PREPAID MENTAL HEALTH SERVICES: A NATIONAL PERSPECTIVE

The purpose of this 1982 national survey of all operational prepaid health plans, or PHPs (including health maintenance organizations), was to provide information on the current coverage of PHP mental health and substance abuse services, benefits and service provision, general and mental health organization characteristics, mental health service costs, and physical and mental health service utilization.^ Two survey instruments were designed, pretested and distributed to all operational PHPs throughout the United States. A total of 237 PHPs were surveyed, of which 205 (86.50 percent) completed and returned both questionnaires.^ One result of the rapid growth in the PHP field over the past ten years has been the expansion in both the number of PHPs as well as the organizational characteristics of these PHPs. However, little attention in the research literature has been given to the application of empirical results to the PHP arrangements. This project has attempted to contribute to current knowledge regarding prepaid mental health services from a national perspective, and explore, on a preliminary descriptive basis, the variety of potential service delivery arrangements for physical and mental health services (total services) and for mental health services.^ The study emphasized that PHPs must continue to monitor the costs and utilization of mental health services, particularly in light of the apparent elimination of data collection and statistical summary responsibilities within the federal government regarding PHP activities as well as the proposed legislation to eliminate mandated mental health and substance abuse services from basic health plan benefits for federally qualified PHPs. ^

Understanding Impediments and Enablers to Physical Activity among African American Adults: A Systematic Review of Qualitative Studies

Objective: To systematically assess and summarize impediments and facilitating factors impacting physical activity participation among African American Adults. ^ Method: A systematic search of the literature was conducted, which included electronic databases, as well as reference list of relevant papers. Only qualitative studies which measured race and ethnicity and had African American as adult participants were included. The main themes and categories from the qualitative studies pertaining to impediments and facilitators to physical activity were identified and summarized, through descriptive meta-synthesis. ^ Result: Twenty nine qualitative studies were included. Twenty-one of the studies only focused on adult African American women, and the barriers and facilitators to physical activity as perceived by them. The biggest individual enabler towards physical activity was the positive health benefits associated with regular physical activity. Social support and easy access to parks and facilities were also identified as enablers. Barriers toward physical activity were lack of time, lack of motivation, long work hours, and physical disabilities. ^ Conclusions: The findings of this review study should be useful to those planning an intervention in African American communities. There is also a need for qualitative studies conducted only among African American men, to better understand their perspective on the facilitators and barriers to physical activity.^

A health disparities perspective on developing emerging infectious disease preparedness

A systematic review of the literature yielded 10 articles that explored the interaction between race/ethnicity, citizenship, socioeconomic status, and health literacy domains with respect to preparedness agenda development. Current emerging infectious disease (EID) preparedness plans do not adequately address the needs of vulnerable populations for the events before, during, and after an epidemic. Central to the disadvantage of most vulnerable populations are various health disparity domains that persist as barriers for individuals and communities alike to engage in preparedness efforts. Seven out of the ten articles discussed the importance of including health disparity domains in preparedness policy. Two proposed frameworks for an emerging infectious disease framework that considers health disparities are presented in this study. ^ Framework 1 is beneficial for the evaluation phase after a disaster has struck and preparedness efforts have been initiated. It considers several existing disparities and remediation strategies at the individual, community, and system levels to reach adequate restructuring of preparedness aims. Framework 2 serves as a "how to" carry out preparedness during a disaster event. It is a revision of a framework proposed by Blumenshine et al. (2008) and explores those characteristics central to pandemic preparedness plan development/deployment. Although two frameworks were devised, no one framework will adequately address the needs of vulnerable populations during an epidemic. However, the two frameworks propose to demonstrate the inclusion of important health disparity domains in preparedness plan development. ^ The National Consensus Panel for Emergency Preparedness and Cultural Diversity has released guidelines that are considered the leading strategies necessary to reorient preparedness infrastructure. In order for vulnerable populations to benefit from ample protection during a disaster, inclusion of health disparity domains in the development phases of preparedness must occur prior to full deployment in communities. Although "promising practices" and other methods at the frontier of exploring these multidimensional constraints has entered the research arena, new studies on adequate preparedness merit further investigation and support.^

