Circadian fluctuations in short time interval estimations: effects of work place factors

Bobko, Natalia

Institute for Occupational Health / Saksagansky St., 75 01033 Kiev Ukraine

+380 44 2894605 / nbobko@bigmir.net

Chernyuk, Vladimir

Institute for Occupational Health / Saksagansky St., 75 01033 Kiev Ukraine

+380 44 2843427   / yik@nanu.kiev.ua

Yavorskiy, Yeugeniy

Institute for Occupational Health / Saksagansky St., 75 01033 Kiev Ukraine

+380 44 2897630 / eugene_yavorsky@mail.ru

ABSTRACT

ABSTRACT

Time intervals of 2, 3, 4 and 5 seconds were estimated by human-operator hourly during simulative 12-h working shifts under 22oC/29oC air temperatures (AT), 60dBA/80dBA noise (N), low/high mental work strain (LWS/HWS). Altogether 9216 human-measures were analysed at p<.05. The most pronounced 5-7 (summer) a.m. time overestimations were smoothed when N or/and AT increased under LWS, became more prominent under HWS when AT increased. Increased strain speeded up the subjective time (ST) including the early morning hours under normal N and AT while under whole set of N and AT levels it speeded up ST at the day shifts and slowed it at nights. Heated environment speeded up ST under LWS at both day and night shifts and slowed ST under HWS at nights. Noise slowed ST at the day shifts under LWS and speeded up ST during the first part of the night shifts under HWS. The higher dependence of ST on the heated environment and noise at the night shifts reflects the higher reactivity and weakness of the adaptation body possibilities at nights.

Keywords

Keywords

Subjective time, circadian rhythms, human-operator, shiftwork, noise, heated environment

INTRODUCTION

INTRODUCTION

A sense of time is the innate human quality that is necessary to adjust effectively to the changing environment. Adequate estimation of short time intervals maintains the reliable human-operator performance, especially under about accident situations.

However subjective time depends on time of day, body state, work place environment and other factors like age, sex, individual differences, etc. [4,5,10,18,25- 27,29,34]. Maximal time overestimation in working people has been found at about 4a.m. [13,28,30]. Moderate mental strain lengthens the individual minute while strong and short mental strain in the opposite could shorten it [18]. The lack of boredom results in the underestimation of time [11]. Increased air temperature (+33.3oC)

shortens the subjective time (within 4 seconds – 1 minute interval) [10] while increased air humidity lengthens the individual minute [27]. Combined effect of heated environment (+35+41oC) and increased air humidity (55-60%) causes the pronounced time underestimation (of 3-second intervals) [25]. Noise could affect temporal discrimination [29]. The estimates of 5-30-second intervals become shorter as the intensity of noise increases from 50 to 80 dB but become longer at 90 dB. In this, noise affects were most prominent for longer intervals (15-30 seconds) [12]. Combined influence of noise, vibration and hypokinesia increased the stability of 0.5- second intervals estimation, the same influences during 43-45 hours caused the similar effect on 2- and 3-second intervals estimation [25]. In this, variations in the work place factor levels (like mental strain, noise, air temperature, etc.) in the real industries take place often.

The purpose was to reveal the circadian fluctuations in the short time interval estimations and the dependence of these ones on mental strain, noise and air temperature among human-operators under round-o-clock shiftwork.

METHODS

Subjects

Participants, 3 male students of 19, 22 and 29 years old, were recruited as volunteers. All three had normal vision, no sleep, medical or psychiatric disorders, they were not on medications and were found to be in a good physical conditions. The tasks, terms and circumstances of the experiment were explained. During training sessions subjects mastered computer based tests and acquainted with the whole scheme of the experiment. Each subject signed an informed consent agreement prior to his participation. Volunteers were paid for their contribution.

Material

The experiment was curried out in a climatic chamber isolated from external light and noise. The humidity was maintained within 40-60%, lightening was constant:

500 lx – at the table, 300 lx – at the PC screen. The chamber was equipped with aconditioner McQuay MCC010CR (2004) intended to maintain climatic conditions under outdoor temperature within a range from –5oC to +40oC.

Three IBM-compatible personal computers, equipped with CPUs Pentium and similar class and RAM from 8 to 32 Mbytes, were used. All computers operated in a single-task environment (MS DOS 7.1). Analogue colour displays were used in a graphics mode with resolution 640 * 350 pixels (refresh rate 60Hz, non-interlaced). Each given task occupied on a display a rectangle area with the dimensions 32 * 7 symbols that took about 11% of a total workspace.

