The Use of Social Media to Increase the Impact of Health Research: Systematic Review.

BACKGROUND: Academics in all disciplines increasingly use social media to share their publications on the internet, reaching out to different audiences. In the last few years, specific indicators of social media impact have been developed (eg, Altmetrics), to complement traditional bibliometric indicators (eg, citation count and h-index). In health research, it is unclear whether social media impact also translates into research impact. OBJECTIVE: The primary aim of this study was to systematically review the literature on the impact of using social media on the dissemination of health research. The secondary aim was to assess the correlation between Altmetrics and traditional citation-based metrics. METHODS: We conducted a systematic review to identify studies that evaluated the use of social media to disseminate research published in health-related journals. We specifically looked at studies that described experimental or correlational studies linking the use of social media with outcomes related to bibliometrics. We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica dataBASE (EMBASE), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases using a predefined search strategy (International Prospective Register of Systematic Reviews: CRD42017057709). We conducted independent and duplicate study selection and data extraction. Given the heterogeneity of the included studies, we summarized the findings through a narrative synthesis. RESULTS: Of a total of 18,624 retrieved citations, we included 51 studies: 7 (14%) impact studies (answering the primary aim) and 44 (86%) correlational studies (answering the secondary aim). Impact studies reported mixed results with several limitations, including the use of interventions of inappropriately low intensity and short duration. The majority of correlational studies suggested a positive association between traditional bibliometrics and social media metrics (eg, number of mentions) in health research. CONCLUSIONS: We have identified suggestive yet inconclusive evidence on the impact of using social media to increase the number of citations in health research. Further studies with better design are needed to assess the causal link between social media impact and bibliometrics.

Phenotype Instance Verification and Evaluation Tool (PIVET): A Scaled Phenotype Evidence Generation Framework Using Web-Based Medical Literature.

BACKGROUND: Researchers are developing methods to automatically extract clinically relevant and useful patient characteristics from raw healthcare datasets. These characteristics, often capturing essential properties of patients with common medical conditions, are called computational phenotypes. Being generated by automated or semiautomated, data-driven methods, such potential phenotypes need to be validated as clinically meaningful (or not) before they are acceptable for use in decision making. OBJECTIVE: The objective of this study was to present Phenotype Instance Verification and Evaluation Tool (PIVET), a framework that uses co-occurrence analysis on an online corpus of publically available medical journal articles to build clinical relevance evidence sets for user-supplied phenotypes. PIVET adopts a conceptual framework similar to the pioneering prototype tool PheKnow-Cloud that was developed for the phenotype validation task. PIVET completely refactors each part of the PheKnow-Cloud pipeline to deliver vast improvements in speed without sacrificing the quality of the insights PheKnow-Cloud achieved. METHODS: PIVET leverages indexing in NoSQL databases to efficiently generate evidence sets. Specifically, PIVET uses a succinct representation of the phenotypes that corresponds to the index on the corpus database and an optimized co-occurrence algorithm inspired by the Aho-Corasick algorithm. We compare PIVET's phenotype representation with PheKnow-Cloud's by using PheKnow-Cloud's experimental setup. In PIVET's framework, we also introduce a statistical model trained on domain expert-verified phenotypes to automatically classify phenotypes as clinically relevant or not. Additionally, we show how the classification model can be used to examine user-supplied phenotypes in an online, rather than batch, manner. RESULTS: PIVET maintains the discriminative power of PheKnow-Cloud in terms of identifying clinically relevant phenotypes for the same corpus with which PheKnow-Cloud was originally developed, but PIVET's analysis is an order of magnitude faster than that of PheKnow-Cloud. Not only is PIVET much faster, it can be scaled to a larger corpus and still retain speed. We evaluated multiple classification models on top of the PIVET framework and found ridge regression to perform best, realizing an average F1 score of 0.91 when predicting clinically relevant phenotypes. CONCLUSIONS: Our study shows that PIVET improves on the most notable existing computational tool for phenotype validation in terms of speed and automation and is comparable in terms of accuracy.

