Delayed weekend sleep pattern in German infants and children aged 0–6 years

Abstract

In this study, parents of pre-school children (0-6 years) answered an online questionnaire (444 girls, 447 boys). Children's bedtimes are earlier before weekdays and later before weekend days, and this difference becomes greater with age suggesting an increasing social jet lag at an early developmental stage. Half of the children have a sleep-onset latency of 15 min or shorter. When asked for children's optimal wake/bedtimes, parents would prefer later weekend rise times but earlier bedtimes both during the week and the weekend. Weekday rise times are determined by bedtimes during the week, awakening of children, parents' schedule and working hours per week. Bedtimes are determined by daytime napping, parental setting of bedtimes, and parental efforts for earlier bedtimes, parental efforts for regular bedtimes and by parental age. Chronotype changes and misalignment occurs at an early developmental stage, suggesting that parental influence exists and has an impact on the sleep-wake cycle (e.g. delaying of bedtimes at the weekend). We encourage parents to maintain a stable bedtime to avoid misalignment.

The influence of personality and chronotype on distance learning willingness and anxiety among vocational high school students in Turkey

“…There are small but significant gender differences with women scoring higher on morningness (Díaz-Morales & Randler, 2008;Randler, 2007). Also, age effects can be found with young children being more morning oriented at the kindergarten age (Randler, Fontius, & Vollmer, 2012) to morningness occurs (Roenneberg, Kuehnle, Pramstaller, Ricken, Havel, Guth, & Merrow, 2004) and people become progressively more morning oriented towards their later years of life (Randler & Bausback, 2010). Despite these common general patterns, significant inter-individual differences in chronotype remain throughout the lifespan.…”

The Rhythm Is Gonna Get You: The Influence of Circadian Rhythm Synchrony on Self‐Control Outcomes

“…The estimated percentage of people who fall within these preference categories varies from study to study, likely because of sample size, different scale cutoffs, and demographic composition. Furthermore, the majority of studies are conducted on student populations, which generally tend to show a stronger evening preference than the general population (e.g., Paine, Gander, & Travier, ; Randler, Fontius, & Vollmer, ). In an attempt to provide a more accurate assessment, Taillard, Philip, Chastang, and Bioulac () developed scale cutoffs more suited to the general population.…”

Development of sleep patterns in children with obese and normal‐weight parents

“…26,27 Weekday-weekend variation is less prominent in young children than in adolescents and adults because of the prevalent morning chronotype as well as fewer social demands. 28 In our analysis, we found that large weekdayweekend variation in sleep schedules of young children was associated with high obesity risk, probably indicating that not all children were at equal risk of sleep variation. Children with parents suffering from obesity showed a larger shift towards later sleep schedules during the weekend than children with normal-weight parents.…”

“…While it may be somewhat arbitrary, the overall prevalence of unfavourable sleep characteristics in our study was in line with previous reports which have reported that 25–50% toddlers have experienced some sleep problems during the first years of life . Parents' own sleep discrepancies between weekday and weekend, which were not included in this study, may partially explain child weekday–weekend sleep variation . Furthermore, participants in the Early STOPP had higher education levels than the general population, which might impact the generalisability of study results.…”

“…20 Parents' own sleep discrepancies between weekday and weekend, which were not included in this study, may partially explain child weekday-weekend sleep variation. 28 Furthermore, participants in the Early STOPP had higher education levels than the general population, 38 which might impact the generalisability of study results. In addition, the size of the population, as well as the differential sample size in the two groups with a small number of children at low obesity risk, might limit the possibility of detecting small but statistically significant differences, and the statistical analyses were performed without controlling for multiple comparisons, which may increase the risk of type I errors.…”