Accuracy and self correction of information received from an internet breast cancer list: content analysis.

OBJECTIVES: To determine the prevalence of false or misleading statements in messages posted by internet cancer support groups and whether these statements were identified as false or misleading and corrected by other participants in subsequent postings. DESIGN: Analysis of content of postings. SETTING: Internet cancer support group Breast Cancer Mailing List. MAIN OUTCOME MEASURES: Number of false or misleading statements posted from 1 January to 23 April 2005 and whether these were identified and corrected by participants in subsequent postings. RESULTS: 10 of 4600 postings (0.22%) were found to be false or misleading. Of these, seven were identified as false or misleading by other participants and corrected within an average of four hours and 33 minutes (maximum, nine hours and nine minutes). CONCLUSIONS: Most posted information on breast cancer was accurate. Most false or misleading statements were rapidly corrected by participants in subsequent postings.

CYTOGENETIC AND DNA CONTENT ANALYSIS IN MULTIPLE MYELOMA

In this dissertation, the cytogenetic characteristics of bone marrow cells from 41 multiple myeloma patients were investigated. These cytogenetic data were correlated with the total DNA content as measured by flow cytometry. Both the cytogenetic information and DNA content were then correlated with clinical data to determine if diagnosis and prognosis of multiple myeloma could be improved.^ One hundred percent of the patients demonstrated abnormal chromosome numbers per metaphase. The average chromosome number per metaphase ranged from 42 to 49.9, with a mean of 44.99. The percent hypodiploidy ranged from 0-100% and the percent hyperdiploidy from 0-53%. Detailed cytogenetic analyses were very difficult to perform because of the paucity of mitotic figures and the poor chromosome morphology. Thus, detailed chromosome banding analysis on these patients was impossible.^ Thirty seven percent of the patients had normal total DNA content, whereas 63% had abnormal amounts of DNA (one patient with less than normal amounts and 25 patients with greater than normal amounts of DNA).^ Several clinical parameters were used in the statistical analyses: tumor burden, patient status at biopsy, patient response status, past therapy, type of treatment and percent plasma cells. Only among these clinical parameters were any statistically significant correlations found: pretreatment tumor burden versus patient response, patient biopsy status versus patient response and past therapy versus patient response.^ No correlations were found between percent hypodiploid, diploid, hyperdiploid or DNA content, and the patient response status, nor were any found between those patients with: (a) normal plasma cells, low pretreatment tumor mass burden and more than 50% of the analyzed metaphases with 46 chromosomes; (b) normal amounts of DNA, low pretreatment tumor mass burden and more than 50% of the metaphases with 46 chromosomes; (c) normal amounts of DNA and normal quantities of plasma cells; (d) abnormal amounts of DNA, abnormal amounts of plasma cells, high pretreatment tumor mass burden and less than 50% of the metaphases with 46 chromosomes.^ Technical drawbacks of both cytogenetic and DNA content analysis in these multiple myeloma patients are discussed along with the lack of correlations between DNA content and chromosome number. Refined chromosome banding analysis awaits technical improvements before we can understand which chromosome material (if any) makes up the "extra" amounts of DNA in these patients. None of the correlations tested can be used as diagnostic or prognostic aids for multiple myeloma. ^

A categorical data analysis approach to estimation of demographic characteristics for Texas county populations

The need for timely population data for health planning and Indicators of need has Increased the demand for population estimates. The data required to produce estimates is difficult to obtain and the process is time consuming. Estimation methods that require less effort and fewer data are needed. The structure preserving estimator (SPREE) is a promising technique not previously used to estimate county population characteristics. This study first uses traditional regression estimation techniques to produce estimates of county population totals. Then the structure preserving estimator, using the results produced in the first phase as constraints, is evaluated.^ Regression methods are among the most frequently used demographic methods for estimating populations. These methods use symptomatic indicators to predict population change. This research evaluates three regression methods to determine which will produce the best estimates based on the 1970 to 1980 indicators of population change. Strategies for stratifying data to improve the ability of the methods to predict change were tested. Difference-correlation using PMSA strata produced the equation which fit the data the best. Regression diagnostics were used to evaluate the residuals.^ The second phase of this study is to evaluate use of the structure preserving estimator in making estimates of population characteristics. The SPREE estimation approach uses existing data (the association structure) to establish the relationship between the variable of interest and the associated variable(s) at the county level. Marginals at the state level (the allocation structure) supply the current relationship between the variables. The full allocation structure model uses current estimates of county population totals to limit the magnitude of county estimates. The limited full allocation structure model has no constraints on county size. The 1970 county census age - gender population provides the association structure, the allocation structure is the 1980 state age - gender distribution.^ The full allocation model produces good estimates of the 1980 county age - gender populations. An unanticipated finding of this research is that the limited full allocation model produces estimates of county population totals that are superior to those produced by the regression methods. The full allocation model is used to produce estimates of 1986 county population characteristics. ^

