Obstructive sleep apnea (OSA) is a highly heterogeneous chronic disease, in which the conventional measure of disease severity, the apnea–hypopnea index (AHI), correlates poorly with patient-reported symptoms and inconsistently with cardiovascular outcomes. The present perspective proposes an initial discussion of a new concept for multidimensional evaluation of patients with OSA that integrates both objective measures of upper airway obstruction (AHI) and chronic intermittent hypoxia (hypoxic burden), along with subjective assessments of nighttime and daytime symptoms burden including snoring, subjective sleep quality, daytime sleepiness, fatigue, and quality of life. This integrated approach aims to improve characterization of patients and guide more individualized therapeutic goals, including improvements in quality of life and reduction in cardiovascular and metabolic consequences. It also supports a call to action in the OSA field, encouraging the development of a more comprehensive assessment of treatment response and clinical meaningfulness in OSA.
IntroductionTo evaluate whether data–driven personalization of positive airway pressure (PAP) comfort settings improves adherence by developing and evaluating a causal machine learning (ML) model for individualized recommendations.MethodsThe model was developed using AirSense 10 data and independently validated in temporally separated AirSense 10 and AirSense 11 cohorts, including 90–day and 1–year follow–up. The primary outcome was Centers for Medicare & Medicaid Services (CMS)–defined PAP adherence (device usage ≥ 4 h/night on ≥ 70% of nights during the first 90 days). Group–level average treatment effect (ATE) was estimated using backdoor adjustment methods. A causal forest model was applied to estimate the conditional average treatment effect for recommending personalized settings. A propensity score–matched analysis compared outcomes between patients whose actual settings matched model recommendations vs. those remaining on device default settings.ResultsThe model estimated ATE at the group level was 2.9 percentage points (p < 0.001), indicating that personalized settings were associated with improved CMS adherence. Covariate balance was achieved (standardized mean difference < 0.1), and model calibration was strong (expected calibration error 0.91%). Patients whose actual PAP settings matched the model–recommended configuration had higher device usage than matched controls who remained on default settings. Subgroup analyses confirmed consistent benefits across age groups, gender, apnea–hypopnea index, and mask type. SHapley Additive exPlanations analysis identified minimum pressure, start pressure and age as key drivers of personalization. Independent validation showed sustained usage benefits across AirSense 10 and AirSense 11 cohorts, with residual AHI remaining below the clinical reference threshold and no clinically meaningful deterioration in mask leak.DiscussionCausal ML–based personalization of PAP comfort settings was associated with improved CMS adherence/device usage. Integration of comfort setting personalization into setup workflows may enhance PAP therapy usage. As a retrospective observational analysis, these findings are associative and hypothesis–generating; the causal–inference framework, refutation testing, and large–scale independent validation provide robustness beyond that of conventional observational studies, although prospective randomized evaluation remains the definitive next step.
The adolescent developmental period is marked by increased social and academic demands, as well as biological changes that lead to profound shifts in sleep and circadian timing. Circadian misalignment, short sleep duration, and irregular sleep patterns are prevalent among adolescents and are linked to a wide range of negative outcomes, including impaired emotional regulation, diminished academic performance, and increased cardiometabolic disease risk. While efforts to promote adolescent sleep health have grown, the multidimensional nature of circadian sleep health remains underassessed in both research and clinical contexts. This review provides conceptual definitions of key circadian sleep health concepts, synthesizing current best practices for measuring circadian sleep health in adolescents across self-report, behavioral, and physiological domains. We organize assessment strategies around three key circadian constructs—chronotype, circadian timing, and circadian alignment—and describe validated tools for each. In addition, we explore measurements of contextual factors influencing circadian function, such as light exposure, meal and exercise timing, pubertal status, and genetic predispositions. Throughout this review, we emphasize the value of a multimodal approach that combines subjective experience with objective biological and behavioral data to improve clinical utility and advance the understanding of circadian sleep health. We conclude by outlining directions for future research, including the need for validated, developmentally appropriate tools and the integration of wearable technologies to improve accessibility and clinical utility. By consolidating core concepts and methodological tools, this review aims to assist researchers and clinicians selecting appropriate assessment strategies and tailoring interventions to improve adolescent circadian sleep health.
