Psychomotor Speed And Sleep Disturbance In Collegiate Athletes
College
College of Health Sciences
Department
Department of Rehabilitation Sciences
Graduate Level
Doctoral
Graduate Program/Concentration
Kinesiology and Rehabilitation
Presentation Type
Poster Presentation
Abstract
Sleep quality plays an essential role in daily functioning and athletic performance, yet its influence on basic motor responses remains unclear. This study examined whether sleep disturbances affect psychomotor speed in college athletes. A total of 112 college-aged athletes completed the Pittsburgh Sleep Quality Index (PSQI), which scores sleep quality on a scale from 0 to 21 (with higher scores indicating poorer sleep). Based on PSQI scores, participants were categorized into three groups: normal sleep quality (scores 0–5; n = 30), mild sleep disturbance (scores 6–10; n = 45), and moderate to severe sleep disturbance (scores ≥11; n = 37).
Psychomotor speed was measured using the Psychomotor Vigilance Task (PVT), a computerized reaction time test that assesses motor responses to visual stimuli. The descriptive statistics showed that the normal sleep group had a mean PVT reaction time of 185.70 milliseconds (SD = 17.14), the mild disturbance group had a mean of 187.73 milliseconds (SD = 24.72), and the moderate/severe disturbance group had a mean of 184.05 milliseconds (SD = 19.78). These figures are consistent with the group means presented in the descriptive table.
A one-way analysis of variance (ANOVA) revealed no significant differences in psychomotor speed among the three groups, F(2,109)=0.306, p=0.737. The effect size was exceedingly small, with an η² value of 0.004 (95% CI: 0.000 to 0.020), showing that sleep quality accounted for less than 1% of the variance in psychomotor speed. To further examine the differences between groups, Tukey’s Honestly Significant Difference (HSD) post hoc tests were conducted. The post hoc comparisons showed that the differences between normal and mild (mean difference = –2.03, p = 0.914), normal and moderate/severe (mean difference = 1.65, p = 0.947), and mild and moderate/severe (mean difference = 3.68, p = 0.717) groups were not statistically significant, as confirmed by confidence intervals that all included zero.
The results indicate that, among college athletes, sleep disturbances as measured by the PSQI do not have a significant impact on psychomotor speed as assessed by the PVT. These findings suggest that basic motor response times are resilient to variations in sleep quality. Future research should explore whether other cognitive or neuromuscular functions might be more sensitive to the effects of sleep disturbances.
Keywords
Sleep quality, Sleep disturbance, Psychomotor speed, Collegiate athletes, Pittsburgh Sleep Quality Index, Psychomotor vigilance task, Reaction time, Sports sciences
Psychomotor Speed And Sleep Disturbance In Collegiate Athletes
Sleep quality plays an essential role in daily functioning and athletic performance, yet its influence on basic motor responses remains unclear. This study examined whether sleep disturbances affect psychomotor speed in college athletes. A total of 112 college-aged athletes completed the Pittsburgh Sleep Quality Index (PSQI), which scores sleep quality on a scale from 0 to 21 (with higher scores indicating poorer sleep). Based on PSQI scores, participants were categorized into three groups: normal sleep quality (scores 0–5; n = 30), mild sleep disturbance (scores 6–10; n = 45), and moderate to severe sleep disturbance (scores ≥11; n = 37).
Psychomotor speed was measured using the Psychomotor Vigilance Task (PVT), a computerized reaction time test that assesses motor responses to visual stimuli. The descriptive statistics showed that the normal sleep group had a mean PVT reaction time of 185.70 milliseconds (SD = 17.14), the mild disturbance group had a mean of 187.73 milliseconds (SD = 24.72), and the moderate/severe disturbance group had a mean of 184.05 milliseconds (SD = 19.78). These figures are consistent with the group means presented in the descriptive table.
A one-way analysis of variance (ANOVA) revealed no significant differences in psychomotor speed among the three groups, F(2,109)=0.306, p=0.737. The effect size was exceedingly small, with an η² value of 0.004 (95% CI: 0.000 to 0.020), showing that sleep quality accounted for less than 1% of the variance in psychomotor speed. To further examine the differences between groups, Tukey’s Honestly Significant Difference (HSD) post hoc tests were conducted. The post hoc comparisons showed that the differences between normal and mild (mean difference = –2.03, p = 0.914), normal and moderate/severe (mean difference = 1.65, p = 0.947), and mild and moderate/severe (mean difference = 3.68, p = 0.717) groups were not statistically significant, as confirmed by confidence intervals that all included zero.
The results indicate that, among college athletes, sleep disturbances as measured by the PSQI do not have a significant impact on psychomotor speed as assessed by the PVT. These findings suggest that basic motor response times are resilient to variations in sleep quality. Future research should explore whether other cognitive or neuromuscular functions might be more sensitive to the effects of sleep disturbances.