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I evaluate two contractualist approaches to the ethics of risk: mutual constraint and the probabilistic, ex ante approach. After explaining how these approaches address problems in earlier interpretations of contractualism, I object that they fail to respond to diverse risk preferences in populations. Some people could reasonably reject the risk thresholds associated with these approaches. A strategy for addressing this objection is considering individual risk preferences, similar to those Buchak discusses concerning expected-utility approaches to risk. I defend the risk-preferences-adjusted (RISPREAD) contractualist approach, which calculates a population’s average risk preference and permits risk thresholds below that preference, only.
To provide insights into the attributes of health-related quality of life (HRQoL) research within the context of economic evaluations for a potential national health technology assessment process in South Africa, and make evidence generation recommendations.
A systematic review was conducted in January 2019 using Medline, the Web of Science (WoS) Core Collection and the South African SciELO collection via the WoS Platform, and in the Cochrane Library. No time restrictions were applied. Duplicate records were removed before first- and second-pass screening by two reviewers working independently.
The review identified 123 publications representing 104 studies since the first-published article appeared in 1996. Only eight studies were randomized controlled trials, most were cross-sectional (n = 54). The EQ-5D, SF-36, and WHOQOL-BREF were the most used HRQoL instruments (n = 35, n = 23, and n = 10, respectively). Instruments were frequently administered in multiple languages, reflecting the cultural groups in which the study was conducted, with the English version of instruments used most often. Studies were predominantly conducted within the public health sector (n = 67), in the Western Cape province (n = 46), in adults (n = 92) and people with HIV (n = 24).
South African specific HRQoL studies have been conducted in a range of settings and populations using mostly generic HRQoL instruments in multiple languages. These studies may provide generalizable, real-world data due to their observational nature. However, more comparative and longitudinal studies should be conducted as this is preferred for economic evaluations and patient, disease, and treatment characteristics should be reported in full.
There are several techniques for estimating health state utility values, each of which presents pros and cons in the context of rare diseases (RDs). Direct approaches (e.g. standard gamble and time trade-off) may be too demanding for patients with RDs, since most of them affect young children or cause cognitive impairment. The alternatives are using “vignettes” that describe hypothetical health states for the general public, which may not reflect the heterogeneous manifestations of RDs, or multi-attribute utility instruments (i.e. indirect techniques), such as EQ-5D, which may be less sensitive in capturing the specificities of RDs. The “rule of rescue” approach is a promising alternative in RDs, since it prioritizes identifiable patients with life-threatening or disabling conditions. However, it raises measurement challenges and ethical issues. Furthermore, the literature reports on relevant implications of choosing a technique over others for health technology assessment, which should be considered in relation to individual RDs.
Chapter 3 explores the promises and contradictions inherent in the information drawn from these local and global knowledge networks. There were tensions that were never quite resolved between the production of locally relevant knowledge that rejected theoretical approaches and a global intellectual movement that praised universal knowledge. The Economic Society responded to this by carefully negotiating the sources of knowledge which it received from its networks, especially on the topics of natural history and medical botany, and building up its own epistemologies and definitions of practical Enlightenment that made the local applicability of any information the ultimate test of its value. Frameworks of knowledge with universal aspirations, such as Linnaean taxonomy, were not welcome when local descriptions would be more translateable within Central America. I argue that these stubbornly local conceptualisations of knowledge became problematic when a comparison with other places was required, for instance in the context of attempting to export plants from Guatemala to other places, and in debating the merits of plantain trees with scholars in other parts of the empire.
As to the sources of ius in interregno, both stable and evolving norms applicable to TG should be considered. Individual customary rules are germinating in relation to TG but not in isolation from the existing principles of self-determination and non-intervention. As to the evolving part of ius in interregno, TI may testify to the emergence of custom. Both domestic laws, unilateral declarations, intrastate agreements or international conventions can be taken into account. Socialisation explains why these and other instruments incorporate TG-relevant patterns. The effects of dominant discourse and mimesis entice a common (legal) culture accounting for both the (socialised) origin of, and (legal) compliance with, specific behavioural patterns. This fertile breeding ground also explains why such patterns are formalised through the adoption of TI, which may or may not be valid on the domestic plane: compliance with international law is expected regardless of how the transition was triggered.
A preponderance of theories have been adopted to identify the determinants of behavior. Despite claims of generalizability, research applying these theories has identified gaps or boundary conditions that delimit their application. Theory integration provides one means to address these gaps. This chapter outlines the contribution of integrated theories to advancing knowledge of behavior change. Four approaches to theory integration are identified and summarized: additional constructs, core constructs, expert consensus, and utility-based approaches. Theory integration is often motivated by the need to reduce redundancy in constructs across existing theories and improve their predictive power to arrive at optimally comprehensive, parsimonious, explanations of behavior. Examples of integrated theories are provided and how they have contributed to theory development outlined. Behavior change interventions based on integrated theory comprise multiple techniques that target change in the constructs that set the integrated theory apart from its constituent theories. While some interventions based on integrated theories have demonstrated efficacy in changing behavior, future research on integrated theories needs to adopt factorial designs that independently target change in integrated theory constructs. Such research will demonstrate the independent and interactive effects of techniques based on the integrated theory on behavior and on measures of the targeted theory construct.
