Examining reports and policies on cognitive enhancement: approaches, rationale, and recommendations

The phenomenon of cognitive enhancement is attracting attention in bioethics literature and beyond, in public policy. In response, three bodies--the British Medical Association (BMA); the Commission de l'éthique de la Science et de la technologie (CEST) du Québec; the American Academy of Neurology (AAN)--have produced reports and guidance on this topic. To gain insights into different public policy approaches, rationales, and recommendations on the topic, we analyzed these reports in depth. We found convergence on the definition (with the exception of the CEST) of cognitive enhancement. However, we noted a lack of critical reflection with respect to the underlying rationale for developing these reports, i.e., that cognitive enhancement practices are rampant and represent major social changes. As it currently stands, cognitive enhancement is constituted in a way that challenges the creation of coherent and effective policy recommendations. However, policy makers should not simply wait for definitional consensus and hope that on balance the benefits turn out to be greater than the risks. Some components of cognitive enhancement could be reduced down to clearly identified policy targets to be further examined. Then, if appropriate, policy should be created that is, amongst other criteria, beneficial to the majority of the population.     

An efficient cross-validation algorithm for window width selection for nonparametric kernel regression

This paper presents an approach to cross-validated window width choice which greatly reduces computation time, which can be used regardless of the nature of the kernel function, and which avoids the use of the Fast Fourier Transform. This approach is developed for window width selection in the context of kernel estimation of an unknown conditional mean.     

Testing the Significance of Categorical Predictor Variables in Nonparametric Regression Models

In this paper we propose a test for the significance of categorical predictors in nonparametric regression models. The test is fully data-driven and employs cross-validated smoothing parameter selection while the null distribution of the test is obtained via bootstrapping. The proposed approach allows applied researchers to test hypotheses concerning categorical variables in a fully nonparametric and robust framework, thereby deflecting potential criticism that a particular finding is driven by an arbitrary parametric specification. Simulations reveal that the test performs well, having significantly better power than a conventional frequency-based nonparametric test. The test is applied to determine whether OECD and non-OECD countries follow the same growth rate model or not. Our test suggests that OECD and non-OECD countries follow different growth rate models, while the tests based on a popular parametric specification and the conventional frequency-based nonparametric estimation method fail to detect any significant difference.     

Simulation-Based Tests that Can Use Any Number of Simulations

Conventional procedures for Monte Carlo and bootstrap tests require that B, the number of simulations, satisfy a specific relationship with the level of the test. Otherwise, a test that would instead be exact will either overreject or underreject for finite B. We present expressions for the rejection frequencies associated with existing procedures and propose a new procedure that yields exact Monte Carlo tests for any positive value of B. This procedure, which can also be used for bootstrap tests, is likely to be most useful when simulation is expensive.     

Designing a non-inferiority study in kidney transplantation: a case study

In organ transplantation, placebo-controlled clinical trials are not possible for ethical reasons, and hence non-inferiority trials are used to evaluate new drugs. Patients with a transplanted kidney typically receive three to four immunosuppressant drugs to prevent organ rejection. In the described case of a non-inferiority trial for one of these immunosuppressants, the dose is changed, and another is replaced by an investigational drug. This test regimen is compared with the active control regimen. Justification for the non-inferiority margin is challenging as the putative placebo has never been studied in a clinical trial. We propose the use of a random-effect meta-regression, where each immunosuppressant component of the regimen enters as a covariate. This allows us to make inference on the difference between the putative placebo and the active control. From this, various methods can then be used to derive the non-inferiority margin. A hybrid of the 95/95 and synthesis approach is suggested. Data from 51 trials with a total of 17,002 patients were used in the meta-regression. Our approach was motivated by a recent large confirmatory trial in kidney transplantation. The results and the methodological documents of this evaluation were submitted to the Food and Drug Administration. The Food and Drug Administration accepted our proposed non-inferiority margin and our rationale.     