Experimental procedure

All three subjects took part in 16 sessions simulated human-operator work of predominantly mental character under low and high work strain during 12-hour day (8:00-20:00) and night (20:00-8:00) shifts. Daylight-saving time was on.

In the beginning of each hour of a 12-hour session all subjects fulfilled computer based tasks on time estimation during about 2 minutes. After that they worked under time pressure computer based tasks during 11 minutes and filled in a questionnaire (paper version) that took about some minutes – while the low work strain was simulated. Under simulation of the high work strain, subjects worked under time pressure test during 17 minutes, then fulfilled pen-and-pencil tasks and filled in the same questionnaire that took about 25 minutes. The rest periods took about 40 minutes per hour within the low strain sessions and 15-17 minutes per hour within the high strain sessions. These ones were used to measure some physiological parameters, to take a meal (2 times during the day time sessions and 1 time – at the night time

sessions), to visit toilet room, etc.

Each session was different in the combination of work place factors examining the interaction of 2 ranges of each of them: 2 periods of time of day – day and night (correspondingly to the day and night shifts), 2 levels of noise of the same spectrum frequency – 60 dBA (permissible level) and 80 dBA (increased level), 2 levels of air temperature - 22oC (optimal level) and 29oC (increased level) and 2 levels of mental work strain – low and high (table 1). Noise was recorded under real industrial conditions – at a control room in a heat power plant.

Table 1. Work place conditions simulated in the course of the experiment

Tasks

Computer based tasks on time estimation included 16 tasks to repeat thetemporal intervals between 2 short sounds accompanied with a visual symbols at the PC screen: 2-, 3-, 4- and 5-second intervals were presented by 4 times in a casual order (modified method from [34]). The real reproduced time interval was registered automatically for each task.

Analysis

Results of (3 subjects * 12 times per session * 16 sessions * 16 temporal tasks

=) 9.216 human-operator tests were analysed by the parameter of the subjective time that was the ratio of the real reproduced time to the real presented time interval. Group approach was used. Basic statistics, ANOVA and regression analysis were performed at a p-value of 0.05. Effects of air temperature, noise, mental strain, time on task, time of day, temporal interval length and inter-individual differences were analysed.

RESULTS

Effects of the simulated work place and accompanying factors on the temporal interval estimations are presented in the table 2.

Table 2. Effects of the work place and accompanying factors on the subjective time

Note: “*” - significant effect (p<0.05), “+” - deviation of the work place factor level from the optimal/permissible level caused the lengthening in the subjective time, “-” – the shortening in it; “0” – non-significant effect (p>0.05).

Increase in the air temperature shortened the subjective time among the overall data (p=0.003), among the night shifts data (p=0.007) and showed similar tendency among the day shift data (p=0.134).

No effect of noise was found but at the night shifts the tendency to shorten the subjective time appeared (p=0.154).

Mental work strain increase at the day shifts also shortened the subjective time (p<0.0001), at the night shifts, in the opposite, lengthened it (p=0.007). Significant opposite effects of the increase in mental strain on the subjective time at the day and night shifts, apparently, were resulted in the absence of significant effect within the overall data.

Time-on-task showed significant effect in the each case, however at the night shifts the effect was more pronounced (p<0.0001) compared to the day shifts (p=0.036). Some increase in time estimations had been found at the 4th hour of time- on-task and also after 8 hours of working in a shift (at 9-12th hours) (fig.1).

Day or night period of time did not effect the subjective time, although the tendency to lengthen the subjective time at the night shifts compared to the day shifts was found (F=2.015, p=0.152).

At the same time, time-of-day effect due to the hourly – 24-anchor – scale showed significant effect on the subjective time (p<0.0001). The most pronounced time overestimation has been found at 5-7 a.m. (fig.2). Some overestimation of time was found also at 10-11 a.m., relatively short subjective time – at 3 and 10 p.m., 1 and 8 a.m.

The length of temporal interval showed highly significant effect on its subjective estimation (F=1425.7, p<0.0001). In this, 2- and 3-second intervals were mainly overestimated, 4- and 5-second intervals – underestimated, summarising in some overestimated subjective time as a mean (1.060+/-0.007).

1,11

1,09

1,07

1,05

Mean-St.Err. Mean Mean+St.Err.