This chapter provides an overview of economic and behavioral economic approaches to behavior change. The chapter begins with a description of the traditional or neoclassical economic view of decision-making using expected utility theory as its basis. Attempts by an external party (e.g., a government or agency) to change behavior are viewed as justifiable in a limited number of circumstances, such as when there are externalities or coordination failures. When behavior change is warranted, neoclassical economics has focused on four options: provide information, increase incentives, reduce prices, or increase subsidies, or impose regulations. To be successful, the approach must change the net benefits of the promoted behavior. The chapter then describes the rationale behind behavioral economic approaches to behavior change, emphasizing the role that “nudges” play in behavior change. Examples are provided of common heuristics and associated decision errors that can result, and how nudges are designed to overcome these decision errors. The underlying rationale and steps for developing nudges are summarized. Current evidence suggests that some nudges can be effective in changing behavior, but more research is needed to demonstrate the effectiveness of many nudge strategies. The chapter concludes with a discussion of the likely long-term impact of nudges in the field of behavior change.
Defined contribution (DC) pension plans have been gaining ground in the last 10–20 years as the preferred system for many countries and other agencies, both private and public. The central question for a DC plan is how to invest in order to reach the participant's retirement goals. Given the financial illiteracy of the general population, it is common to offer a default policy for members who do not actively make investment choices. Using data from the Chilean system, we discuss an investment model with fixed contribution rates and compare the results with the existing default policy under multiple objectives. Our results indicate that the Chilean default policy has good overall performance, but specific closed-loop policies have a higher probability of achieving desired retirement goals and can reduce the expected shortfall at retirement.
This chapter presents a staple of Feature Engineering: the automatic reduction of features, either by direction selection or by projection to a smaller feature space. Central to Feature Engineering are efforts to reduce the number of features, as uninformative features bloat the ML model with unnecessary parameters. In turn, too many parameters then either produces suboptimal results, as they are easy to overfit, or require large amounts of training data. These efforts are either by explicitly dropping certain features (feature selection) or mapping the feature vector, if it is sparse, into a lower, denser dimension (dimensionality reduction). There are also cover some algorithms that perform feature selection as part of their inner computation (embedded feature selection or regularization). Feature selection takes the spotlight within Feature Engineering due to its intrinsic utility for Error Analysis. Some techniques such as feature ablation using wrapper methods are used as the starting step before a feature drill down. Moreover, as feature selection helps build understandable models, it intertwines with Error Analysis as the analysis profits from such understandable models.
We study networks of interacting queues governed by utility-maximising service-rate allocations in both discrete and continuous time. For finite networks we establish stability and some steady-state moment bounds under natural conditions and rather weak assumptions on utility functions. These results are obtained using direct applications of Lyapunov–Foster-type criteria, and apply to a wide class of systems, including those for which fluid-limit-based approaches are not applicable. We then establish stability and some steady-state moment bounds for two classes of infinite networks, with single-hop and multi-hop message routes. These results are proved by considering the infinite systems as limits of their truncated finite versions. The uniform moment bounds for the finite networks play a key role in these limit transitions.
This paper defends revealed preference theory against a pervasive line of criticism, according to which revealed preference methodology relies on appealing to some mental states, in particular an agent’s beliefs, rendering the project incoherent or unmotivated. I argue that all that is established by these arguments is that revealed preference theorists must accept a limited mentalism in their account of the options an agent should be modelled as choosing between. This is consistent both with an essentially behavioural interpretation of preference and with standard revealed preference methodology. And it does not undermine the core motivations of revealed preference theory.
This is a commentary on Miller and Widiger’s (this volume) excellent chapter on personality disorders from the perspective of five factor personality models. In this commentary, the author discusses several issues of importance as the field moves forward with respect to dimensional personality-based diagnosis of personality disorder, most of which center on clinical application. First, a question is posed as to what level of personality abstraction is necessary for optimal formulation of personality disorders; although most five-factor models are established at the domain level, proposed personality disorder trait profiles appear at a much narrower facet level for which less scholarly consensus exist. Moreover, the author calls for more research into determining at what threshold on various trait dimensions clinical dysfunction begins to emerge. He also notes that most assessment devices currently available for dimensional trait models do not meet the Standards for Educational and Psychological Testing, which needs to be rectified prior to clinical application. Such tests also need to include validity scales to assess for noncredible responding. Finally, the author recommends that proposed personality inventories for these dimensional personality models show incremental utility above and beyond already well-established clinical assessment instruments.