Examining Reports and Policies on Cognitive Enhancement: Approaches,Rationale, and Recommendations

The phenomenon of cognitive enhancement is attracting attention in bioethics literature and beyond, in public policy. In response, three bodies—the British Medical Association (BMA); the Commission de l'éthique de la Science et de la technologie (CEST) du Québec; the American Academy of Neurology (AAN)—have produced reports and guidance on this topic. To gain insights into different public policy approaches, rationales, and recommendations on the topic, we analyzed these reports in depth. We found convergence on the definition (with the exception of the CEST) of cognitive enhancement. However, we noted a lack of critical reflection with respect to the underlying rationale for developing these reports, i.e., that cognitive enhancement practices are rampant and represent major social changes. As it currently stands, cognitive enhancement is constituted in a way that challenges the creation of coherent and effective policy recommendations. However, policy makers should not simply wait for definitional consensus and hope that on balance the benefits turn out to be greater than the risks. Some components of cognitive enhancement could be reduced down to clearly identified policy targets to be further examined. Then, if appropriate, policy should be created that is, amongst other criteria, beneficial to the majority of the population.     

Ethical issues in the translation of social neuroscience: a policy analysis of current guidelines for public dialogue in human research

Social neuroscience and its potential implications create an interesting case study for examining human research ethics policies on the topic of public communication of research. We reviewed mainstream national and international human research ethics guidelines and policies on issues of public communication of research. Our analysis relied on five thematic nets to capture the interactions between research and the public: public understanding, knowledge translation, public participation, social outcomes, and dual use. Coverage of these topics is sparse and inconsistent in mainstream policies and guidelines. We identify three options to address these gaps and analyze their strengths and weaknesses.     

A Smooth Nonparametric,Multivariate, Mixed-Data Location-Scale Test

Abstract

A number of tests have been proposed for assessing the location-scale assumption that is often invoked by practitioners. Existing approaches include Kolmogorov–Smirnov and Cramer–von Mises statistics that each involve measures of divergence between unknown joint distribution functions and products of marginal distributions. In practice, the unknown distribution functions embedded in these statistics are typically approximated using nonsmooth empirical distribution functions (EDFs). In a recent article, Li, Li, and Racine establish the benefits of smoothing the EDF for inference, though their theoretical results are limited to the case where the covariates are observed and the distributions unobserved, while in the current setting some covariates and their distributions are unobserved (i.e., the test relies on population error terms from a location-scale model) which necessarily involves a separate theoretical approach. We demonstrate how replacing the nonsmooth distributions of unobservables with their kernel-smoothed sample counterparts can lead to substantial power improvements, and extend existing approaches to the smooth multivariate and mixed continuous and discrete data setting in the presence of unobservables. Theoretical underpinnings are provided, Monte Carlo simulations are undertaken to assess finite-sample performance, and illustrative applications are provided.     

Examining the relationship between Latinas' perceptions about what constitutes domestic violence and domestic violence victimization

Domestic violence is a serious issue for U.S. Latinas. Better understanding of the potential risk or protection that cultural perceptions about what constitutes domestic violence may convey can help strengthen interventions. Therefore, a convenience sample of 93 Latinas was surveyed about their current levels of domestic violence victimization, acculturation, and demographics, as well as about whether 5 behavioral scenarios constituted domestic violence. Hierarchical multiple regressions were performed to examine the relationships between the 5 perception items and domestic violence victimization. After adjusting for established risk factors, only viewing male partner stalking and female verbal aggression as domestic violence were significantly associated with decreased domestic violence victimization. Findings can be integrated into the development and implementation of culturally competent interventions targeting Latinas.     

A follow-up study of homeless women

This article presents an in-depth analysis of the changes observed in 25 homeless women with drug and alcohol abuse problems participating in a case management program. Participation in the program ranged from 6 to 44 months. Thirty-two percent of all participants' situations were considered to have improved, while 20% remained stable. Less improvement was noted in the situations of women followed for 3 years or more (14.3% improved, 28.6% stable). Domains showing the most improvement were housing, financial situation, and substance abuse. Deterioration was primarily attributable to physical and mental health problems. These findings could indicate that although a case management program can initially contribute to improving the living conditions of its clients, acquisitions are difficult to maintain over an extended period. Health and substance abuse play a crucial role in the deterioration process.