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From an evolutionary perspective, aggression is viewed as a flexible context-specific adaption that was selected for because it enhanced the survival and reproductive success of ancestral humans. Evolutionary pressures have impinged differentially on the sexes, leading to the hypothesis that sex differences should be manifest in aggressive behavior. Evidence to date supports key predictions made from sexual selection theory that women direct their aggression primarily toward same-sex competitors, which peaks as mate competition intensifies. Women demonstrate a notable preference across cultures for more indirect, as opposed to direct, forms of intrasexual rivalry as a likely consequence of heightened obligatory parental investment, lower lifetime reproductive potential, and the greater importance of maternal survival for the health and longevity of offspring. An evolutionary approach can yield unique insights into the sex-differentiated functions, development, and outcomes of aggressive behavior.
Radiocarbon (14C) ages cannot provide absolutely dated chronologies for archaeological or paleoenvironmental studies directly but must be converted to calendar age equivalents using a calibration curve compensating for fluctuations in atmospheric 14C concentration. Although calibration curves are constructed from independently dated archives, they invariably require revision as new data become available and our understanding of the Earth system improves. In this volume the international 14C calibration curves for both the Northern and Southern Hemispheres, as well as for the ocean surface layer, have been updated to include a wealth of new data and extended to 55,000 cal BP. Based on tree rings, IntCal20 now extends as a fully atmospheric record to ca. 13,900 cal BP. For the older part of the timescale, IntCal20 comprises statistically integrated evidence from floating tree-ring chronologies, lacustrine and marine sediments, speleothems, and corals. We utilized improved evaluation of the timescales and location variable 14C offsets from the atmosphere (reservoir age, dead carbon fraction) for each dataset. New statistical methods have refined the structure of the calibration curves while maintaining a robust treatment of uncertainties in the 14C ages, the calendar ages and other corrections. The inclusion of modeled marine reservoir ages derived from a three-dimensional ocean circulation model has allowed us to apply more appropriate reservoir corrections to the marine 14C data rather than the previous use of constant regional offsets from the atmosphere. Here we provide an overview of the new and revised datasets and the associated methods used for the construction of the IntCal20 curve and explore potential regional offsets for tree-ring data. We discuss the main differences with respect to the previous calibration curve, IntCal13, and some of the implications for archaeology and geosciences ranging from the recent past to the time of the extinction of the Neanderthals.
Which factors explain variation in the gendered composition of governing cabinets? To address this question, we transpose the idea of proportionality between legislative seat shares and cabinet seats shares from studies of the partisan composition of cabinets to studies of the gender composition of cabinets. Gamson's law identifies a strong association between the proportion of legislative seats a party contributes to a governing coalition and the proportion of seats the party receives in the cabinet. We attempt to gender Gamson's law. We develop a theory of why a gendered Gamson's logic should apply to cabinets in parliamentary systems. We test our intuition via analysis of a new dataset covering 18 OECD parliamentary systems from 1990 through early 2019. We find a strong relationship between the gendered distribution of seats in governing parties’ parliamentary delegations and the gendered distribution of seats in the cabinets those parties create.
Opioid antagonists may mitigate medication-associated weight gain and/or metabolic dysregulation. ENLIGHTEN-2 evaluated a combination of olanzapine and the opioid antagonist samidorphan (OLZ/SAM) vs olanzapine for effects on weight gain and metabolic parameters over 24 weeks in adults with stable schizophrenia.
This phase 3, double-blind study (ClinicalTrials.gov: NCT02694328) enrolled adults 18–55 yo with stable schizophrenia, randomized 1:1 to once-daily OLZ/SAM or olanzapine. Co-primary endpoints were percent change from baseline in body weight and proportion of patients with ≥10% weight gain at week 24. Waist circumference and fasting metabolic parameters were also measured. Completers could enter a 52-week open-label safety extension.
561 patients were randomized: 550 were dosed, 538 had ≥1 post-baseline weight assessment, and 352 (64%) completed; 10.9% discontinued due to AEs. At week 24, least squares mean (SE) percent weight change from baseline was 4.21 (0.68)% with OLZ/SAM and 6.59 (0.67)% with olanzapine (difference, −2.38 [0.76]%; P=0.003). Fewer patients treated with OLZ/SAM (17.8%) had ≥10% weight gain vs olanzapine (29.8%; odds ratio=0.50; P=0.003). The change from baseline in waist circumference was significantly smaller with OLZ/SAM (P<0.001). Common AEs (≥10%) with OLZ/SAM and olanzapine were weight increased (24.8%, 36.2%), somnolence (21.2%, 18.1%), dry mouth (12.8%, 8.0%), and increased appetite (10.9%, 12.3%), respectively. Metabolic parameter changes were generally small and remained stable with long-term OLZ/SAM treatment.
