The aim of this study was to investigate the development of infant and toddler sleep patterns. Data were collected on 841 children (aged from birth to 36 months) via a free, publicly available, commercially sponsored iPhone app. Analyses were conducted on caregiver recordings of 156 989 sleep sessions across a 19-month period. Detailed visualizations of the development of sleep across the first 3 years of life are presented. In the first 3 months, sleep sessions primarily lasted less than 3.5 h throughout the day. Between 3 and 7 months old, sleep consolidated into two naps of about 1.5 h in length and a night-time sleep session of about 10.5 h. Across age groups, a negative relationship was observed between the start of bedtime and the length of the night-time sleep session (i.e. later bedtime is associated with a shorter night-time sleep period). The length of daytime sleep sessions (naps) varied with age, decreasing between 1 and 5 months old, and then increasing monotonically through 28 months. Morning wake time was observed to be invariant in children aged 5-36 months. Sleep patterns are ever-changing across the first few years with wide individual variability. Sleep patterns start to develop more clearly at 5-6 months, when longer night-time sleep duration begins and sleep consolidation occurs. Daytime sleep patterns appeared to become more consistent and consolidated later in age than night-time sleep. Finally, there is greater variability in bedtimes than wake times, with bedtimes having a greater influence on night-time sleep duration.

This paper provides a scoping review of behavioural interventions that target household energy demand. We evaluate 584 empirical papers that test the effectiveness of a behavioural intervention to change behaviour associated with household energy demand. The most studied behavioural tools are providing timely feedback and reminders and making information intuitive and easy to access, followed by (in order) communicating a norm, reframing consequences, making behaviour observable, obtaining a commitment, setting proper defaults, and transitions and habit disruption. The most studied demand-side behaviour is electricity use. There is high heterogeneity in effect sizes. We classified the target behaviours of each study as avoid, shift, or improve behaviours and find that avoid behaviours (in particular, reducing electricity usage) are the predominant focus of researchers. The effectiveness of interventions differs across avoid, shift, and improve responses and by the behavioural tool. Specifically, shifting behaviours are less effectively motivated than avoiding behaviours by using an information intervention but more effectively by using a norm intervention. We review the literature to provide further information about which behavioural tools are most effective for specific contexts. The effectiveness of most behavioural tools are augmented when they are used in the right combination with other tools. We recommend that researchers focus future work on high impact behaviours and the evaluation of synergistic combinations of behavioural interventions.

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