Technology assessment and the 'ethical matrix'

This paper explores the usefulness of the 'ethical matrix', proposed by Ben Mepham, as a tool in technology assessment, specifically in food ethics. We consider what the matrix is, how it might be useful as a tool in ethical decision-making, and what drawbacks might be associated with it. We suggest that it is helpful for fact-finding in ethical debates relating to food ethics; but that it is much less helpful in terms of weighing the different ethical problems that it uncovers. Despite this drawback, we maintain that, with some modifications, the ethical matrix can be a useful tool in debates in food ethics. We argue that useful modifications might be to include future generations amongst the stakeholders in the matrix, and to substitute the principle of solidarity for the principle of justice. Electronic Publication     

Alcohol Measures and Terms: A Perfect Storm for Chronic Confusion

Abstract

Members in the prevention and treatment fields continue to examine how to most effectively assess and label high volume alcohol consumption. Terms such as “binge” drinking have resulted in considerable controversy and debate. Conventionally the criteria for assessing high-risk drinking includes: five or drinks for men and four or more drinks for women during a sitting/event/occasion within the previous two weeks. Several standardized instruments simply use the cut off for high-risk drinking as five or more drinks and do not include the gender variable when defining this behavior. Both of these measures have undergone criticism for not including a more specific time element. Yet asking respondents to recall specific time frames from a night of heavy drinking may also compromise validity. Further the 5+/4+ or 5+ drinking criterion does not adequately assess intoxication levels or more extreme levels of alcohol consumption. A variety of special measures and terms have been created to capture heavy drinking behaviors and ritualistic behavior. Researchers and practitioners may benefit by using different measures and terms based on context and their specific prevention goals.     

Cognitions and Distress in Caregivers after Their Child's Sexual Abuse Disclosure

The impact of child sexual abuse on children is well documented, but few studies have examined the impact of a child's sexual abuse disclosure on maternal caregivers. The studies that have been conducted suggest that parental response postdisclosure is variable. The present study examined the association between maternal attributions and abuse-specific cognitions with depression and trauma symptoms postdisclosure. Participants included 68 nonoffending maternal caregivers of children between the ages of 3 and 17 years who experienced child sexual abuse. Findings indicated that caregivers' abuse-specific cognitions were the best predictor of self-reported symptoms of depression after controlling for general negative attributions. These findings suggest that in order to reduce caregivers' distress and to enhance their support of their children, it is important to assess and treat caregivers' abuse-specific cognitions.

     

A new perspective on quality

The U.S. health care sector consumes nearly 13 percent of our nation's gross national product, $800 billion annually. Our nation allocates the highest amount per capita to health care in the world. Yet many measures of health care outcomes from these expenditures are inferior to other developed nations. The American health care system costs too much, excludes too many, fails too often, contains much excessive and inappropriate care, and knows too little about the effectiveness of the things it does. The purpose of this article is to discuss current payers' perspectives on the potential for quality improvement in the U.S. health care system.     

Predicting Home Run Production in Major League Baseball Using a Bayesian Semiparametric Model

This article attempts to predict home run hitting performance of Major League Baseball players using a Bayesian semiparametric model. Following Berry, Reese and Larkey we include in the model effects for era of birth, season of play, and home ball park. We estimate performance curves for each player using orthonormal quartic polynomials. We use a Dirichlet process prior on the unknown distribution for the coefficients of the polynomials, and parametric priors for the other effects. Dirichlet process priors are useful in prediction for two reasons: (1) an increased probability of obtaining more precise prediction comes with the increased flexibility of the prior specification, and (2) the clustering inherent in the Dirichlet process provides the means to share information across players. Data from 1871 to 2008 were used to fit the model. Data from 2009 to 2016 were used to test the predictive ability of the model. A parametric model was also fit to compare the predictive performance of the models. We used what we called “pure performance” curves to predict future performance for 22 players. The nonparametric method provided superior predictive performance.