Effect of warning placement on the information processing of college students reading an OTC drug facts panel

Objective: To compare three over-the-counter (OTC) Drug Facts panel versions for information processing optimization among college students.

Participants: University of Houston students (N = 210) participated in a cross-sectional survey from January to May 2010.

Methods: A current FDA label was compared to two experimental labels developed using the theory of CHREST to test information processing by re-positioning the warning information within the Drug Facts panel. Congruency was defined as placing like information together. Information processing was evaluated using the OTC medication Label Evaluation Process Model (LEPM): label comprehension, ease-of-use, attitude toward the product, product evaluation, and purchase intention.

Results: Experimental label with chunked congruent information (uses-directions-other information-warnings) was rated significantly higher than the current FDA label and had the best average scores among the LEPM information processing variables.

Conclusion: If replications uphold these findings, the FDA label design might be revised to improve information processing.     

A three-city comparison of drug use and drug use before sex among young men who have sex with men in the United States

High rates of drug use have been documented among young men who have sex with men (YMSM). However, updated prevalence data are needed to understand current trends, especially for drug use before sex. We used baseline data from an HIV prevention trial to examine demographic differences in drug use and drug use before sex among YMSM in Atlanta, Chicago, and New York City. Marijuana was the most commonly used drug, but alkyl nitrites (“poppers”), cocaine, and Ecstasy were also commonly used. Drug use was more prevalent among older and White YMSM, and it was similar across cities, although use of poppers and polydrug use were more common in New York City. Our data generally support national prevention efforts.     

Challenging the techno-politics of anonymity: the case of cryptomarket users

Anonymity is treated as a problem of governance that can be subject to technical resolution. We use the example of the darknet to critically examine this approach. We explore the background assumptions that have been made about anonymity as a quality of social life. We conceive of anonymity as a way of engaging and maintaining social relationships in an anonymous mode. We draw on a study of darknet ‘cryptomarket’ users who mainly use the darknet to buy and sell illicit drugs, discuss drug quality and share information on safe and effective use. We identify the personal satisfaction that comes from interacting anonymously online, the challenges this represents for maintaining trusted interactions and how they are overcome, and the combination of technology and action involved in maintaining anonymity. We argue that attempts to promote de-anonymising norms and technology are based on an erroneous understanding of what anonymity is.     

Appalachian Women’s Use of Substance Abuse Treatment: Examining the Behavioral Model for Vulnerable Populations

The Gelberg–Andersen Behavioral Model for Vulnerable Populations was applied to understand vulnerable Appalachian women’s (N = 400) utilization of addiction treatment. A secondary data analysis included multiple multivariate analyses. The strongest correlates of treatment utilization included ever injecting drugs (OR = 2.77), limited availability of substance abuse treatment facilities (OR = 2.03), and invalidated violence abuse claims (OR = 2.12). This study contributes theory-driven research to the greater social work addiction literature by confirming that vulnerable domains related to substance abuse treatment utilization warrant unique considerations compared to nonvulnerable domains. Findings also highlight the importance of understanding the unique role that cultural factors play in treatment utilization among Appalachian women. Inferences relevant to clinicians and policymakers are discussed.     

The Race and Class Privilege of Motherhood: TheNew York Times Presentations of Pregnant Drug‐Using Women1

Prior research has examined race and class bias embedded in media presentations of pregnant drug users; however, this past research is limited in identifying biases because it focuses on single substances—primarily crack cocaine. I build on this work by conducting a comparative analysis of more than 15 years worth of New York Times articles on three drugs (crack cocaine, alcohol, and tobacco) used during pregnancy. These three drugs have varying levels of deleterious effects on fetal development and infant health, as well as varying levels of use by poor and minority women. Because of this variation, I am able to assess whether media coverage of pregnant drug‐using women is proportional to the documented adverse consequences of specific drugs or, rather, whether media coverage is higher and more negative for poor and minority pregnant women regardless of the degree of adverse health consequences associated with the specific drug used. Through this analysis, I demonstrate that the prevalence and framing of news stories about pregnant drug‐using women has little to do with protecting the health of children. Rather, concern for children is a rhetorical tool used to define poor and minority women as bad mothers and blame them for contemporary changes in families.     

高效液相色谱法分离手性药物扑尔敏

液相色谱法广泛应用于手性分离,而纤维素是一类常用的色谱固定相.本文制备了醋酸纤维素液相色谱固定相,并采用湿法装柱,考察了柱性能,并对不同进样量的扑尔敏进行了拆分试验,结果表明:当进样量为0.4μL时,可以达到基线分离;当进样量为0.5μL时,样品过载,只能部分分离.     

The Community Context of Family Structure and Adolescent Drug Use

Using data from the National Educational Longitudinal Study (NELS), this article investigates a number of hypotheses used to explain the relationship between family structure and adolescent drug use. In particular, using linked community‐level data, an explicit examination of hypotheses drawn from a community‐context model is conducted. These hypotheses posit that the impact of family structure on adolescent behavior is, in part, explained by the different types of communities within which families reside and that community characteristics moderate the impact of family structure on drug use. The results of multilevel regression models fail to support these hypotheses; adolescents who reside in single‐parent or stepparent families are at heightened risk of drug use irrespective of community context. Moreover, adolescents who reside in single father families are at risk of both higher levels of use and increasing use over time. A significant community‐level effect involves jobless men: Adolescents are at increased risk of drug use if they reside in communities with a higher proportion of unemployed and out‐of‐workforce men.     

Computational Comparison Studies of Quadratic Assignment Like Formulations for the In Silico Sequence Selection Problem in De Novo Protein Design

In this paper an O(n²) mathematical formulation for in silico sequence selection in de novo protein design proposed by Klepeis et al. (2003, 2004), in which the number of additional variables and linear constraints scales with the square of the number of binary variables, is compared to three O(n) formulations. It is found that the O(n²) formulation is superior to the O(n) formulations on most sequence search spaces. The superiority of the O(n²) formulation is due to the reformulation linearization techniques (RLTs), since the O(n²) formulation without RLTs is found to be computationally less efficient than the O(n) formulations. In addition, new algorithmic enhancing components of RLTs with inequality constraints, triangle inequalities, and Dead-End Elimination (DEE) type preprocessing are added to the O(n²) formulation. The current best O(n²) formulation, which is the original formulation from Klepeis et al. (2003, 2004) plus DEE type preprocessing, is proposed for in silico sequence search. For a test problem with a search space of 3.4×10⁴⁵ sequences, this new improved model is able to reduce the required CPU time by 67%.     

Fitting models for the joint action of two drugs using SAS

Combinations of drugs are increasingly being used for a wide variety of diseases and conditions. A pre-clinical study may allow the investigation of the response at a large number of dose combinations. In determining the response to a drug combination, interest may lie in seeking evidence of 'synergism', in which the joint action is greater than the actions of the individual drugs, or of 'antagonism', in which it is less. Two well-known response surface models representing no interaction are Loewe additivity and Bliss independence, and Loewe or Bliss synergism or antagonism is defined relative to these. We illustrate an approach to fitting these models for the case in which the marginal single drug dose-response relationships are represented by four-parameter logistic curves with common upper and lower limits, and where the response variable is normally distributed with a common variance about the dose-response curve. When the dose-response curves are not parallel, the relative potency of the two drugs varies according to the magnitude of the desired effect and the models for Loewe additivity and synergism/antagonism cannot be explicitly expressed. We present an iterative approach to fitting these models without the assumption of parallel dose-response curves. A goodness-of-fit test based on residuals is also described. Implementation using the SAS NLIN procedure is illustrated using data from a pre-clinical study.