Cross-Disciplinary Collaboration Behavior of Practitioners in the Treatment of Anxiety Disorders

Current research on the collaborative behaviors of conventional and alternative health care providers for the treatment of anxiety is lacking. While there are multiple studies looking at alternative health care integration into primary care, none of them look at anxiety specifically. The purpose of this paper is to provide a preliminary exploration of possible barriers to collaboration between conventional and alternative health care providers for the treatment of anxiety. Quantitative data on collaboration behavior patterns were obtained with an anonymous survey. Data from the surveys were analyzed using a chi-square analysis. Along with these numerical data narrative data from the survey and interviews were collected in order to assess beliefs about the barriers to collaboration from different health care providers. The results indicate that conventional providers collaborate the least with alternative providers and alternative providers collaborate the least with conventional providers. The descriptive results regarding the barriers to collaboration from the study illustrated a common theme, specifically, the lack of education of conventional providers on alternative health care practices on anxiety. This is an exploratory study: therefore it would be beneficial for future researchers to look deeper into the beliefs of health care providers on the barriers to collaboration, possibly identifying the specific barriers to collaboration for each type of healthcare provider.

The Health Behavior Change Competency Checklist (HBCCC): Instrument development and psychometric evaluation.

More than half of morbidity and mortality in the United States can be attributed to behavior-related disease, such as tobacco use, physical inactivity, poor diet and alcohol consumption. Given the increased prevalence of behaviorally related medical health concerns, physician competence in the implementation of effective behavior change strategies is quickly becoming an essential skill. However, only recently have primary care residency programs begun to systematically teach and evaluate motivational interviewing skills critical to influencing health behavior, and use of standardized, objective assessment tools to assess skillfulness has been largely absent. This paper reports the development of a checklist, the Health Behavior Change Competency Checklist (HBCCC). The instrument captures the theoretical model of behavior change, motivational interviewing, in a practical and versatile manner. Psychometric evaluation demonstrated moderate efficacy. Namely, results indicated the HBCCC possesses good reliability, as evidenced by high internal consistency, and adequate construct validity. It also displayed considerable utility and practical application. While these results provide several reasons for confidence in the HBCCC, item revision and additional testing are required in order to establish it as a meaningful and valuable instrument.

Electroencephalogram based Causality Graph Analysis in Behavior Tasks of Parkinson’s Disease Patients

Electroencephalographic (EEG) signals of the human brains represent electrical activities for a number of channels recorded over a the scalp. The main purpose of this thesis is to investigate the interactions and causality of different parts of a brain using EEG signals recorded during a performance subjects of verbal fluency tasks. Subjects who have Parkinson's Disease (PD) have difficulties with mental tasks, such as switching between one behavior task and another. The behavior tasks include phonemic fluency, semantic fluency, category semantic fluency and reading fluency. This method uses verbal generation skills, activating different Broca's areas of the Brodmann's areas (BA44 and BA45). Advanced signal processing techniques are used in order to determine the activated frequency bands in the granger causality for verbal fluency tasks. The graph learning technique for channel strength is used to characterize the complex graph of Granger causality. Also, the support vector machine (SVM) method is used for training a classifier between two subjects with PD and two healthy controls. Neural data from the study was recorded at the Colorado Neurological Institute (CNI). The study reveals significant difference between PD subjects and healthy controls in terms of brain connectivities in the Broca's Area BA44 and BA45 corresponding to EEG electrodes. The results in this thesis also demonstrate the possibility to classify based on the flow of information and causality in the brain of verbal fluency tasks. These methods have the potential to be applied in the future to identify pathological information flow and causality of neurological diseases.