There are several factors that influence computerized neurocognitive testing performance however, one factor that has not been examined is the potential deleterious effects of cognitive fatigue from an academic school day combined with time of computerized neurocognitive testing (CNT) administration. The primary purpose of this study was to compare before-and after-school CNT performance and total symptoms in non-concussed high school student athletes. The secondary purpose of this study was to compare before-school and after-school CNT performance and total symptoms and chronotypes in non-concussed student athletes. A crossover design was used to compare before-and after-school CNT performance and total symptoms of 39 non-concussed high school student athletes with an average age of 15.74 (SD = 1.04). Based on previous literature a hypothesis was made that high school student athletes would report higher self-reported fatigue after-school than before-school. Differences in CNT performance and total symptoms were measured by comparing composite scores of verbal memory, visual memory, processing speed, reaction time and total symptoms. In addition, to main outcome measures, several measures were used to control for potential confounding factors that could influence CNT performance. Before-school self-reported fatigue (M = 3.83, SD = 1.64) was significantly higher than after-school (M = 3.06, SD = 1.91) self-reported fatigue. There were no significant differences in verbal memory t(38) = 0.80, p = .43, visual memory t(38) = -0.78, p = .44, processing speed t(38) = .07, p = .94, reaction time t(38) = 1.45, p = .16, or total symptoms t(38) = -0.64, p = .52, between before-school and after-school. Lastly, there were no significant differences in verbal memory F (1, 37) = 1.17, p = .21, η2 = .04, visual memory F (1, 37) = .05, p = .28, η2 = .00, processing speed F (1, 37) = 0.75, p = .39, η2 = .02, reaction time F (1, 37) = 1.65, p = .21, η2 = .04, or total symptoms F (1, 37) = 0.57, p = .46, η2 = .02 between morning and evening chronotypes. The results from this study suggest that sports medicine professionals can administer CNT before-or after-school depending on their schedule and the athlete’s academic and athletic schedule.
","abstract_html":"<p>There are several factors that influence computerized neurocognitive testing performance however, one factor that has not been examined is the potential deleterious effects of cognitive fatigue from an academic school day combined with time of computerized neurocognitive testing (CNT) administration. The primary purpose of this study was to compare before-and after-school CNT performance and total symptoms in non-concussed high school student athletes. The secondary purpose of this study was to compare before-school and after-school CNT performance and total symptoms and chronotypes in non-concussed student athletes. A crossover design was used to compare before-and after-school CNT performance and total symptoms of 39 non-concussed high school student athletes with an average age of 15.74 (SD = 1.04). Based on previous literature a hypothesis was made that high school student athletes would report higher self-reported fatigue after-school than before-school. Differences in CNT performance and total symptoms were measured by comparing composite scores of verbal memory, visual memory, processing speed, reaction time and total symptoms. In addition, to main outcome measures, several measures were used to control for potential confounding factors that could influence CNT performance. Before-school self-reported fatigue (M = 3.83, SD = 1.64) was significantly higher than after-school (M = 3.06, SD = 1.91) self-reported fatigue. There were no significant differences in verbal memory t(38) = 0.80, p = .43, visual memory t(38) = -0.78, p = .44, processing speed t(38) = .07, p = .94, reaction time t(38) = 1.45, p = .16, or total symptoms t(38) = -0.64, p = .52, between before-school and after-school. Lastly, there were no significant differences in verbal memory F (1, 37) = 1.17, p = .21, η2 = .04, visual memory F (1, 37) = .05, p = .28, η2 = .00, processing speed F (1, 37) = 0.75, p = .39, η2 = .02, reaction time F (1, 37) = 1.65, p = .21, η2 = .04, or total symptoms F (1, 37) = 0.57, p = .46, η2 = .02 between morning and evening chronotypes. The results from this study suggest that sports medicine professionals can administer CNT before-or after-school depending on their schedule and the athlete’s academic and athletic schedule.</p>","abstract_has_math":false,"creators":["Anderson, Morgan"],"institution":null,"degree_name":"Master of Science in Kinesiology (MS)","degree_level":"Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Gray, Michelle","Ganio, Matthew S."],"advisors":["Elbin, Robert J."],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-05-01T07:00:00Z","date_published":"2017-05-01T07:00:00Z","updated_at":"2026-07-24T00:58:26Z","subjects":["Health and environmental sciences","Athletes","Concussion","Neurocognitive","Computational Neuroscience","Exercise Science"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarworks.uark.edu/etd/1929","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Gray, Michelle","Ganio, Matthew S."]},{"key":"dc:contributor.advisor","label":"Advisor","values":["Elbin, Robert J."]