1,03

1,01

1 2 3 4 5 6 7 8 9 10 11 12time on task (hours)

Fig. 1. Subjective time fluctuations during the simulated working shifts

1,16

1,14

1,12

1,1

Mean+St.Err. Mean

Mean-St.Err.

1,08

1,06

1,04

1,02

1

0,98

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

time of day

Fig. 2. Subjective time fluctuations during 24 hour cycle

No individual differences in the temporal interval estimations have been found. The calculated regression equations showed the following: (1) for the overall data:

Y (overall)= 1.060 – ((0.001*N)) – 0.010*T – ((0.004*S)) + ((0.004*D));(2) for the day shift data:

Y (day shifts)= 1.056 + ((0.004*N)) – (0.007*T) – 0.020*S;(3) for the night shift data:

Y (night shifts)= 1.064 – (0.007*N) – 0.013*T + 0.013*S;where Y – subjective time, N – noise, T – air temperature, S – mental work strain, D – period of day (day or night shift), the bold type means the significant coefficient at p<0.05, normal type within the breaks means the tendency at 0.20<p<0.05, normal type within the double breaks means the non-significant coefficient.

Considering the opposite directed effects of the mental work strain on the temporal interval estimation at the day and night shifts, the regression equations were calculated also for the sessions with the low and high mental work strain separately for the day and night shifts:

(4) for the day shifts under the low work strain:

Y (day shift, low strain) = 1.076 + 0.013*N – 0.015*T;(5) at the night shifts under the low work strain:

Y (night shift, low strain) = 1.051 – ((0.004*N)) – 0.042*T;(6) at the day shifts under the high work strain:

Y (day shift, high strain) = 1.036 – ((0.005*N)) + ((0.001*T));(7) at the night shifts under the high work strain:

Y (night shift, high strain) = 1.076 – ((0.010*N)) + 0.017*T.

So, at night shifts the sensitivity of the subjective time to air temperature and/or noise increase was higher compared to the day shifts: the corresponding coefficients in the 3rd equation are higher than in the 2nd one.

The sensitivity of the subjective time to an increase in the air temperature at nights also was found to be higher compared to the day shifts: in the 5th and 7th equations the corresponding coefficients were higher than in the 4th and 6th equations; the effect was not significant at the day shifts under the high work strain only. In this, an increase in air temperature resulted in the lengthening of the subjective time under the high work strain at the night shifts and in the shortening of it – under the low work strain at both day and night shifts.

Noise increase lengthened the subjective time at the day shifts under the low work strain and showed the opposite tendency at the night shifts under the high work strain.

Consequently as a whole at the night shifts the sensitivity of the subjective time to the increases in the work place factors (air temperature, noise) from the optimal/permissible to some increased levels are higher compared to the day shifts (due to the equations 2 and 3). In this, effect of air temperature increase from 22oC to 29oC has been pronounced to the higher extent than effect of the noise increase from 60 dBA to 80 dBA. Work strain increase leads to the opposite directed changes (p<.05) in the subjective time at the day and night shifts: shortens the subjective time at the day and lengthens it at the night shifts. The effect is some more prominent at the day shifts. Air temperature increase leads to the shortening in the subjective time under the low work strain at both day and night shifts and to the lengthening in the subjective time under the high work strain, which is significant (p<.05) at the night shifts.

Changes in the work strain, deviations in the levels of noise and air temperature were accompanied with the changes in the prominence of 24-hour variations of the subjective time and the displacements of their local minimums and maximums (fig. 3, 4: considering highly significant dependence of the subjective estimations of the real temporal interval on the length of it, the mean subjective estimation of each interval length by each subject was considered as 100%).

Within the frames of optimal air temperature and permissible noise the increase in the mental work strain as a whole shortened the subjective time including smoothing the early morning time overestimation (fig.3).

Fig.3. Circadian fluctuations in the subjective time under permissible level of noise (60 dBA) and optimal air temperature (22oC): effect of mental work strain

Y-axis – subjective time in %; 100% - 24-hour mean of the individual estimation of the each temporal interval under the low work strain. X-axis – time of day (hours). Mean and Mean+/-Standard Error are presented for each hour.

Within the frames of the low or high mental work strain there were found the different effects of the increase in noise or/and air temperature on the subjective time (fig.4).

Under the low work strain the increase in noise or/and air temperature smoothed the early morning lengthening in the subjective time, under the high work strain, in the opposite, the increase in the prominence of the early morning lengthening in the subjective time was found when the air temperature increased.

