Nap Time Research Articles

Association between screen time, homework and reading duration, sleep duration, social jetlag and mental health among Chinese children and adolescents

ObjectivesTo examine the associations of screen time, homework and reading duration, sleep duration, social jetlag with mental health in children and adolescents, as well as its gender differences.MethodsFrom December 2023 to April 2024, a total of 62 395 children and adolescents were selected from 51 schools in 17 cities of China by stratified cluster sampling. Screen time, homework and reading duration, sleep duration, and social jetlag were calculated by answering the questions about watching TV time, playing smartphones time, doing homework time, reading extracurricular books time, bedtime, wake-up time, and nap time during weekdays and weekends. Mental health was assessed by the Revised Mental Health Inventory-5 (MHI-5). The generalized linear model was used to determine the association between screen time, homework and reading duration, sleep duration, social jetlag, and mental health in children and adolescents.ResultsThe generalized linear model results showed that longer watching TV time, longer playing smartphones time, longer homework time, and greater social jetlag were correlated with poorer mental health in children and adolescents, while longer nighttime sleep duration, and longer daytime nap duration were correlated with better mental health. Moreover, in primary school and junior high school, we found that this association was stronger during the weekdays. However, in senior high school, this association was stronger during the weekends. After according to gender stratified, we found that the strength of this association was different in boys and girls at different study phases. Furthermore, our findings also revealed a significant quadratic relationship, indicating the association of better mental health with an optimal amount of sleep duration.ConclusionsThere was a significant association between screen time, homework and reading duration, sleep duration, social jetlag, and mental health in children and adolescents. This study has the potential to offer useful insights for the prevention and control of mental health issues in children and adolescents.

Napping and Obesity in Adults - What do we Know?

To review the evidence on the relationship between daytime napping and obesity. There is concern that napping may be harmful to metabolic health. Prospective studies have shown long time daytime napping (> 1h) is associated with increased diabetes risk which may be partly associated with obesity. Evidence from numerous cross-sectional studies and meta-analyses of cross-sectional studies have shown that long time napping (> 1h) but not short time napping is associated with increased risk of obesity, and this is seen worldwide. Inference regarding the nature of association from cross-sectional studies is limited; it is suggested the association is bidirectional. Prospective studies on the association between daytime napping and obesity are few and results unclear. Large longitudinal studies integrating daytime napping duration and night-time sleep behaviour and detailed information on lifestyle influences is needed to help elucidate further the associations of long time napping with obesity.

Validation of intrinsic capacity and healthy sleep pattern in middle-aged and older adults: a longitudinal Chinese study assessing healthy ageing

ObjectivesIntrinsic capacity (IC), a multidimensional construct encompassing mental and physical capacities, has been established in the aging framework by the World Health Organization. However, the detailed relationship between IC and Chinese sleep patterns (nighttime sleep and post-lunch naps) remains inadequately elucidated. MethodsParticipants in this study were individuals aged ≥45 years residing in China, included in the China Health and Retirement Longitudinal Study (CHARLS). We analyzed 4 years of CHARLS data from the first wave (May 2011–March 2012) to the second wave (July 2015–January 2016). Data from these waves were utilized for longitudinal analysis. Self-reported data included nighttime sleep and nap duration, along with other baseline characteristics. The IC evaluation involved physical examinations and blood tests. Initially, linear regression was used to assess the relationship between total sleep duration, nighttime sleep duration, nap duration, and IC change between the two waves that were determined by marginal effects (ME) and their corresponding 95% confidence intervals (CIs). Regression splines were employed to explore potential nonlinear associations. Subgroup and sensitivity analyses were conducted to investigate the heterogeneity of IC change under specific conditions and the robustness of our results. Mediation analysis was performed to identify potential factors mediating the relationship between sleep patterns and IC change. ResultsBoth excessive (>10 h) (total, ME: −1.12; 95% CI: −1.61, −0.64; nighttime, ME: −1.44; 95% CI: −2.29, −0.59) and insufficient (<6 h) sleep duration (total, ME: −0.43; 95% CI: −0.68, −0.18; nighttime, ME: −0.50; 95% CI: −0.73, −0.27) negatively impacted IC change. Moderate naps (≤60 min) mitigated the decline in IC change (ME: 0.28; 95% CI: 0.07, 0.49). IC values decreased at the slowest rate when nap time constituted one-seventh of total sleep time. The onset of dyslipidemia partially mediated the association between naps (≤60 min) and IC change (P = 0.02). ConclusionsThese findings suggest that maintaining a healthy sleep pattern of 6−8 h of nighttime or total sleep, along with a post-lunch nap of ≤60 min, helps preserve optimal IC or delay its decline. This is particularly beneficial for cognitive, psychological, and locomotion performance among middle-aged and older adults.

