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Placing evolutionary events in the context of geological time is a fundamental goal in paleobiology and macroevolution. In this Element we describe the tripartite model used for Bayesian estimation of time calibrated phylogenetic trees. The model can be readily separated into its component models: the substitution model, the clock model and the tree model. We provide an overview of the most widely used models for each component and highlight the advantages of implementing the tripartite model within a Bayesian framework.
The law of trusts and estates has a gendered history that helps to put Estate of Myers into context. Under the law of England, adopted by most states in this country, husbands and wives were deemed to be one person: the husband.
Simulations are playing an increasingly important role in paleobiology. When designing a simulation study, many decisions have to be made and common challenges will be encountered along the way. Here, we outline seven rules for executing a good simulation study. We cover topics including the choice of study question, the empirical data used as a basis for the study, statistical and methodological concerns, how to validate the study, and how to ensure it can be reproduced and extended by others. We hope that these rules and the accompanying examples will guide paleobiologists when using simulation tools to address fundamental questions about the evolution of life.
The pan-Canadian Oncology Drug Review (pCODR) evaluates new cancer drugs for public funding recommendations. While pCODR's deliberative framework evaluates overall clinical benefit and includes considerations for exceptional circumstances, rarity of indication is not explicitly addressed. Given the high unmet need that typically accompanies these indications, we explored the impact of rarity on oncology HTA recommendations and funding decisions.
We examined pCODR submissions with final recommendations from 2012 to 2017. Incidence rates were calculated using pCODR recommendation reports and statistics from the Canadian Cancer Society. Indications were classified as rare if the incidence rate was lower than 1/100,000 diagnoses, a definition referenced by the Canadian Agency for Drugs and Technologies in Health. Each pCODR final report was examined for the funding recommendation/justification, level of supporting evidence (presence of a randomized control trial [RCT]), and time to funding (if applicable).
Of the ninety-six pCODR reviews examined, 16.6 percent were classified as rare indications per above criteria. While the frequency of positive funding recommendations were similar between rare and nonrare indication (78.6 vs. 75 percent), rare indications were less likely to be presented with evidence from RCT (50 vs. 90 percent). The average time to funding did not differ significantly across provinces.
Rare indications appear to be associated with weaker clinical evidence. There appears to be no association between rarity, positive funding recommendations, and time to funding. Further work will evaluate factors associated with positive recommendations and the real-world utilization of funded treatments for rare indications.
It is not clear to what extent associations between schizophrenia, cannabis use and cigarette use are due to a shared genetic etiology. We, therefore, examined whether schizophrenia genetic risk associates with longitudinal patterns of cigarette and cannabis use in adolescence and mediating pathways for any association to inform potential reduction strategies.
Associations between schizophrenia polygenic scores and longitudinal latent classes of cigarette and cannabis use from ages 14 to 19 years were investigated in up to 3925 individuals in the Avon Longitudinal Study of Parents and Children. Mediation models were estimated to assess the potential mediating effects of a range of cognitive, emotional, and behavioral phenotypes.
The schizophrenia polygenic score, based on single nucleotide polymorphisms meeting a training-set p threshold of 0.05, was associated with late-onset cannabis use (OR = 1.23; 95% CI = 1.08,1.41), but not with cigarette or early-onset cannabis use classes. This association was not mediated through lower IQ, victimization, emotional difficulties, antisocial behavior, impulsivity, or poorer social relationships during childhood. Sensitivity analyses adjusting for genetic liability to cannabis or cigarette use, using polygenic scores excluding the CHRNA5-A3-B4 gene cluster, or basing scores on a 0.5 training-set p threshold, provided results consistent with our main analyses.
Our study provides evidence that genetic risk for schizophrenia is associated with patterns of cannabis use during adolescence. Investigation of pathways other than the cognitive, emotional, and behavioral phenotypes examined here is required to identify modifiable targets to reduce the public health burden of cannabis use in the population.
In their chapter, Bach and Presnall-Shvorin (this volume) introduce guidelines for incorporating empirically-driven trait models of personality pathology, codified in the DSM-5 and ICD-11, into therapeutic practice. Though the authors of this commentary are supportive of the effort to bridge research with clinical practice, they suggest that a mechanistic model which accounts for personality processes underlying descriptive traits could offer greater precision than traits alone. Furthermore, they argue that clinical dysfunction can only be meaningfully defined and treated with an understanding of dynamic, contextualized aspects of personality. To illustrate how a mechanistic model could complement and extend Bach and Presnall’s recommendations, the authors present a case conceptualization using cybernetic theory. Finally, they review how idiographic data gleaned from ambulatory assessment methods provide insight into pathological processes ideal for therapeutic intervention. To achieve a generalizable approach flexible enough to adapt to the individual, they encourage the development of treatment models that go beyond traits to mechanistically link stable and dynamic personality features into a unified framework.
To test the psychometric properties of the Quality Indicator for Rehabilitative Care (QuIRC), refine the toolkit and compare results with service user experiences.
