The impact of uncertainty in society on the use of traditional, complementary and alternative medicine: a comparative study on visits to alternative/traditional/folk health care practitioners.

BACKGROUND: While traditional, complementary and alternative medicine (TCAM) is gaining increased interest worldwide, the structural factors associated with the usage of TCAM at the social level have not been sufficiently explored. We aim to understand the social structure of uncertainty in society that affects the TCAM usage for men and women. METHODS: We studied 32 countries using data from the International Social Survey Programme and the World Bank. In this study, we defined TCAM usage as visits to an alternative/traditional/folk health care practitioner during the past 12 months. We performed a correlation analysis and used a generalized linear model . RESULTS: The prevalence of TCAM usage in terms of visits to practitioners was 26.1% globally, while usage varied across the 32 countries. Generalized linear models showed that unemployment rate was associated with the prevalence of TCAM usage in terms of visits to practitioners. CONCLUSIONS: At the social-structural level TCAM usage involving visits to practitioners was related to job insecurity. Job insecurity led to a decrease in TCAM usage regarding visits to practitioners. These findings suggest that it is necessary to consider the social-structural factors of uncertainty in society when designing health policies related to TCAM.

A Japanese nationwide survey for evaluation of the comprehensibility of alternative audiometry display formats: Insight into otolaryngologists' cognitive processes.

OBJECTIVE: The present study aimed to elucidate opinions regarding comprehensibility of audiometry display formats among otolaryngologists in Japan, and to identify the characteristics of otolaryngologists' cognitive processes for audiometry. METHODS: We conducted a cross-sectional nationwide questionnaire-based mail survey regarding the comprehensibility of audiometry display formats among 543 Japanese otolaryngologists. Of 543 otolaryngologists to whom the questionnaires were mailed, 137 replied to the questions. For the analysis, the sample size used was 112 participants. The questionnaire contained questions regarding the otolaryngologists' occupational characteristics, and assessed their opinions of four comprehensibility aspects of five display formats. RESULTS: Otolaryngologists in clinics indicated that the passage of time and changes in thresholds of each frequency in numeric tables were ordinary or incomprehensible. More than 60% of otolaryngologists with extensive experience in using electronic medical records indicated that both, the passage of time and change in the thresholds in overlaid thresholds on a chart were comprehensible. CONCLUSIONS: Display formats in audiometry influenced the comprehension of pure tone audiometry data. Our results suggest that overlaid thresholds on a chart rather than numeric table or multi-dimensional charts are the primary choice for computerized audiometry display formats in most aspects of audiometry.

External validation of the TRISS, CRASH, and IMPACT prognostic models in severe traumatic brain injury in Japan.

In Japan, a range of patients with traumatic brain injury (TBI) has been recorded in a nationwide database (Japan Neurotrauma Data Bank; JNTDB). This study aimed to externally validate three international prediction models using JNTDB data: Trauma and Injury Severity Score (TRISS), Corticosteroid Randomization After Significant Head Injury (CRASH), and International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT). We also aimed to validate the applicability of these models in the Japanese population. Of 1,091 patients registered in the JNTDB from July 2009 to June 2011, we analyzed data for 635 patients. We examined factors associated with mortality in-hospital and unfavorable outcomes 6 months after TBI by applying the TRISS, CRASH, and IMPACT models. We also conducted an external validation of these models based on these data. The patients' mean age was 60.1 ±21.1 years, and 342 were alive at the time of discharge (53.9%). Univariate analysis revealed eight major risk factors for mortality in-hospital: age, Glasgow Coma Scale (GCS), Injury Severity Score (ISS), systolic blood pressure, heart rate, mydriasis, acute epidural hematoma (AEDH), and traumatic subarachnoid hemorrhage. A similar analysis identified five risk factors for unfavorable outcomes at 6 months: age, GCS, ISS, mydriasis, and AEDH. For mortality in-hospital, the TRISS had a satisfactory area under the curve value (0.75). For unfavorable outcomes at 6 months, the CRASH (basic and computed tomography) and IMPACT (core and core extended) models had satisfactory area under the curve values (0.86, 0.86, 0.81, and 0.85, respectively). The TRISS, CRASH, and IMPACT models were suitable for application to the JNTDB population, indicating these models had high value in Japanese patients with neurotrauma.

