7 resultados para Communication and interaction

em DigitalCommons@The Texas Medical Center


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Objective. This study examines post-crisis family stress, coping, communication, and adaptation using the Double ABC-X Model of Family Adaptation in families with a pregnant or postpartum adolescent living at home. ^ Methods. Ninety-eight pregnant and parenting adolescents between ages 14 and 18 years (Group 1 at 20 or more weeks gestation; Group 2 at delivery and 8 weeks postpartum) and their parent(s) completed instruments congruent with the model to measure family stress, coping, communication, and adaptation. Descriptive family data was obtained. Mother-daughter data was analyzed for differences between subjects and within subjects using paired t-tests. Correlational analysis was used to examine relationships among variables. ^ Results. More than 90% of families were Hispanic. There were no significant differences between mother and daughter mean scores for family stress or communication. Adolescent coping was not significantly correlated to family coping at any interval. Adolescent family adaptation scores were significantly lower than mothers' scores at delivery and 8 weeks postpartum. Mean individual ratings of family variables did not differ significantly between delivery and 8 weeks postpartum. Simultaneous multiple regression analysis showed that stress, coping, and communication significantly influenced adaptation for mothers and daughters at all three intervals. The relative contributions of the three independent variables exhibited different patterns for mothers and daughters. Parent-adolescent communication accounted for most of the variability in adaptation for daughters at all three intervals. Daughters' family stress ratings were significant for adaptability (p = .01) during the pregnancy and for cohesion (p = .03) at delivery. Adolescent coping (p = .03) was significant for cohesion at 8 weeks postpartum. Family stress was a significant influence at all three intervals for mothers' ratings of family adaptation. Parent-adolescent communication was significant for mother's perception of both family cohesion (p < .001) and adaptability (p < .001) at delivery and 8 weeks, but not during pregnancy. ^ Conclusions. Mothers' and daughters' ratings of family processes were similar regarding family stress and communication, but were significantly different for family adaptation. Adolescent coping may not reflect family coping. Family communication is a powerful component in family functioning and may be an important focus for interventions with adolescents and parents. ^

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Objectives: The purpose of this study is to understand the perceived effects of patient-dental staff communication and cultural diversity on the utilization of dental services in the U.S. by Saudi Arabian students who live in the U.S. and enrolled into the King Abdullah Scholarship program. Methods: The study design was an analytical cross-sectional study. Data for this study was obtained from the Saudi Dental Servicers Utilization Survey, a voluntary internet survey available online for one month through Facebook. Ordered logistic regression analyses and multinomial logistic regression analyses were used to measure the relationships between patient-dental staff communication and cultural diversity on the utilization of dental services. Results: Eight hundred and forty-seven responses were analyzed for this study. Overall, the majority of Saudi students reported having excellent communication experience with dental providers in the U.S. More than 58% of respondents reported at least one regular dental visit last year. Factors that influenced the use of regular dental care were: dentist's explanation of treatment plan, response of dental staff to patient's needs, respectful and polite dental staff, dental staff kindness, availability of up-to-date equipment, and overall communication with dentist. However, the utilization of emergency dental care was not associated with any measurement of patient-dental provider communication. Overall future utilization of dental care is associated with all aspects of patient-dental staff communication measured in this survey. Furthermore, more utilization of regular dental care was related to respondent's perception of the importance of trustworthiness dental staff and the importance of a dentist's reputation was only marginally associated. Respondent's perception of dentist's reputation was associated with more use of emergency dental services. Respondents are more likely to anticipate using dental care in the future if they perceived trustworthiness dental staff, and the dentist's reputation as influencing factors to their usage of dental services. Conclusions: Patient-dental staff communication was partially associated with utilization of regular dental care, not associated with utilization of emergency dental care, and broadly associated with anticipated future utilization of dental care. In addition, trustworthy dental staff, and a dentist's reputation were considered to be strong influencing factors towards utilization of dental services.^

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Despite current enthusiasm for investigation of gene-gene interactions and gene-environment interactions, the essential issue of how to define and detect gene-environment interactions remains unresolved. In this report, we define gene-environment interactions as a stochastic dependence in the context of the effects of the genetic and environmental risk factors on the cause of phenotypic variation among individuals. We use mutual information that is widely used in communication and complex system analysis to measure gene-environment interactions. We investigate how gene-environment interactions generate the large difference in the information measure of gene-environment interactions between the general population and a diseased population, which motives us to develop mutual information-based statistics for testing gene-environment interactions. We validated the null distribution and calculated the type 1 error rates for the mutual information-based statistics to test gene-environment interactions using extensive simulation studies. We found that the new test statistics were more powerful than the traditional logistic regression under several disease models. Finally, in order to further evaluate the performance of our new method, we applied the mutual information-based statistics to three real examples. Our results showed that P-values for the mutual information-based statistics were much smaller than that obtained by other approaches including logistic regression models.

