Dataset Information

Development of a PubMed Based Search Tool for Identifying Sex and Gender Specific Health Literature.

ABSTRACT: An effective literature search strategy is critical to achieving the aims of Sex and Gender Specific Health (SGSH): to understand sex and gender differences through research and to effectively incorporate the new knowledge into the clinical decision making process to benefit both male and female patients. The goal of this project was to develop and validate an SGSH literature search tool that is readily and freely available to clinical researchers and practitioners.PubMed, a freely available search engine for the Medline database, was selected as the platform to build the SGSH literature search tool. Combinations of Medical Subject Heading terms, text words, and title words were evaluated for optimal specificity and sensitivity. The search tool was then validated against reference bases compiled for two disease states, diabetes and stroke.Key sex and gender terms and limits were bundled to create a search tool to facilitate PubMed SGSH literature searches. During validation, the search tool retrieved 50 of 94 (53.2%) stroke and 62 of 95 (65.3%) diabetes reference articles selected for validation. A general keyword search of stroke or diabetes combined with sex difference retrieved 33 of 94 (35.1%) stroke and 22 of 95 (23.2%) diabetes reference base articles, with lower sensitivity and specificity for SGSH content.The Texas Tech University Health Sciences Center SGSH PubMed Search Tool provides higher sensitivity and specificity to sex and gender specific health literature. The tool will facilitate research, clinical decision-making, and guideline development relevant to SGSH.

SUBMITTER: Song MM

PROVIDER: S-EPMC4761798 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Development of a PubMed Based Search Tool for Identifying Sex and Gender Specific Health Literature.

Song Michael M MM Simonsen Cheryl K CK Wilson Joanna D JD Jenkins Marjorie R MR

Journal of women's health (2002) 20151110 2

<h4>Background</h4>An effective literature search strategy is critical to achieving the aims of Sex and Gender Specific Health (SGSH): to understand sex and gender differences through research and to effectively incorporate the new knowledge into the clinical decision making process to benefit both male and female patients. The goal of this project was to develop and validate an SGSH literature search tool that is readily and freely available to clinical researchers and practitioners.<h4>Methods ...[more]

PMID: 26555409

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Project description:BACKGROUND: The identification of health services research in databases such as PubMed/Medline is a cumbersome task. This task becomes even more difficult if the field of interest involves the use of diverse methods and data sources, as is the case with nurse staffing research. This type of research investigates the association between nurse staffing parameters and nursing and patient outcomes. A comprehensively developed search strategy may help identify nurse staffing research in PubMed/Medline. METHODS: A set of relevant references in PubMed/Medline was identified by means of three systematic reviews. This development set was used to detect candidate free-text and MeSH terms. The frequency of these terms was compared to a random sample from PubMed/Medline in order to identify terms specific to nurse staffing research, which were then used to develop a sensitive, precise and balanced search strategy. To determine their precision, the newly developed search strategies were tested against a) the pool of relevant references extracted from the systematic reviews, b) a reference set identified from an electronic journal screening, and c) a sample from PubMed/Medline. Finally, all newly developed strategies were compared to PubMed's Health Services Research Queries (PubMed's HSR Queries). RESULTS: The sensitivities of the newly developed search strategies were almost 100% in all of the three test sets applied; precision ranged from 6.1% to 32.0%. PubMed's HSR queries were less sensitive (83.3% to 88.2%) than the new search strategies. Only minor differences in precision were found (5.0% to 32.0%). CONCLUSIONS: As with other literature on health services research, nurse staffing studies are difficult to identify in PubMed/Medline. Depending on the purpose of the search, researchers can choose between high sensitivity and retrieval of a large number of references or high precision, i.e. and an increased risk of missing relevant references, respectively. More standardized terminology (e.g. by consistent use of the term "nurse staffing") could improve the precision of future searches in this field. Empirically selected search terms can help to develop effective search strategies. The high consistency between all test sets confirmed the validity of our approach.

