THE INTERACTION BETWEEN INTERNAL AND EXTERNAL INFORMATION ON RELATIONAL DATA SEARCH

People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.

Using citation data to improve retrieval from MEDLINE.

OBJECTIVE: To determine whether algorithms developed for the World Wide Web can be applied to the biomedical literature in order to identify articles that are important as well as relevant. DESIGN AND MEASUREMENTS A direct comparison of eight algorithms: simple PubMed queries, clinical queries (sensitive and specific versions), vector cosine comparison, citation count, journal impact factor, PageRank, and machine learning based on polynomial support vector machines. The objective was to prioritize important articles, defined as being included in a pre-existing bibliography of important literature in surgical oncology. RESULTS Citation-based algorithms were more effective than noncitation-based algorithms at identifying important articles. The most effective strategies were simple citation count and PageRank, which on average identified over six important articles in the first 100 results compared to 0.85 for the best noncitation-based algorithm (p < 0.001). The authors saw similar differences between citation-based and noncitation-based algorithms at 10, 20, 50, 200, 500, and 1,000 results (p < 0.001). Citation lag affects performance of PageRank more than simple citation count. However, in spite of citation lag, citation-based algorithms remain more effective than noncitation-based algorithms. CONCLUSION Algorithms that have proved successful on the World Wide Web can be applied to biomedical information retrieval. Citation-based algorithms can help identify important articles within large sets of relevant results. Further studies are needed to determine whether citation-based algorithms can effectively meet actual user information needs.

A day in the life of PubMed: analysis of a typical day's query log.

OBJECTIVE: To characterize PubMed usage over a typical day and compare it to previous studies of user behavior on Web search engines. DESIGN: We performed a lexical and semantic analysis of 2,689,166 queries issued on PubMed over 24 consecutive hours on a typical day. MEASUREMENTS: We measured the number of queries, number of distinct users, queries per user, terms per query, common terms, Boolean operator use, common phrases, result set size, MeSH categories, used semantic measurements to group queries into sessions, and studied the addition and removal of terms from consecutive queries to gauge search strategies. RESULTS: The size of the result sets from a sample of queries showed a bimodal distribution, with peaks at approximately 3 and 100 results, suggesting that a large group of queries was tightly focused and another was broad. Like Web search engine sessions, most PubMed sessions consisted of a single query. However, PubMed queries contained more terms. CONCLUSION: PubMed's usage profile should be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.

UNSUPERVISED INDEXING OF MEDLINE ARTICLES THROUGH GRAPH-BASED RANKING

The biomedical literature is extensively catalogued and indexed in MEDLINE. MEDLINE indexing is done by trained human indexers, who identify the most important concepts in each article, and is expensive and inconsistent. Automating the indexing task is difficult: the National Library of Medicine produces the Medical Text Indexer (MTI), which suggests potential indexing terms to the indexers. MTI’s output is not good enough to work unattended. In my thesis, I propose a different way to approach the indexing task called MEDRank. MEDRank creates graphs representing the concepts in biomedical articles and their relationships within the text, and applies graph-based ranking algorithms to identify the most important concepts in each article. I evaluate the performance of several automated indexing solutions, including my own, by comparing their output to the indexing terms selected by the human indexers. MEDRank outperformed all other evaluated indexing solutions, including MTI, in general indexing performance and precision. MEDRank can be used to cluster documents, index any kind of biomedical text with standard vocabularies, or could become part of MTI itself.

A PROCESS FOR ACHIEVING COMPARABLE DATA FROM HETEROGENEOUS DATABASES

The current state of health and biomedicine includes an enormity of heterogeneous data ‘silos’, collected for different purposes and represented differently, that are presently impossible to share or analyze in toto. The greatest challenge for large-scale and meaningful analyses of health-related data is to achieve a uniform data representation for data extracted from heterogeneous source representations. Based upon an analysis and categorization of heterogeneities, a process for achieving comparable data content by using a uniform terminological representation is developed. This process addresses the types of representational heterogeneities that commonly arise in healthcare data integration problems. Specifically, this process uses a reference terminology, and associated "maps" to transform heterogeneous data to a standard representation for comparability and secondary use. The capture of quality and precision of the “maps” between local terms and reference terminology concepts enhances the meaning of the aggregated data, empowering end users with better-informed queries for subsequent analyses. A data integration case study in the domain of pediatric asthma illustrates the development and use of a reference terminology for creating comparable data from heterogeneous source representations. The contribution of this research is a generalized process for the integration of data from heterogeneous source representations, and this process can be applied and extended to other problems where heterogeneous data needs to be merged.

