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. ^

Evaluation of therapist and client language in Motivational Interviewing (MI) sessions: A secondary analysis of data from the Southern Methodist Alcohol Research Trial (SMART) study

In the United States, “binge” drinking among college students is an emerging public health concern due to the significant physical and psychological effects on young adults. The focus is on identifying interventions that can help decrease high-risk drinking behavior among this group of drinkers. One such intervention is Motivational interviewing (MI), a client-centered therapy that aims at resolving client ambivalence by developing discrepancy and engaging the client in change talk. Of late, there is a growing interest in determining the active ingredients that influence the alliance between the therapist and the client. This study is a secondary analysis of the data obtained from the Southern Methodist Alcohol Research Trial (SMART) project, a dismantling trial of MI and feedback among heavy drinking college students. The present project examines the relationship between therapist and client language in MI sessions on a sample of “binge” drinking college students. Of the 126 SMART tapes, 30 tapes (‘MI with feedback’ group = 15, ‘MI only’ group = 15) were randomly selected for this study. MISC 2.1, a mutually exclusive and exhaustive coding system, was used to code the audio/videotaped MI sessions. Therapist and client language were analyzed for communication characteristics. Overall, therapists adopted a MI consistent style and clients were found to engage in change talk. Counselor acceptance, empathy, spirit, and complex reflections were all significantly related to client change talk (p-values ranged from 0.001 to 0.047). Additionally, therapist ‘advice without permission’ and MI Inconsistent therapist behaviors were strongly correlated with client sustain talk (p-values ranged from 0.006 to 0.048). Simple linear regression models showed a significant correlation between MI consistent (MICO) therapist language (independent variable) and change talk (dependent variable) and MI inconsistent (MIIN) therapist language (independent variable) and sustain talk (dependent variable). The study has several limitations such as small sample size, self-selection bias, poor inter-rater reliability for the global scales and the lack of a temporal measure of therapist and client language. Future studies might consider a larger sample size to obtain more statistical power. In addition the correlation between therapist language, client language and drinking outcome needs to be explored.^

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.

The relationship between risk perception and ethnicity as an explanation for late stage skin cancer diagnosis in Black and Hispanic populations: An analysis using data from the 2005 Health Information and National Trends Survey

Objective. The purpose of this study was to determine the relationship between ethnicity and skin cancer risk perception while controlling for other risk factors: education, gender, age, access to healthcare, family history of skin cancer, fear, and worry. ^ Methods. This study utilized the Health Information National Trends Survey (HINTS) dataset, a nationally representative sample of 5,586 individuals 18 years of age or older. One third of the respondents were chosen at random and asked questions involving skin cancer. Analysis was based on questions that identified skin cancer risk perception, fear of finding skin cancer, and frequency of worry about skin cancer and a variety of sociodemographic factors. ^ Results. Ethnicity had a significant impact on risk perception scores while controlling for other risk factors. Other risk factors that also had a significant impact on risk perception scores included family history of skin cancer, age, and worry. ^