BackgroundObstructive sleep apnea (OSA) is typically evaluated with single-night sleep studies. In adults, night-to-night variability (NtNV) is well documented, but less so in children. The current study evaluated NtNV in apnea events for misclassification in disease severity in young children to investigate if multi-night sleep-recordings may be clinically relevant to improve diagnostic accuracy and affect treatment decisions.MethodsParents/guardians of healthy 4–9-year-old children participating in a study to evaluate prevalence of OSA were asked to record the child's sleep for up to 5-nights. This analysis is from children who completed three consecutive night sleep recordings.ResultsAverage age of participants was 6.1 years (n = 200, 58.0%-girls/42.0%-boys), prevalence of overweight/obesity was 25% and moderate-severe-OSA (AHI3% ≥ 5) based on single-night testing protocol was 29.0%. Using the highest AHI3% value from the three recordings, the first-night correctly identified 57.0% of participants and adding a second night identified 86.0% of participants, with 14% of participants not identified until the third night of sleep testing.Bland-Altman plots (BAplots) demonstrated non-statistically significant mean-differences and 95% upper and lower-limits (LOA95%) close in absolute terms night-one/night-two; −0.024 events/hour-of-sleep LOA95% [−5.062, 5.013], 8.0% of observations outside the LOA95% (p = 0.894) and night-two/night-three; −0.009 events/hour of sleep, LOA95% [−5.227, 5.209] and 6.0% of observations outside LOA95%, (p = 0.9620).The intra-class correlation coefficient (ICC) for AHI3% for all 3 nights was 0.45 [0.37, 0.54], p < 0.001, for night-one/night-two (0.44; p < 0.001), and night-two/night-three (0.44; p < 0.001). Cohens Kappa (0.304–0.462) and Brennan-Prediger Kappa (0.403–0.490), respectively indicated low-to-moderate interrater agreement, with quadratic-weighted Cohen's Kappa for the four ordinal severity categories of 0.37 and 0.48 for the two night-pairs, demonstrating NtNV, which is consistent with the variability demonstrated by the BAplots.ConclusionObserved NtNV in apnea events affected severity categorization, suggesting that multi-night sleep testing may have clinical value and improve accuracy of sleep apnea evaluation in young children.Clinical trial registrationURL: clinicaltrials.gov/study/NCT05479201, identifier NCT0547920 .
BackgroundObstructive sleep apnea (OSA) is a significant contributor to cardiometabolic diseases, yet its burden and metabolic consequences remain underexplored in the United Arab Emirates (UAE). Additionally, little is known about how OSA risk relates to early metabolic and renal abnormalities in young adults. This study evaluated the association between OSA risk and a comprehensive profile of cardiometabolic and renal biomarkers in a large cohort of young Emirati adults.MethodsThis cross-sectional study included 5,242 participants from the UAE Healthy Future Study. OSA risk was assessed using the STOP-Bang questionnaire and classified as no-to-low (score 0–2) or intermediate-to-high (score ≥3). Biomarkers assessed included HbA1c, lipid profile, ApoA, ApoB, C-reactive protein (CRP), serum creatinine, and urine microalbumin. Group differences were examined using t-tests and χ2 tests. Multivariable linear regression models adjusted for sociodemographic, lifestyle, and clinical covariates were used to assess associations between OSA risk and biomarker levels. Sensitivity analyses were conducted excluding participants with diabetes or dyslipidaemia.ResultsThe mean age was 27.5 years, and 30% of participants were classified as intermediate-to-high OSA risk. The intermediate-to-high OSA risk group exhibited greater adiposity, higher blood pressure, and more adverse cardiometabolic profiles than the no-to-low risk group. After adjustment, intermediate-to-high OSA risk was associated with elevated HbA1c (β = 0.18%, 95% CI: 0.14–0.23), higher total cholesterol, LDL-C, triglycerides, and ApoB, and lower HDL-C and ApoA (all p < 0.001). Inflammatory and renal markers were similarly elevated, including CRP (β = 0.14 mg/dL, 95% CI: 0.10, 0.18), serum creatinine (β = 0.11 mg/dL, 95% CI: 0.09, 0.13), and urine microalbumin (β = 3.61 mg/dL, 95% CI: 1.64, 5.60). Sex-stratified analyses showed higher median blood pressure and creatinine in males, and higher HDL-C and CRP in females. Sensitivity analyses produced consistent results for most biomarkers, except for urine microalbumin, which became non-significant.ConclusionsElevated OSA risk was consistently associated with adverse cardiometabolic and renal profiles in young adults. These findings suggest that STOP-Bang may serve as a useful screening tool for early risk detection, warranting validation in longitudinal studies.
