsing remitting MS living in Scotland between May 2016 and March 2019. Established with the aim of addressing this need for individualised predictive tools, the cohort is designed to combine detailed clinical phenotyping with imaging, genetic and biomarker metrics of disease activity and progression. Recruitment, baseline assessment and follow up at year one is complete and longer-term follow up is planned, beginning at five years after first visit. The study aims to address the biology and determinants of disease heterogeneity in MS. Here we describe the cohort design and present a profile of the participants at baseline and one year of follow up.
Is cheating intuitive when it serves self-interest? The literature on intuitive honesty versus dishonesty remains controversial. In two studies, we used both betweensubjects (Study 1, N = 90) and within-subjects (Study 2, N = 93) cognitive load manipulations to induce intuition and tested the intuitive dishonesty hypothesis with behavioral cheating paradigms. Results showed that cognitive load increased lying across multiple tasks (Studies 1 and 2). Moreover, the intuitive dishonesty effect occurred only for individuals low in Honesty-Humility (Study 2). The findings are discussed with regard to current debates about intuitive dishonesty.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.