Tracking medical genetic literature through machine learning.

There has been remarkable progress in identifying the causes of genetic conditions as well as understanding how changes in specific genes cause disease. Though difficult (and often superficial) to parse, an interesting tension involves emphasis on basic research aimed to dissect normal and abnormal biology versus more clearly clinical and therapeutic investigations. To examine one facet of this question and to better understand progress in Mendelian-related research, we developed an algorithm that classifies medical literature into three categories (Basic, Clinical, and Management) and conducted a retrospective analysis. We built a supervised machine learning classification model using the Azure Machine Learning (ML) Platform and analyzed the literature (1970-2014) from NCBI's Entrez Gene2Pubmed Database (http://www.ncbi.nlm.nih.gov/gene) using genes from the NHGRI's Clinical Genomics Database (http://research.nhgri.nih.gov/CGD/). We applied our model to 376,738 articles: 288,639 (76.6%) were classified as Basic, 54,178 (14.4%) as Clinical, and 24,569 (6.5%) as Management. The average classification accuracy was 92.2%. The rate of Clinical publication was significantly higher than Basic or Management. The rate of publication of article types differed significantly when divided into key eras: Human Genome Project (HGP) planning phase (1984-1990); HGP launch (1990) to publication (2001); following HGP completion to the "Next Generation" advent (2009); the era following 2009. In conclusion, in addition to the findings regarding the pace and focus of genetic progress, our algorithm produced a database that can be used in a variety of contexts including automating the identification of management-related literature.

NCI's Physician Data Query (PDQ®) cancer information summaries: history, editorial processes, influence, and reach.

In the National Cancer Act of 1971, the Director of the National Cancer Institute (NCI) was given a mandate to "Collect, analyze, and disseminate all data useful in the prevention, diagnosis, and treatment of cancer, including the establishment of an International Cancer Research Data Bank (ICRDB) to collect, catalog, store, and disseminate insofar as feasible the results of cancer research undertaken in any country for the use of any person involved in cancer research in any country" (National Cancer Act of 1971, S 1828, 92nd Congress, 1st Sess (1971)). In subsequent legislation, the audience for NCI's information dissemination activities was expanded to include physicians and other healthcare professionals, patients and their families, and the general public, in addition to cancer researchers. The Institute's response to these legislative requirements was to create what is now known as the Physician Data Query (PDQ®) cancer information database. From its beginnings in 1977 as a database of NCI-sponsored cancer clinical trials, PDQ has grown to include extensive information about cancer treatment, screening, prevention, supportive and palliative care, genetics, drugs, and more. Herein, we describe the history, editorial processes, influence, and global reach of one component of the PDQ database, namely its evidence-based cancer information summaries for health professionals. These summaries are widely recognized as important cancer information and education resources, and they further serve as foundational documents for the development of other cancer information products by NCI and other organizations.

Measuring the food environment using geographical information systems: a methodological review.

OBJECTIVE: Through a literature review, we investigated the geographic information systems (GIS) methods used to define the food environment and the types of spatial measurements they generate. DESIGN: Review study. SETTING: Searches were conducted in health science databases, including Medline/Pubmed, PsycINFO, Francis and GeoBase. We included studies using GIS-based measures of the food environment published up to 1 June 2008. RESULTS: Twenty-nine papers were included. Two different spatial approaches were identified. The density approach quantifies the availability of food outlets using the buffer method, kernel density estimation or spatial clustering. The proximity approach assesses the distance to food outlets by measuring distances or travel times. GIS network analysis tools enable the modelling of travel time between referent addresses (home) and food outlets for a given transportation network and mode, and the assumption of travel routing behaviours. Numerous studies combined both approaches to compare food outlet spatial accessibility between different types of neighbourhoods or to investigate relationships between characteristics of the food environment and individual food behaviour. CONCLUSIONS: GIS methods provide new approaches for assessing the food environment by modelling spatial accessibility to food outlets. On the basis of the available literature, it appears that only some GIS methods have been used, while other GIS methods combining availability and proximity, such as spatial interaction models, have not yet been applied to this field. Future research would also benefit from a combination of GIS methods with survey approaches to describe both spatial and social food outlet accessibility as important determinants of individual food behaviours.

