Effects of Mass and Interpersonal Communication on Breast Cancer Screening: Advancing Agenda-Setting Theory in Health Contexts

Drawing on components of agenda-setting theory and the two-step flow of information from mass media to news audiences, this study examines the effects of mass and interpersonal communication on breast cancer screening practices among college- and middle-aged women (n = 284). We theorized that screening behaviors among younger women would be influenced more by interpersonal sources of information while screening among middle-aged women would be more influenced by exposure to mass-mediated information. Findings supported anticipated patterns, revealing important and varying roles for both mass and interpersonal communication in the health behaviors of women. Implications for health practitioners and campaign planners, as well as recommendations for future research, are discussed.     

Automated Classification to Improve the Efficiency of Weeding Library Collections

Previous studies have shown that weeding a library collection benefits patrons and increases circulation rates. However, the time required to review the collection and make weeding decisions presents a formidable obstacle. This study empirically evaluated methods for automatically classifying weeding candidates. A data set containing 80,346 items from a large-scale weeding project running from 2011 to 2014 at Wesleyan University was used to train six machine learning classifiers to predict a weeding decision of either ‘Keep’ or ‘Weed’ for each candidate. The study found statistically significant agreement (p?=?0.001) between classifier predictions and librarian judgments for all classifier types. The naive Bayes and linear support vector machine classifiers had the highest recall (fraction of items weeded by librarians that were identified by the algorithm), while the k-nearest-neighbor classifier had the highest precision (fraction of recommended candidates that librarians had chosen to weed). The variables found to be most relevant were: librarian and faculty votes for retention, item age, and the presence of copies in other libraries.     

Why Users Share the News: A Theory of Reasoned Action-Based Study on the Antecedents of News-Sharing Behavior

Social media have become an integral part of online news use, affecting how individuals find, consume, and share news. By applying the Theory of Reasoned Action (TRA), this study investigates the effects of motives, attitude, and intention on news-sharing behavior among German social media users (n = 333). Findings show that news-sharing attitude and subjective norms have a positive effect on news-sharing intention, which in turn has a positive effect on actual news-sharing behavior. Taken together, we see that a new media behavior in the early phases of its societal diffusion—like social media news sharing in Germany in 2015—can mainly be explained by a rational choice logic and is rooted in the motives of socializing and information seeking. This finding thus reflects the double nature of social media as a means for both information retrieval and social grooming.     

EUROPEAN PUBLIC PERCEPTIONS OF SCIENCE

In this paper we explore the relationships between public interestin, knowledge of, and attitudes towards science and technologyand the level of industrialization in 12 countries of the EuropeanCommunity. Using the 1989 Eurobarometer survey no 31 (N=11,678),we constructed four scales measuring interest, knowledge, generalattitudes to science, and support for EC funded science foreach of the 12 EC countries. We found that overall factual scientificknowledge correlates moderately positively with interest andattitudes to science. For example the Netherlands and GreatBritain have relatively high levels of knowledge, interest,and support for science in general. Spain and Greece have relativelylow levels of knowledge, interest, and support for science ingeneral. However, the simple correlation hides more complexrelationships. First, the variance within and across countriesof knowledge, attitudes and interest increases with nationallevels of knowledge. This indicates greater degrees of polarizationof both support and interest. Second, the data indicates a post-industrialismeffect: knowledge, interest in, and attitudes to science showa curvilinear relationship with levels of industrialization.The decline of interest in science and the less positive attitudesin highly developed countries requires further exploration.Third, we found, that the consistency of the knowledge and theattitude measures declines as the national level of knowledgeincreases. We suggest that this reflects a knowledge-ignoranceparadox and knowledge specialization among informed populations.Support for EC level science follows a different pattern. Wefound that France, Italy, and Spain show high levels of supportfor EC level science. This is not the case in Great Britainand Germany. The pattern suggests that attitudes towards ECscience are formed on the basis of national level scientificstrength: if the national science base is strong, EC scienceinitiatives find less support and vice versa. These findingsrepresent a first step towards a comparative assessment of publicunderstanding of science in EC countries.     

Knee extensor and flexor torque development with concentric and eccentric isokinetic training

This study assessed muscular torque and rate of torque development following concentric (CON) or eccentric (ECC) isokinetic training. Thirty-eight women were randomly assigned to either CON or ECC training groups. Training consisted of knee extension and flexion of the nondominant leg three times per week for 20 weeks (SD = 1). Eccentric training increased ECC knee extension and flexion peak torque more than CON training. The ECC group improved acceleration time and time to peak torque with ECC movements versus the CON group. Slow-velocity ECC isokinetic training yielded greater ECC and similar CON torque development gains versus CON training over the course of 20 weeks in young women.     

The graph-theoretic field model— II. application of multi-terminal representations to field problems

This paper is a sequel to a paper entitled “The Graph-Theoretic Field Model—I: Modelling and Formulations” (1). Herein, the Theory of Multi-Terminal Representations is applied to the Graph-Theoretic Field Model to provide mathematical models of finite elements. The element models are obtained solely from the algebraic building blocks of the Graph-Theoretic Field Model, without recourse to any functional mathematics. The theory of Multi-Terminal Representations is developed for both linear and non-linear problems. Examples of the application of the theory to one- and two-dimensional field problems are presented from heat conduction and electrostatics.