OBJETIVOS DE LA INVESTIGACIÓN

obtained mid-sleep values are compared to the phase of activity and rest on the morning, evening, and night shifts, as well as on the respective free days. MSFEscn will be correlated to the phase of actimetry on free days following the evening shift to test the validity of MSFEscn as a measure for chronotype. The criteria for validity will be based on comparisons to the correlation between MSFscn and phase of actimetry on free days in day workers.

4.3.1 Methods

4.3.1.1 Participants

A total of 39 shift workers (25 women and 14 men, Mage = 31.7 years, age range: 21-50) from the three-shift-model and 70 day workers (41 women and 29 men, Mage = 31.7 years, age range: 21-50) volunteered to participate in this study. The shift workers were employees at a Siemens security switch manufacturing plant in Cham, Germany. The mean shift work employment was 10.1 years. The day workers were employees of the OSRAM head office in Munich, as well as participants recruited for a study on daylight savings time, consisting mostly of students. Participants were recruited by means of flyers as well as talks given at scheduled meetings. Participants from the DST study were recruited mostly through personal contact and word of mouth.

4.3.1.2 Materials

The materials used in this study were daqtometer®, for the assessment of 24 hour actimetry Shift

so as to allocate the actimetry data to corresponding work and free days, and a daqtometer protocol. Please see General Methods.

4.3.1.3 Procedure

The Daqtometer® were distributed to the participants at the workplace to be worn for six continuous weeks (night and day), together with the six-week long sleep logs and the MCTQ/MCTQShift. All participants were thoroughly briefed before the study began. A one- to-one person training session lasting roughly 15-20 minutes was conducted before agreement of participation to ensure that participants were familiar with the Daqtometer® and the sleep logs. The participants worked their usual work schedule. Data collection by the shift workers took place between June and July 2008 in Cham. Data collection for the day workers took place at two separate time points in Munich, one between September and October 2006 and one between January and March 2008.

4.3.2 Results

The phase of activity was analyzed by means of the centre of gravity method (CoACT) (see Kenagy, 1980), which is independent of the individual shape of the activity profile. Daily values of centre of gravity (ψAct) were calculated individually for each participant with the ChronoProgramm. Based on entries into the daily sleep logs, the data were then categorized according to whether the given day was a workday or a free day, as well as according to the shift it belonged to. Time spans of removal of the Daqtometer® were excluded. A moving average sine adaptation over subsequent days for each shift without smoothing or filtering resulted in seven ψAct data points per shift, which were averaged to obtain a mean ψAct for

computed for workdays and for free days, for each shift, as indicated in Figure 3.2. The mixed week was excluded from analysis. Only participants with complete data sets were included. Thirty-three participants remained.

Table 4.5. Correlation Coefficients between MCTQShift _{and Actimetry}

Note: Spearman Rho correlation coefficients (ρ) between mid-sleep from the MCTQShift _{and average} centre of gravity from the actimetry data (ψAct) in 33 rotating shift workers. To correct for Bonferroni, alpha was set at .01. *p≤ .01.

Results from the Kolmogorov-Smirnov test showed a significant deviation from normality for some of the variables involved. As such, only non-parametric correlations were computed, by means of Spearman Rho correlations. To correct for Bonferroni, alpha was set at .01 (1-tailed). Table 4.5. presents the correlations between mid-sleep values from the MCTQShift and the ψAct for work and for free days, for each shift. Overall, mid-sleep values from the MCTQShift correlated well with the corresponding phase of activity, for all free days and for workdays, except for the morning shift. The reason why phase of activity in the morning shift did not correlate with MSW may be due to the low variance on morning shifts, due to the high constraints on the timing of sleep and activity. The best correlation was obtained for free days following the evening shift.

Work Days Free Days Morning Shift - .02 .47* Evening Shift .62* .70* Night Shift .56* -.68*

4.3.2.1 Validation of MSFEscn

The validity of MSFE_{scn as a measure of chronotype was examined by means of} comparison to phase of activity on free days following the evening shift. MSFEscn was computed for each individual as indicated in Figure 3.5., whereby only individuals who reported not waking-up to an alarm clock were considered. Only individuals for whom all data were present were considered. A total number of 26 rotating shift workers remained. Results from the Kolmogorov-Smirnov test showed no significant deviation from normality for all variables involved. Alpha was set at 0.01 to correct for Bonferroni. Results from the Pearson Product-Moment Correlation showed that MSFEscn correlated significantly with ψAct for free days following the evening shift: r (26) = .48, p ≤ .05 (one-tailed hypothesis).

4.3.2.2 Comparison to day workers

In order to compare the validity of MSFEscn as a measure of chronotype in shift workers to that of MSFscn in day workers, the same analysis was computed for day workers. Daily values of centre of gravity (CoGs, ψAct) were calculated for work days and for free days, which were averaged over one workweek. From the entries into the MCTQ, MSFscn was computed as indicated in Figure 3.5. After exclusion of individuals waking up with the use of an alarm clock, 41 day workers remained. Results from the Kolmogorov-Smirnov test showed no significant deviation from normality for both variables involved. In day workers too, MSFscn significantly correlated with Centre of Gravity of activity on free days (Pearson Product-Moment correlation): r (41) = .39, p ≤ .05 (one-tailed).

4.4 Physiological Phase Markers and their Relationship to the MCTQShift: