The Neural Substrates of Multisensory Speech Perception

Comprehending speech is one of the most important human behaviors, but we are only beginning to understand how the brain accomplishes this difficult task. One key to speech perception seems to be that the brain integrates the independent sources of information available in the auditory and visual modalities in a process known as multisensory integration. This allows speech perception to be accurate, even in environments in which one modality or the other is ambiguous in the context of noise. Previous electrophysiological and functional magnetic resonance imaging (fMRI) experiments have implicated the posterior superior temporal sulcus (STS) in auditory-visual integration of both speech and non-speech stimuli. While evidence from prior imaging studies have found increases in STS activity for audiovisual speech compared with unisensory auditory or visual speech, these studies do not provide a clear mechanism as to how the STS communicates with early sensory areas to integrate the two streams of information into a coherent audiovisual percept. Furthermore, it is currently unknown if the activity within the STS is directly correlated with strength of audiovisual perception. In order to better understand the cortical mechanisms that underlie audiovisual speech perception, we first studied the STS activity and connectivity during the perception of speech with auditory and visual components of varying intelligibility. By studying fMRI activity during these noisy audiovisual speech stimuli, we found that STS connectivity with auditory and visual cortical areas mirrored perception; when the information from one modality is unreliable and noisy, the STS interacts less with the cortex processing that modality and more with the cortex processing the reliable information. We next characterized the role of STS activity during a striking audiovisual speech illusion, the McGurk effect, to determine if activity within the STS predicts how strongly a person integrates auditory and visual speech information. Subjects with greater susceptibility to the McGurk effect exhibited stronger fMRI activation of the STS during perception of McGurk syllables, implying a direct correlation between strength of audiovisual integration of speech and activity within an the multisensory STS.

Defining the regions of homology between human chromosome 16p12--13 and mouse chromosomes

In this study, the evolutionary relationship between human chromosome 16p12-p13 and mouse chromosomes was investigated by determining the order of marker loci in the region and then identifying the chromosomal locations of the homologous loci in mice. Eighteen genes from human 16 were mapped to fifteen subchromosomal regions by a variety of mapping approaches.^ Thirteen of the genes were mapped in the mouse. Linkage analysis with backcross mice and segregation analysis in a mouse - Chinese Hamster Ovary (CHO) somatic cell hybrid panel informative for different regions of mouse genome were used. The results assigned the thirteen genes to three different mouse chromosomes.^ A group of six genes on mouse 16 was found to be closely linked to Scid. The order of Myh11 and Mrp remains ambiguous since no recombination was detected in backcross analysis. Their relative position in human is also uncertain since they were shown to be very close to each other. For the other mouse loci, an unambiguous gene order could be determined and was found to be identical to that in human. Therefore, they comprise a new conserved linkage group between the two species. The orientation of the group was inverted relative to the centromeres, i.e. the proximal loci in one species become distal in another. The size of the group was estimated to be from 4.4 to 8 Mb and 10 to 32 cM in human. In mouse, it was about 21 cM in the backcross analysis. The two boundaries of the conserved linkage were defined within a 1 Mb range. It is now possible to predict the locations of mouse homologs for some human disease genes based on their locations on human 16p.^ The six human 16p genes that map to MMU7 showed a different gene order in mouse than in human. No recombination was found between Crym and Umod while Crym was distal to D16S79A and proximal to D16S92. The location of Stp and Cdr2 with respect to the above four loci was not determined since they were not mapped in the same set of backcross mice. These genes greatly expanded an existing conserved synteny group between the human 16p12-p13 region and the MMU7. It now consists of eleven loci that span a region of probably more than 10 Mb in human. The gene order derived from this study provided further evidence for chromosomal rearrangements within the conserved synteny. (Abstract shortened by UMI.) ^

Revising the National Ambient Air Quality Standards: The integration of science and policy

Under the Clean Air Act, Congress granted discretionary decision making authority to the Administrator of the Environmental Protection Agency (EPA). This discretionary authority involves setting standards to protect the public's health with an "adequate margin of safety" based on current scientific knowledge. The Administrator of the EPA is usually not a scientist, and for the National Ambient Air Quality Standard (NAAQS) for particulate matter (PM), the Administrator faced the task of revising a standard when several scientific factors were ambiguous. These factors included: (1) no identifiable threshold below which health effects are not manifested, (2) no biological basis to explain the reported associations between particulate matter and adverse health effects, and (3) no consensus among the members of the Clean Air Scientific Advisory Committee (CASAC) as to what an appropriate PM indicator, averaging period, or value would be for the revised standard. ^ This project recommends and demonstrates a tool, integrated assessment (IA), to aid the Administrator in making a public health policy decision in the face of ambiguous scientific factors. IA is an interdisciplinary approach to decision making that has been used to deal with complex issues involving many uncertainties, particularly climate change analyses. Two IA approaches are presented; a rough set analysis by which the expertise of CASAC members can be better utilized, and a flag model for incorporating the views of stakeholders into the standard setting process. ^ The rough set analysis can describe minimal and maximal conditions about the current science pertaining to PM and health effects. Similarly, a flag model can evaluate agreement or lack of agreement by various stakeholder groups to the proposed standard in the PM review process. ^ The use of these IA tools will enable the Administrator to (1) complete the NAAQS review in a manner that is in closer compliance with the Clean Air Act, (2) expand the input from CASAC, (3) take into consideration the views of the stakeholders, and (4) retain discretionary decision making authority. ^