IntroductionSleep disordered breathing (SDB) is known to be a comorbidity associated with congenital heart disease (CHD). This review evaluates the role of sleep disorders as a contributing factor to impairments in cardiovascular health, neurocognitive function, and health-related quality of life in individuals with CHD.MethodsA narrative review was conducted across PubMed, Ovid, and Cochrane Library (1990–2025) searches for studies cross-referencing “congenital heart disease” or “Fontan circulation” with sleep-related terms. Inclusion criteria were studies in CHD populations using objective or self-report sleep assessments; exclusions included non-English, non-original data, or conference abstracts. References of included articles were also screened to identify additional potentially relevant articles. Thirty three of 523 articles screened met inclusion criteria.ResultsSDB is prevalent in both children and adults with CHD, with reported rates ranging from 31 to 63% in adults and up to 57% in children. Both obstructive and central sleep apnea are observed. Comorbid SDB is associated with increased inpatient mortality in infants, poorer quality of life in children and adults, neurocognitive impairments, and increased cardiovascular risk including arrhythmias and paradoxical emboli. Evidence for effective treatment remains limited, though lifestyle, behavioral, and ventilation strategies show potential benefit.DiscussionSDB is common in both children and adults with CHD and has a negative association with behavior, cognition and quality of life for people with CHD.
Obesity and obstructive sleep apnea (OSA) are highly prevalent and interconnected conditions that contribute to the global burden of chronic non-communicable diseases. Fine particulate matter (PM2.5), a major component of air pollution, has emerged as a relevant factor linked to metabolic dysfunction and sleep disturbances. Chronic exposure to PM2.5 has been related to higher body mass index (BMI), central fat deposition, metabolic syndrome, and increased OSA risk and severity. Obesity remains the main modifiable risk factor for OSA, whereas intermittent hypoxia and sleep fragmentation can aggravate hormonal, inflammatory, and metabolic disturbances involved in weight gain. PM2.5 exposure and OSA overlap through pathways involving systemic inflammation, oxidative stress, neuroendocrine dysregulation, and gut microbiota alterations. These converging mechanisms highlight the potential role of environmental pollution and sleep disruption in obesity pathophysiology, particularly in urban populations chronically exposed to adverse environmental conditions. This review synthesizes current epidemiological and mechanistic evidence, identifies important knowledge gaps, and proposes shared biological pathways that may inform future research on the interplay among PM2.5 exposure, OSA, and obesity.
