Descriptive statistics
Most of the mothers (66.5%) had to stop working or to start working from home in smart modality (Table 1). Mothers had similar age and number of children regardless of working conditions. Their children had similar age, about 4 years old on average. Mothers had a relatively high fear of contagion, and most of them knew someone who had contracted COVID-19 or passed away due to the contagion. Most of the children used to go to kindergarten before the lockdown, and they were informed about COVID-19 by their family using different modalities.
Changes in mothers
Sleep timing was markedly affected by the lockdown, with mothers starting to go bed on average ~ 54 min later (F1,241 = 116.7, p < 0.0001, \(\eta_{p}^{2}\) = 0.33), although this effect was less marked in mothers there were still going to work outside to their home (F3,242 = 4.00, p = 0.009, \(\eta_{p}^{2}\) = 0.04, Fig. 1a). Mothers started to wake up ~ 57 min later (F1,241 = 129.89, p < 0.0001, \(\eta_{p}^{2}\) = 0.35, Fig. 1b), regardless of the working situation. Overall, mothers showed a sleep quality worsening during lockdown (F1,241 = 76.91, p < 0.0001, \(\eta_{p}^{2}\) = 0.24, Fig. 1c), regardless of the working situation. This worsening was also confirmed by the proportion of mothers reporting poor sleep (i.e., PSQI > 5), which increased from 21.54% before the lockdown to 48.37% during the lockdown (\(\chi_{1}^{2}\) = 42.7, p < 0.001; odds ratio 4.82 [CI 2.84–8.68]).
Focusing on time experience (Fig. 1d), we observed that the mothers felt that the speed of the hours (F1,241 = 56.07, p < 0.0001, \(\eta_{p}^{2}\) = 0.19), the days (F1,241 = 60.26, p < 0.0001, \(\eta_{p}^{2}\) = 0.20), and the week (F1,241 = 46.56, p < 0.0001, \(\eta_{p}^{2}\) = 0.16) were slowing down during the lockdown. Moreover, they felt a marked decrease in time pressure (F1,241 = 135.78, p < 0.0001, \(\eta_{p}^{2}\) = 0.36) and an increase in time expansion (F1,241 = 116.13, p < 0.0001, \(\eta_{p}^{2}\) = 0.33) during the lockdown.
Looking at the SDQ subscales, we observed an increase in emotion symptoms (EMO) during the lockdown (F1,241 = 19.41, p < 0.0001, \(\eta_{p}^{2}\) = 0.07), but not in conduct problems (COND) or hyperactivity/inattention (HYPER) (all p’s > 0.23).
Changes in children
As for the mothers, children’ sleep timing was markedly affected by the lockdown. Children went to be on average ~ 53 min later (F1,241 = 259.0, p < 0.0001, \(\eta_{p}^{2}\) = 0.52, Fig. 2a), and wake up ~ 66 min later (F1,241 = 260.35, p < 0.0001, \(\eta_{p}^{2}\) = 0.52, Fig. 2b). The total score of the SDSC did not significantly change during the lockdown (F1,241 = 0.001, p = 0.970, \(\eta_{p}^{2}\) = 0.01). Similarly, the proportion of children with some sleep difficulties (i.e., SDSC > 39) was stable, from 41.46% before the lockdown to 44.72% during the lockdown (\(\chi_{1}^{2}\) = 0.71, p = 0.399; odds ratio 1.23 [CI 0.74–2.04]).
As regards time experience, mothers reported an increased sense of boredom during the lockdown in their children (F1,241 = 79.39, p < 0.0001, \(\eta_{p}^{2}\) = 0.24), in particular mothers who kept working in smart modality. Children also showed increased difficulties to follow daily routines (F1,241 = 55.35, p < 0.0001, \(\eta_{p}^{2}\) = 0.19), although their ability to keep track of the passage of time did not change during the lockdown (F1,241 = 0.01, p = 0.938, \(\eta_{p}^{2}\) < 0.01).
Focusing on the BRIEF-P, children showed an increased score in the Inhibitory Self-Control Index (ISCI) (F1,241 = 7.43, p = 0.007, \(\eta_{p}^{2}\) = 0.03, Fig. 2c), with the proportion of children with self-control difficulties (i.e., ISCI > 65) increased from 14.29% before the lockdown to 21.23% during the lockdown (\(\chi_{1}^{2}\) = 12.6, p < 0.001; odds ratio 6.67 [CI 1.98–35.04]).
Looking at the SDQ subscales, we observed an increase in emotion symptoms (EMO) (F1,241 = 6.57, p = 0.011, \(\eta_{p}^{2}\) = 0.03), conduct problems (COND) (F1,241 = 9.01, p = 0.003, \(\eta_{p}^{2}\) = 0.04), and hyperactivity/inattention (HYPER) issues (F1,241 = 31.56, p < 0.0001, \(\eta_{p}^{2}\) = 0.12) during the lockdown, regardless of the mother working situation (Fig. 2d).
Relationship between mothers’ and children’ sleep changes
Considering the age of the children (2–5 years old), it was expected that changes in the mothers' sleep timing would be associated with those of their children. Moreover, we expected that a lowering in children’ sleep quality would make their mothers’ sleep worse. Exploring these relationships, we observed a positive association between changes in the sleep quality of mothers and their children (r = 0.25, p < 0.001, Fig. 3a), although this relationship was driven by the mothers who continued working from home (r = 0.29, p = 0.003), and by the mothers who used to work but had to stop during the lockdown (r = 0.31, p = 0.012), but not by the mothers who did not work (r = 0.21, p = 0.135), and by the mother who continued working outside (r = − 0.10, p = 0.590). Also, later the mothers went to bed during the lockdown, later did their children (r = 0.30, p < 0.001), again with some differences due to the working conditions (see Fig. 3b). Similarly, the change in mother waketime was strongly associated with the change in children’ waketime (r = − 0.50, p < 0.001, Fig. 3c).
Factors associated with change in inhibitory self-control in children
The multiple regression model showed that the changes in children’s inhibitory self-control were associated with their sleep quality as well as their mothers’ sleep quality, i.e., worst sleep quality, worse inhibitory self-control, and by the total score of the mothers’ DERS, i.e., more the mothers had difficulties in regulating emotions, worse resulted the children’s inhibitory self-control (see Table 2). Children’ age, working condition of mothers, and the other factors were not significant associated with the changes in children’s inhibitory self-control. For all variables, tolerance was > 0.872 and VIF was < 1.14, indicating that multicollinearity was not a concern. Also, the data met the assumption of independent errors (Durbin–Watson value = 1.86) and the normal Q–Q plot of standardized residuals showed points that were not completely on the line, but close.
Table 2 Multiple regressions on change in inhibitory self-control in children Factors associated with change in SDQ total scores in mothers
The multiple regression on the change in mothers' strengths and difficulties (Table 3) showed the change in their sleep quality as well as in their children was associated with the change in their SDQ total score (i.e., worst the sleep quality, worse the SDQ scores). Also, the change in time pressure was associated with the change in SDQ total score (i.e., increased time pressure, worse SDQ scores) and in the fear of the COVID-19 (higher the fear, worse the SDQ scores). The other factors, including the working condition, were not significant. Variables showed a tolerance > 0.879 and a VIF < 1.15, indicating again that multicollinearity was not a concern. The data met the assumption of independent errors (Durbin–Watson value = 2.02) and the normal Q–Q plot of standardized residuals showed points that were not completely on the line, but close.
Table 3 Multiple regressions on change in SDQ total score in mothers