The purpose of this rejoinder is to emphasize several important areas of future research that were mentioned by one or both commentaries. First, the authors discuss issues related to multi-source assessment, such as the importance of further research on informant bias, and argue that the information gleaned from multiple sources is worth the added assessment burden. Second, they underscore the importance of longitudinal assessment both in capturing the treatment-relevant within-person processes through which personality pathology unfolds, as well as tracking therapeutic progress. They assert that a given measure’s ability to reliably and validly measure change over time should be considered when evaluating its clinical utility. Finally, they emphasize the need for greater attention to clinical utility of dimensional PD assessment measures.
The authors of this commentary aim to expand on particular points covered in the chapter by Evans, Williams and Simms, and discuss other issues that were not covered there. First, they discuss future research directions for, and the potential utility of, multisource assessments of personality pathology. Second, they emphasize the need for aspects of clinical utility within some of the reviewed measures (e.g., norms, validity scales). Third, they discuss the need for further examinations into the feasibility and utility of longitudinal assessments of personality pathology (e.g., dynamics in the context of treatment). Fourth, they describe two recent measures of personality pathology that warrant further validation. Lastly, they emphasize the need for a conceptual and measurement-based consensus regarding the multidimensional nature of personality pathology as a whole.
The purpose of this chapter is to review the current state of the dimensional assessment of personality disorder (PD). The first part of the chapter serves as a review of the most well-established and commonly used measures of maladaptive personality traits. Measures that assess the psychosocial impairment associated with personality pathology also are reviewed. Areas of discontinuity among these measures (e.g., theoretical origin, method of scale construction, degree of correspondence with well-known trait dimensions, attention received in the empirical literature, degree of bipolarity of underlying dimensions) are emphasized, and the clinical utility of measures is evaluated. The second part of the chapter focuses on several controversial issues with which the field of dimensional PD assessment now is grappling. These issues include (a) the psychometric distinction of personality traits from personality functioning, (b) the incremental utility of adaptive trait assessment, (c) the question of maladaptive trait bipolarity, (d) facet-level differences versus domain-level similarity across competing PD trait models, and (e) the value of multi-source assessment.
Evans et al. (this volume) reviewed prominent dimensional measures of personality, discussed the clinical usefulness of these measures, and provided an overview of personality assessment issues. This commentary focuses on the clinical utility and applications of personality traits and assessment, as well as factors relevant to bridging the research-to-practice gap. In order to adequately disseminate and implement evidence-based personality assessments into practice, personality pathology researchers should be taking active steps to move the empirical base (e.g., validated models of personality, evidence-based assessments, aspects of clinical utility) into application. The process of translating these traits and measures into practice may include assessing barriers to use among practitioners, addressing matters of acceptability and feasibility, and providing training and consultation to practitioners. The authors review benefits of including adaptive traits in assessment and practice (e.g., assist with collaborative treatment planning, decrease stigma), provide commentary on the incremental utility of dysfunction including the use of external correlates, and outline the importance of bipolarity of dimensional trait measures.
Because personality disorders are seen as highly complex there is a natural tendency to describe them in convoluted and multifaceted language. Novelists and playwrights have done this for hundreds of years; it is not the task of nosologists to repeat it. Instead we need a simpler classification of a very common disorder, as even if we lose some of the subtlety of the condition this is more than compensated by greater use and understanding. We also need to pay more attention to science rather than to clinical intuition in our terminology. Both the DSM-5 alternative model and the new ICD-11 classification have moved towards a dimensional system of classification that should help in selecting treatment and diluting the pervasive and unhelpful spread of the grossly heterogeneous condition, horderline. This has hindered progress and made us forget the many parts of personality disorder that are not in any way connected to the borderline spectrum and yet which are highly relevant pathologies.
The use of dimensional personality traits with explicit ties to general or normative personality has gone mainstream with instantiation in the most recent version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the soon to be released 11th revision of the International Classification of Diseases (ICD-11). Much of the theoretical and empirical work that supports the transition to dimensional trait-based models of personality disorder has used the prominent five-factor model of personality to do so, which suggests that five basic dimensions capture much of the important and reliable personality variance: neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. This chapter reviews this literature and demonstrates how general and pathological five-factor models of personality are parsimonious, valid, and useful. The authors believe that the use of such models for the diagnosis of personality disorder represents a much needed and empirically supported movement to integrate normative and pathological personality.
This paper discusses the need for a health economics perspective and some of the central methodological issues raised by economic appraisals, including cost-effectiveness and cost-utility analyses. It illustrates how cost-effectiveness studies can inform policy and practice decisions concerning the treatment of schizophrenia, focusing on five generic evaluation questions commonly raised. Examples are drawn from recent and current UK research.
This paper provides a brief overview of issues to consider in evaluating patient benefit from health care. Different types of measures are described and it is noted that the choice of measure is dependent upon the purpose of the study. The cost-utility approach to evaluation is discussed in more detail. This approach is often criticised but it raises important issues in medical decision-making and has considerable potential in the evaluation of patient benefit from health care.