Access to oral care --- A systematic review of a continuing public health issue among older adults

Oral health is essential for the general well being of the individual and collectively for the health of the population. Oral health can be maintained by routine dental care and visits to dental professionals, but accessing professional dental care may be a continuing difficulty in vulnerable older adult population. Many older adults are not frequent users of dental care, though oral health is crucial to their well-being and overall health. Access to care is the timely use of personal health services to achieve the best possible health outcomes. ^ Objectives: The aims of this review are to (i) to analyze and elucidate the relationship between socio-economic disparities in gender, ethnicity, poverty status, education and the continuing public issue of access to oral care, (ii) to identify the underlying causes through which these factors can affect access to oral care. This review will provide a knowledgeable basis for development of interventions to provide adequate access to oral care in older adults and implementing policies to ensure access to oral care; through highlighting the various socio economic factors that affect access to oral care among older adults. ^ Methods: This paper used a purposeful review of literature on socioeconomic disparities in access to oral care among older adults. The references considered in this review included all the relevant articles, surveys and reports published in English language, since the year 1985 to 2010, in the United States. The articles selected were scrutinized for relevancy to the topic of access to oral care and which included discussions of the effects of gender, ethnicity, poverty status, educational status in accessing oral care. ^ Results: Evidence confirmed the continuing disparity in access to oral care among older adults. The possible links identified were gender inequality, ethnic differences, income levels and educational differences affecting access to oral care. The underlying causes linking these factors with access to oral care were established. ^ Conclusion: The analysis of the literature review findings supported the prevalence of disparities in gender, ethnicity, income and education with its possible links affecting access to oral care. The underlying causes helped to understand the reasons behind this growing issue of inaccessible oral care. Further research is needed to develop policies and target dental public health efforts towards specific problem areas ensuring equitable access to oral services and consequently, improve the health of older adults.^

POPULATION CODING IN LAMINAR CORTICAL CIRCUITS

One of the fundamental questions in neuroscience is to understand how encoding of sensory inputs is distributed across neuronal networks in cerebral cortex to influence sensory processing and behavioral performance. The fact that the structure of neuronal networks is organized according to cortical layers raises the possibility that sensory information could be processed differently in distinct layers. The goal of my thesis research is to understand how laminar circuits encode information in their population activity, how the properties of the population code adapt to changes in visual input, and how population coding influences behavioral performance. To this end, we performed a series of novel experiments to investigate how sensory information in the primary visual cortex (V1) emerges across laminar cortical circuits. First, it is commonly known that the amount of information encoded by cortical circuits depends critically on whether or not nearby neurons exhibit correlations. We examined correlated variability in V1 circuits from a laminar-specific perspective and observed that cells in the input layer, which have only local projections, encode incoming stimuli optimally by exhibiting low correlated variability. In contrast, output layers, which send projections to other cortical and subcortical areas, encode information suboptimally by exhibiting large correlations. These results argue that neuronal populations in different cortical layers play different roles in network computations. Secondly, a fundamental feature of cortical neurons is their ability to adapt to changes in incoming stimuli. Understanding how adaptation emerges across cortical layers to influence information processing is vital for understanding efficient sensory coding. We examined the effects of adaptation, on the time-scale of a visual fixation, on network synchronization across laminar circuits. Specific to the superficial layers, we observed an increase in gamma-band (30-80 Hz) synchronization after adaptation that was correlated with an improvement in neuronal orientation discrimination performance. Thus, synchronization enhances sensory coding to optimize network processing across laminar circuits. Finally, we tested the hypothesis that individual neurons and local populations synchronize their activity in real-time to communicate information about incoming stimuli, and that the degree of synchronization influences behavioral performance. These analyses assessed for the first time the relationship between changes in laminar cortical networks involved in stimulus processing and behavioral performance.

NOVEL PHANTOMS AND POST-PROCESSING FOR DIFFUSION SPECTRUM IMAGING

High Angular Resolution Diffusion Imaging (HARDI) techniques, including Diffusion Spectrum Imaging (DSI), have been proposed to resolve crossing and other complex fiber architecture in the human brain white matter. In these methods, directional information of diffusion is inferred from the peaks in the orientation distribution function (ODF). Extensive studies using histology on macaque brain, cat cerebellum, rat hippocampus and optic tracts, and bovine tongue are qualitatively in agreement with the DSI-derived ODFs and tractography. However, there are only two studies in the literature which validated the DSI results using physical phantoms and both these studies were not performed on a clinical MRI scanner. Also, the limited studies which optimized DSI in a clinical setting, did not involve a comparison against physical phantoms. Finally, there is lack of consensus on the necessary pre- and post-processing steps in DSI; and ground truth diffusion fiber phantoms are not yet standardized. Therefore, the aims of this dissertation were to design and construct novel diffusion phantoms, employ post-processing techniques in order to systematically validate and optimize (DSI)-derived fiber ODFs in the crossing regions on a clinical 3T MR scanner, and develop user-friendly software for DSI data reconstruction and analysis. Phantoms with a fixed crossing fiber configuration of two crossing fibers at 90° and 45° respectively along with a phantom with three crossing fibers at 60°, using novel hollow plastic capillaries and novel placeholders, were constructed. T2-weighted MRI results on these phantoms demonstrated high SNR, homogeneous signal, and absence of air bubbles. Also, a technique to deconvolve the response function of an individual peak from the overall ODF was implemented, in addition to other DSI post-processing steps. This technique greatly improved the angular resolution of the otherwise unresolvable peaks in a crossing fiber ODF. The effects of DSI acquisition parameters and SNR on the resultant angular accuracy of DSI on the clinical scanner were studied and quantified using the developed phantoms. With a high angular direction sampling and reasonable levels of SNR, quantification of a crossing region in the 90°, 45° and 60° phantoms resulted in a successful detection of angular information with mean ± SD of 86.93°±2.65°, 44.61°±1.6° and 60.03°±2.21° respectively, while simultaneously enhancing the ODFs in regions containing single fibers. For the applicability of these validated methodologies in DSI, improvement in ODFs and fiber tracking from known crossing fiber regions in normal human subjects were demonstrated; and an in-house software package in MATLAB which streamlines the data reconstruction and post-processing for DSI, with easy to use graphical user interface was developed. In conclusion, the phantoms developed in this dissertation offer a means of providing ground truth for validation of reconstruction and tractography algorithms of various diffusion models (including DSI). Also, the deconvolution methodology (when applied as an additional DSI post-processing step) significantly improved the angular accuracy of the ODFs obtained from DSI, and should be applicable to ODFs obtained from the other high angular resolution diffusion imaging techniques.

Evaluation of the impact of access to free influenza vaccine on immunization rates for children with cystic fibrosis

Children with cystic fibrosis are at increased risk of seasonal influenza associated complications, which makes them a judicious target of interventions designed to increase influenza vaccination rates. The Baylor College of Medicine/Texas Children's Hospital Pediatric Cystic Fibrosis (BCM/TCH CF) Care Center implemented an enhanced multi-component initiative designed to increase influenza vaccination rates in its patient population during the 2011-2012 influenza season. We evaluated the impact of specific components of this intervention on vaccination rates among the clinic's patient population via a historical medical chart review and examined the relationship between vaccination status and the number of pulmonary exacerbations requiring hospital admission during the influenza season. The multi-component intervention was comprised of providing influenza free of charge in the CF Care Center, reminders via phone call and letters, and drive through influenza vaccine clinics on nights and weekends. The intervention to increase influenza vaccination rates led to overall improved vaccination rates among the patients at the BCM/TCH CF Care Center, increasing from 90% adherence observed during the 2010-2011 season to 94% adherence during the 2011-2012 season. The availability of free influenza vaccine in the CF Care Center, combined with reminders about being vaccinated early in the season proved to be the most effective practices for improving the vaccination rate in the CF Care Center.^