A study on indoor air quality at daycare centers using IoT environmental sensors

ABSTRACT Indoor air quality (IAQ) is a major concern at daycare centers, due to the weaker immune system of children. Although IAQ is typically measured in accordance with the ISO-16000 standard, environmental sensors have recently become widely used due to their ability to consistently monitor air quality at a lower cost. In this study, We installed IoT sensors indoors and outdoors at ten daycare centers to measure PM(PM2.5, PM10), CO2, temperature, and humidity, as well as window opening-closing sensors to identify ventilation behavior. Indoor PM concentrations were consistently lower than outdoor levels, increasing from 7:00 AM, peaking between 9:00 AM and 12:00 PM, and decreasing during nap time (12:00 PM to 2:00 PM). CO2 levels were generally higher indoors than outdoors, peaking at 2:00 PM before decreasing. Windows were opened more frequently at 7:00 AM, 8:30 AM, and 3:00 PM. The correlation analysis revealed that significant factors influencing CO2 concentration were window opening duration. Ventilation rates per person at the daycare centers ranged from 1.77 to 10.69 m3/h, below both Korean and ASHRAE guidelines. The results of this study can provide valuable insights for developing strategies to improve indoor air quality in daycare centers that depend on window ventilation.

A case for the use of deep learning algorithms for individual and population level assessments of mental health disorders: Predicting depression among China's elderly

BackgroundWith the continuous advancement of age in China, attention should be paid to the mental well-being of the elderly population. The present study uses a novel machine learning (ML) method on a large representative elderly database in China as a sample to predict the risk factors of depression in the elderly population from both holistic and individual level. MethodsA total of participants met the inclusion criteria from the fourth waves of the China Health and Retirement Longitudinal Study (CHARLS) were analyzed with ML algorithms. The level of depression was assessed by the 10-item Center for Epidemiological Studies Depression Scale (CESD-10). ResultsThe current study found top 5 factors that were important for predicting depression in the elderly population in China, including average sleep time, gender, age, social activities and nap time during the day. The results also provide reliable diagnostic likelihood at the individual level to support clinicians identify the most impactful factors contributing to patient depression. Our findings also suggested that activities such as interacting with friends and play ma-Jong, chess or join community clubs may have a positive collaborative effect for elderly's mental health. ConclusionsHolistic approaches are an effective method of deriving and interpreting sophisticated models of mental health in elderly populations. More detailed information about a patient's demographics, medical history, sleeping patterns and social/leisure activities can help to inform policy and treatment interventions on a population and individual level. Large scale surveys such as CHARLS are effective methods for testing the most accurate models, however, further research using professional clinical input could further advance the field.

Association between nighttime sleep duration, nap time, and mild cognitive impairment in Chinese older adults: a cross-sectional study

ObjectiveThis study aims to investigate the relationship between midday nap time, nighttime sleep duration, and mild cognitive impairment (MCI) in Chinese older adults and determine the recommended sleep duration to provide a scientific basis for preventing and managing MCI in this population.MethodsUtilizing the 2020 China Health and Retirement Longitudinal Study database, the demographic data, health status, and lifestyle information of the study participants were collected. A total of 5,314 valid samples were included in the analysis. Logistic regression and restricted cubic spline plots were employed to explore the relationship between sleep patterns and MCI.ResultsIn the cross-sectional analysis, a linear relationship was observed between midday nap duration and MCI among Chinese elderly. The probability of MCI was lowest among those who napped for less than 30 min at noon. Compared with individuals who napped for30-90 min, those who did not nap were more likely to have MCI (OR = 1.30, 95% CI: 1.05–1.60). Older adults with napping duration < 30 min (OR = 0.73, 95% CI:0.56–0.95) also exhibited lower probability of MCI when compared those without napping habit, Nighttime sleep duration exhibited a U-shaped relationship with MCI. Individuals with less than approximately 6 h of nighttime sleep showed a gradual decrease in the probability of MCI with increasing sleep duration, whereas those with more than 7.5 h demonstrated an increase in the probability of MCI with longer sleep duration. Older adults who slept less than 6 h at night (OR = 1.22, 95% CI: 1.01 ~ 1.46) or more than 8 h (OR = 1.78, 95% CI: 1.35–2.33) were more likely to develop MCI compared with those who slept 6 to 8 h.ConclusionAfter controlling for potential confounding variables, both nighttime sleep duration and midday nap duration exhibited a nonlinear “U”-shaped relationship with MCI among the elderly. The probability of depression was lower with a nap duration of approximately 60 min, and the optimal nighttime sleep duration was 6–8 h, with around 7 h providing the greatest cognitive benefits.