Increased air temperature under the low mental strain, and, to the lesser extent, increased noise under the high mental strain (except night) mainly shortened the subjective time compared to its mean circadian level under favourable work place factors.

DISCUSSION

It is found that the circadian fluctuations in the short time interval estimations include some relatively stable ups and downs with the most pronounced overestimation in the early morning hours (5-7 a.m. under summer time). This goes right with the literature data [13,28,30]. On the other hand, the early morning peak in the road traffic accidents has been described [1,2].

Less pronounced time overestimation found at 10-11 a.m. (that is 9-10 a.m. ofa real local time) coincides with the circadian improvement in a short term memory and the efficiency in some tests involving attention and reaction time [7].

Fig.4. Circadian fluctuations in the subjective time: effects of noise and air temperature

Y-axis – subjective time in %; 100% - 24-hour mean of the individual estimations of the each temporal interval under corresponding work strain. X-axis – time of day (hours). Mean and Mean+/-Standard Error are presented for each hour.

Relatively short subjective time found at 3 p.m. (that is 2 p.m. of a real local time) makes some parallels with the known from literature post lunch deep in the efficiency and increases in the accidents and injuries [6,8,9,14,15,20,22,24,31,33],

Relatively short subjective time about midnight (10 p.m., 1 a.m.) makes some links with the described midnight maximums in the accidents and injuries at the industry enterprises [16,17], as well as with the times when the most large accidents of the XX century involving human factor occurred – at Bhopal chemical factory (0h 40 min), Axxon Valdez oil tanker (0h 04min) and Chernobyl NPP (1h 23 min – 1 h of summer time – 1h of decreed time=23h 23 min).

Relatively short subjective time found at 8 a.m. could evidence the generalbody activation in the morning that coincided with the shift start in the experiment conducted.

Some increases in the subjective time found at the 4th hour on a duty and after8 hours of working go right with the “black times” in safety found at the 2nd-4th hours of time on duty [14] and the sharp increase in the work injuries after 8 hours of timeon task [3].

Thus, the subjective time seems to be connected with the different cognitive functions and also parameters of working in the real production conditions (efficiency, accidents and injuries in the industry, transportation, etc.). Some studies showed its links to the reaction time [23], motor timing [32], memory [21], attention concentration [19], etc.

The revealed underestimation of time under the high work strain compared to the low work strain is in the accordance with the literature data [11,18]. This one was found under normal noise and air temperature levels during both day and night shifts. Under the whole set of the studied levels of air temperature and noise the time underestimation under increase in mental work strain was found only during the day shifts; the increased levels of these factors caused the lengthening in the subjective time at night, mainly for the account of the second part of it including early morning hours.

Described in literature shortening in the subjective time under the airtemperature increase [10,25] was found under the low work strain only: it was significant (at p<.05) during both the night and the day shifts. The opposite regularity was found under the high mental work strain, i.e. the lengthening in the subjective time under the air temperature increase that was significant at the night shifts and was not significant in the day shifts (see the equations 4-7 and fig.4). Under both low and high work strain the prominence of the air temperature effect was higher at night.

Noise slowed the subjective time during the day shifts and first part of the night shifts under the low mental strain. The opposite tendency was found at nights under the high mental strain (see the equations 4-7 and fig.4).

Hence, mental work strain, noise and air temperature could make the significant effects on the subjective time that in its turn could contribute into the human-operator reliability.

The early morning overestimation of time (that could be connected with theearly morning peak in the road accidents [1,2]) under the low work strain could be smoothed with noise or/and air temperature increase while under the high work strain only the further lengthening in the subjective time could be reached with the air temperature increase.

As a whole, at night the dependence of the subjective time on the work place factors (air temperature, noise) is pronounced to the more high extent compared to the day time. This evidences the more high reactivity and weakness of the body adaptation possibilities at night. Mental strain effect, in the opposite, is less pronounced at night evidencing the shortage of body resources to maintain the demanding work strain that in its nature is the reflection of the same – the weakness of body possibilities to adjust to working at night compared to the day time.