BodyMap-Xs: anatomical breakdown of 17 million animal ESTs for cross-species comparison of gene expression.

BodyMap-Xs (http://bodymap.jp) is a database for cross-species gene expression comparison. It was created by the anatomical breakdown of 17 million animal expressed sequence tag (EST) records in DDBJ using a sorting program tailored for this purpose. In BodyMap-Xs, users are allowed to compare the expression patterns of orthologous and paralogous genes in a coherent manner. This will provide valuable insights for the evolutionary study of gene expression and identification of a responsive motif for a particular expression pattern. In addition, starting from a concise overview of the taxonomical and anatomical breakdown of all animal ESTs, users can navigate to obtain gene expression ranking of a particular tissue in a particular animal. This method may lead to the understanding of the similarities and differences between the homologous tissues across animal species. BodyMap-Xs will be automatically updated in synchronization with the major update in DDBJ, which occurs periodically.

Social determinants affecting the use of complementary and alternative medicine in Japan: An analysis using the conceptual framework of social determinants of health.

This study aims to use the conceptual framework of social determinants of health (SDH) to elucidate the social determinants that affect the use of complementary and alternative medicine (CAM) from the perspectives of both intermediary and structural determinants. Data were derived from a survey mailed to 1,500 randomly selected residents (20-69 years old; May-July 2009) of Sendai city in Japan. A generalized linear model was used in the analysis, with CAM use over the past one month as the dependent variable, SDH structural and intermediary determinants as independent variables, and demographic characteristics, indicators of health status, and the evaluation of health or healthcare systems as control variables. The prevalence of CAM usage was 62.1%. The generalized linear model showed that middle subjective social status (OR = 1.47; 95% CI: 1.04-2.07) as structural determinants was significantly associated with CAM usage. Adding the intermediary determinants, the same effect was observed. When demographic characteristics, indicators of health status, and the evaluation of health or healthcare systems were introduced as control variables, the associations of the structural determinants disappeared, revealing that hope (OR = 1.25; 95%CI: 1.04-1.50) as intermediary determinants was associated with the use of CAM. Female sex (OR = 1.47; 95% CI: 1.02-2.12) and health anxiety (OR = 1.68; 95% CI: 1.20-2.34) were associated with CAM usage. We found that intermediary rather than structural determinants were associated with CAM usage. Hope as an intermediary determinant was particularly associated with CAM usage.

The prevalence of mental distress before the Great East Japan Earthquake and the associated impact of an aged society: An ecological study.

Various studies have determined that the Great East Japan Earthquake (GEJE) caused mental distress among residents in affected areas. However, previous studies had not considered the prevalence of mental distress before the GEJE, and ignored the impact of an aged society on mental distress. Therefore, we aimed to describe the prevalence of mental distress before the GEJE in Miyagi Prefecture, Japan and elucidate the effect of an aged society on mental distress. We conducted an ecological study, using municipality in Miyagi Prefecture as the study unit. We used the cross-sectional mail survey data conducted in February 2011. We performed a correlation analysis in each of the 39 municipalities in Miyagi Prefecture. The prevalence of serious mental distress was 9.1%. The proportion of the population aged 65 years or older was related to the prevalence of serious mental distress in municipalities with a low proportion of all workers engaged in primary industry and with a high estimated number of inpatients with mental illness. We found that residents in Miyagi Prefecture suffered from poor mental health before the GEJE. Aged society was related to serious mental distress in the areas with advanced industrial structure and more patients with mental illness. We should approach mental health problems in the context of social structure, particularly in an aged society, based on facts about mental distress before the GEJE.

The Human Anatomic Gene Expression Library (H-ANGEL), the H-Inv integrative display of human gene expression across disparate technologies and platforms.

