Novel insights from actigraphy: Anxiety is associated with sleep quantity but not quality during childhood

Remote sensing mental health: A systematic review of factors essential to clinical translation from validation research

Background

Mental illness remains a major global health challenge largely due to the absence of definitive biomarkers applicable to diagnostics and care processes. Although remote sensing technologies, embedded in devices such as smartphones and wearables, offer a promising avenue for improved mental health assessments, their clinical integration has been slow.

Objective

This scoping review, following preferred reporting items for systematic reviews and meta-analyses guidelines, explores validation studies of remote sensing in clinical mental health populations, aiming to identify critical factors for clinical translation.

Methods

Comprehensive searches were conducted in six databases. The analysis, using narrative synthesis, examined clinical and socio-demographic characteristics of the populations studied, sensing purposes, temporal considerations and reference mental health assessments used for validation.

Results

The narrative synthesis of 50 included studies indicates that ten different sensor types have been studied for tracking and diagnosing mental illnesses, primarily focusing on physical activity and sleep patterns. There were many variations in the sensor methodologies used that may affect data quality and participant burden. Observation durations, and thus data resolution, varied by patient diagnosis. Currently, reference assessments predominantly rely on deficit focussed self-reports, and socio-demographic information is underreported, therefore representativeness of the general population is uncertain.

Conclusion

To fully harness the potential of remote sensing in mental health, issues such as reliance on self-reported assessments, and lack of socio-demographic context pertaining to generalizability need to be addressed. Striking a balance between resolution, data quality, and participant burden whilst clearly reporting limitations, will ensure effective technology use. The scant reporting on participants' socio-demographic data suggests a knowledge gap in understanding the effectiveness of passive sensing techniques in disadvantaged populations.

Self-reported quantity and quality of sleep in children and adolescents with a chronic condition compared to healthy controls

To assess self-reported quantity and quality of sleep in Dutch children with a chronic condition compared to healthy controls and to the recommended hours of sleep for youth. Sleep quantity and quality were analyzed in children with a chronic condition (cystic fibrosis, chronic kidney disease, congenital heart disease, (auto-)immune disease, and medically unexplained symptoms (MUS); n = 291; 15 ± 3.1 years, 63% female. A subset of 171 children with a chronic condition were matched to healthy controls using Propensity Score matching, based on age and sex, ratio 1:4. Self-reported sleep quantity and quality were assessed with established questionnaires. Children with MUS were analyzed separately to distinguish between chronic conditions with and without an identified pathophysiological cause. Generally, children with a chronic condition met the recommended amount of sleep, however 22% reported poor sleep quality. No significant differences in sleep quantity and quality were found between the diagnosis groups. Children with a chronic condition and with MUS slept significantly more than healthy controls at ages 13, 15, and 16. Both at primary and secondary school, poor sleep quality was least frequent reported in children with a chronic condition and most often reported in children with MUS.  Conclusion: Overall, children with chronic conditions, including MUS, met the recommended hours of sleep for youth, and slept more than healthy controls. However, it is important to obtain a better understanding of why a substantial subset of children with chronic conditions, mostly children with MUS, still perceived their sleep quality as poor. What is Known: • According to the Consensus statement of the American Academy of Sleep medicine, typically developing children (6 to 12 years) should sleep 9 to 12 h per night, and adolescents (13 to 18 years) should sleep 8 to 10 h per night. • Literature on the optimal quantity and quality of sleep in children with a chronic condition is very limited. What is New: Our findings are important and provide novel insights: • In general, children with a chronic condition sleep according to the recommended hours of sleep. • A substantial subset of children with chronic conditions, perceived their sleep quality as poor. Although this was reported mostly by children with medically unexplained symptoms (MUS), the found poor sleep quality was independent of specific diagnosis.

Meta-analysis of age and actigraphy assessed sleep characteristics across the lifespan

STUDY OBJECTIVES

Sleep quantity and continuity vary across the lifespan. Actigraphy is a reliable and widely-used behavioral measure of sleep in research and personal health monitoring. This meta-analysis provides a novel examination of whether age (in years) is associated with actigraphy-assessed sleep across the lifespan.

METHODS

A systematic search of PubMed, Embase.com, Cochrane CENTRAL, and PsycINFO using "actigraphy" and "sleep" terms provided 7,079 titles/abstracts; studies of individuals with known psychiatric or medical comorbidities were excluded. Ninety-one articles (N = 23,365) provided data for six meta-analyses examining sleep duration (k = 89), sleep efficiency (k = 58), bedtime (k = 19) and waketime (k = 9) for individuals ages 6-21, and bedtime (k = 7) and waketime (k = 7) for individuals ages 22 and older.

RESULTS

At older ages, sleep duration was shorter (r = -0.12) and sleep efficiency was lower (r = -0.05). Older age was associated with later bedtime (r = 0.37) and wake-up time (r = 0.24) from ages 6-21, whereas older age was associated with earlier bedtime (r = -0.66) and wake-up time (r = -0.59) for ages 22 and above. The strength of these associations was modified by study continent, but not by any other moderator.

CONCLUSIONS

Age was negatively associated with actigraphy-assessed sleep duration and efficiency, but the effects were small in magnitude. On the other hand, large associations were observed between age and sleep timing, despite a smaller literature and the absence of analyzable data for ages 30-60. Changes in sleep timing, rather than changes in sleep duration or continuity, may better characterize the effects of age on human sleep.

Within-person fluctuations in stressful life events, sleep, and anxiety and depression symptoms during adolescence: a multiwave prospective study

BACKGROUND

Adolescence is characterized by substantial changes in sleep behavior, heightened exposure to stressful life events (SLEs), and elevated risk for internalizing problems like anxiety and depression. Although SLEs are consistently associated with the onset of internalizing psychopathology, the mechanisms underlying this relationship remain poorly understood, especially at the within-person level. Here, we leverage a high-frequency longitudinal design to examine sleep as a potential mechanism linking SLEs to increases in anxiety and depression symptoms over a one-year period.

METHODS

Thirty female adolescents aged 15-17 years completed 12 monthly in-laboratory assessments of exposure to SLEs and symptoms of anxiety and depression (n = 355 monthly assessments), and wore an actigraphy wristband for continuous monitoring of sleep for the duration of the study (n = 6,824 sleep days). Multilevel models examined concurrent and lagged within-person associations between SLEs, sleep duration and timing regularity, and anxiety and depression symptoms.

RESULTS

Within-person fluctuations in SLEs were associated with variability in sleep duration both concurrently and prospectively, such that when adolescents experienced greater SLEs than was typical for them, they exhibited more variable sleep duration that same month as well as the following month. In turn, within-person increases in sleep duration variability predicted greater anxiety symptoms in the same month and mediated the association between SLEs and anxiety.

CONCLUSIONS

These findings highlight sleep disruptions as a mechanism underlying the longitudinal associations between SLEs and anxiety symptoms, and suggest that interventions promoting sleep schedule consistency may help mitigate risk for stress-related psychopathology in adolescence.