A regional cooperative acquisition program for monographs.

A cooperative acquisition program for monographs for the twelve resource libraries in Region IX of the Regional Medical Library Network is described. Each of the participating libraries has agreed to purchase all books of an assigned publisher which fall within a prescribed subject-format profile. It is hoped that this will help to reduce unnecessary duplication and contribute toward the development of resources in the region.     

Communicating Prevention: The Effects of the keepin' it REAL Classroom Videotapes and Televised PSAs on Middle-School Students' Substance Use

This study sought to determine if exposure to two communication-oriented activities, videotapes and public service announcements, accounts for changes in substance use among adolescents participating in the Drug Resistance Strategies Project's keepin' it REAL adolescent substance use prevention curriculum. Middle-school students (4,734, 72% Latino) responded to questionnaires related to these analyses. An analysis of covariance (ANCOVA) model was fit separately to six substance use outcomes. The results suggested that intervention students who saw four or five videos engaged in less substance use in the past month than did students who saw fewer videos. Having seen the PSAs one or more times did not predict the reported change in substance use.     

Program Evaluation in Libraries: Relating Operations and Clients

Evaluators of library programs have different perspectives on why to conduct an evaluation and also how to do so. The author suggests that a minimal approach to conducting a library program evaluation is to prove that the program exists. But this perspective has expanded to include different degrees of interest in the client and operations, culminating in a combined focus that leads evaluators to conduct outcome assessments. The chapter includes speculation on what motivates managers to undertake an evaluation, a review of some ways that library evaluations are conducted, and a discussion of several examples of program evaluations. Though there are not single directives for undertaking a library program evaluation, there are a variety of tools and advice to entice librarians to do more of them as a way to improve understanding the value of a library to its clientele and in society.     

Design and evaluation of a personal digital assistant- based alerting service for clinicians.

PURPOSE: This study describes the system architecture and user acceptance of a suite of programs that deliver information about newly updated library resources to clinicians' personal digital assistants (PDAs). DESCRIPTION: Participants received headlines delivered to their PDAs alerting them to new books, National Guideline Clearinghouse guidelines, Cochrane Reviews, and National Institutes of Health (NIH) Clinical Alerts, as well as updated content in UpToDate, Harrison's Online, Scientific American Medicine, and Clinical Evidence. Participants could request additional information for any of the headlines, and the information was delivered via e-mail during their next synchronization. Participants completed a survey at the conclusion of the study to gauge their opinions about the service. RESULTS/OUTCOME: Of the 816 headlines delivered to the 16 study participants' PDAs during the project, Scientific American Medicine generated the highest proportion of headline requests at 35%. Most users of the PDA Alerts software reported that they learned about new medical developments sooner than they otherwise would have, and half reported that they learned about developments that they would not have heard about at all. While some users liked the PDA platform for receiving headlines, it seemed that a Web database that allowed tailored searches and alerts could be configured to satisfy both PDA-oriented and e-mail-oriented users.     

Analysis of Statistical Question Classification for Fact-Based Questions

Question classification systems play an important role in question answering systems and can be used in a wide range of other domains. The goal of question classification is to accurately assign labels to questions based on expected answer type. Most approaches in the past have relied on matching questions against hand-crafted rules. However, rules require laborious effort to create and often suffer from being too specific. Statistical question classification methods overcome these issues by employing machine learning techniques. We empirically show that a statistical approach is robust and achieves good performance on three diverse data sets with little or no hand tuning. Furthermore, we examine the role different syntactic and semantic features have on performance. We find that semantic features tend to increase performance more than purely syntactic features. Finally, we analyze common causes of misclassification error and provide insight into ways they may be overcome.