Restoring mortality as a measure of community health

In the last several decades traditional community health indicators have become ambiguous and lost some of their relevance. During this same period national and international health agencies adopted new expanded definitions of Health that include underlying social determinants. These two influences are responsible for a proliferation of new health indicators and many are constructed from a combination of older mortality measures and available information on morbidity. Problems inherent in attempting to combine these sources of information have produced a situation where some indicators are difficult to calculate at the national level and may not function at all for small communities. What is needed is a relevant measure of the burden of ill health appropriate for smaller populations that is accessible to local health planners. ^ Death records are still the best available population health information. In Europe the burden of health problems is often portrayed using 'premature' death. Health agencies in the United States have moved to adopt Years of Potential Life Lost. Both these regions are also developing systems of 'avoidable' or 'preventable' death as health indicators. This research proposes a method combining these methodologies to produce a relevant indicator portraying the burden of ill health in communities. ^

Procedure for the identification of population characteristics for targeting intervention services on the basis of outcome-goal priorities: Case management services for the chronic mentally ill

Although the processes involved in rational patient targeting may be obvious for certain services, for others, both the appropriate sub-populations to receive services and the procedures to be used for their identification may be unclear. This project was designed to address several research questions which arise in the attempt to deliver appropriate services to specific populations. The related difficulties are particularly evident for those interventions about which findings regarding effectiveness are conflicting. When an intervention clearly is not beneficial (or is dangerous) to a large, diverse population, consensus regarding withholding the intervention from dissemination can easily be reached. When findings are ambiguous, however, conclusions may be impossible.^ When characteristics of patients likely to benefit from an intervention are not obvious, and when the intervention is not significantly invasive or dangerous, the strategy proposed herein may be used to identify specific characteristics of sub-populations which may benefit from the intervention. The identification of these populations may be used both in further informing decisions regarding distribution of the intervention and for purposes of planning implementation of the intervention by identifying specific target populations for service delivery.^ This project explores a method for identifying such sub-populations through the use of related datasets generated from clinical trials conducted to test the effectiveness of an intervention. The method is specified in detail and tested using the example intervention of case management for outpatient treatment of populations with chronic mental illness. These analyses were applied in order to identify any characteristics which distinguish specific sub-populations who are more likely to benefit from case management service, despite conflicting findings regarding its effectiveness for the aggregate population, as reported in the body of related research. However, in addition to a limited set of characteristics associated with benefit, the findings generated, a larger set of characteristics of patients likely to experience greater improvement without intervention. ^

THE BACON CHOW STUDY: THE RELATIONSHIP BETWEEN INFECTIOUS ILLNESS AND GROWTH OF INFANTS

Multiple dietary deficiencies and high rates of infectious illness are major health problems leading to malnutrition and limitation of growth of children in developing countries. Longitudinal studies which provide information on illness incidence and growth velocity are needed in order to untangle the complex interrelationship between nutrition, illness and growth. From 1967 to 1973, researchers led by Dr. Bacon Chow of the Johns Hopkins University School of Hygiene undertook a quasi-experimental prospective study in Suilin Township, Taiwan to determine the effects of a nutritional supplement to the diets of pregnant and lactating women on the growth, development and resistance to disease of their offspring. This dissertation presents results from the analysis of infant morbidity and postnatal growth.^ Maternal nutritional supplementation has no apparent effect on the postnatal growth or morbidity of infants. Significant sex differences exist in growth response to illness and in illness susceptibility. Male infants have more diarrhea and upper respiratory illness. Respiratory illness is positively associated with growth rate in weight in the first semester of life. Diarrhea is significantly negatively associated with growth in length in the second semester. Small-for-date infants are more susceptible to illness in general and have a different pattern of growth response than large-for-date infants.^ Principal components analysis of illness data is shown to be an effective technique for making more precise use of ambiguous morbidity data. Multiple regression with component scores is an accurate method for estimating variance in growth rate predicted by indepenent illness variables. A model is advanced in which initial postnatal growth rate determines subsequent susceptibility to nutritional stress and infection. Initial growth rate is a function of prenatal nutrition, but is not significantly affected by maternal supplementation during gestation or lactation. Critical evaluation is made of nutritional supplementation programs which do not afford disease control.^

Errors in the administration of medication in inpatient hospitals: A systematic review of the research literature on commercial computerized physician order entry systems

Errors in the administration of medication represent a significant loss of medical resources and pose life altering or life threatening risks to patients. This paper considered the question, what impact do Computerized Physician Order Entry (CPOE) systems have on medication errors in the hospital inpatient environment? Previous reviews have examined evidence of the impact of CPOE on medication errors, but have come to ambiguous conclusions as to the impact of CPOE and decision support systems (DSS). Forty-three papers were identified. Thirty-one demonstrated a significant reduction in prescribing error rates for all or some drug types; decreases in minor errors were most often reported. Several studies reported increases in the rate of duplicate orders and failures to remove contraindicated drugs, often attributed to inappropriate design or to an inability to operate the system properly. The evidence on the effectiveness of CPOE to reduce errors in medication administration is compelling though it is limited by modest study sample sizes and designs. ^