BackgroundQuantitative REM sleep without atonia (RSWA) metrics are increasingly used to characterize isolated REM sleep behavior disorder (iRBD) and as candidate biomarkers. Cohort follow-up often reports rising RSWA, but within-individual trajectories, particularly when tonic and phasic components diverge, remain sparsely documented.MethodsA man in his mid-seventies with iRBD underwent four attended video-polysomnograms over −6.5 years. Submental EMG was quantified using a REM sleep atonia index (RAI) with pre-specified exclusion of REM mini-epochs contaminated by artifact or physiological activation (arousal-linked activation and respiratory-event adjacency). Tonic and phasic submental RSWA components were extracted concurrently. Diary-anchored interviews around each visit captured enactment frequency, ordinal ratings of dream vividness/recall and sleep-related accidental harm.ResultsCorrected RAI varied non-monotonically (0.268, 0.401, 0.313, 0.463). Tonic and phasic RSWA dissociated: tonic activity declined overall, whereas phasic activity rose early and remained elevated. PSG-night enactment frequency tracked REM sleep opportunity (Spearman ρ = 0.89; n = 4) more closely than corrected RAI or tonic/phasic indices. Sleep-related harm was absent at the final visit despite persistent phasic activity.ConclusionIn this case, longitudinal RSWA did not behave as a single monotone scalar. Component-wise reporting alongside explicit REM sleep opportunity and exclusion accounting may be essential for interpreting apparent longitudinal change and relating electrophysiology to behavioral expression.
ObjectiveThe ripple effects of gun violence are far reaching, particularly for children impacted by this trauma. Many of the available sources of mental health support in the wake of gun violence do not address disrupted sleep, which commonly develops as a consequence of loss.MethodWe recruited adults for focus groups who are caregivers to a child or young adult impacted by loss due to gun violence from the Victim Support Services department of a police department in the US Southeast. The children to whom the adult provides care were required to be 13 years of age or younger. The aim of the focus groups was to understand sleep difficulties and ascertain the feasibility of a mindfulness-based behavioral intervention smartphone application (app) for sleep. Interviews were audio recorded, transcribed verbatim, and then analyzed in accordance with the constant comparison method.ResultsThe average age of caregivers in the sample (n = 8) was 50 years of age (s.d. = 8.9); 100% were female and 100% were Black/African American. Themes from the qualitative analysis suggested that caregivers experienced sleep difficulties that were intimately related to grief and trauma due to loss. Caregivers also described sleep difficulties in their children in the wake of loss. Participants provided favorable reactions to the mindfulness app as feasible and appropriate for families like them.ConclusionsFocus groups revealed sleep difficulties among families impacted by loss due to gun violence. Reactions to the mindfulness app were positive. Future research should evaluate the impact of the mindfulness intervention on child and caregiver mental and sleep health.
IntroductionYoung Black children experience poorer sleep health than children from other racial/ethnic groups. Tailored family-centered interventions are needed to improve sleep health among young Black children. Tailoring requires information about parent perceptions, practices and context. The purpose of this study was to (1) understand the contextual definition of sleep health for Black families; (2) bedtime routines and sleep practices among Black families; and (3) parent preferences that may inform intervention design.MethodsWe engaged 30 Black parents of 3–8-year-old children with mild sleep problems (e.g., child takes >30 min to fall asleep at bedtime) in this study. Parents completed three ratings scales about sleep health practices and child bedtime behavior and a semi-structured interview. Statistical analysis included descriptive statistics and correlations. We used an implementation science rapid qualitative analysis approach to analyze qualitative data from the interviews.ResultsThe final sample identified as 52% African-American, 14% Jamaican, 10% Haitian, and 26% mixed multi-ethnic groups. Parent mean age was 41 years and child mean age were 5 years old. About 80% of responders were women. About one-third of the sample held a doctoral degree, and half the sample had a bachelor's or Master's degree. Parents answered 56% of sleep knowledge questions accurately (ranging from 32 to 100%) and reported an average of two sleep problems. Parents described healthy sleep as involving flexibility in sleep timing and bedtime routines. More than half of parents reported co-sleeping practices, with reasons ranging from a strategy to address night wakings, to a way to preserve bonding. Later child bedtime (after 9 pm) was associated with bedtime resistance, permissive parenting, and parent stress. Many parents reported that they had poor sleep quality and duration.DiscussionFindings elucidate a range of factors to consider in tailoring sleep health interventions for Black families of young children. These include the common practice of co-sleeping, parents' value for flexibility related to bedtime and bedtime routines, and parents' own challenges with getting enough and good quality sleep. Tailored family-centered interventions will benefit from considering these factors.