The Human Anatomic Gene Expression Library (H-ANGEL) is a resource for information concerning the anatomical distribution and expression of human gene transcripts. The tool contains protein expression data from multiple platforms that has been associated with both manually annotated full-length cDNAs from H-InvDB and RefSeq sequences. Of the H-Inv predicted genes, 18 897 have associated expression data generated by at least one platform. H-ANGEL utilizes categorized mRNA expression data from both publicly available and proprietary sources. It incorporates data generated by three types of methods from seven different platforms. The data are provided to the user in the form of a web-based viewer with numerous query options. H-ANGEL is updated with each new release of cDNA and genome sequence build. In future editions, we will incorporate the capability for expression data updates from existing and new platforms. H-ANGEL is accessible at http://www.jbirc.aist.go.jp/hinv/h-angel/.

Psychometric validation of a new measurement instrument for time-oriented patient information in electronic medical records: A questionnaire survey of physicians.

RATIONALE, AIMS, AND OBJECTIVES: Time is an important element in medical data. Physicians record and store information about patients' disease progress and treatment response in electronic medical records (EMRs). Because EMRs use timestamps, physicians can identify patterns over time regarding a patient's disease and treatment (eg, laboratory values and medications). However, analyses of physicians' use and satisfaction with EMRs have focused on functionality, storage, and system operation rather than the use of time-oriented information. This study aimed to understand physicians' needs regarding time-oriented patient information in EMRs in clinical practice. METHODS: The reliability and validity of the items in the questionnaire were evaluated in 87 physicians at a national university hospital. Internal consistency was satisfactory (Cronbach alpha coefficient, 0.87). RESULTS: Four dimensions were identified in exploratory factor analysis. Correlations between the 4 dimensions supported the construct validity of the items. Scores of time-oriented patients' medical history in the 4 dimensions showed a significant association with physician age. Based on confirmatory factor analysis, associations were significant and positive (P < .001). In terms of the needs of physicians regarding time-oriented patient information in EMRs, both time-oriented treatment results followed by time-oriented team information had significant positive associations. CONCLUSION: Our study suggests that 4 specific time-oriented patient information factors in EMRs are needed by physicians. Exploring physicians' needs regarding patient-specific time-oriented information may provide a better understanding of the barriers facing the adoption and use of EMRs (eg, decision-making and practice safety concerns) and lead to better acceptance of EMRs in physicians' clinical practices.

Automatic recognition of topic-classified relations between prostate cancer and genes using MEDLINE abstracts.

BACKGROUND: Automatic recognition of relations between a specific disease term and its relevant genes or protein terms is an important practice of bioinformatics. Considering the utility of the results of this approach, we identified prostate cancer and gene terms with the ID tags of public biomedical databases. Moreover, considering that genetics experts will use our results, we classified them based on six topics that can be used to analyze the type of prostate cancers, genes, and their relations. METHODS: We developed a maximum entropy-based named entity recognizer and a relation recognizer and applied them to a corpus-based approach. We collected prostate cancer-related abstracts from MEDLINE, and constructed an annotated corpus of gene and prostate cancer relations based on six topics by biologists. We used it to train the maximum entropy-based named entity recognizer and relation recognizer. RESULTS: Topic-classified relation recognition achieved 92.1% precision for the relation (an increase of 11.0% from that obtained in a baseline experiment). For all topics, the precision was between 67.6 and 88.1%. CONCLUSION: A series of experimental results revealed two important findings: a carefully designed relation recognition system using named entity recognition can improve the performance of relation recognition, and topic-classified relation recognition can be effectively addressed through a corpus-based approach using manual annotation and machine learning techniques.

Gene-L'EXPO: a tool to extract knowledge From transcriptomes and find 'Literature-Sparse' relationships between genes and tissues.

