Sleep disturbance occurs early in Huntington's disease (HD). Consumer- and research-grade activity monitors may enable routine assessment of sleep disturbances in HD. We compared Actiwatch Spectrum Pro, Jawbone UP2 and Fitbit One to the gold standard, polysomnography, in four late presymptomatic and three early HD participants. Compared to polysomnography, all ambulatory monitors overestimated total sleep time by >60 minutes and sleep efficiency by ∼15%. Thus, for assessment of specific sleep parameters in HD, none of the activity monitors are sufficiently accurate to replace polysomnography, although they may be sufficient for estimating overall sleep-wake patterns. Larger sample replication is required.

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Activity monitoring devices claiming to measure sleep have increased in popularity within research and consumer settings. However, validation studies on many of these devices are lacking. We examined twenty-nine healthy adults (Mage = 32.4, SDage = 11.6) overnight using three activity monitors (Actiwatch Spectrum Pro standard and sensitive settings, Fitbit One, Jawbone UP2) and polysomnography. We evaluated agreement between each device and polysomnography on total sleep time (TST) and sleep efficiency (SE). Clinically meaningful limits of agreement were set at ±30 minutes for TST and ±5% for SE. Each activity monitor overestimated TST and SE compared to polysomnography, and except for Actiwatch Spectrum Pro in sensitive setting, exceeded clinically meaningful agreement limits. Using Actiwatch Spectrum Pro sensitive as the gold standard, both consumer devices overestimated TST and SE, but their mean errors were generally not clinically meaningful (except Fitbit One’s error for SE). Actiwatch Spectrum Pro in its sensitive setting may be a valid substitute for polysomnography when measuring TST and SE. Choice of consumer device as an actigraphy replacement will depend on context. Jawbone UP2 shows closer agreement with Actiwatch Spectrum Pro, though Fitbit One demonstrates less variation in TST and SE estimations.

Background Most adolescents are sleep deprived on school days, yet how they self‐regulate their sleep–wake behaviours is poorly understood. Using ecological momentary assessment, this intense longitudinal study explored patterns of adolescents’ daily bedtime and risetime planning and execution, and whether these behaviours predicted sleep opportunity. Methods Every afternoon, for 2 school weeks and the subsequent 2 vacation weeks, 205 (54.1% female, 64.4% non‐White) adolescents from year 10 to 12 (M ± SDage = 16.9 ± 0.9) reported their plans for bedtime (BT) that evening, and for risetimes (RT) the following day. Actual daily sleep was measured via actigraphy and sleep diary. Results Some adolescents never planned bedtime (school 19.5%, non‐school 53.2%) or risetime (school 1.5%, non‐school 24.4%). More adolescents planned consistently (≥75% of days) on school (BT = 29.9%, RT = 61.3%) compared to non‐school nights (BT = 3.5%, RT = 2.5%). On average, adolescents went to bed later than planned, with longer delays on non‐school (71 min) compared to school nights (46 min). Of those who executed their plans within ≤15 min, more did it consistently (≥75% of days) on school (BT = 40.9%, RT = 67.7%) than on non‐school nights/days (BT = 29.7%, RT = 58.6%). Mixed effects models utilizing daily data, controlling for sex, race, and study day, showed that bedtime planning predicted longer time in bed (TIB; p < .01) on school and shorter TIB on non‐school nights (p < .01); and greater delay in actual (compared to planned) BT predicted shorter TIB (p < .001). Conclusions Adolescents may require support during the transition from parent‐controlled to autonomous sleep self‐regulation. Bedtime planning on school nights and going to bed as planned are two modifiable sleep regulatory behaviours that are protective and potential therapeutic targets for increasing sleep opportunity in adolescents.

Introduction This intense longitudinal study examined factors that facilitate and hinder sufficient and good quality sleep in adolescents’ everyday life. Methods 205 (54.2% female, 64.4% non-white) Year 10–12 adolescents (Mage = 16.9 ± 0.9) completed daily morning surveys and wore actigraphy over 2 school-weeks and 2 subsequent vacation-weeks. Morning surveys assessed self-reported sleep and the usage of 8 facilitators and 6 barriers of sleep from the previous night. Linear mixed-effects models examined contribution of facilitators/barriers to actigraphy and self-reported total sleep time (TST) and sleep onset latency (SOL), controlled for age, sex, race, place of birth, and study day. Schooldays/non-schooldays was included as a moderator. Results Seven facilitators and two barriers were endorsed by high proportions (&gt;30%) of adolescents as frequently (≥50% days) helping/preventing them from achieving good sleep. Facilitators predicting longer TST and shorter SOL, were: “follow body cues”, “manage thoughts and emotions”, “create good sleep environment”, “avoid activities interfering with sleep” and “plan bedtime and go to bed as planned” (only TST on schooldays). Barriers predicting shorter TST and longer SOL, were: “pre-bedtime thoughts and emotions”, “unconducive sleep environment”, “activities interfering with sleep”, “inconsistent routines” and “other household members’ activities”. Overall, facilitators or barriers explained an additional 1–5% (p-values &lt; .001) of variance beyond the covariates. Discussion Adolescents perceive a range of factors as facilitating and as preventing sufficient and good quality sleep in everyday life. These factors are predictive of their sleep duration and onset latency, and need further research to understand their functions and clinical implications.