Automated information retrieval in science and technology.

The rapid advances in computer and communication technology in the 1970's have enabled large interactive scientific and technical information retrieval systems to be implemented. Major search services today offer on-line access to millions of bibliographic citations and an increasing number of "electronic handbooks." In addition, development of knowledge bases is well under way. Despite the impressive speed and flexibility of interactive retrieval systems, their impact has been lessened by limited awareness of their existence, uneven quality of retrieval, inadequate linkages among data bases, and reliance on specially trained intermediaries.

Information retrieval in digital libraries: bringing search to the net.

A digital library enables users to interact effectively with information distributed across a network. These network information systems support search and display of items from organized collections. In the historical evolution of digital libraries, the mechanisms for retrieval of scientific literature have been particularly important. Grand visions in 1960 led first to the development of text search, from bibliographic databases to full-text retrieval. Next, research prototypes catalyzed the rise of document search, from multimedia browsing across local-area networks to distributed search on the Internet. By 2010, the visions will be realized, with concept search enabling semantic retrieval across large collections.

Effectiveness of IT-based diabetes management interventions: a review of the literature.

BACKGROUND: Information technology (IT) is increasingly being used in general practice to manage health care including type 2 diabetes. However, there is conflicting evidence about whether IT improves diabetes outcomes. This review of the literature about IT-based diabetes management interventions explores whether methodological issues such as sample characteristics, outcome measures, and mechanisms causing change in the outcome measures could explain some of the inconsistent findings evident in IT-based diabetes management studies. METHODS: Databases were searched using terms related to IT and diabetes management. Articles eligible for review evaluated an IT-based diabetes management intervention in general practice and were published between 1999 and 2009 inclusive in English. Studies that did not include outcome measures were excluded. RESULTS: Four hundred and twenty-five articles were identified, sixteen met the inclusion criteria: eleven GP focussed and five patient focused interventions were evaluated. Nine were RCTs, five non-randomised control trials, and two single-sample before and after designs. Important sample characteristics such as diabetes type, familiarity with IT, and baseline diabetes knowledge were not addressed in any of the studies reviewed. All studies used HbA1c as a primary outcome measure, and nine reported a significant improvement in mean HbA1c over the study period; only two studies reported the HbA1c assay method. Five studies measured diabetes medications and two measured psychological outcomes. Patient lifestyle variables were not included in any of the studies reviewed. IT was the intervention method considered to effect changes in the outcome measures. Only two studies mentioned alternative possible causal mechanisms. CONCLUSION: Several limitations could affect the outcomes of IT-based diabetes management interventions to an unknown degree. These limitations make it difficult to attribute changes solely to such interventions.

Impact of anesthesia on transcranial electric motor evoked potential monitoring during spine surgery: a review of the literature.

OBJECT: Transcranial motor evoked potential (TcMEP) monitoring is frequently used in complex spinal surgeries to prevent neurological injury. Anesthesia, however, can significantly affect the reliability of TcMEP monitoring. Understanding the impact of various anesthetic agents on neurophysiological monitoring is therefore essential. METHODS: A literature search of the National Library of Medicine database was conducted to identify articles pertaining to anesthesia and TcMEP monitoring during spine surgery. Twenty studies were selected and reviewed. RESULTS: Inhalational anesthetics and neuromuscular blockade have been shown to limit the ability of TcMEP monitoring to detect significant changes. Hypothermia can also negatively affect monitoring. Opioids, however, have little influence on TcMEPs. Total intravenous anesthesia regimens can minimize the need for inhalational anesthetics. CONCLUSIONS: In general, selecting the appropriate anesthetic regimen with maintenance of a stable concentration of inhalational or intravenous anesthetics optimizes TcMEP monitoring.

[Searching for evidence-based data]. / Recherche de données factuelles.

