LGBT individuals face many barriers in accessing healthcare, including discrimination, lack of access, misunderstanding, and fear. As a consequence, many LGBT individuals do not regularly access appropriate and timely care. The more informed healthcare professionals are, LGBT patients and clients will become more comfortable in an environment that is often alienating, disrespectful, and traumatic. Learn more about the course by visiting: https://nnlm.gov/classes/LGBTHealth
Online Resources to Support Evidence-Based Practice on Population Health: An Introduction to MedlinePlus, PubMed, and HSRProj
The goal of this class is to increase understanding of Complementary and Alternative Medicine (CAM). Students will learn the history of CAM and its impact on medical practices. They will learn how CAM is used, how to evaluate CAM website, and how to look up information about the effectiveness of CAM therapies.
- Teacher: Dana Abbey
In the words of the immortal Yogi Berra, “if you don’t know where you’re going, you might not get there.” Participants will learn how to identify desired outcomes, create an outcomes-based project plan using logic models, and then write objectives and evaluation plans based on those logic models. It provides an ideal framework for developing funding proposals, sets the stage for setting up a quality control system to make sure your project stays on track, and provide a structure for your final reports.
- Teacher: Lorraine Dong
Community assessment is the essential fact-finding phase of program development. You form a picture of a target community or user group in order to develop beneficial programs and services for it. But community assessment, particularly for outreach programs, can be so much more than an evaluation activity.
This class is designed to assist librarians and others who work with diverse populations in locating health information. The resources presented are selected for their emphasis on providing culturally relevant information in the preferred language of the population.
This specialized class will help improve your effectiveness in searching PubMed and related NLM and NIH databases for literature information on chemicals, drugs and genetics. The course covers drug information databases, searching for chemicals and with chemical nomenclature and locating literature related to genetics and genomics. This course assumes a strong working knowledge of PubMed including an understanding of automatic term mapping, the importance of reviewing the Details box after searches, and using the Advanced search page and the MeSH database. For more information: visit http://nnlm.gov/training/chemdrugs/
ClinicalTrials.gov is the openly available federal registry and results database of publicly and privately funded clinical studies conducted in the United States and around the world. As of June 2017, ClinicalTrials.gov provided access to nearly 250,000 study records and more than 26,700 studies with summary results. ClinicalTrials.gov is a vital resource for researchers, healthcare providers, and health sciences librarians who wish to consult the entire body of evidence on any particular topic.
- Teacher: Dana Abbey
This class is intended to hone basic searching techniques and the ability to develop search strategies that will take advantage of the PubMed interface to MEDLINE. The course will explore various methods for searching the PubMed system. Topics covered include Automatic Term Mapping, Search Results, Features Bar, Related Citations, My NCBI, Searching with MeSH, and Single Citation Matcher.
This course will provide an overview of the system and demonstrate utilizing the features of PubMed to search effectively.
- Moderator: Patricia Devine
Cool Creative Communications: Dazzling Data Visualization
This class covers concepts of visually representing data and proven tools that are effective in making data understood at a glance. Students will increase their knowledge on data visualization concepts and a variety of data visualization applications. Students will complete assigned exercises that they will share with their class peers. Class participants are expected to spend 1.5 hours on content learning, 3 hours of in-depth learning on a selected tool/application and prepare a visualization, and .5 hours on peer critique.
- Instructor: Tony Nguyen
Health Sciences Library support for data researchers and computer scientists is a new role for health sciences librarians. Work being done in biomedical big data fields and precision medicine is being shared through The Big Data to Knowledge (BD2K) Initiative's weekly online lecture series discussing the data science underlying modern biomedical research. The series began in September 2016 and is scheduled to run through early 2017. The weekly presentations are from experts across the country covering the basics of data management, representation, computation, statistical inference, data modeling, and other topics relevant to “big data” in biomedicine. The webinar series will provide essential training suitable for individuals at an introductory overview level. All video presentations from the seminar series will be streamed for live viewing, recorded, and posted online for future viewing and reference. This webinar series is a collaboration between the TCC, the NIH Office of the Associate Director for Data Science, and BD2K Centers Coordination Center (BD2KCCC). Support for data researchers at all points of the research lifecycle is likely to become a primary role for health sciences librarians. What kind of library support researchers want and what kinds of skills librarians need to have in order to meet that need remain unanswered questions. If health sciences librarians want to provide meaningful contributions to a growing field, discussions need to take place and action plans need to be created.
CE Contact Hours: 2 per video, reflection, and evaluation submitted.
The learning objective of the live debriefing discussions is to increase awareness of the roles the librarian can play to support researchers in the data lifecycle.
If you have any questions or comments, contact firstname.lastname@example.org
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