The increasing volume and diversity of transcriptome data in the public domain offer an opportunity to advance new questions and hypotheses. We anticipate that tools that can visualize the gap in the distribution of information between the scientific literature and actual data would prompt such questions. We focused on the roles played by various genes in tissues, and have developed a database that contrasts information on gene expression in tissues with PubMed text and transcriptome data. Data pairs of tissues and the genes that might be expressed there were automatically extracted from text with vocabularies for the genes and tissues. The anatomical categories of various expressed sequence tag (EST) libraries were also automatically determined. These types of information were linked using the hierarchical structure of the Metathesaurus in UMLS.

Linking the clinical vocabulary of diseases to the genes by mapping UMLS to OMIM allelic variant fields.

To link clinical vocabulary of diseases to gene entries in Online Mendelian Inheritance in Man (OMIM), we comprehensively matched diseases from Unified Medical Language System (UMLS) Metathesaurus to the OMIM text in Allelic Variant fields that describe relations between the mutations or polymorphisms of the genes and the phenotypes. Out of 1,786 genes having the field, 1,445 genes (80.9%) had matches with 2,417 types of diseases or disorders. The links are accessible at http://www.genelexpo.jp/diseases/.

A Web-based platform to find out relations between OMIC data and clinical features.

We developed a platform that visualizes all the dimensions of so-called 'OMIC' data from genomic, transcriptomic, and proteomic domains, and helps users identify interesting data dimensions that might be associated with a set of clinical features of diseases. For this, we organized the textual descriptions of Clinical Synopsis fields in OMIM (Online Mendelian Inheritance in Man) into a quantitative format, and developed a Web-based interactive and graphical search system.

Extraction of gene-disease relations from Medline using domain dictionaries and machine learning.

We describe a system that extracts disease-gene relations from Medline. We constructed a dictionary for disease and gene names from six public databases and extracted relation candidates by dictionary matching. Since dictionary matching produces a large number of false positives, we developed a method of machine learning-based named entity recognition (NER) to filter out false recognitions of disease/gene names. We found that the performance of relation extraction is heavily dependent upon the performance of NER filtering and that the filtering improves the precision of relation extraction by 26.7% at the cost of a small reduction in recall.

GenoCache: a Genomics and Cancer Chemoprevention portal.

To integrate cancer chemoprevention information on a genomics basis, we have built a Web site named GenoCache (Genomics and Cancer Chemoprevention) that would provide users with a molecular biological view of cancer chemoprevention. The site is organized in four viewpoints: substances, genes or gene products with their genetic variations, cells or tissues with various cancer development states, and "pathways" or sequential interactions between these objects. We linked the relevant genes to dbSNP.

Indexing anatomical concepts to OMIM Clinical Synopsis using the UMLS Metathesaurus.

As a first step toward the quantitative comparison of clinical features of diseases, we indexed the text descriptions in the Clinical Synopsis section of the Online Mendelian Inheritance in Man (OMIM) with concepts for the body parts, organs, and tissues contained in the Metathesaurus of the Unified Medical Language System (UMLS). We also indexed the text with the diseases and disorders having links to body parts specified in the thesaurus. The vocabulary size was approximately 177,540 representations for 81,435 concepts, and 2,161 concepts were indexed to 3,779 OMIM entries. The indexed concepts included 134 concepts for the noun forms of anatomical concepts and 985 indexed concepts for diseases and disorders that were linked to 132 and 408 anatomical concepts, respectively. We report herein that the retrieval of OMIM entries for diseases affecting specific organs can be made more comprehensive through the anatomical concepts indexed to the Clinical Synopsis or linked to the indexed concepts, as compared to simply matching organ names to the Clinical Synopsis text. The recall and precision of identifying relevant body parts in the Clinical Synopsis were calculated as 78% and 92.5%, respectively, based on random sampling. The examination of the unidentified body parts due to lack of indexed diseases and disorders showed that although most of the concepts for diseases and disorders were contained in the Metathesaurus, their relations to body parts were not. The indexing result proved the effectiveness of the Metathesaurus as a resource for the identification of concepts indicating body parts, diseases, and disorders.