CONCLUSIONS

A sense of time (at least regarding short time intervals) seems to be one of the key functions of human nervous system that is linked to the different relatively pure (memory, attention, reaction time, etc.) and integral (professional performance, safety) cognitive functions of human-operator. This found its reflection in circadian fluctuations of the short time interval estimations that include the most pronounced and stable time overestimations in the early morning hours (at 5-7 a.m. due to summer time). Less pronounced overestimations were found at 10-11 a.m., relatively short subjective time – at 3 p.m., about midnight and at 8 a.m. In this, both – relatively short and long subjective times could affect human-operator performance.

Under relatively normal levels of noise and air temperature, as a whole, the subjective time under the high mental work strain is shorter compared to the low work strain including the early morning hours. Under the whole set of the studied variety of noise and air temperature – from permissible/optimal to some increased – levels, the increased strain speeded up the subjective time at the day shifts and slowed it at the night shifts. Effects of noise and/or air temperature increase were different under different levels of work strain and different periods of 24-hour circle.

The early morning peak of time overestimations could be smoothed with noise or/and air temperature increase under the low mental work strain while under the high work strain only the further lengthening in the subjective time could be reached with the air temperature increase.

Increase in the air temperature speeded up (p<.05) the subjective time underthe low work strain at both day and night shifts and slowed the subjective time under the high mental strain that was significant (p<.05) at the night shifts. Under both low and high work strain the effect of air temperature increase was more pronounced at night.

Noise slowed the subjective time at the day shifts under the low mental strainand speeded up the subjective time during the first part of the night shifts under the high mental strain.

The higher dependence of the subjective time on noise and heated environment that was found at the night shifts reflects the higher reactivity and weakness of the adaptation body possibilities at nights. The strict monitoring of these work place factors as well as work strain level has to be recommended in the professions where safety is paramount.

ACKNOWLEDGMENTS

We would like to thank our colleagues who contributed into the data collection: Dr. O.M.Tkachenko, Mrs. T.S.Chuy, Mrs. T.Ye.Strelkovskaya, Dr. V.B.Lastovchenko, Mrs. L.Alekseyeva, Mrs. O.P.Nagornyuk.

REFERENCES

• 1. Akerstedt, T., Kecklund, G., Age, gender and early morning highway accidents. J Sleep Res 10, 2 (2001), 105110.
• 2. Akerstedt, T., Kecklund, G., Horte, L.G., Night driving, season, and the risk of highway accidents. Sleep 24, 4 (2001), 401406.
• 3. Akerstedt,  T.,  Work  injuries  and  time  of  day  –  National  data.  Shiftwork International Newsletter 12, 1 (1995), 2.
• 4. Alianchikova, Yu.O., Smirnov, A.G., Link between individual minute and anxiety in

neurosis patients. Fiziologiya Cheloveka 23, 5 (1997), 51-54 [In Russian].