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

The location of majority and minority populations with respect to commercial treatment, storage, and disposal facilities in Texas

There is a growing interest in the location of Treatment, Storage, and Disposal (TSDF) sites in relation to minority communities. A number of studies have been completed, and the results of these studies have been varied. Some of the studies have shown a strong positive correlation between the location of TSDF sites and minority populations, while a few have shown no significance in that relationship. The major difference between these studies has been in the areal unit used.^ This study compared the minority populations of Texas census tracts and ZIP codes containing a TSDF using the associated county as the comparison population. The hypothesis of this study was that there was no difference between using census tracts and ZIP codes to analyze the relationship of minority populations and TSDF's. The census data used was from 1990, and the initial list of TSDF sites was supplied by the Texas Natural Resource Conservation Commission. The TSDF site locations were checked using graphical information systems (GIS) programs, in order to increase the accuracy of the identity of exposed ZIP codes and census tracts. The minority populations of the exposed areal units were compared using proportional differences, crosstables, maps, and logistic regression. The dependent variable used was the exposure status of the areal units under study, including counties, census tracts, and ZIP codes. The independent variables used included minority group proportion and grouping of the proportions, educational status, household income, and home value.^ In all cases, education was significant or near significant at the.05 level. Education rather than minority proportion was therefore the most significant predictor of the exposure status of a census tract or ZIP code. ^

A MANAGEMENT INFORMATION SYSTEM AND EVALUATION SCHEME FOR THE UNIVERSITY OF TEXAS EMPLOYEE ASSISTANCE PROGRAMS

Early Employee Assistance Programs (EAPs) had their origin in humanitarian motives, and there was little concern for their cost/benefit ratios; however, as some programs began accumulating data and analyzing it over time, even with single variables such as absenteeism, it became apparent that the humanitarian reasons for a program could be reinforced by cost savings particularly when the existence of the program was subject to justification.^ Today there is general agreement that cost/benefit analyses of EAPs are desirable, but the specific models for such analyses, particularly those making use of sophisticated but simple computer based data management systems, are few.^ The purpose of this research and development project was to develop a method, a design, and a prototype for gathering managing and presenting information about EAPS. This scheme provides information retrieval and analyses relevant to such aspects of EAP operations as: (1) EAP personnel activities, (2) Supervisory training effectiveness, (3) Client population demographics, (4) Assessment and Referral Effectiveness, (5) Treatment network efficacy, (6) Economic worth of the EAP.^ This scheme has been implemented and made operational at The University of Texas Employee Assistance Programs for more than three years.^ Application of the scheme in the various programs has defined certain variables which remained necessary in all programs. Depending on the degree of aggressiveness for data acquisition maintained by program personnel, other program specific variables are also defined. ^

Information bias and lifetime mortality risks of radiation-induced cancer

Additive and multiplicative models of relative risk were used to measure the effect of cancer misclassification and DS86 random errors on lifetime risk projections in the Life Span Study (LSS) of Hiroshima and Nagasaki atomic bomb survivors. The true number of cancer deaths in each stratum of the cancer mortality cross-classification was estimated using sufficient statistics from the EM algorithm. Average survivor doses in the strata were corrected for DS86 random error ($\sigma$ = 0.45) by use of reduction factors. Poisson regression was used to model the corrected and uncorrected mortality rates with covariates for age at-time-of-bombing, age at-time-of-death and gender. Excess risks were in good agreement with risks in RERF Report 11 (Part 2) and the BEIR-V report. Bias due to DS86 random error typically ranged from $-$15% to $-$30% for both sexes, and all sites and models. The total bias, including diagnostic misclassification, of excess risk of nonleukemia for exposure to 1 Sv from age 18 to 65 under the non-constant relative projection model was $-$37.1% for males and $-$23.3% for females. Total excess risks of leukemia under the relative projection model were biased $-$27.1% for males and $-$43.4% for females. Thus, nonleukemia risks for 1 Sv from ages 18 to 85 (DRREF = 2) increased from 1.91%/Sv to 2.68%/Sv among males and from 3.23%/Sv to 4.02%/Sv among females. Leukemia excess risks increased from 0.87%/Sv to 1.10%/Sv among males and from 0.73%/Sv to 1.04%/Sv among females. Bias was dependent on the gender, site, correction method, exposure profile and projection model considered. Future studies that use LSS data for U.S. nuclear workers may be downwardly biased if lifetime risk projections are not adjusted for random and systematic errors. (Supported by U.S. NRC Grant NRC-04-091-02.) ^