OLZ/SAM treatment limited weight gain associated with olanzapine. Metabolic parameter changes were generally small, similar between groups over 24 weeks, and remained stable over an additional 52 weeks of open-label OLZ/SAM treatment.
Information technology has played a substantial role in healthcare since the 1960s. Its adoption has rapidly progressed. In 2007, only 2.2 percent of American hospitals had mature electronic medical record systems, while by 2017, 73.1 percent had mature systems. This chapter aims to inform readers about the historical drivers of health information technology (IT) adoption, as well as about the status of the industry today. The chapter provides detailed explanations of how health IT is being used by healthcare providers, payers, and consumers. Multistakeholder products and services are discussed, and the health information technology services industry is explored. The chapter concludes with a discussion of international adoption of health information technology, the size and growth of the industry, and the future of the health IT industry.
UK Biobank is a well-characterised cohort of over 500 000 participants including genetics, environmental data and imaging. An online mental health questionnaire was designed for UK Biobank participants to expand its potential.
Describe the development, implementation and results of this questionnaire.
An expert working group designed the questionnaire, using established measures where possible, and consulting a patient group. Operational criteria were agreed for defining likely disorder and risk states, including lifetime depression, mania/hypomania, generalised anxiety disorder, unusual experiences and self-harm, and current post-traumatic stress and hazardous/harmful alcohol use.
A total of 157 366 completed online questionnaires were available by August 2017. Participants were aged 45–82 (53% were ≥65 years) and 57% women. Comparison of self-reported diagnosed mental disorder with a contemporary study shows a similar prevalence, despite respondents being of higher average socioeconomic status. Lifetime depression was a common finding, with 24% (37 434) of participants meeting criteria and current hazardous/harmful alcohol use criteria were met by 21% (32 602), whereas other criteria were met by less than 8% of the participants. There was extensive comorbidity among the syndromes. Mental disorders were associated with a high neuroticism score, adverse life events and long-term illness; addiction and bipolar affective disorder in particular were associated with measures of deprivation.
The UK Biobank questionnaire represents a very large mental health survey in itself, and the results presented here show high face validity, although caution is needed because of selection bias. Built into UK Biobank, these data intersect with other health data to offer unparalleled potential for crosscutting biomedical research involving mental health.
Although apps are increasingly being used to support the diagnosis, treatment and management of mental illness, there is no single means through which costs associated with mental apps are being reimbursed. Furthermore, different apps are amenable to different means of reimbursement as not all apps generate value in the same way.
To provide insights into how apps are currently generating value and being reimbursed across the world, with a particular focus on the situation in the USA.
An international team performed secondary research on how apps are being used and on common pathways to remuneration.
The uses of apps today and in the future are reviewed, the nature of the value delivered by apps is summarised and an overview of app reimbursement in the USA and other countries is provided. Recommendations regarding how payments might be made for apps in the future are discussed.
Currently, apps are being reimbursed through channels with other original purposes. There may be a need to develop an app-specific channel for reimbursement which is analogous to the channels used for devices, drugs and laboratory tests.
Marine plastic pollution is a global environmental concern. With reference to approaches in contemporary archaeology, object biographies and psychology, this article presents the application of a novel participatory (‘World Café’) methodology that aims both to understand how marine plastic pollution occurs and to demonstrate the value of the approach for encouraging behaviour change. As proof of concept, the authors present the preliminary results of fieldwork involving local people in the Galápagos archipelago to demonstrate the benefits of an archaeological approach in developing new frameworks to help mitigate this critical environmental threat.
Studies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds.
We examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes.
In COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47–0.68%, p = 2.0 × 10−8–1.0 × 10−10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10−8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10−6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10−11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10−7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10−16).
AUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.