The foundation of evidence-based medicine is critical analysis and synthesis of the best data available concerning a given health problem. These factual data are accessible because of the availability on the Internet of web tools specialized in research for scientific publications. A bibliographic database is a collection of bibliographic references describing the documents indexed. Such a reference includes at least the title, summary (or abstract), a set of keywords, and the type of publication. To conduct a strategically effective search, it is necessary to formulate the question - clinical, diagnostic, prognostic, or related to treatment or prevention - in a form understandable by the research engine. Moreover, it is necessary to choose the specific database or databases, which may have particular specificity, and to analyze the results rapidly to refine the strategy. The search for information is facilitated by the knowledge of the standardized terms commonly used to describe the desired information. These come from a specific thesaurus devoted to document indexing. The most frequently used is MeSH (Medical Subject Heading). The principal bibliographic database whose references include a set of describers from the MeSH thesaurus is Medical Literature Analysis and Retrieval System Online (Medline), which has in turn become a subpart of a still more vast bibliography called PubMed, which indexes an additional 1.4 million references. Numerous other databases are maintained by national or international entities. These include the Cochrane Library, Embase, and the PASCAL and FRANCIS databases.

The development of the Medical Literature Analysis and Retrieval System (MEDLARS).

OBJECTIVE: The research provides a chronology of the US National Library of Medicine's (NLM's) contribution to access to the world's biomedical literature through its computerization of biomedical indexes, particularly the Medical Literature Analysis and Retrieval System (MEDLARS). METHOD: Using material gathered from NLM's archives and from personal interviews with people associated with developing MEDLARS and its associated systems, the author discusses key events in the history of MEDLARS. DISCUSSION: From the development of the early mechanized bibliographic retrieval systems of the 1940s and to the beginnings of online, interactive computerized bibliographic search systems of the early 1970s chronicled here, NLM's contributions to automation and bibliographic retrieval have been extensive. CONCLUSION: As NLM's technological experience and expertise grew, innovative bibliographic storage and retrieval systems emerged. NLM's accomplishments regarding MEDLARS were cutting edge, placing the library at the forefront of incorporating mechanization and technologies into medical information systems.

Usefulness of the on-line data base CANCERLIT: an evaluation study based on consecutive searches in CANCERLIT and MEDLINE for oncologists.

Two on-line data bases of the National Library of Medicine, CANCERLIT and MEDLINE, were evaluated in a user-oriented study for their usefulness for oncologists in cancer research and in clinical practice. The CANCERLIT data base was preferred for 12 of 16 literature searches requested by oncologists, and in 4 instances no preference was indicated. The implications of the study are discussed with regard to data base content and user preferences.

Application of the office or home computer to searching the medical literature.

Search of the medical literature has, until recently, most often been conducted by medical librarians. The recent development of "user friendly" systems and competition among an increasing number of commercial and non-commercial vendors now provide the opportunity to personally conduct literature searches using a home or office computer without enormous investment in time, training or equipment. Hardware requirements and general principles of computerized literature searching are described, and the various services available for individual subscription are summarized, including National Library of Medicine (NLM) MEDLINE; Bibliographic Retrieval Services (BRS) and BRS/Saunders Colleague; PaperChase; Dialog/Knowledge Index; American Medical Association (AMA) Minet; and MEDIS.

The role of the term schizophrenia in the decline of diagnoses of multiple personality.

The syndrome of multiple (dissociated) personality fell into disrepute around 1910. This has been attributed to loss of interest in hypnosis; psychiatrists believed the syndrome resulted from hypnosis and that they were duped. However, around 1910 an important event occurred in psychiatry: Bleuler introduced the term "schizophrenia' to replace "dementia praecox.' This factor also played a role in the decline of recognition of the multiple personality syndrome, and many of these cases were diagnosed as schizophrenia. A review of Index Medicus from 1903 through 1978 shows a dramatic decline in the number of reports of multiple personality after the diagnosis of schizophrenia "caught on,' especially in the United States. A review of clinical reports indicates that many patients with multiple personality had been diagnosed and treated as schizophrenics.

