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Twitter is a popular social media platform used by organizations for communication and marketing purposes. Many libraries, including members of the Association of Academic Health Sciences Libraries (AAHSL), have Twitter accounts, but how do these libraries use Twitter to communicate with their constituents and are they using it effectively? This study is a large-scale observational study of Twitter use within AAHSL libraries and reflects on the usage patterns present in the context of social media best practices. This study also aims to expand upon best practices for implementing and maintaining a Twitter account in a health sciences library setting.

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CONTEXT: During the past 20 years, colleges of osteopathic medicine (COMs) have made several advances in research that have substantially improved the osteopathic medical profession and the health of the US population. Furthering the understanding of research at COMs, particularly the factors influencing the attainment of extramural funds, is highly warranted and coincides with the missions of most COMs and national osteopathic organizations. OBJECTIVES: To describe bibliometric measures (numbers of peer-reviewed publications [ie, published articles] and citations of these publications, impact indices) at COMs from 2006 through 2010 and to examine statistical associations between these measures and the amount of National Institutes of Health (NIH) research funds awarded to COMs in 2006 and 2010. METHODS: A customized, systematic search of the Web of Science database was used to obtain bibliometric measures for 28 COMs. For the analyses, the bibliometric measures were summed or averaged over a 5-year period (2006 through 2010). The NIH database was used to obtain the amount of NIH funds for research grants and contracts received by the 28 COMs. Bivariate and multivariate statistical procedures were used to explore relationships between bibliometric measures and NIH funding amounts. RESULTS: The COMs with 2010 NIH funding, compared with COMs without NIH funding, had greater numbers of publications and citations and higher yearly average impact indices. Funding from the NIH in 2006 and 2010 was positively and significantly correlated with the numbers of publications, citations, and citations per publication and impact indices. The regression analysis indicated that 63.2% and 38.5% of the total variance in 2010 NIH funding explained by the model (adjusted R(2)=0.74) was accounted for by 2006 NIH funding and the combined bibliometric (ie, publications plus citations), respectively. CONCLUSION: Greater scholarly output leads to the procurement of more NIH funds for research at COMs.

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Bibliometric indicators can assist biomedical researchers in determining the nature of their influence and impact of their research. In recent years, demands by academic faculty for bibliometric analyses have risen considerably at the University at Buffalo (UB). Consequently, library staff at the Health Sciences Library (HSL) began to offer bibliometric services, a series of workshops and consultations to meet faculty requests. This column highlights the implementation, assessment, and challenges of UB HSL's "Tenure Metrics" program.

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OBJECTIVE: The objective of this study was to analyze bibliometric data from ISI, National Institutes of Health (NIH)-funding data, and faculty size information for Association of American Medical Colleges (AAMC) member schools during 1997 to 2007 to assess research productivity and impact. METHODS: This study gathered and synthesized 10 metrics for almost all AAMC medical schools(n=123): (1) total number of published articles per medical school, (2) total number of citations to published articles per medical school, (3) average number of citations per article, (4) institutional impact indices, (5) institutional percentages of articles with zero citations, (6) annual average number of faculty per medical school, (7) total amount of NIH funding per medical school, (8) average amount of NIH grant money awarded per faculty member, (9) average number of articles per faculty member, and (10)average number of citations per faculty member. Using principal components analysis, the author calculated the relationships between measures, if they existed. RESULTS: Principal components analysis revealed 3 major clusters of variables that accounted for 91% of the total variance: (1) institutional research productivity, (2) research influence or impact, and (3)individual faculty research productivity. Depending on the variables in each cluster, medical school research may be appropriately evaluated in a more nuanced way. Significant correlations exist between extracted factors, indicating an interrelatedness of all variables. Total NIH funding may relate more strongly to the quality of the research than the quantity of the research. The elimination of medical schools with outliers in 1 or more indicators (n=20)altered the analysis considerably. CONCLUSIONS: Though popular, ordinal rankings cannot adequately describe the multidimensional nature of a medical school's research productivity and impact. This study provides statistics that can be used in conjunction with other sound methodologies to provide a more authentic view of a medical school's research. The large variance of the collected data suggests that refining bibliometric data by discipline, peer groups, or journal information may provide a more precise assessment.

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OBJECTIVE: The research sought to ascertain medical and dental libraries' collection development policies, evaluation methods, purchase decisions, and issues that relate to print and electronic United States Medical Licensing Examination (USMLE) and National Board Dental Examination (NBDE) preparation materials. METHODS: The investigators surveyed librarians supporting American Association of Medical Colleges (AAMC)-accredited medical schools (n = 58/125) on the USMLE and librarians supporting American Dental Association (ADA)-accredited dental schools (n = 23/56) on the NBDE. The investigators analyzed the data by cross-tabulating and filtering the results using EFM Continuum web survey software. Investigators also surveyed print and electronic USMLE and NBDE preparation materials from 2004-2007 to determine the number of publications and existence of reviews. RESULTS: A majority of responding AAMC libraries (62%, n = 58) provide at least 1 electronic or online USMLE preparation resource and buy an average of 11.6 print USMLE titles annually. Due to a paucity of NBDE print and electronic resources, ADA libraries bought significantly fewer print resources, and only 1 subscribed to an electronic resource. The most often reported evaluation methods for both populations were feedback from medical or dental students, feedback from medical or dental faculty, and online trials. Some AAMC (10%, n = 58) and ADA libraries (39%, n = 23) libraries reported that no evaluation of these materials occured at their libraries. CONCLUSIONS: From 2004-2007, publishers produced 45 USMLE preparation resources (total n = 546) to every 1 NBDE preparation resource (total n = 12). Users' needs, institutional missions and goals, financial status, and official collection policies most often underlie decisions to collect or not collect examination preparation materials. Evaluating the quality of examination preparation materials can be problematic due to lack of published reviews, lack of usability testing by libraries, and librarians' and library users' unfamiliarity with the actual content of examinations. Libraries must integrate faculty and students into the purchase process to make sure examination preparation resources of the highest quality are purchased.

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