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Between the 1990 and 2000 Censuses, the Latino population accounted for 40% of the increase in the nation’s total population. The growing population of Latinos underscores the importance for understanding factors that influence whether and how Latinos take care of their health. According to the U.S. Department of Human Health Service’s Office of Minority Health (OMH), Latinos are at greater risk for health disparities (2003). Factors such as lack of health insurance and access to preventive care play a major role in limiting Latino use of primary health care (Institute of Medicine, 2005). Other significant barriers to preventive health care maintenance behaviors have been identified in current literature such as primary care physician interaction, self-perceived health status, and socio-cultural beliefs and traditions (Rojas-Guyler, King, Montieth and 2008; Meir, Medina, and Ory, 2007; Black, 1999). Despite these studies, there remains less information regarding interpersonal perceptions, environmental dynamics and individual and cultural attitudes relevant to utilization of healthcare (Rojas-Guyler, King, Montieth and 2008; Aguirre-Molina, Molina and Zambrana, 2001). Understanding the perceptions of Latinos and the barriers to health care could directly affect healthcare delivery. Improved healthcare utilization among Latinos could reduce the long term health consequences of many preventable and manageable diseases. The purpose of this study was to explore Latino perceptions of U.S. health care and desired changes by Latinos in the U.S. healthcare system. The study had several objectives, including to explore perceived barriers to healthcare utilization and the resulting effects on health among Latinos, to describe culturally influenced attitudes about health care and use of health care services among Latinos, and to make recommendations for reducing disparities by improving healthcare and its utilization. The current study utilized data that were collected as part of a larger study to examine multidimensional, cross-cultural issues relevant to interactions between healthcare consumers and providers. Qualitative methods were used to analyze four Spanish-language focus group transcripts to interpret cultural influences on perceptions and beliefs among Latinos. Direct coding of transcript content was carried out by two reviewers, who conducted independent reviews of each transcript. Team members developed and refined thematic categories, positive and negative cases, and example text segments for each theme and sub-theme. Incongruities of interpretations were resolved through extensive discussion. Study participants included 44 self-identified Latino adults (16 male, 28 female) between age 18 and 64 years. Thirty seven (84.1%) of the participants were immigrants. The study population comprised eight ethnic subgroups. While 31% of the participants reported being employed on a full-time basis, only 18.4% had medical insurance that was private or employee sponsored. Five major themes regarding the perceptions and healthcare utilization behaviors of Latinos were consistent across all focus groups and were identified during the analysis. These were: (1) healthcare utilization, experience, and access; (2) organizational and institutional systems; (3) communication and interpersonal interactions between healthcare provider, staff, and patient; (4) Latinos’ perception of their own health status; (5) cultural influences on healthcare utilization, which included an innovation termed culturally-bound locus of control. Healthcare utilization was directly influenced by healthcare experience, access, current health status, and cultural factors and indirectly influenced by organizational systems. There was a strong interdependence among the main themes. The ability to communicate and interact effectively with healthcare providers and navigate healthcare systems (organizational and institutional access) significantly influenced the participant’s health care experience, most often (indirectly) impacting utilization negatively. ^ Research such as this can help to identify those perceptions and attitudes held by Latinos concerning utilization or underutilization of healthcare systems. These data suggest that for healthcare utilization to improve among Latinos, healthcare systems must create more culturally competent environments by providing better language services at the organizational level and more culturally sensitive providers at the interpersonal level. Better understanding of the complex interactions between these impediments can aid intervention developments, and help health providers and researchers in determining appropriate, adequate, and effective measurers of care to better increase overall health of Latinos.^