Data Accuracy in Medical Record Abstraction

Clinical Research Data Quality Literature Review and Pooled Analysis We present a literature review and secondary analysis of data accuracy in clinical research and related secondary data uses. A total of 93 papers meeting our inclusion criteria were categorized according to the data processing methods. Quantitative data accuracy information was abstracted from the articles and pooled. Our analysis demonstrates that the accuracy associated with data processing methods varies widely, with error rates ranging from 2 errors per 10,000 files to 5019 errors per 10,000 fields. Medical record abstraction was associated with the highest error rates (70–5019 errors per 10,000 fields). Data entered and processed at healthcare facilities had comparable error rates to data processed at central data processing centers. Error rates for data processed with single entry in the presence of on-screen checks were comparable to double entered data. While data processing and cleaning methods may explain a significant amount of the variability in data accuracy, additional factors not resolvable here likely exist. Defining Data Quality for Clinical Research: A Concept Analysis Despite notable previous attempts by experts to define data quality, the concept remains ambiguous and subject to the vagaries of natural language. This current lack of clarity continues to hamper research related to data quality issues. We present a formal concept analysis of data quality, which builds on and synthesizes previously published work. We further posit that discipline-level specificity may be required to achieve the desired definitional clarity. To this end, we combine work from the clinical research domain with findings from the general data quality literature to produce a discipline-specific definition and operationalization for data quality in clinical research. While the results are helpful to clinical research, the methodology of concept analysis may be useful in other fields to clarify data quality attributes and to achieve operational definitions. Medical Record Abstractor’s Perceptions of Factors Impacting the Accuracy of Abstracted Data Medical record abstraction (MRA) is known to be a significant source of data errors in secondary data uses. Factors impacting the accuracy of abstracted data are not reported consistently in the literature. Two Delphi processes were conducted with experienced medical record abstractors to assess abstractor’s perceptions about the factors. The Delphi process identified 9 factors that were not found in the literature, and differed with the literature by 5 factors in the top 25%. The Delphi results refuted seven factors reported in the literature as impacting the quality of abstracted data. The results provide insight into and indicate content validity of a significant number of the factors reported in the literature. Further, the results indicate general consistency between the perceptions of clinical research medical record abstractors and registry and quality improvement abstractors. Distributed Cognition Artifacts on Clinical Research Data Collection Forms Medical record abstraction, a primary mode of data collection in secondary data use, is associated with high error rates. Distributed cognition in medical record abstraction has not been studied as a possible explanation for abstraction errors. We employed the theory of distributed representation and representational analysis to systematically evaluate cognitive demands in medical record abstraction and the extent of external cognitive support employed in a sample of clinical research data collection forms. We show that the cognitive load required for abstraction in 61% of the sampled data elements was high, exceedingly so in 9%. Further, the data collection forms did not support external cognition for the most complex data elements. High working memory demands are a possible explanation for the association of data errors with data elements requiring abstractor interpretation, comparison, mapping or calculation. The representational analysis used here can be used to identify data elements with high cognitive demands.

A process evaluation of a health literacy intervention targeting pediatric providers' communication skills at the Texas Children's Health Plan

Background. Health literacy is an important determinant for quality health care, and affects communication between patients and physicians. Poor communication may result in negative effects in health. Improved communication between patients and physicians could positively affect health outcomes. Communication skills are teachable.^ Objectives. (1) to evaluate the process involved in the design and implementation of a health literacy intervention targeting pediatric providers’ communication skills at the Texas Children’s Health Plan in Houston, Texas; and (2) to describe lessons learned from this process that may be used in future attempts to address the issue of health literacy and health communication. ^ Design/methods. The process evaluation of the implementation of a health literacy strategy at the Texas Children’s Health Plan (TCHP) consisted of a critical analysis of all documents and minutes from meetings of the team of investigators. It also involved a secondary analysis of data collected between December 2006 and June 2007. Descriptive statistics, paired t-test and Wilcoxon-signed-rank test were employed in analyzing the data. This information was complemented with a limited review of existing literature on communication skills training programs. ^ Results. The design of the educational intervention followed recommendations from experts in the field of health literacy. The delivery of the intervention was possible and benefited from existing resources and logistics within the TCHP. Very few targeted providers participated in two offerings of the workshop (6.6% and 1.7% respectively). After the educational intervention, providers showed increased knowledge of health literacy facts and its effects in health (p=0.001); increased awareness of the low health literacy problem (p=0.003); increased expectations for change in practice (p=0.002), and intent to use health literacy strategies for communication immediately following the intervention (p=0.001). Low participation indicated the need for further investigation of barriers to, and means for successful implementation of programs aimed to improving health communication. ^ Conclusions. A short, focused intervention utilizing health literacy strategies for communication appeared effective in increasing knowledge and intentions for change in a small group of pediatric providers. ^

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.^