BackgroundSleep is an important regulator of metabolic and cardiovascular health. Insufficient sleep is associated with adverse health behaviors and increased cardiovascular risk in young adults. Understanding sleep patterns and risk awareness in this group is essential for prevention.MethodsA nationally representative cross-sectional survey was conducted among 9,874 final-year Polish secondary school students. The questionnaire assessed sleep duration, physical activity, diet, alcohol and tobacco use, screen time, body mass index (BMI) and blood pressure. Associations between weekday sleep duration and lifestyle factors and cardiovascular risk were analyzed.ResultsOver 46% of students reported sleeping less than 7 h on weekdays, with longer sleep on weekends (6.7 ± 1.3 vs. 9.0 ± 1.5 h, p < 0.001). Short sleep was associated with higher consumption of processed foods, alcohol use, tobacco smoking, lower winter physical activity, and greater screen time. Students sleeping <7 h were more often underweight or obese. Awareness of short sleep as a cardiometabolic risk factor was limited.ConclusionsInsufficient sleep is common among Polish young adults and is associated with an unfavorable behavioral and cardiometabolic risk profile.
ObjectivesTo summarize findings and provide methodological critique of studies examining the impact of sleep promotion strategies in childcare on young children's sleep outcomes.MethodsThe search run in PubMed, PsycINFO, and CINAHL yielded a total of 3,528 unique articles. Eligible studies included young children (under 5 years old); assessed the impact of at least one sleep promotion strategy whether structural (e.g., mandatory naptime) or behavioral (e.g., music) with both within- and between-subject designs eligible); and included at least one quantitative child sleep outcome.Results6 studies met the eligibility criteria. Identified childcare sleep promotion strategies included mandatory naptime (n = 4), music (n = 1), and massage therapy (n = 1). Findings indicated that mandatory naptime was associated with increased napping. One study found that mandatory naptime was associated with reduced nighttime sleep and total daily sleep duration. Music and massage therapy were associated with reduced nap latency.ConclusionsThere is a paucity of research on sleep promotion strategies in childcare. This is an important research gap given the established health benefits of sufficient sleep and that many children from historically disadvantaged backgrounds depend on naps to meet their sleep needs. Future studies examining the effects of sleep promotion strategies other than mandated naptime, such as the sleep environment and provider behaviors, are needed.
Rationale and study objectives:To develop a method for apnea-hypopnea index (AHI) estimation using a chest-worn accelerometer, as an approach to obstructive sleep apnea diagnosis and long-term monitoring of treatment, for example through positional therapy. Methods:We developed a method for AHI estimation by combining a cardiorespiratory sleep staging algorithm with an adapted neural network for detecting respiratory events. Originally based on electrocardiography and respiratory impedance plethysmography, the network was retrained using chest-wall accelerometry-based instantaneous heart rate and respiratory effort. Training and validation utilized accelerometer data from 413 participants across two centers, recorded during diagnostic overnight polysomnography (PSG), in absence of any therapy. The dataset was split equally: half was used to train the neural network, and the remaining half to evaluate its performance. This evaluation compared the accelerometry-derived overnight AHI against the reference from PSG, both overall and separately for supine and non-supine sleeping positions. Results:Sleep staging reached substantial agreement with polysomnography, achieving a Cohen's kappa coefficient of agreement of 0.67 for four-class sleep staging (Wake/REM/N1-N2/N3). AHI was estimated with highly reliable, showing an intraclass correlation coefficient of 0.90 (95% CI: 0.86-0.92) when compared to polysomnography-derived values. Performances were consistent in both supine and non-supine sleeping positions. Positive likelihood ratios were high (7.1, 16.0, and 165.7 for the mild, moderate, and severe OSA severity classes, using near-boundary double labeling). Negative likelihood ratios were low (0.095, 0.153, and 0.069 for the same cases). Conclusion:AHI can be reliably estimated using chest-wall accelerometry. This approach may be used in diagnostic tests for OSA but also to assess residual AHI during positional therapy.
Excessive daytime sleepiness (EDS) is a frequent complaint in the general population. Other than being a common symptom associated with various sleep disorders, EDS may be a consequence of chronic sleep deprivation or the primary symptom of central disorders of hypersomnolence (CDH). In addition to narcolepsy type 1 (NT1), the other conditions within the CDH spectrum are less well-defined and share considerable clinical and neurophysiological similarities. Herein, we describe the clinical management of a complex case that highlights several challenges in the diagnostic process of a patient with EDS and a history of obsessive-compulsive disorder (OCD). In the absence of other sleep disorders, secondary structural causes, and orexin deficiency as possible causes for EDS, the patient was initially diagnosed with NT2 based on electrophysiological criteria. However, the clinical course, which showed only a partial response to various stimulant medications for subjective and objective daytime sleepiness, led us to question the diagnosis. A detailed psychiatric and neuropsychological assessment revealed, in addition to the previously identified severe OCD and anxiety, a diagnosis of attention deficit hyperactivity disorder (ADHD), subsequently leading to a revised diagnosis of hypersomnia associated with a psychiatric disorder (HPSY). The literature regarding OCD and sleep disorders remains scarce but the connection between ADHD and hypersomnia, as well as narcolepsy, is well-established. Our case report illustrates that a psychiatric and neuropsychological assessment should be considered mandatory for patients with objective EDS.
IntroductionThe stresses of military service can contribute independently to mental health and sleep problems in military personnel that persist after leaving military service. Understanding how sleep and mental health challenges contribute to behavioral health outcomes is key to supporting this population. To advance these goals, this study examined associations among PTSD, sleep disturbance, and suicide risk in U.S. veterans.MethodsOnline survey data using valid and reliable measures were collected from3,188 veterans living in Southern California as part of a large needs assessment; suicide risk was measured by the SBQ-R, which assess ideation, behaviors and attempts. A structural equation modeling approach was used to test the direct effects of PTSD on sleep problems and suicide risk, the direct effect of sleep on suicide risk, and an indirect effect of PTSD on suicide risk through the sleep pathway.ResultsFindings demonstrated significant direct effects for PTSD (B = 0.05, p < 0.001) and sleep problems (B = 0.74, p < 0.001) on suicide risk, as well as a significant indirect effect for PTSD on suicide risk through the sleep pathway (B = 0.05, p < 0.05). The structural model explained 55.3% of the variance in sleep difficulties and 29.9% of the variance in suicide risk.DiscussionResults advance the understanding of how sleep problems may be associated with the risk of suicide in U.S. veterans, both directly through its effects on suicide risk and indirectly through the effects on PTSD symptomatology. Practitioners and policy makers may consider ensuring the assessment and treatment of sleep problems in veterans are included in suicide prevention models.
IntroductionThe return to normal life following the COVID-19 pandemic was evaluated in terms of anxiety upon awakening, sleep quality indicators, and dream characteristics.MethodsThe sample comprised 394 women and 107 men who completed an online self-report questionnaire between August 15, 2022, and December 8, 2022 about their sleep and dream experience from the previous night. Respondents completed the Anxiety upon Awakening Assessment Questionnaire (CEAD, as per the Spanish acronym) and evaluated their experiences of the pandemic. The data were compared to those obtained before the pandemic and those collected during lockdown in a previous study.ResultsAfter the return to normal life, 46.5% of respondents recalled at least one dream scene, and nightmares were recorded in 4.6% of cases. This percentage did not differ significantly from those observed during lockdown or before the pandemic. Compared with the previous periods, participants also reported more dreams with anxious content and greater dream recall. A return to a sleep duration of between 6 and 7 h was observed. However, anxiety upon awakening was higher, suggesting that full normalization had not yet occurred at the time of this study.ConclusionIn this sample, nightmare frequency was less sensitive than anxiety upon awakening to post-pandemic sleep-related emotional activation. The findings may be compatible with emotional-processing accounts of dreaming and with a homeostatic interpretation of sleep in which emotional dream content did not translate into more awakenings.
