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Dynamically generating T32 training documents using structured data.

ABSTRACT: Background:The US National Institutes of Health (NIH) funds academic institutions for training doctoral (PhD) students and postdoctoral fellows. These training grants, known as T32 grants, require schools to create, in a particular format, seven or eight Word documents describing the program and its participants. Weill Cornell Medicine aimed to use structured name and citation data to dynamically generate tables, thus saving administrators time. Case Presentation:The author's team collected identity and publication metadata from existing systems of record, including our student information system and previous T32 submissions. These data were fed into our ReCiter author disambiguation engine. Well-structured bibliographic metadata, including the rank of the target author, were output and stored in a MySQL database. We then ran a database query that output a Word extensible markup (XML) document according to NIH's specifications. We generated the T32 training document using a query that ties faculty listed on a grant submission with publications that they and their mentees authored, bolding author names as required. Because our source data are well-structured and well-defined, the only parameter needed in the query is a single identifier for the grant itself. The open source code for producing this document is at http://dx.doi.org/10.5281/zenodo.2593545. Conclusions:Manually writing a table for T32 grant submissions is a substantial administrative burden; some documents generated in this manner exceed 150 pages. Provided they have a source for structured identity and publication data, administrators can use the T32 Table Generator to readily output a table.

SUBMITTER: Albert PJ

PROVIDER: S-EPMC6579602 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Dynamically generating T32 training documents using structured data.

Albert Paul James PJ Joshi Ayesha A

Journal of the Medical Library Association : JMLA 20190701 3

<h4>Background</h4>The US National Institutes of Health (NIH) funds academic institutions for training doctoral (PhD) students and postdoctoral fellows. These training grants, known as T32 grants, require schools to create, in a particular format, seven or eight Word documents describing the program and its participants. Weill Cornell Medicine aimed to use structured name and citation data to dynamically generate tables, thus saving administrators time.<h4>Case presentation</h4>The author's team ...[more]

PMID: 31258448

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Project description:PURPOSE: The effectiveness of physical examination skills (PES) training is very rarely assessed using the "post-then-pre" approach. In this study, a retro-pre-questionnaire was used to study the effect of structured physical examination skills training (SPEST) imparted to second-year undergraduate medical students. METHODS: KIST Medical College (KISTMC) affiliated to Tribhuvan University Nepal admitted its first batch of MBBS students in November 2008. The university curriculum recommends the involvement of Medicine and Surgery Departments in PES training, but the methods for teaching and assessment are not well defined. KISTMC has made training more structured and involved the Medicine, Surgery, Gynaecology and Obstetrics, Orthopaedics, ENT, Ophthalmology, Paediatrics, and Family Medicine Departments. SPEST includes the teaching/learning of basic PES for 210 minutes once a week for 28 weeks. Self-assessment is done by using a retro-pre-questionnaire at the end of the last session of training, and these data are analysed using SPSS. RESULTS: Out of 100 students, 98 participated in the objective structured clinical examination (OSCE); 82 completed the retro-pre-questionnaire. Forty-six skills representing various systems were selected for inclusion in the retro-pre-questionnaire from among the many skills taught in different departments. The average perceived skills score (maximum score, 46×4=184) before training was 15.9 and increased to 116.5 after training. The increase was statistically significant upon the application of a paired t-test. CONCLUSION: The students perceived that their level of skills improved after the training. The retro-pre- instrument seems to be useful for assessing the learners' self-reported changes in PES after training if a large number of skills need to be assessed. However, it should be noted that although a retro-pre-questionnaire may reveal valuable information, it is not a substitute for an objective measure or gold standard.

Dataset Information

Dynamically generating T32 training documents using structured data.

Publications

Dynamically generating T32 training documents using structured data.

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