• 5. Ariznavarreta, C, Cardinali, D.P., Villanъa, M.A., Granados, B., Martнn, M., Chiesa, J.J., Golombek, D.A., Tresguerres, J.A. Circadian rhythms in airline  pilots submitted to longhaul transmeridian flights. Aviat Space Environ Med 73, 5 (May 2002),  445455.
• 6. Atkinson, G., Reilly, T., Circadian variation in sports performance. Sports Med 21, 4 (1996), 292312.
• 7. Blake, M.J.F., Time of day effects on performance in a range of tasks. Psychonomic Science 9 (1967), 349350.
• 8. Carrier, J., Monk, T.H., Circadian rhythms of performance: new trends. Chronobiol Int  17, 6 (2000), 719732.
• 9. Colquhoun, P., Performance rhythms. Biological Rhythms (Ed: J.Aschoff). Mir, Moscow, 1 (1984), 389408 [In Russian].
• 10. Curley, M.D., Hawkins, R.N., Cognitive performance during a heat acclimatization regimen. Aviat Space Environ Med 54, 8 (1983), 709713.
• 11. Danckert, J.A., Allman, A.A., Time flies when you're having fun: temporal estimation and the experience of boredom. Brain Cogn 59, 3 (2005), 236245.
• 12. Delay, E.R., Mathey, M.E., Effects of ambient noise on time estimation by humans. Percept Mot Skills 61, 2 (1985), 415419.
• 13. Fleishman, A.N., Changed consciousness states in operators of metallurgical industry at night time. Medicina Truda i Promyshlennaya Ecologiya 7 (2001), 44 49 [In Russian].
• 14. Folkard, S., Black times: temporal determinants of  transport safety. Accid Anal Prev  29, 4 (1997), 417430.
• 15. Folkard, S., Effects on performance efficiency. Shiftwork. Problems and Solutions (Ed: W.P. Colquhoun, G. Costa, S. Folkard, P. Knauth). Lang, Frankfurt am Main; Berlin; Bern; New York; Paris; Wien (1996), 113139.
• 16. Folkard,  S.,  Hill,  J.,  Shiftwork  and  accidents.  Shiftwork  2000.  Implications  for Science,  Practice  and  Business  (Ed:  T.Marek,  H.Oginska,  J.Pokorski,  G.Costa, S.Folkard). Jagiellonian University, Krakow (2000), 1128.
• 17. Folkard, S., Tucker, P.T., Shift work, safety and productivity. Occup Med (Lond) 53, 2 (2003), 95101.
• 18. Goosev, Ye.V., Individual estimation of temporal intervals as a possible criterion of fatigue. Proc. of the 4th AllUnion Conference “Medicalphysiological and organizational aspects of elaboration of active rest programms”. Moscow (1982), 7375 [In Russian].
• 19. Ikeda, T., Concentrationeffect and underestimation of time by acoustic stimuli Shinrigaku Kenkyu 63, 3, (Aug 1992), 157162 [In Japanese].
• 20. Kundi, M., Sprenger, J., Gartner, J., Accidents in bus and tram drivers – length of duty and time of day effects. Shiftwork International Newsletter 22, 2 (2005), 95.
• 21. Lalonde, R., Hannequin, D., The neurobiological basis of time estimation and temporal order. Rev Neurosci 10, 2 (1999) 5173.
• 22. Lenne, M.G., Triggs, T.J., Redman, J.R., Circadian issues in driving. Proc. of the Second International Conference in “Fatigue and Transportation: Engineering, Enforcement and Education Solutions”. Fremantle, Western Australia, February 11 16, 1996 (Ed: L.Hartley). Promaco Convention Pty Ltd, Fremantle (1996), 283 301.
• 23. MacDonald, C.J., Meck, W.H., Systemslevel integration of interval timing and reaction time. Neurosci Biobehav Rev. 28, 7, (Nov 2004), 747769.
• 24. McDougall, S., Tyrer, V., Folkard, S., Searching for signs, symbols, and icons: effects   of   time   of   day,   visual   complexity,   and   grouping.   J.   Experimental Psychology: Applied 12, 2 (2006), 118128.
• 25. Medvedev, V.I., Bagrova, N.D., Stability in time perception as one of the criteria of humanoperator  workability  estimation.  Fiziologiya  Cheloveka  3,  2  (1977),  288 294 [In Russian].
• 26. Moiseyeva, N.I., Perception of time by human consciousness. Chronobiology and Chronomedicine (Ed: F.I.Komarov). Medicine, Moscow (1989), p.261277 [In Russian].
• 27. Moiseyeva,  N.I.,  Sysuyev,  V.M.  (1981).  Temporal  Environment  and  Biological Rhythms. Nauka, Leningrad [In Russian].
• 28. Oranskiy, I.E. (1988). Natural Medicinal Factors and Biological Rhythms. Medicine, Moscow [In Russian].
• 29. Rammsayer, T., Ulrich, R., No evidence for qualitative differences in the processing of short and long temporal intervals. Acta Psychol (Amst) 120, 2 (2005), 141171.
• 30. Razumov, A.N., Oranskiy, I.E. (2004). Natural Medicinal Factors and Biological Rhythms in Recovery Chronomedicine. Medicine, Moscow [In Russian].
• 31. Reinberg, O., Reinberg, A., Tehard, B., Mechkouri M. Accidents in children do not happen at random: predictable timeofday incidence of childhood trauma. Chronobiol Int 19, 3 (2002), 615631.
• 32. Rubia,  K.,  Smith,  A.,  The  neural  correlates  of  cognitive  time  management:  a review. Acta Neurobiol Exp (Wars) 64, 3 (2004), 329340.
• 33. Smith,     L.,    Shiftwork,     sleep    disturbance     and    sleepiness.     Shiftwork     2000. Implications   for     Science,   Practice   and  Business  (Ed:   T.Marek,   H.Oginska, J.Pokorski, G.Costa, S.Folkard). Jagiellonian University, Krakow (2000), P.4569.
• 34. Tsukanov,      B.I.,      Factor     of    time      and     cardiovascular       disease     problem.

Psihologicheskiy Zhurnal 10, 1 (1989), 83-88 [In Russian].