Sleep, Wellness, and Mood of Personnel Standing Watch on US Navy Information Warfare Watchfloors

This project aimed to improve the sleep, wellness, and mood of personnel standing watch on US Navy Information Warfare watchfloors. Data were collected from 82 participants on two US Navy watchfloors. Volunteers wore ŌURA rings and completed questionnaires at the beginning and end of the study. Our findings suggest that the 6-section/8-hour-shift watchbill is generally preferable to the 4-section/12-hour-shift watchbill. We developed general guidelines and recommendations for fatigue mitigation based on the data collected from the two watchfloors, the predicted effectiveness of the two watchbills calculated using the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE-FAST) model, and background literature on shiftwork. The recommendations for watchstanders focused on sleep hygiene practices, sleep environment, timing of sleep and naps, light management, the use of caffeine, alcohol, and nicotine, nutrition, and exercise.

Observed relationships between nap practices, executive function, and developmental outcomes in Tunisian childcare centers

The objective of this design was to conduct an observational study comparing anthropometric characteristics, cognitive functions, as well as gross and fine motor skills. The study included 118 preschool-aged children (47 boys, 71 girls) enrolled in childcare centers. They were categorized into two groups based on their nap habits. The nap group comprised 59 children (23 boys, 36 girls), age (mean ​± ​standard deviation) ([3.96 ​± ​0.54] years) who took naps after lunch, while the no-nap group included 59 children (24 boys, 35 girls) age (mean ​± ​standard deviation) ([4.18 ​± ​0.61] years) who remained awake during this period. The results showed that the napping group had significantly higher scores for body mass index (BMI) (p ​< ​0.000 1), height-for-age z score (HAZ) (p ​= ​0.003), and higher BAZ (BMI-for-age z score) scores (p ​< ​0.000 1), compared to the No-nap group. In terms of cognitive function, the study revealed that the napping group had better working memory performance compared to the No-nap group (p ​= ​0.002), but no significant impact on inhibition was observed. The results also showed that taking a nap may improve functional mobility (p ​= ​0.003) and upper body strength (p ​= ​0.026) especially in boys. Future research could investigate the long-term effects of inadequate nap time on children's health and development and also develop and evaluate interventions to improve nap time habits in preschool children.

Children’s Sleep and Human Capital Production

Abstract This paper uses exogenous variation in sleep induced by sunset time to present the first human capital estimates of (i) the effects of child sleep from the developing world and (ii) the long-run effects of child sleep in any context. Later sunset reduces children’s sleep: when the sun sets later, children go to bed later but fail to compensate by waking up later. Sleep-deprived children study less and increase nap time and indoor leisure activities. Short-run sleep loss decreases children’s test scores. Chronic sleep deficits translate into fewer years of education and lower primary and middle school completion rates among school-age children.

Bidirectional associations between the duration and timing of nocturnal sleep and daytime naps in adolescents differ from weekdays to weekends.

Previous studies examining bidirectional relationships between nocturnal sleep and napping have focused on sleep duration, leaving a gap in our understanding of how sleep timing contributes. Here, we assessed the duration and timing for night sleep and daytime naps, to evaluate how the previous night's sleep influences the next day's napping, and how napping influences same-night nocturnal sleep. We analyzed sleep diary and actigraphy data from 153 teens (males = 43.8%, mean age = 16.6 years). Participants who never napped were excluded. Nocturnal sleep-nap relationships were investigated using logistic and linear regression models separately for weekdays and weekends. Participants napped an average of 2.3 times a week. 167 school day naps and 107 weekends were recorded. Naps were on average 82.12 ± 53.34 minutes and the average nap onset was 14:58 ± 3.78 hours. Their duration, start and end times did not significantly differ between weekdays and weekends. Nocturnal sleep duration did not predict next-day nap occurrence or duration. However, on school days, earlier wake times significantly increased the likelihood of napping that day, and advanced nap timing. On weekends, later bedtimes and wake times delayed nap timing. On school days, napping longer than one's average shortened nocturnal sleep whereas on weekends, waking from a nap later than one's average delayed bedtimes. Early wake times increase the likelihood of napping and advance the time of a nap that day. Naps may be detrimental to the same night's sleep only if they are long and occur late, as these can delay bedtimes and shorten nocturnal sleep duration, especially on school days. The Cognitive and Metabolic Effects of Sleep Restriction in Adolescents (NFS4), https://clinicaltrials.gov/study/NCT03333512, ID: NCT03333512. Investigating Preferred Nap Schedules for Adolescents (NFS5), https://clinicaltrials.gov/study/NCT04044885, ID: NCT04044885.