A consensus workshop on low-calorie sweeteners (LCS) was held in November 2018 where seventeen experts (the panel) discussed three themes identified as key to the science and policy of LCS: (1) weight management and glucose control; (2) consumption, safety and perception; (3) nutrition policy. The aims were to identify the reliable facts on LCS, suggest research gaps and propose future actions. The panel agreed that the safety of LCS is demonstrated by a substantial body of evidence reviewed by regulatory experts and current levels of consumption, even for high users, are within agreed safety margins. However, better risk communication is needed. More emphasis is required on the role of LCS in helping individuals reduce their sugar and energy intake, which is a public health priority. Based on reviews of clinical evidence to date, the panel concluded that LCS can be beneficial for weight management when they are used to replace sugar in products consumed in the diet (without energy substitution). The available evidence suggests no grounds for concerns about adverse effects of LCS on sweet preference, appetite or glucose control; indeed, LCS may improve diabetic control and dietary compliance. Regarding effects on the human gut microbiota, data are limited and do not provide adequate evidence that LCS affect gut health at doses relevant to human use. The panel identified research priorities, including collation of the totality of evidence on LCS and body weight control, monitoring and modelling of LCS intakes, impacts on sugar reduction and diet quality and developing effective communication strategies to foster informed choice. There is also a need to reconcile policy discrepancies between organisations and reduce regulatory hurdles that impede low-energy product development and reformulation.
Scholars and policy makers need systematic assessments of the validity of the measures produced by V-Dem. In Chapter 6, we present our approach to comparative data validation – the set of steps we take to evaluate the precision, accuracy, and reliability of our measures, both in isolation and compared to extant measures of the same concepts. Our approach assesses the degree to which measures align with shared concepts (content validation), shared rules of translation (data generation assessment), and shared realities (convergent validation). Within convergent validity, we execute two convergent validity tests. First, we examine convergent validity as it is typically conceived – examining convergence between V-Dem measures and extant measures. Second, we evaluate the level of convergence across coders, considering the individual coder and country traits that predict coder convergence. Throughout the chapter, we focus on three indices included in the V-Dem data set: polyarchy, corruption, and core civil society. These three concepts collectively provide a “hard test” for the validity of our data, representing a range of existing measurement approaches, challenges, and solutions.
This chapter sets forth the conceptual scheme for the V–Dem project. We begin by discussing the concept of democracy. Next, we lay out seven principles by which this key concept may be understood – electoral, liberal, majoritarian, consensual, participatory, deliberative, and egalitarian. Each defines a “variety“ of democracy, and together they offer a fairly comprehensive accounting of the concept as used in the world today. Next, we show how this seven-part framework fits into our overall thinking about democracy, including multiple levels of disaggregation – to components, subcomponents, and indicators. The final section of the chapter discusses several important caveats and clarifications pertaining to this ambitious taxonomic exercise.
This chapter recounts how a project of this scale came together and why it has succeeded. Five main factors were responsible for V–Dem’s success: timing, inclusion, deliberation, administrative centralization, and fund–raising. First, planning for V-Dem began at a time when both social scientists and practitioners were realizing that they needed better democracy measures. This made it possible to recruit collaborators and find funding. Second, the leaders of the project were always eager to expand the team to acquire whatever expertise they lacked and share credit with everyone who contributed. Third, the project leaders practiced an intensely deliberative decision–making style to ensure that all points of view were consulted and only decisions that won wide acceptance were adopted. Fourth, centralizing the execution of the agreed–upon tasks helped tremendously by streamlining processes and promoting standardization, documentation, professionalization, and coordination of a large number of intricate steps. Finally, successful fund–raising from a mix of both research foundations and bilateral and multilateral organizations has been critical.
In this chapter we focus on the measurement of five key principles of democracy – electoral, liberal, participatory, deliberative, and egalitarian. For each principle, we discuss (1) the theoretical rationale for the selected indicators, (2) whether these indicators are correlated strongly enough to warrant being collapsed into an index, and (3) the justification of aggregation rules for moving from indicators to components and from components to higher–level indices. In each section we also (4) highlight the top– and bottom–five countries on each principle of democracy in early (1812 or 1912) and late (2012) years of our sample period, as well as the aggregate trend over the whole time period 1789–2017 (where applicable). Finally, we (5) look at how the different principles are intercorrelated in order to assess the trade–offs involved between the conceptual parsimony achieved by aggregating to a few general concepts and the retention of useful variation permitted by aggregating less.
Four characteristics of V-Dem data present distinct opportunities and challenges for explanatory analysis: (1) the large number of democracy indicators (i.e., variables), (2) the measurement of concepts by multiple coders filtered through the V-Dem measurement model, (3) the large number of years in the data set, and 4) the ex ante potential for dependence across countries (generically referred to as spatial dependence). This chapter discusses 3 challenges and 10 opportunities that are implied by these characteristics. At the end of this chapter, we also discuss three assumptions that are implicit in most analyses of observational indicators of macro-features at the national level, which aim to draw conclusions about causal relationships.