Project description:Growing evidence suggests that chemicals in disparate structural classes activate specific subsets of PPARγ’s transcriptional programs to generate adipocytes with distinct phenotypes. Our objectives were to 1) establish a novel classification method to predict PPARγ-interacting and modifying chemicals and 2) create taxonomy labels to group chemicals based on their effects on PPARγ’s transcriptome and downstream metabolic functions. We tested the hypothesis that an environmental ligand highly ranked by the taxonomy, but that segregated from the therapeutic ligands, would induce white but not brite adipogensis. 3T3-L1 cells were differentiated in the presence of 76 chemicals (negative controls, synthetic nuclear receptor ligands known to influence adipocyte biology, suspected environmental PPARγ ligands). Differentiation was assessed by measuring lipid accumulation. mRNA expression was determined by highly multiplexed RNA-Seq and validated by RT-qPCR. A novel classification model was developed using an amended random forest procedure. A subset of environmental contaminants identified as strong PPARγ agonists were characterized further for lipid handling, mitochondrial biogenesis and cellular respiration in 3T3-L1 cells and primary human preadipocytes. The 76 chemicals generated a spectrum of adipogenic differentiation. We used lipid accumulation and RNA sequencing data to develop a classification system that 1) identified PPARγ agonists and 2) sorted agonists into likely white or brite adipocyte inducers. Expression of Cidec, was the most efficacious indicator for strong PPARγ activation. Two known environmental PPARγ ligands, tetrabromobisphenol A, and triphenyl phosphate, which sorted distinctly from therapeutic ligands, induced white but not brite adipocyte genes and induced fatty acid uptake but not mitochondrial biogenesis in 3T3-L1 cells. The highly ranked agonists, tonalid and quinoxyfen, also induced white adipogenesis in 3T3-L1 cells and primary human preadipocytes. A novel classification procedure accurately identified environmental chemicals as PPARγ-modifying chemicals distinct from known PPARγ-modifying therapeutics.

Project description:BACKGROUND:Integrated care is an increasingly important principle for organising healthcare. Integrated care models show promise in reducing resource wastage and service fragmentation whilst improving the accessibility, patient-centredness and quality of care for patients. Those needing reliable access to the growing research evidence base for integrated care can be frustrated by search challenges reflective of the topic's complexity. The aim of this study is to report the empirical development and validation of two search filters for rapid and effective retrieval of integrated care evidence in PubMed. One filter is optimised for recall and the other for precision. METHODS:An Expert Advisory Group comprising international integrated care experts guided the study. A gold standard test set of citations was formed from screening Handbook Integrated Care chapter references for relevance. This set was divided into a Term Identification Set (20%) for determining candidate terms using frequency analysis; a Filter Development Set (40%) for testing performance of term combinations; and a Filter Validation Set (40%) reserved for confirming final filter performance. In developing the high recall filter, recall was steadily increased while maintaining precision at ?50%. Similarly, the high precision filter sought to maximise precision while keeping recall ?50%. For each term combination tested, an approximation of precision was obtained by reviewing the first 100 citations retrieved in Medline for relevance. RESULTS:The gold standard set comprised 534 citations. The search filter optimised for recall ('Broad Integrated Care Search') achieved 86.0-88.3% recall with corresponding low precision (47-53%). The search filter optimised for precise searching ('Narrow Integrated Care Search') demonstrated precision of 73-95% with recall reduced to between 55.9 and 59.8%. These filters are now available as one-click URL hyperlinks in the website of International Foundation for Integrated Care. CONCLUSIONS:The Broad and Narrow Integrated Care Search filters provide potential users, such as policy makers and researchers, seamless, reliable and ongoing access to integrated care evidence for decision making. These filters were developed according to a rigorous and transparent methodology designed to circumvent the challenges of information retrieval posed by this complex, multifaceted topic.

Dataset Information

Development of a PubMed Based Search Tool for Identifying Sex and Gender Specific Health Literature.

Publications

Development of a PubMed Based Search Tool for Identifying Sex and Gender Specific Health Literature.

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