3 resultados para Behavior analysis

em Digital Commons @ DU | University of Denver Research


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In the first wave, behaviorists questioned the conventional wisdom that inner experience was relevant to understanding human behavior. In the 1970s, cognitive-behavioral theories emphasized the importance of the cognitive element, not just the environment, in explaining and modifying behavior. The third wave is drawn from advances in basic and applied behavior analysis of language, Eastern mystical traditions, and less empirically oriented therapeutic approaches. Examples include Acceptance and Commitment Therapy (ACT), Dialectical Behavior Therapy (DBT), Functional Analytic Psychotherapy (FAP), and Mindfulness Based Cognitive Therapy (IBCT). This study reports a survey of clinicians and non-clinicians who self-identify with second or third wave approaches, and a group of undergraduate psychology students intended to represent a layperson or folk psychological approach. Their preferences, in the context of 10 clinical vignettes, among 5 different therapeutic responses or interventions that included "ACT-like," "cognitive," and commonsense or "neutral" options were measured. Third wave-oriented respondents exhibited more consistency than others in their preference for interventions that match their self-identified theoretical orientation, however the author suggests that construction of the vignettes may have influenced this result.

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The current study evaluated the State Juvenile Diversion Program, managed by the District Attorney’s (DA) office in Denver Colorado. The purpose of this study was to review factors, which potentially contribute to success or failure in diversion. Research in diversion programing typically focuses on recidivism rates, but fails to examine which factors contribute to program completion. The analysis was conducted using data from 57 juveniles who entered the DA diversion program in 2015. This represents the majority of juveniles in the diversion program rather than a sample. The current study confirmed prior research findings that those juveniles who do not successfully complete a diversion program are more likely to reoffend. Additionally, the factors which were significantly correlated with successful completion of the diversion program were grade point average (GPA) and number of municipal tickets. The number of behavior reports in school before and after the Diversion program was significantly lower for both groups. Non-significant findings are also discussed as they may help guide future research.

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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.