Adverse effects of diagnostic tests. A study of the quality of reporting.

Information about the risks of diagnostic tests is incomplete, and its quality has not been studied. A set of criteria was devised and applied to 434 published reports to assess the quality of data about supposed adverse effects associated with 25 diagnostic procedures. Using these criteria, authors' conclusions concerning types of sequelae were supported by published findings in only 41% of reports. Information regarding frequency of these risks was upheld in 20%. Sound clinical judgment requires more dependable data than are presently available.

Efficacy of metformin in the treatment of NIDDM. Meta-analysis.

OBJECTIVE: The results differ concerning randomized controlled trials of the effects of metformin on blood glucose regulation and body weight. To get a systematic overview, a meta-analysis of the efficacy of metformin was performed by comparing metformin with placebo and sulfonylurea. RESEARCH DESIGN AND METHODS: All randomized controlled trials published since 1957 were selected by searching the Current List of Medical Literature, Cumulated Index Medicus, Medline, and Embase, Meta-analysis was performed calculating weighted mean difference (WMD) of fasting blood glucose, glycosylated hemoglobin, and body weight. RESULTS: Nine randomized controlled trials comparing metformin with placebo and ten comparing metformin with sulfonylurea were identified. The WMD between metformin and placebo after treatment for fasting blood glucose was -2.0 mmol/l (95% CI -2.4 to -1.7) and for glycosylated hemoglobin -0.9% (95% CI -1.1 to -0.7). Body weight WMD was not significant after treatment. Sulfonylurea and metformin lowered blood glucose and glycosylated hemoglobin equally, while there was a significant WMD of body weight (-2.9 kg [95% CI -4.4 to -1.1]) because of a 1.7-kg mean increase after sulfonylurea and a 1.2-kg mean decrease after metformin. CONCLUSIONS: Metformin lowers blood glucose and glycosylated hemoglobin significantly, compared with placebo. Metformin and sulfonylurea have an equal effect on fasting blood glucose and glycosylated hemoglobin, but the body weight is significantly lower after metformin compared with sulfonylurea treatment because of an increase in body weight after sulfonylurea treatment.

Safety of nifedipine in patients with hypertension: a meta-analysis.

Our objective was to compare cardiovascular event rates in patients with mild or moderate hypertension who received nifedipine with active drug controls. We performed a MEDLARS search using the MeSH heading "hypertension" and the text word "nifedipine" to identify all articles that were published between 1966 and August 1995 in English, French, German, Italian, and Spanish languages and that involved human subjects. The computerized search was supplemented by a manual search of article bibliographies. Review of 1880 citations revealed 98 randomized controlled clinical trials that met protocol criteria. Articles were extracted independently by two doctors who were blinded for author, institution, and treatment regimen, using a structured, pretested extraction form. Differences of opinion were resolved by consensus. Fourteen events occurred in 5198 exposures (0.27%) to nifedipine and 24 events in 5402 exposures (0.44%) to other active drug controls. Unadjusted odds ratios for nifedipine versus controls were 0.49 (95% confidence interval [CI], 0.22-1.09) for definitive events (death, nonfatal myocardial infarction or stroke, revascularization procedure) and 0.61 (95% CI, 0.31-1.17) for all events (definitive plus increased angina). The odds ratio for nifedipine monotherapy (sustained- or extended-release in 91% of exposures) was nonsignificantly higher for definitive and all events (odds ratio, 1.40; 95% CI, 0.49-4.03 and odds ratio, 1.39; 95% CI, 0.59-3.32, respectively). The odds ratio for nifedipine in combination with another drug was significantly lower for definitive and all events (odds ratio, 0.09; 95% CI, 0.01-0.66 and odds ratio, 0.15; 95% CI, 0.03-0.65, respectively). Differences in odds ratio for nifedipine monotherapy and combined therapy were statistically significant (P=.02 for definitive events and P=.001 for all events). Results support the safety of sustained- and extended-release nifedipine in the treatment of mild or moderate hypertension when it is used in combination with other drugs.