SOCIAL AND BIOLOGICAL DETERMINANTS OF SHORT-TERM GROWTH VELOCITY AMONG PRESCHOOLERS OF RURAL GUATEMALA: A PATH ANALYSIS APPROACH (WEIGHT-GAIN, IRON DEFICIENCY, GASTROINTESTINAL SYMPTOMS)

This dissertation develops and tests through path analysis a theoretical model to explain how socioeconomic, socioenvironmental, and biologic risk factors simultaneously influence each other to further produce short-term, depressed growth in preschoolers. Three areas of risk factors were identified: child's proximal environment, maturational stage, and biological vulnerability. The theoretical model represented both the conceptual framework and the nature and direction of the hypotheses. Original research completed in 1978-80 and in 1982 provided the background data. It was analyzed first by nested-analysis of variance, followed by path analysis. The study provided evidence of mild iron deficiency and gastrointestinal symptomatology in the etiology of depressed, short-term weight gain. Also, there was evidence suggesting that family resources for material and social survival significantly contribute to the variability of short-term, age-adjusted growth velocity. These results challenge current views of unifocal intervention, whether for prevention or control. For policy formulations, though, the mechanisms underlying any set of interlaced relationships must be decoded. Theoretical formulations here proposed should be reassessed under a more extensive research design. It is suggested that studies should be undertaken where social changes are actually in progress; otherwise, nutritional epidemiology in developing countries operates somewhere between social reality and research concepts, with little grasp of its real potential. The study stresses that there is a connection between substantive theory, empirical observation, and policy issues. ^

A comparative state policy analysis of the adoption of birth defects surveillance legislation

Birth defects are the leading cause of infant mortality in the United States and are a major cause of lifetime disability. However, efforts to understand their causes have been hampered by a lack of population-specific data. During 1990–2004, 22 state legislatures responded to this need by proposing birth defects surveillance legislation (BDSL). The contrast between these states and those that did not pass BDSL provides an opportunity to better understand conditions associated with US public health policy diffusion. ^ This study identifies key state-specific determinants that predict: (1) the introduction of birth defects surveillance legislation (BDSL) onto states' formal legislative agenda, and (2) the successful adoption of these laws. Secondary aims were to interpret these findings in a theoretically sound framework and to incorporate evidence from three analytical approaches. ^ The study begins with a comparative case study of Texas and Oregon (states with divergent BDSL outcomes), including a review of historical documentation and content analysis of key informant interviews. After selecting and operationalizing explanatory variables suggested by the case study, Qualitative Comparative Analysis (QCA) was applied to publically available data to describe important patterns of variation among 37 states. Results from logistic regression were compared to determine whether the two methods produced consistent findings. ^ Themes emerging from the comparative case study included differing budgetary conditions and the significance of relationships within policy issue networks. However, the QCA and statistical analysis pointed to the importance of political parties and contrasting societal contexts. Notably, state policies that allow greater access to citizen-driven ballot initiatives were consistently associated with lower likelihood of introducing BDSL. ^ Methodologically, these results indicate that a case study approach, while important for eliciting valuable context-specific detail, may fail to detect the influence of overarching, systemic variables, such as party competition. However, QCA and statistical analyses were limited by a lack of existing data to operationalize policy issue networks, and thus may have downplayed the impact of personal interactions. ^ This study contributes to the field of health policy studies in three ways. First, it emphasizes the importance of collegial and consistent relationships among policy issue network members. Second, it calls attention to political party systems in predicting policy outcomes. Finally, a novel approach to interpreting state data in a theoretically significant manner (QCA) has been demonstrated.^

The sequence comparison index: A novel method for comparing proteins and proteomes

Historically morphological features were used as the primary means to classify organisms. However, the age of molecular genetics has allowed us to approach this field from the perspective of the organism's genetic code. Early work used highly conserved sequences, such as ribosomal RNA. The increasing number of complete genomes in the public data repositories provides the opportunity to look not only at a single gene, but at organisms' entire parts list. ^ Here the Sequence Comparison Index (SCI) and the Organism Comparison Index (OCI), algorithms and methods to compare proteins and proteomes, are presented. The complete proteomes of 104 sequenced organisms were compared. Over 280 million full Smith-Waterman alignments were performed on sequence pairs which had a reasonable expectation of being related. From these alignments a whole proteome phylogenetic tree was constructed. This method was also used to compare the small subunit (SSU) rRNA from each organism and a tree constructed from these results. The SSU rRNA tree by the SCI/OCI method looks very much like accepted SSU rRNA trees from sources such as the Ribosomal Database Project, thus validating the method. The SCI/OCI proteome tree showed a number of small but significant differences when compared to the SSU rRNA tree and proteome trees constructed by other methods. Horizontal gene transfer does not appear to affect the SCI/OCI trees until the transferred genes make up a large portion of the proteome. ^ As part of this work, the Database of Related Local Alignments (DaRLA) was created and contains over 81 million rows of sequence alignment information. DaRLA, while primarily used to build the whole proteome trees, can also be applied shared gene content analysis, gene order analysis, and creating individual protein trees. ^ Finally, the standard BLAST method for analyzing shared gene content was compared to the SCI method using 4 spirochetes. The SCI system performed flawlessly, finding all proteins from one organism against itself and finding all the ribosomal proteins between organisms. The BLAST system missed some proteins from its respective organism and failed to detect small ribosomal proteins between organisms. ^