The New Futuro College Plan: Facilitating College Access

Built on a free, bilingual, "high-touch, high-tech" platform, New Futuro has created a robust community of Latino students and parents, non-profit organizations, education institutions, government agencies, and corporations to connect those that need help with those that provide it. One of the resources developed by New Futuro is a proprietary 10-Steps College Plan that provides structured information targeted to Latino students and families to help them prepare, apply and pay for college.

Perspective from the Ed Tech Field

Dr. Karen Billings discusses how working at a non-profit trade association has provided a unique perspective on how schools are using technology to support the teaching and learning process.

When Policy Opportunity is not Enough: College Access and Enrollment Patterns among Texas Percent Plan Eligible Students

In 1998, Texas initiated a bold new statewide university admission policy aimed at increasing college access for traditionally underserved students in the state. House Bill 588 (known as the Texas Top 10 Percent Plan (TTPP)) guaranteed automatic admission to the college or university of their choice for all top performing students in Texas public high schools. Fourteen years after the plan’s implementation, we see great strides and complexities in understanding student outcomes as a result of the percent plan. However, the legal controversy over the percent plan both in Texas and other states incorporating similar yet distinctly motivated alternative admissions plans continues to play out from institutional decision boards to the highest court in the nation. This study seeks to add to that discussion by exploring two questions. Descriptively, what are the admission and enrollment patterns within racial/ethnic groups of percent plan eligible students, over time, for Texas elite, emergent elite, and remaining public institutions? Given that all eligible percent plan students may enter the institution of choice in Texas, does which type of institution a TTPP student chooses relate to their race/ethnicity? The descriptive story told by the admission and enrollment distributions of equally eligible TTPP students is a complex but compelling one. Fundamentally, it identifies that statistically different application and enrollment patterns exist for Hispanic and especially African American TTPP beneficiaries relative to their White and Asian American counterparts.

Commentary on "When Policy Opportunity is not Enough: College Access and Enrollment Patterns among Texas Percent Plan Eligible Students"

Invited commentary on "When Policy Opportunity is not Enough: College Access and Enrollment Patterns among Texas Percent Plan Eligible Students" by Catherine Horn and Stella Flores.

The impact of parent acculturation on parental fruit and vegetable intake, child fruit and vegetable intake, and child perceived access and availability to fruits and vegetables in the home environment

The purpose of this thesis was to investigate the association between parent acculturation and parental fruit and vegetable intake, child fruit and vegetable intake, and child access and availability to fruits and vegetables. Secondary data analysis was performed on a convenience sample of low-income Hispanic-identifying parents (n = 177) and children from a baseline survey from the Sprouting Healthy Kids intervention. T tests were used to examine the association between parent acculturation status (acculturated or non-acculturated) and fruit intake, vegetable intake and combined fruit and vegetable intake of both the parent and the child. T tests were also used to determine the relationship between parent acculturation and child access and availability to fruits, vegetables, and combined fruits and vegetables. Statistical significance was set at a p level of 0.05. The mean FVI for the parents and children were 3.41 servings and 2.96 servings, respectively. Statistical significance was found for the relationships between parent acculturation and parent fruit intake and parent acculturation and child fruit access. Lower acculturation of the parent was significantly related to higher fruit intake. Counter to the hypothesis, higher acculturation was found to be associated with greater access to fruits for the child. These findings suggest the necessity for not only culturally specific nutrition interventions, but the need for interventions to target behaviors for specific levels of acculturation within a culture. ^

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Media Influence on Youth: Scientific Evidence, Policy Considerations, and the History of Media Self-Regulation

This invited commentary reviews the survey research described in "Examining the Relationship between Media use and Aggression, Sexuality, and Body Image" and situates this research within the recent history of entertainment media regulation.