Following the initial development of the toolkit, it was translated into the languages of the partner countries and piloted. It was then refined to maximize a) its inter-rater reliability, b) its usability and c) its ability to deliver assessments relevant to each country's established systems of change at local, regional and national level. Managers of participating units were re-interviewed using the refined tool. QuIRC scores were compared against service users’ quality of life, autonomy, experiences of care and markers of recovery to assess whether the QuIRc could provide a proxy-assessment of the unit's promotion of service users’ autonomy and Recovery.
The tool was piloted in 20 units in each country (a total of 200 units). Inter-rater reliability was assessed using intra-class correlations and Cohen's Kappa coefficients. Factors with low reliability or extreme response biases were dropped. Remaining items were subjected to an exploratory factor analysis to test domain allocation and improve internal consistency. QuIRC domain ratings were compared by country and facility type and with service user assessments. The QuIRC was found to have high reliability, to be easy to use and there was high correlation between domain ratings and service users’ ratings.
The European Commission's Green Paper on Mental Health highlighted the need to improve the social inclusion, human rights and dignity, of mentally ill people. It recognised evidence for improved quality of life and social inclusion provided by deinstitutionalization of services. This study, funded by the EC, explores the relationship between unit characteristics and quality of care, as recorded by the Quality Indicator for Rehabilitative Care (QuIRC).
QuIRC's seven domain scores were analyzed for associations with unit, patient and staff variables, using linear regression.
Unit location affected Living Environment (LE) domain scores. Size of units was associated with all domains apart from Human Rights (HR). Resident characteristics showed single gender, percentage of lower functioning residents, both affected some domains. Staff intensity scores were not associated with any domain of care, but specific disciplines affected particular domain scores Lower quartile results across domains suggest that 25% of European units studied score less than 50% on individual domains’ quality scores.
Results suggest the preferability of residential rehabilitation units that are city-based, in the community, smaller in size, and have both men and women residents; where the proportions of detained patients, and patients with a high level of need, are low; and where the staff group includes an employment specialist and a psychologist, but does not include a social worker or a psychiatrist. Average unit performances for different countries in Europe need to be established and considered in developing preliminary quality targets to be reached in particular timescales.
To identify the specific components of care that key stakeholders in ten European countries at different stages of de-institutionalization regard as most important in promoting recovery in this group; to measure consensus between and across stakeholder groups and countries; and to develop a conceptual framework of ‘domains’ of care.
Each participating country completed a series of conventional three-round Delphi exercises with four separate panels of experts; service users, mental health professionals, carers and advocates. In Round 1 an initial open question asked respondents to identify up to 10 components of care they considered most important in promoting recovery. In Round 2 these ideas were fed back to the group and rated on a 5-point scale. In Round 3 the group re-rated the components in the light of information about the whole group's response. Components achieving high importance rankings and high consensus were grouped into domains.
The 40 participating panels generated around 4,000 separate items of care. From these, eleven broad domains of recovery practice were identified. Results will be presented descriptively to show the domains and components of care considered to be most important to recovery, and to show consensus within and across countries, and between stakeholder groups. It will be seen that there was generally high consensus between groups and countries but some modest differences in priorities.
Delphi methodology is useful in eliciting and evaluating different perspectives on recovery-based practice. Strengths and weaknesses of the approach will be discussed.
Animal experimental studies suggest that 5-HT4 receptor activation holds promise as a novel target for the treatment of depression and cognitive impairment. 5-HT4 receptors are post-synaptic receptors that are located in striatal and limbic areas known to be involved in cognition and mood. Consistent with this, 5-HT4 receptor agonists produce rapid antidepressant effects in a number of animal models of depression, and pro-cognitive effects in tasks of learning and memory. These effects are accompanied by molecular changes, such as the increased expression of neuroplasticity-related proteins that are typical of clinically useful antidepressant drugs. Intriguingly, these antidepressant-like effects have a fast onset of their action, raising the possibility that 5-HT4 receptor agonists may be a particularly useful augmentation strategy in the early stages of SSRI treatment. Until recently, the translation of these effects to humans has been challenging. Here, we review the evidence from animal studies that the 5-HT4 receptor is a promising target for the treatment of depression and cognitive disorders, and outline a potential pathway for the efficient and cost-effective translation of these effects into humans and, ultimately, to the clinic.
Most of what clinical psychology concerns itself with is directly unobservable. Concepts like neuroticism and depression, but also learning and development, represent dispositions, states, or processes that must be inferred and cannot (currently) be directly measured. Latent variable modeling, as a statistical framework, encompasses a range of techniques that involve estimating the presence and effect of unobserved variables from observed data. This chapter provides a nontechnical overview of latent variable modeling in clinical psychology. Dimensional latent variable models are emphasized, although categorical and hybrid models are touched on briefly. Challenges with specific models, such as the bifactor model are discussed. Examples draw from the psychopathology literature.