This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Description
In rehabilitation settings, activity limitation can be a significant barrier to recovery. This study sought to examine the effects of state and trait level benefit finding, positive affect, and catastrophizing on activity limitation among individuals with a physician-confirmed diagnosis of either Osteoarthritis (OA), Fibromyalgia (FM), or a dual diagnosis of

In rehabilitation settings, activity limitation can be a significant barrier to recovery. This study sought to examine the effects of state and trait level benefit finding, positive affect, and catastrophizing on activity limitation among individuals with a physician-confirmed diagnosis of either Osteoarthritis (OA), Fibromyalgia (FM), or a dual diagnosis of OA/FM. Participants (106 OA, 53 FM, and 101 OA/FM) who had no diagnosed autoimmune disorder, a pain rating above 20 on a 0-100 scale, and no involvement in litigation regarding their condition were recruited in the Phoenix metropolitan area for inclusion in the current study. After initial questionnaires were completed, participants were trained to complete daily diaries on a laptop computer and instructed to do so a half an hour before bed each night for 30 days. In each diary, participants rated their average daily pain, benefit finding, positive affect, catastrophizing, and activity limitation. A single item, "I thought about some of the good things that have come from living with my pain" was used to examine the broader construct of benefit finding. It was hypothesized that state and trait level benefit finding would have a direct relation with activity limitation and a partially mediated relationship, through positive affect. Multilevel modeling with SAS PROC MIXED revealed that benefit finding was not directly related to activity limitation. Increases in benefit finding were associated, however, with decreases in activity limitation through a significant mediated relationship with positive affect. Individuals who benefit find had a higher level of positive affect which was associated with decreased activity limitation. A suppression effect involving pain and benefit finding at the trait level was also found. Pain appeared to increase the predictive validity of the relation of benefit finding to activity limitation. These findings have important implications for rehabilitation psychologists and should embolden clinicians to encourage patients to increase positive affect by employing active approach-oriented coping strategies like benefit finding to reduce activity limitation.
ContributorsKinderdietz, Jeffrey Scott (Author) / Zautra, Alex (Thesis advisor) / Davis, Mary (Committee member) / Barrera, Manuel (Committee member) / Okun, Morris (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Virtual environments are used for many physical rehabilitation and therapy purposes with varying degrees of success. An important feature for a therapy environment is the real-time monitoring of a participants' movement performance. Such monitoring can be used to evaluate the environment in addition to the participant's learning. Methods for monitoring

Virtual environments are used for many physical rehabilitation and therapy purposes with varying degrees of success. An important feature for a therapy environment is the real-time monitoring of a participants' movement performance. Such monitoring can be used to evaluate the environment in addition to the participant's learning. Methods for monitoring and evaluation include tracking kinematic performance as well as monitoring muscle and brain activities through EMG and EEG technology. This study aims to observe trends in individual participants' motor learning based on changes in kinematic parameters and use those parameters to characterize different types of learners. This information can then guide EEG/EMG data analysis in the future. The evaluation of motor learning using kinematic parameters of performance typically compares averages of pre- and post-data to identify patterns of changes of various parameters. A key issue with using pre- and post-data is that individual participants perform differently and have different time-courses of learning. Furthermore, different parameters can evolve at independent rates. Finally, there is great variability in the movements at early stages of learning a task. To address these issues, a combined approach is proposed using robust regression, piece-wise regression and correlation to categorize different participant's motor learning. Using the mixed reality rehabilitation system developed at Arizona State University, it was possible to engage participants in motor learning, as revealed by improvements in kinematic parameters. A combination of robust regression, piecewise regression and correlation were used to reveal trends and characterize participants based on motor learning of three kinematic parameters: trajectory error, supination error and the number of phases in the velocity profile.
ContributorsAttygalle, Suneth Satoshi (Author) / He, Jiping (Thesis advisor) / Rikakais, Thanassis (Committee member) / Iasemidis, Leonidas (Committee member) / Arizona State University (Publisher)
Created2010