The results were collated for the class and analysed. Data were analysed by using the Statistical Package for Social Sciences (SPSS) for Windows. A two way ANOVA with repeated measures was used to investigate if any significant differences were apparent between N/SD4-17 and N/SD zero for the 5 times of day. According to Mauchly’s test of sphericity, the degrees of freedom were corrected in the normal way, using Huynh-Feldt (>0.75) or Greenhouse geisser (<0.05). For analysis of performance variables the first and last three dart throws were not included.
3. Results (See tables 1 & 2) Oral temperature showed a diurnal variation with lowest values in the morning between 08:00h- 12:00h and highest values in the evening between 16:00-20:00h; p>0.05 (see figure 2). Results for performance F 1, 58 = 24.485, p < 0.05 and for time; F 5, 290 = 16.494, p < 0.05 both indicate a significant difference. There was no significant interaction between performance and time F 5, 290 = 0.678 p > 0.05. Mean difference of performance between normal and deprived sleep was 7.516, p < 0.05 (see figure 2) thus showing that there is a significant difference between the two groups. N zero and SD zero results were also analysed (figure 3): performance F 1, 58 = 29.825, p < 0.05 and for time; F 5, 290 = 6.815, p < 0.05. This shows a significant difference.
4. Discussion and Conclusion. The aim of this study was to explore changes occurring between performance and temperature over different times throughout the day. It also looked to see if sleep deprivation had an effect on performance. The graphs indicate that performance peaks in the evening, which for this type of performance variable would not be expected as it is a fine motor skill test. Hand steadiness is at an optimum level for performance due to arousal levels being at their lowest in the diurnal peak in the morning, which helps increase accuracy (Reilly et al., 1997).
Figure 2 shows no significant variation in temperature over the two experimental days (F=0.863) On both days temperature follows time of day differences peaking at 1600h (normal sleep at 36.2C and deprived sleep at 36.C) Acrophase and amplitude of temperature remain unchanged during exercise. Acrophase in larks occur earlier than that of owls (Reilly et al., 2004). There was no significant correlation between temperature and chronotype (t57= -4.708, p < 0.05) (figures 15 and 16) The two separate conditions were not individually analysed for biorhythm and standard deviation, a mean was taken from both days, biorhythm and standard deviation for temperature can be found.
There were significant differences between N_4-17 and SD_4-17 (F= 25.485) and N_zero and SD_zero (F= 29.825), which was expected, as previous research had shown sleep deprivation to impair performance. Figures 3 and 4 show that performance means (4-17 and zero respectively) were affected by time of day differences on both days, showing that circadian rhythm affects performance. Figures 9-12 show mean, standard deviations and biorhythms for performance (4-17 and zero).
A factor which should however be considered is that of motivational levels. Reilly et al., (2004) stated that, motivational levels affect performance levels (Reilly et al., 2004); this factor could affect this study as participants were asked to take part in a repetitive test. Another factor that should be taken into account with this type of study is the build up of ‘fatigue’ due to time awake (Carrier and Monk 2000).
Obviously during the sleep deprived day participants would feel greater fatigue, but during the ‘normal’ day, fatigue due to time awake cannot be ignored. This could be one of the reasons why some of the data was seen as unreliable. Figures 21-24 show correlations between chronotype and the performance variables. There was no obvious correlation between chronotype and N_4-17 (t57 = -9.383, p < 0.05) and SD_4-17 (t57 = -6.067, p < 0.05). Figure 5 shows time of day differences for tiredness and alertness scores. SD_tiredness scores were significantly higher then N_tiredness (F=61.211) and SD_alertness scores were significantly lower that N_alertness (F=43.122). Figures 7-10 show mean, standard deviations and biorhythm for tiredness and alertness variables.
Figures 17-20 show the correlation of chronotype and the variables. Tiredness showed a significant negative correlation with chronotype (N_tiredness, t57 = 26.235, p > 0.05 and SD_tiredness, t57 = 25.702, p > 0.05) and alertness showed a significant positive correlation with chronotype (N_alerness, t57 = 31.420, p > 0.05 and SD_alertness, t57 = 33.467, p > 0.05). Reilly et al. (2004) suggests there is a rhythm in arousal and alertness, which means that even during wakefulness individuals are ready for different performance types.
The hormone, melatonin synthesised by the pineal gland affects alertness, by the amount released at different times during the day. It’s been suggested that levels of hormones circulating the body can affect performance (Reilly et al., 2004). The change in alertness scores shows that sleep deprivation reduces alertness for the rest of the day, although time of day differences remain unchanged.
These findings suggest that partial sleep deprivation impairs cognitive performance. The conclusions drawn from this study are limited to fine motor skill performance, such as dart throwing and other activities which involve similar processes. However it would be interesting to do further research to see if these findings can be transferred to other activities which require explosive power (sprinting, long jump) or endurance (long distance running), to confirm the findings of Martinez and Coyle’s (2007) study into sleep duration and physical and mental fatigue. In summary, it should, firstly, be noted that the data was found to be unreliable, this indicates that the results from the ANOVA’s may also not be accurate, however, it can still be stated that partial sleep deprivation is likely to impair cognitive performance.
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