HPV knowledge, HPV vaccine awareness and initiation among Hispanics: The role of language, information seeking, and information scanning

Background. Among Hispanics, the HPV vaccine has the potential to eliminate disparities in cervical cancer incidence and mortality but only if optimal rates of vaccination are achieved. Media can be an important information source for increasing HPV knowledge and awareness of the vaccine. Very little is known about how media use among Hispanics affects their HPV knowledge and vaccine awareness. Even less is known about what differences exist in media use and information processing among English- and Spanish-speaking Hispanics.^ Aims. Examine the relationships between three health communication variables (media exposure, HPV-specific information scanning and seeking) and three HPV outcomes (knowledge, vaccine awareness and initiation) among English- and Spanish-speaking Hispanics.^ Methods. Cross-sectional data from a survey administered to Hispanic mothers in Dallas, Texas was used for univariate and multivariate logistic regression analyses. Sample used for analysis included 288 mothers of females aged 8-22 recruited from clinics and community events. Dependent variables of interest were HPV knowledge, HPV vaccine awareness and initiation. Independent variables were media exposure, HPV-specific information scanning and seeking. Language was tested as an effect modifier on the relationship between health communication variables and HPV outcomes.^ Results. English-speaking mothers reported more media exposure, HPV-specific information scanning and seeking than Spanish-speakers. Scanning for HPV information was associated with more HPV knowledge (OR = 4.26, 95% CI = 2.41 - 7.51), vaccine awareness (OR = 10.01, 95% CI = 5.43 - 18.47) and vaccine initiation (OR = 2.54, 95% CI = 1.09 - 5.91). Seeking HPV-specific information was associated with more knowledge (OR = 2.27, 95% CI = 1.23 - 4.16), awareness (OR = 6.60, 95% CI = 2.74 - 15.91) and initiation (OR = 4.93, 95% CI = 2.64 - 9.20). Language moderated the effect of information scanning and seeking on vaccine awareness.^ Discussion. Differences in information scanning and seeking behaviors among Hispanic subgroups have the potential to lead to disparities in vaccine awareness.^ Conclusion. Findings from this study underscore health communication differences among Hispanics and emphasize the need to target Spanish language media as well as English language media aimed at Hispanics to improve knowledge and awareness.^

STUDIES ON CHOLINERGIC FUNCTION AND MEMORY IN MICE (CHOLINOTOXINS, WORKING, REFERENCE MEMORY, RADIAL ARM MAZE)

Considerable evidence suggests that central cholinergic neurons participate in either acquisition, storage or retrieval of information. Experiments were designed to evaluate information processing in mice following either reversible or irreversible impairment in central cholinergic activity. The cholinergic receptor antagonists, atropine and methylatropine were used to reversibly inhibit cholinergic transmission. Irreversible impairment in central cholinergic function was achieved by central administration of the cholinergic-specific neurotoxins, N-ethyl-choline aziridinium (ECA) and N-ethyl-acetylcholine aziridinium (EACA).^ ECA and EACA appear to act by irreversible inhibition of high affinity choline uptake (proposed rate-limiting step in acetylcholine synthesis). Intraventricular administration of ECA or EACA produced persistent reduction in hippocampal choline acetyltransferase activity. Other neuronal systems and brain regions showed no evidence of toxicity.^ Mice treated with either ECA or EACA showed behavioral deficits associated with cholinergic dysfunction. Passive avoidance behavior was significantly impaired by cholinotoxin treatment. Radial arm maze performance was also significantly impaired in cholinotoxin-treated animals. Deficits in radial arm maze performance were transient, however, such that rapid and apparent complete behavioral recovery was seen during retention testing. The centrally active cholinergic receptor antagonist atropine also caused significant impairment in radial arm maze behavior, while equivalent doses of methylatropine were without effect.^ The relative effects of cholinotoxin and receptor antagonist treatment on short-term (working) memory and long-term (reference) memory in radial arm maze behavior were examined. Maze rotation studies indicated that there were at least two different response strategies which could result in accurate maze performance. One strategy involved the use of response algorithms and was considered to be a function of reference memory. Another strategy appeared to be primarily dependent on spatial working memory. However, all behavioral paradigms with multiple trails have reference memory requirements (i.e. information useful over all trials). Performance was similarly affected following either cholinotoxin or anticholinergic treatment, regardless of the response strategy utilized. In addition, rates of behavioral recovery following cholinotoxin treatment were similar between response groups. It was concluded that both cholinotoxin and anticholinergic treatment primarily resulted in impaired reference memory processes. ^