The health and nutritional status of multiethnic perimenopausal women

An integrated, dual-phase study design assessed the health and nutritional status and practices of African-American (A-A), Caribbean (A-C), and white non-Hispanic (W-A) women during perimenopause (40–55 years). During Phase I, four focus groups (n = 37) of male and female participants discussed the health and social implications of perimenopause. A conceptual framework for the main study (Phase II) was developed from the focus groups' findings, in concert with the main study's specific aims and objectives. ^ The main study, a cross-sectional survey, quantitatively assessed the health and nutritional status of a convenience sample of 109 women (25 A-A, 31 A-C and 53 W-A), who met specific eligibility criteria. Using seven instruments, sociodemographic, dietary, medical, reproductive health, health practice and anthropometric data were collected. ^ The groups were of comparable age, education, and socioeconomic status (SES). Despite these similarities, statistically significant interethnic nutritional status differences were found. Significantly more total energy and energy from fat were consumed by A-A than W-A and A-C women. Also, significantly more A-A and A-C than W-A women were overweight or obese with android-type weight patterning. ^ Overall, iron and calcium Recommended Dietary Allowances (RDA's) were not met by 35% and 68% of participants, respectively. Iron deficiency anemia was reported by 29% of participants while 33% reported heavier menstrual bleeding. Coupled with suboptimal iron intakes, this is likely to present a serious public health problem. Similarly, increased bone demineralization characteristic of perimenopause, coupled with suboptimal calcium intakes could precipitate another public health problem, osteoporosis. ^ Participants had different expectations about the role of medical care during perimenopause. Significantly more white (57%) than black (38% [A-A and AC]) women sought medical attention for symptoms. Whereas Hormone Replacement Therapy (HRT) was prescribed for 25% of them, only 13% were compliant at enrollment. ^ The trends and statistically significant findings of this study have huge public health policy implications. It is imperative that appropriate policies are formulated to ensure that America's ethnically diverse perimenopausal women have ready access to culturally appropriate care. This would optimize their health outcomes, and enhance their quality of life and productive capacities at this critical juncture of their lives. ^

Abstractions to support dynamic adaptation of communication frameworks for user-centric communication

The convergence of data, audio and video on IP networks is changing the way individuals, groups and organizations communicate. This diversity of communication media presents opportunities for creating synergistic collaborative communications. This form of collaborative communication is however not without its challenges. The increasing number of communication service providers coupled with a combinatorial mix of offered services, varying Quality-of-Service and oscillating pricing of services increases the complexity for the user to manage and maintain ‘always best’ priced or performance services. Consumers have to manually manage and adapt their communication in line with differences in services across devices, networks and media while ensuring that the usage remain consistent with their intended goals. This dissertation proposes a novel user-centric approach to address this problem. The proposed approach aims to reduce the aforementioned complexity to the user by (1) providing high-level abstractions and a policy based methodology for automated selection of the communication services guided by high-level user policies and (2) providing services through the seamless integration of multiple communication service providers and providing an extensible framework to support the integration of multiple communication service providers. The approach was implemented in the Communication Virtual Machine (CVM), a model-driven technology for realizing communication applications. The CVM includes the Network Communication Broker, the layer responsible for providing a network-independent API to the upper layers of CVM. The initial prototype for the NCB supported only a single communication framework which limited the number, quality and types of services available. Experimental evaluation of the approach show the additional overhead of the approach is minimal compared to the individual communication services frameworks. Additionally the automated approach proposed out performed the individual communication services frameworks for cross framework switching.

Instituting Tobacco-Free Employee Policies: An Invasion of Privacy or an Employer’s Legal Right?

Rising health care costs are causing some employers to assess and regulate the health behaviors of their employees. Different approaches and levels of non-smoking regulations are discussed, and the legal parameters and challenges of regulating employees’ private behaviors are explored.

