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.^

Nursing faculty intention to use service learning as pedagogy in higher education

The purpose of this study was to identify the factors that motivate nursing faculty to use service learning. The study was based on the theory of planned behavior (TPB), which implies that the target behavior of intention to use service learning in higher education is influenced by the predictor variables of behavior beliefs (attitude), normative beliefs (peer influence), and control beliefs (confidence and resources). External variables were also considered (years of teaching experience, tenure status, and the type of curriculum). Group interviews and a pilot test were conducted to create the instrument for the study, and Cronbach alpha were calculated for survey item reliability. The participants were full time undergraduate nursing faculty members (n=-160) in the Southeastern United States who taught in universities with accredited nurse education programs. Demographic data as well as scores on scaled survey responses were used to evaluate the intention of nursing faculty to use service learning in their classes. Pearson product moment correlation coefficient and path analysis were applied to the data. The correlation findings indicated that there were statistically significant relationships between behavior beliefs, normative beliefs, and control beliefs and nursing faculty intention to use service learning. The path analysis also indicated that behavior beliefs and normative beliefs were significant, while control beliefs were not a strong influence on intention to use service learning. Normative beliefs showed the strongest direct influence. The use of a community based curriculum also had a positive influence on intention, and faculty with tenure status were more likely to have positive behavior beliefs (attitude) towards service learning. Finally, as teaching experience increased, positive attitudes towards the intention to use service learning decreased. Seventy-nine percent of the variation in the intention to use service learning was explained by the theory of planned behavior, the type of curriculum, teaching experience, and tenure status. These results will assist nursing administration and faculty to design strategies to facilitate the implementation of service learning pedagogy, as well as a community based curriculum which will help meet the 21st century goals set forth from the American Association of Colleges of Nursing.