The epidemiology of left ventricular outflow tract obstruction defects in Texas, 2002-2008: An update and assessment of effect heterogeneity

Left ventricular outflow tract (LVOT) defects are an important group of congenital heart defects (CHDs) because of their associated mortality and long-term complications. LVOT defects include aortic valve stenosis (AVS), coarctation of aorta (CoA), and hypoplastic left heart syndrome (HLHS). Despite their clinical significance, their etiology is not completely understood. Even though the individual component phenotypes (AVS, CoA, and HLHS) may have different etiologies, they are often "lumped" together in epidemiological studies. Though "lumping" of component phenotypes may improve the power to detect associations, it may also lead to ambiguous findings if these defects are etiologically distinct. This is due to potential for effect heterogeneity across component phenotypes. ^ This study had two aims: (1) to identify the association between various risk factors and both the component (i.e., split) and composite (i.e., lumped) LVOT phenotypes, and (2) to assess the effect heterogeneity of risk factors across component phenotypes of LVOT defects. ^ This study was a secondary data analysis. Primary data were obtained from the Texas Birth Defect Registry (TBDR). TBDR uses an active surveillance method to ascertain birth defects in Texas. All cases of non complex LVOT defects which met our inclusion criteria during the period of 2002–2008 were included in the study. The comparison groups included all unaffected live births for the same period (2002–2008). Data from vital statistics were used to evaluate associations. Statistical associations between selected risk factors and LVOT defects was determined by calculating crude and adjusted prevalence ratio using Poisson regression analysis. Effect heterogeneity was evaluated using polytomous logistic regression. ^ There were a total of 2,353 cases of LVOT defects among 2,730,035 live births during the study period. There were a total of 1,311 definite cases of non-complex LVOT defects for analysis after excluding "complex" cardiac cases and cases associated with syndromes (n=168). Among infant characteristics, males were at a significantly higher risk of developing LVOT defects compared to females. Among maternal characteristics, significant associations were seen with maternal age > 40 years (compared to maternal age 20–24 years) and maternal residence in Texas-Mexico border (compared to non-border residence). Among birth characteristics, significant associations were seen with preterm birth and small for gestation age LVOT defects. ^ When evaluating effect heterogeneity, the following variables had significantly different effects among the component LVOT defect phenotypes: infant sex, plurality, maternal age, maternal race/ethnicity, and Texas-Mexico border residence. ^ This study found significant associations between various demographic factors and LVOT defects. While many findings from this study were consistent with results from previous studies, we also identified new factors associated with LVOT defects. Additionally, this study was the first to assess effect heterogeneity across LVOT defect component phenotypes. These findings contribute to a growing body of literature on characteristics associated with LVOT defects. ^

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.

Formalizing a Conceptual Framework of Work Domain Knowledge

Background: The failure rate of health information systems is high, partially due to fragmented, incomplete, or incorrect identification and description of specific and critical domain requirements. In order to systematically transform the requirements of work into real information system, an explicit conceptual framework is essential to summarize the work requirements and guide system design. Recently, Butler, Zhang, and colleagues proposed a conceptual framework called Work Domain Ontology (WDO) to formally represent users’ work. This WDO approach has been successfully demonstrated in a real world design project on aircraft scheduling. However, as a top level conceptual framework, this WDO has not defined an explicit and well specified schema (WDOS) , and it does not have a generalizable and operationalized procedure that can be easily applied to develop WDO. Moreover, WDO has not been developed for any concrete healthcare domain. These limitations hinder the utility of WDO in real world information system in general and in health information system in particular. Objective: The objective of this research is to formalize the WDOS, operationalize a procedure to develop WDO, and evaluate WDO approach using Self-Nutrition Management (SNM) work domain. Method: Concept analysis was implemented to formalize WDOS. Focus group interview was conducted to capture concepts in SNM work domain. Ontology engineering methods were adopted to model SNM WDO. Part of the concepts under the primary goal “staying healthy” for SNM were selected and transformed into a semi-structured survey to evaluate the acceptance, explicitness, completeness, consistency, experience dependency of SNM WDO. Result: Four concepts, “goal, operation, object and constraint”, were identified and formally modeled in WDOS with definitions and attributes. 72 SNM WDO concepts under primary goal were selected and transformed into semi-structured survey questions. The evaluation indicated that the major concepts of SNM WDO were accepted by 41 overweight subjects. SNM WDO is generally independent of user domain experience but partially dependent on SNM application experience. 23 of 41 paired concepts had significant correlations. Two concepts were identified as ambiguous concepts. 8 extra concepts were recommended towards the completeness of SNM WDO. Conclusion: The preliminary WDOS is ready with an operationalized procedure. SNM WDO has been developed to guide future SNM application design. This research is an essential step towards Work-Centered Design (WCD).