},{"key":"dc:creator","label":"Author","values":["Anderson, Morgan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2017"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2019-05-08T07:00:00Z"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Kinesiology (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Health and environmental sciences","Athletes","Concussion","Neurocognitive","Computational Neuroscience","Exercise Science"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarworks.uark.edu/etd/1929"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["There are several factors that influence computerized neurocognitive testing performance however, one factor that has not been examined is the potential deleterious effects of cognitive fatigue from an academic school day combined with time of computerized neurocognitive testing (CNT) administration. The primary purpose of this study was to compare before-and after-school CNT performance and total symptoms in non-concussed high school student athletes. The secondary purpose of this study was to compare before-school and after-school CNT performance and total symptoms and chronotypes in non-concussed student athletes. A crossover design was used to compare before-and after-school CNT performance and total symptoms of 39 non-concussed high school student athletes with an average age of 15.74 (SD = 1.04). Based on previous literature a hypothesis was made that high school student athletes would report higher self-reported fatigue after-school than before-school. Differences in CNT performance and total symptoms were measured by comparing composite scores of verbal memory, visual memory, processing speed, reaction time and total symptoms. In addition, to main outcome measures, several measures were used to control for potential confounding factors that could influence CNT performance. Before-school self-reported fatigue (M = 3.83, SD = 1.64) was significantly higher than after-school (M = 3.06, SD = 1.91) self-reported fatigue. There were no significant differences in verbal memory t(38) = 0.80, p = .43, visual memory t(38) = -0.78, p = .44, processing speed t(38) = .07, p = .94, reaction time t(38) = 1.45, p = .16, or total symptoms t(38) = -0.64, p = .52, between before-school and after-school. Lastly, there were no significant differences in verbal memory F (1, 37) = 1.17, p = .21, η2 = .04, visual memory F (1, 37) = .05, p = .28, η2 = .00, processing speed F (1, 37) = 0.75, p = .39, η2 = .02, reaction time F (1, 37) = 1.65, p = .21, η2 = .04, or total symptoms F (1, 37) = 0.57, p = .46, η2 = .02 between morning and evening chronotypes. The results from this study suggest that sports medicine professionals can administer CNT before-or after-school depending on their schedule and the athlete’s academic and athletic schedule.
"]},{"key":"dc:title","label":"Title","values":["Comparing Before-and After-School Neurocognitive Performance in High School Athletes- Implications for Concussion Management"]}]}],"canonical_facts":{"dc:contributor":["Gray, Michelle","Ganio, Matthew S."],"dc:contributor.advisor":["Elbin, Robert J."],"dc:creator":["Anderson, Morgan"],"dc:date":["2017"],"dc:date.available":["2019-05-08T07:00:00Z"],"dc:description.abstract":["There are several factors that influence computerized neurocognitive testing performance however, one factor that has not been examined is the potential deleterious effects of cognitive fatigue from an academic school day combined with time of computerized neurocognitive testing (CNT) administration. The primary purpose of this study was to compare before-and after-school CNT performance and total symptoms in non-concussed high school student athletes. The secondary purpose of this study was to compare before-school and after-school CNT performance and total symptoms and chronotypes in non-concussed student athletes. A crossover design was used to compare before-and after-school CNT performance and total symptoms of 39 non-concussed high school student athletes with an average age of 15.74 (SD = 1.04). Based on previous literature a hypothesis was made that high school student athletes would report higher self-reported fatigue after-school than before-school. Differences in CNT performance and total symptoms were measured by comparing composite scores of verbal memory, visual memory, processing speed, reaction time and total symptoms. In addition, to main outcome measures, several measures were used to control for potential confounding factors that could influence CNT performance. Before-school self-reported fatigue (M = 3.83, SD = 1.64) was significantly higher than after-school (M = 3.06, SD = 1.91) self-reported fatigue. There were no significant differences in verbal memory t(38) = 0.80, p = .43, visual memory t(38) = -0.78, p = .44, processing speed t(38) = .07, p = .94, reaction time t(38) = 1.45, p = .16, or total symptoms t(38) = -0.64, p = .52, between before-school and after-school. Lastly, there were no significant differences in verbal memory F (1, 37) = 1.17, p = .21, η2 = .04, visual memory F (1, 37) = .05, p = .28, η2 = .00, processing speed F (1, 37) = 0.75, p = .39, η2 = .02, reaction time F (1, 37) = 1.65, p = .21, η2 = .04, or total symptoms F (1, 37) = 0.57, p = .46, η2 = .02 between morning and evening chronotypes. The results from this study suggest that sports medicine professionals can administer CNT before-or after-school depending on their schedule and the athlete’s academic and athletic schedule.
"],"dc:identifier":["https://scholarworks.uark.edu/etd/1929"],"dc:subject":["Health and environmental sciences","Athletes","Concussion","Neurocognitive","Computational Neuroscience","Exercise Science"],"dc:title":["Comparing Before-and After-School Neurocognitive Performance in High School Athletes- Implications for Concussion Management"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science in Kinesiology (MS)"]},"updated_at":"2026-07-24T00:58:26Z"}