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This study was conducted under the auspices of the Subcommittee on Risk Communication and Education of the Committee to Coordinate Environmental Health and Related Programs (CCEHRP) to determine how Public Health Service (PHS) agencies are communicating information about health risk, what factors contributed to effective communication efforts, and what specific principles, strategies, and practices best promote more effective health risk communication outcomes.^ Member agencies of the Subcommittee submitted examples of health risk communication activities or decisions they perceived to be effective and some examples of cases they thought had not been as effective as desired. Of the 10 case studies received, 7 were submitted as examples of effective health risk communication, and 3, as examples of less effective communication.^ Information contained in the 10 case studies describing the respective agencies' health risk communication strategies and practices was compared with EPA's Seven Cardinal Rules of Risk Communication, since similar rules were not found in any PHS agency. EPA's rules are: (1) Accept and involve the public as a legitimate partner. (2) Plan carefully and evaluate your efforts. (3) Listen to the public's specific concerns. (4) Be honest, frank, and open. (5) Coordinate and collaborate with other credible sources. (6) Meet the needs of the media. (7) Speak clearly and with compassion.^ On the basis of case studies analysis, the Subcommittee, in their attempts to design and implement effective health risk communication campaigns, identified a number of areas for improvement among the agencies. First, PHS agencies should consider developing a focus specific to health risk communication (i.e., office or specialty resource). Second, create a set of generally accepted practices and guidelines for effective implementation and evaluation of PHS health risk communication activities and products. Third, organize interagency initiatives aimed at increasing awareness and visibility of health risk communication issues and trends within and between PHS agencies.^ PHS agencies identified some specific implementation strategies the CCEHRP might consider pursuing to address the major recommendations. Implementation strategies common to PHS agencies emerged in the following five areas: (1) program development, (2) building partnerships, (3) developing training, (4) expanding information technologies, and (5) conducting research and evaluation. ^

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My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

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Applying Theoretical Constructs to Address Medical Uncertainty Situations involving medical reasoning usually include some level of medical uncertainty. Despite the identification of shared decision-making (SDM) as an effective technique, it has been observed that the likelihood of physicians and patients engaging in shared decision making is lower in those situations where it is most needed; specifically in circumstances of medical uncertainty. Having identified shared decision making as an effective, yet often a neglected approach to resolving a lack of information exchange in situations involving medical uncertainty, the next step is to determine the way(s) in which SDM can be integrated and the supplemental processes that may facilitate its integration. SDM involves unique types of communication and relationships between patients and physicians. Therefore, it is necessary to further understand and incorporate human behavioral elements - in particular, behavioral intent - in order to successfully identify and realize the potential benefits of SDM. This paper discusses the background and potential interaction between the theories of shared decision-making, medical uncertainty, and behavioral intent. Identifying Shared Decision-Making Elements in Medical Encounters Dealing with Uncertainty A recent summary of the state of medical knowledge in the U.S. reported that nearly half (47%) of all treatments were of unknown effectiveness, and an additional 7% involved an uncertain tradeoff between benefits and harms. Shared decision-making (SDM) was identified as an effective technique for managing uncertainty when two or more parties were involved. In order to understand which of the elements of SDM are used most frequently and effectively, it is necessary to identify these key elements, and understand how these elements related to each other and the SDM process. The elements identified through the course of the present research were selected from basic principles of the SDM model and the “Data, Information, Knowledge, Wisdom” (DIKW) Hierarchy. The goal of this ethnographic research was to identify which common elements of shared decision-making patients are most often observed applying in the medical encounter. The results of the present study facilitated the understanding of which elements patients were more likely to exhibit during a primary care medical encounter, as well as determining variables of interest leading to more successful shared decision-making practices between patients and their physicians. Understanding Behavioral Intent to Participate in Shared Decision-Making in Medically Uncertain Situations Objective: This article describes the process undertaken to identify and validate behavioral and normative beliefs and behavioral intent of men between the ages of 45-70 with regard to participating in shared decision-making in medically uncertain situations. This article also discusses the preliminary results of the aforementioned processes and explores potential future uses of this information which may facilitate greater understanding, efficiency and effectiveness of doctor-patient consultations.Design: Qualitative Study using deductive content analysisSetting: Individual semi-structure patient interviews were conducted until data saturation was reached. Researchers read the transcripts and developed a list of codes.Subjects: 25 subjects drawn from the Philadelphia community.Measurements: Qualitative indicators were developed to measure respondents’ experiences and beliefs related to behavioral intent to participate in shared decision-making during medical uncertainty. Subjects were also asked to complete the Krantz Health Opinion Survey as a method of triangulation.Results: Several factors were repeatedly described by respondents as being essential to participate in shared decision-making in medical uncertainty. These factors included past experience with medical uncertainty, an individual’s personality, and the relationship between the patient and his physician.Conclusions: The findings of this study led to the development of a category framework that helped understand an individual’s needs and motivational factors in their intent to participate in shared decision-making. The three main categories include 1) an individual’s representation of medically uncertainty, 2) how the individual copes with medical uncertainty, and 3) the individual’s behavioral intent to seek information and participate in shared decision-making during times of medically uncertain situations.