Thesis (Ph. D.)--Ball State University, 2009. / Title from PDF t.p. (viewed on Nov. 12, 2009). Includes bibliographical references (p. 111-123).

Thesis (M.Ed.)--Cleveland State University, 2007. / Abstract. Title from PDF t.p. (viewed on May 8, 2008). Includes bibliographical references (p. 60-62). Available online via the OhioLINK ETD Center. Also available in print.

Thesis (M.S.)--Eastern Illinois University, 2008. / Includes bibliographical references (leaves 35-40).

Thesis (M.A.I.S.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 65-69). Also available on the World Wide Web.

Master's thesis - - State University of New York College at Cortland, 2009 - - Department of Kinesiology. / Includes bibliographical references (p. 25-7).

Based on Self-Determination Theory (e.g., Deci & Ryan, 1985a, 2000; Ryan & Deci, 2002) this research focused on the motivation of ten elite Ethiopian male and female long distance runners. The semi-structured interview guide based on the SDT was transcribed verbatim and subjected to an inductive-deductive analysis approach based on the methodological guidance provided by Maykut & Morehouse (1994). Results revealed the integrated type of motivation to be the most evident among the runners. The data were organized into three broad categories that emerged through the interviews. The three categories are nationalism, economics and fame. Within each category there are themes or subcategories that emerged across various perceptions of the Ethiopian runners. The data revealed that among different types of motivation classified by the Self-Determination Theory (e.g., Deci & Ryan, 1985a, 2000; Ryan & Deci, 2002) there are multiple social factors that influence Ethiopian runners as well.

Thesis (M.A.)--University of Alabama at Birmingham, 2009. / Title from PDF title page (viewed Jan. 28, 2010). Includes bibliographical references (p. 23-24).

No description available.

Access to abstract permanently restricted to Ball State community only / Access to thesis permanently restricted to Ball State community only / School of Physical Education, Sport, and Exercise Science

Athletes complete a balance of training loads and rest periods, risking overtraining when this balance favors excessive training. Diagnostic biomarkers have been suggested but a clear diagnostic method is not available. This preliminary study's objective was to use data standardization to improve an electronic nose's (enose) discrimination model for athletes' breathprints after cumulative and acute training loads. Collegiate long distance runners were observed throughout competitive training seasons. Prolonged training effects were observed through Profile of Mood States (POMS) surveys and blood and breath samples collected at the beginning (Pre-Study) and end of the training season (Post-Study). Immediate training effects were observed for one low (LI) and one high (HI) intensity acute training load. Subjects provided blood and breath samples before the LI (BSR) and HI (BLR), completed the training load, and provided blood and breath samples after each training load (ASR; ALR). Blood was analyzed for antioxidant enzymes (catalase, glutathione peroxidase, and glutathione reductase). Breath samples were analyzed with a Cyranose® 320 (C320) enose. Age, gender, and training loads affected oxidative states, with the HI having more effect than the LI. Mood profiles indicated healthy and successful athletes. Neither POMS nor blood parameters suggested overtrained athletes. The C320 successfully discriminated between breathprints of athletes correlating to the training loads. Direct data standardization through carbon dioxide as a baseline sensor purge correctly classified 100 percent of the data through linear discriminant analysis (LDA). Indirect data standardization by subtracting Pre-Study data from the subsequent data classes (e.g. BSR) correctly classified 96 percent of the data. An LDA on the combined blood parameters correctly classified 61.9 percent of the data. The blood analyses required invasive sample collections and involved procedures that took a long time (hours). In comparison, the best C320 model correctly classified 96 percent of the data and required less invasive sample collections, simple analysis, and short result times (minutes). Evidence suggested the C320 will provide a simple and noninvasive method for clinically diagnosing the onset of overtraining. The unit is small, handheld, rapid, and noninvasive so it could also be used on- site to provide immediate feedback for training optimization. / Ph. D.