Targeted dream incubation (TDI) is a highly effective method for eliciting hypnagogic dreams related to specific topics through the presentation of verbal prompts and serial awakenings at sleep onset. In this pilot study, we tested whether TDI at sleep onset can effectively direct dream content in subsequent rapid eye movement (REM) sleep. We allowed participants a daytime nap opportunity following TDI at sleep onset. Serial awakenings were performed both at sleep onset and after entry into REM sleep. Our primary objective was to assess whether the TDI protocol during the sleep onset period would continue to affect dream content in REM sleep, producing dreams of the target content (“tree”) in the first REM awakening. Our second objective was to assess incorporation when participants received additional TDI prompts following REM awakenings. All 11 participants successfully incubated the target theme at sleep onset, and eight subsequently obtained REM sleep. Four of these participants (50%) incorporated the target theme into their first REM dream, and five incorporated the target theme in subsequent REM dreams (63%). Results provide preliminary evidence that TDI may impact dreams in REM sleep. This method of engineering dreams across sleep stages may be useful for understanding how dream generation and function may be continuous or different across sleep stages.
IntroductionDespite advancements in sleep medicine, inadequate sleep habits among young children persist. Establishing appropriate sleep habits in early childhood is essential for supporting physical, emotional, and cognitive development. However, scalable and personalized behavioral interventions for caregivers in community settings remain scarce, particularly AI-enabled systems designed for real-world implementation.MethodsThis study evaluated adherence, perceived usefulness, and feasibility of Nenne Navi-AI among 50 caregivers recruited in Hirosaki City, Japan, through community health checkups, childcare facilities, and public advertisements. The culturally tailored application integrates supervised machine-learning models with rule-based algorithms to provide personalized guidance and ongoing support for promoting healthier sleep habits.ResultsDuring the 6-month intervention, only 3 of 50 caregivers (6%) experienced continuous 3-month data-entry lapses, with no withdrawals. Significant pre-post improvements were observed in children's number of awakenings after sleep onset and subjective sleep quality ratings. Subgroup analyses suggested improvements among children with poorer baseline sleep habits (≥0.5 SD worse than the sample mean). Post-intervention assessments confirmed high caregiver acceptability, satisfaction, and reduced parenting stress.ConclusionsNenne Navi-AI demonstrates high feasibility with excellent 6-month adherence and favorable usability feedback. The system shows promise for improving early childhood sleep (night-waking), enhances caregiving experiences, reduces negative parenting emotions, and provides a scalable framework for future AI-enabled pediatric sleep interventions.
IntroductionSleep is essential for human health. For low-income individuals and families, sufficient, high-quality, regular sleep can be difficult to obtain due to two main barriers: factors that prevent optimum sleep hygiene behaviors and aspects of the bedroom environment, such as noise and temperature, that reduce sleep. This article describes the rationale and design of the Good Nights Sleep Program, a pilot of a randomized clinical trial (clinicaltrials.gov/study/NCT06249217) that combines education with behavior change strategies that lead children and their parents to select, implement, and track changes to their sleep behaviors and environments. Following the conceptual description of the interventions, descriptive statistics from the pilot study are presented.MethodsThe study enrolled parent-child dyads with a mean family income-to-needs ratio of 1.68 (75% Black; 25% White).ResultsFindings provided proof of concept for the intervention and descriptive preliminary evidence. Children receiving the intervention had longer actigraphy-derived sleep hours compared to waitlist control-arm participants, and parents had shorter self-reported usual sleep latency and more consistent actigraphic wake times.DiscussionThe Good Nights Sleep Program offers a promising model for empowering children and parents to make attainable changes that yield benefits for their sleep.
