Correlates of voluntary HIV testing and counseling among middle aged and older Latinas

This study identifies and describes HIV Voluntary Counseling and Testing (VCT) of middle aged and older Latinas. The rate of new cases of HIV in people age 45 and older is rapidly increasing, with a 40.6% increase in the numbers of older Latinas infected with HIV between 1998 and 2002. Despite this increase, there is paucity of research on this population. This research seeks to address the gap through a secondary data analysis of Latina women. The aim of this study is twofold: (1) Develop and empirically test a multivariate model of VCT utilization for middle aged and older Latinas; (2) To test how the three individual components of the Andersen Behavioral Model impact VCT for middle aged and older Latinas. The study is organized around the three major domains of the Andersen Behavioral Model of service use that include: (a) predisposing factors; (b) enabling characteristics and (c) need. Logistic regression using structural equation modeling techniques were used to test multivariate relationships of variables on VCT for a sample of 135 middle age and older Latinas residing in Miami-Dade County, Florida. Over 60% of participants had been tested for HIV. Provider endorsement was found to he the strongest predictor of VCT (odds ration [OR] 6.38), followed by having a clinic as a regular source of healthcare (OR=3.88). Significant negative associations with VCT included self rated health status (OR=.592); Age (OR=.927); Spanish proficiency (OR=.927); number of sexual partners (OR=.613) and consumption of alcohol during sexual activity (.549). As this line of inquiry provides a critical glimpse into the VCT of older Latinas, recommendations for enhanced service provision and research will he offered.

Middle school teachers' intentions to refer eating disorder students for professional counseling

Eating disorders can lead to a negative impact on students' academic growth, nutrition and can cause death (Claude-Pierre, 1997; Manley, Rickson, & Standeven, 2000; Romeo, 1996). Early intervention by referring students to professional counseling might help counter these negative consequences. The teacher is in the position to assist students by providing health information, identifying those with problems, and intervening for a variety of dysfunctions that may include the eating disorders called anorexia nervosa and bulimia nervosa (Myers-Clark & Christopher, 2000). However teachers are in a difficult position to know when to address student concerns and judge what action to take (Ransley, 1999). Teachers' engagement seems crucial (Smolak, Harris, Levine, & Shisslak, 2001) since eating disorders are being identified in younger children. The purpose of this study was to examine (a) the relationships of the theoretical constructs, attitude, subjective norm, and perceived behavioral control of the theory of planned behavior as predictors of behavioral intention (Ajzen & Fishbein, 1980) of middle school teachers to identify and refer suspected anorexia nervosa (AN) and/or bulimia nervosa (BN) students for professional help; and (b) the actual behavior of middle school teachers who reported having ever referred a student suspected of having AN and BN and those teachers who reported not having made such a referral. One hundred fourteen middle school teachers in Broward County, Florida volunteered to participate in the ex post facto research. Data were collected from a questionnaire. Multiple regression analysis revealed that the constructs of subjective norm (perception of what others think about one's performance of behavior combined with motivation to comply) and perceived behavioral control (perception regarding the extent of the difficulty of performing the behavior) were predictive of teachers' intent (likelihood of engaging in a behavior) to refer. However, the analysis revealed that attitude (overall positive or negative feeling with respect to performing the behavior) was not predictive of teachers' intent. Discriminant function analysis revealed that both intent and perceived behavioral control were predictive of group membership, either having referred a student suspected of having an eating disorder for counseling or not having made such a referral. Attitude and subjective norm were not predictive of group membership.

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.^

Diabetes Self-management Behaviors, Medical Care, Glycemic Control, and Self-rated Health in US Men by Race/Ethnicity

Men, particularly minorities, have higher rates of diabetes as compared with their counterparts. Ongoing diabetes self-management education and support by specialists are essential components to prevent the risk of complications such as kidney disease, cardiovascular diseases, and neurological impairments. Diabetes self-management behaviors, in particular, as diet and physical activity, have been associated with glycemic control in the literature. Recommended medical care for diabetes may differ by race/ethnicity. This study examined data from the National Health and Nutrition Examination Surveys, 2007 to 2010 for men with diabetes (N = 646) from four racial/ethnic groups: Mexican Americans, other Hispanics, non-Hispanic Blacks, and non-Hispanic Whites. Men with adequate dietary fiber intake had higher odds of glycemic control (odds ratio = 4.31, confidence interval [1.82, 10.20]), independent of race/ethnicity. There were racial/ethnic differences in reporting seeing a diabetes specialist. Non-Hispanic Blacks had the highest odds of reporting ever seeing a diabetes specialist (84.9%) followed by White non-Hispanics (74.7%), whereas Hispanics reported the lowest proportions (55.2% Mexican Americans and 62.1% other Hispanics). Men seeing a diabetes specialist had the lowest odds of glycemic control (odds ratio = 0.54, confidence interval [0.30, 0.96]). The results of this study suggest that diabetes education counseling may be selectively given to patients who are not in glycemic control. These findings indicate the need for examining referral systems and quality of diabetes care. Future studies should assess the effectiveness of patient-centered medical care provided by a diabetes specialist with consideration of sociodemographics, in particular, race/ethnicity and gender.

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.