*Postsecondary access for individuals with psychological disabilities: An analysis of federal rulings and institutional philosophies, *policies, and practices

This study was a qualitative investigation, with demographic quantitative features, of post-secondary educational access and legal guidelines for individuals with psychological disabilities. Although disability laws have positively influenced post-secondary educational attitudes and practices relative to accommodating many individuals with disabilities, prevailing stigmas regarding mental illness have discouraged the equal access to higher education for individuals with psychological disabilities. Little research concentrating on this area was found.^ Thirty-six relevant legal case decisions, focusing on a variety of realms of higher education, were scrutinized. The policies, procedures, and practices of six Southeastern United States universities were analyzed through official documents and participant responses from disability service providers and other university employees. Comparisons were made between legal cases, and within and between universities. Case findings also provided standards through which participating university practices could be studied.^ The legal analysis revealed that most institutions did not discriminate against individuals with psychological disabilities. Practices of a few of these institutions, however, suggested non-compliance despite favorable decisions on their behalf. Institutions found to have discriminatory practices were cited for inadequate procedures, or for presumptive assessments of the educational functioning levels of individuals with psychological disabilities.^ Participant university practices generally suggested disability law compliance; however, certain campus interventions were determined to be ineffective in identifying, addressing, and communicating about the educational needs of individuals with psychological disabilities. The most effective services for these individuals, who were described as rapidly increasing in number but lagging in self-advocacy and acceptance by others, went beyond legal requirements.^ Recommendations were made for institutional practices concerning disability-related documentation, written standards and operations, and student identification and referral. Directions for future research focused on study skills training for students; exposure of mental health professionals to client educational needs; and expansion of the current research, on a nationwide collegiate level, and a parallel analysis focusing on business and industry. ^

Context -aware data caching for mobile computing environments

The deployment of wireless communications coupled with the popularity of portable devices has led to significant research in the area of mobile data caching. Prior research has focused on the development of solutions that allow applications to run in wireless environments using proxy based techniques. Most of these approaches are semantic based and do not provide adequate support for representing the context of a user (i.e., the interpreted human intention.). Although the context may be treated implicitly it is still crucial to data management. In order to address this challenge this dissertation focuses on two characteristics: how to predict (i) the future location of the user and (ii) locations of the fetched data where the queried data item has valid answers. Using this approach, more complete information about the dynamics of an application environment is maintained. ^ The contribution of this dissertation is a novel data caching mechanism for pervasive computing environments that can adapt dynamically to a mobile user's context. In this dissertation, we design and develop a conceptual model and context aware protocols for wireless data caching management. Our replacement policy uses the validity of the data fetched from the server and the neighboring locations to decide which of the cache entries is less likely to be needed in the future, and therefore a good candidate for eviction when cache space is needed. The context aware driven prefetching algorithm exploits the query context to effectively guide the prefetching process. The query context is defined using a mobile user's movement pattern and requested information context. Numerical results and simulations show that the proposed prefetching and replacement policies significantly outperform conventional ones. ^ Anticipated applications of these solutions include biomedical engineering, tele-health, medical information systems and business. ^

Statistical dialog management for health interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. ^ Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. ^ The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. ^ In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.^

A simulation-based decision support system for evaluating operating policies in an emergency room facility

Increased pressure to control costs and increased competition has prompted health care managers to look for tools to effectively operate their institutions. This research sought a framework for the development of a Simulation-Based Decision Support System (SB-DSS) to evaluate operating policies. A prototype of this SB-DSS was developed. It incorporates a simulation model that uses real or simulated data. ER decisions have been categorized and, for each one, an implementation plan has been devised. Several issues of integrating heterogeneous tools have been addressed. The prototype revealed that simulation can truly be used in this environment in a timely fashion because the simulation model has been complemented with a series of decision-making routines. These routines use a hierarchical approach to organize the various scenarios under which the model may run and to partially reconfigure the ARENA model at run time. Hence, the SB-DSS tailors its responses to each node in the hierarchy.

User Effects on Wearable Conformal SCMR System

The performance of a compact, wearable Conformal Strongly Coupled Magnetic Resonance (CSCMR) system is studied when the antenna is in the air and is worn on a user’s arm. The wireless powering system consists of the receiver and load elements designed on a printed circuit board that is attached to a polyester fabric band. The wearable antenna achieves high efficiency, has a small volume, and can be easily printed on substrates. Although the user effect on mobile terminal antennas has been studied in detail, absorption losses in wearable antennas have not been widely investigated. Our results show that efficiency of the antenna in free space is 70% and on a user’s arm is 50%. Human tissue in the close proximity of our wearable Conformal SCMR caused a decrease in radiated efficiency and total efficiency. This undesired degradation in antenna efficiency might be attributed to body loss and absorption losses. Our findings can be used as a reference for future studies on wearable devices and their applications, such as health and sports monitoring.

Statistical Dialog Management for Health Interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.