Future pandemic influenza control (FPIC) related strategic management plan based on the 2009 H1N1 pandemic influenza review of health policy decisions, their practice and implications

This cross-sectional study is based on the qualitative and quantitative research design to review health policy decisions, their practice and implications during 2009 H1N1 influenza pandemic in the United States and globally. The “Future Pandemic Influenza Control (FPIC) related Strategic Management Plan” was developed based on the incorporation of the “National Strategy for Pandemic Influenza (2005)” for the United States from the U.S. Homeland Security Council and “The Canadian Pandemic Influenza Plan for the Health Sector (2006)” from the Canadian Pandemic Influenza Committee for use by the public health agencies in the United States as well as globally. The “global influenza experts’ survey” was primarily designed and administered via email through the “Survey Monkey” system to the 2009 H1N1 influenza pandemic experts as the study respondents. The effectiveness of this plan was confirmed and the approach of the study questionnaire was validated to be convenient and the excellent quality of the questions provided an efficient opportunity to the study respondents to evaluate the effectiveness of predefined strategies/interventions for future pandemic influenza control.^ The quantitative analysis of the responses to the Likert-scale based questions in the survey about predefined strategies/interventions, addressing five strategic issues to control future pandemic influenza. The effectiveness of strategies defined as pertinent interventions in this plan was evaluated by targeting five strategic issues regarding pandemic influenza control. For the first strategic issue pertaining influenza prevention and pre pandemic planning; the confirmed effectiveness (agreement) for strategy (1a) 87.5%, strategy (1b) 91.7% and strategy (1c) 83.3%. The assessment of the priority level for strategies to address the strategic issue no. (1); (1b (High Priority) > 1a (Medium Priority) > 1c (Low Priority) based on the available resources of the developing and developed countries. For the second Strategic Issue encompassing the preparedness and communication regarding pandemic influenza control; the confirmed effectiveness (agreement) for the strategy (2a) 95.6%, strategy (2b) 82.6%, strategy (2c) 91.3% and Strategy (2d) 87.0%. The assessment of the priority level for these strategies to address the strategic issue no. (2); (2a (highest priority) > 2c (high priority) >2d (medium priority) > 2b (low priority). For the third strategic issue encompassing the surveillance and detection of pandemic influenza; the confirmed effectiveness (agreement) for the strategy (3a) 90.9% and strategy (3b) 77.3%. The assessment of the priority level for theses strategies to address the strategic Issue No. (3) (3a (high priority) > 3b (medium/low priority). For the fourth strategic issue pertaining the response and containment of pandemic influenza; the confirmed effectiveness (agreement) for the strategy (4a) 63.6%, strategy (4b) 81.8%, strategy (4c) 86.3%, and strategy (4d) 86.4%. The assessment of the priority level for these strategies to address the strategic issue no. (4); (4d (highest priority) > 4c (high priority) > 4b (medium priority) > 4a (low priority). The fifth strategic issue about recovery from influenza and post pandemic planning; the confirmed effectiveness (agreement) for the strategy (5a) 68.2%, strategy (5b) 36.3% and strategy (5c) 40.9%. The assessment of the priority level for strategies to address the strategic issue no. (5); (5a (high priority) > 5c (medium priority) > 5b (low priority).^ The qualitative analysis of responses to the open-ended questions in the study questionnaire was performed by means of thematic content analysis. The following recurrent or common “themes” were determined for the future implementation of various predefined strategies to address five strategic issues from the “FPIC related Strategic Management Plan” to control future influenza pandemics. (1) Pre Pandemic Influenza Prevention, (2) Seasonal Influenza Control, (3) Cost Effectiveness of Non Pharmaceutical Interventions (NPI), (4) Raising Global Public Awareness, (5) Global Influenza Vaccination Campaigns, (6)Priority for High Risk Population, (7) Prompt Accessibility and Distribution of Influenza Vaccines and Antiviral Drugs, (8) The Vital Role of Private Sector, (9) School Based Influenza Containment, (10) Efficient Global Risk Communication, (11) Global Research Collaboration, (12) The Critical Role of Global Public Health Organizations, (13) Global Syndromic Surveillance and Surge Capacity and (14) Post Pandemic Recovery and Lessons Learned. The future implementation of these strategies with confirmed effectiveness to primarily “reduce the overall response time’ in the process of ‘early detection’, ‘strategies (interventions) formulation’ and their ‘implementation’ to eventually ensure the following health outcomes: (a) reduced influenza transmission, (b) prompt and effective influenza treatment and control, (c) reduced influenza related morbidity and mortality.^