Do Sleep Time and Duration Affect the Development of Prehypertension in Undergraduate Medical Students? An Experience from a Tertiary Care Hospital in Kolkata

Abstract Introduction and Objective Hypertension is an evolving public health challenge at present, and it is preceded by a prehypertensive stage. Irregular sleep duration and pattern have been found to be linked with cardiovascular diseases. Medical students are highly vulnerable to low quality sleep due to pressure regarding the academic curriculum and poor lifestyle. The present study aimed to estimate the prevalence of prehypertension, describe the risk factors and sleep patterns of undergraduate medical students, and determine the association, if any, involving sleep time and duration and prehypertension. Materials and Methods Data was collected from 254 undergraduate medical students via the Pittsburgh Sleep Quality Index (PSQI) questionnaire and a self-structured questionnaire. The frequency of events was established and the Chi-squared and t-tests were applied to determine the association. Finally, regression analysis was performed to determine the correlation. Results Male sex, high body mass index (BMI), poor sleep quality, and night sleep duration shorter than 5 hours were found to be significant risk factors for the development of prehypertensive condition (prevalence of 42.5%). However, there were no statistically significant associations regarding prehypertension and family history, junk food and salt intake, physical activity and daytime napping, bedtime, and wake-up time. Night sleep duration shorter than 5 hours presented an odds ratio of 4.713 (p = 0.010) for the development of prehypertension after adjusting for other risk factors, such as male sex, sleep quality, and high BMI. Discussion and Conclusion A high prevalence of prehypertension (42.5%) was noted among undergraduate medical students. Night sleep duration shorter than 5 hours was a significant risk factor for the development of prehypertension, whereas sleep time was not significantly associated with prehypertension.

Mendelian randomization study supports positive bidirectional causal relationships between genetically predicted insomnia symptom and liability to benign prostatic hyperplasia

BackgroundSleep quality may be related to benign prostatic hyperplasia (BPH), however causal associations have not been established. This study aimed to evaluate causal relationships between six sleep traits ([i] day time napping, [ii] daytime sleepiness, [iii] insomnia, [iv] long sleep duration, [v] short sleep duration, and [vi] sleep duration per hour) and BPH through a bidirectional Mendelian randomization (MR) study.MethodsGenome-wide association summary statistics of sleep traits and BPH were downloaded from public databases. Inverse variance weighting (IVW) was used as the main approach for causal inference. For causal estimates identified by IVW, various sensitivity analyses were performed to assess the reliability of the results: (i) four additional MR methods to complement IVW; (ii) Cochran’s Q test to assess heterogeneity; (iii) MR-Egger intercept test and MR-PRESSO global test to assess horizontal pleiotropy; and (iv) leave-one-out method to assess stability.ResultsForward MR analyses indicated that genetically predicted insomnia symptom significantly increased BPH risk (OR = 1.267, 95% CI: 1.003–1.601, P = 0.048), while reverse MR analyses identified that genetically predicted liability to BPH significantly increased the incidence of insomnia (OR = 1.026, 95% CI: 1.000-1.052, P = 0.048). In a replicate MR analysis based on summary statistics including exclusively male participants, the finding of increased risk of BPH due to genetically predicted insomnia symptom was further validated (OR = 1.488, 95% CI: 1.096–2.022, P = 0.011). No further causal links were identified. In addition, sensitivity tests demonstrated the reliability of the MR results.ConclusionThis study identified that a higher prevalence of genetically predicted insomnia symptoms may significantly increase the risk of BPH, while genetically predicted liability to BPH may in turn increase the incidence of insomnia symptom. Therefore, improving sleep quality and reducing the risk of insomnia could be a crucial approach for the prevention of BPH.

Benefits of napping habits in healthy adults: Maintaining alerting performance and cortisol levels change within 90 min of habitual napping time

BackgroundNapping is garnering increased attention as a strategy for adults to sustain alertness and alleviate stress in contemporary society. The nuances of napping habits are emerging as an independent factor influencing the extent of individual benefits. This study aimed to demonstrate the long-term benefits of napping and explore the impact of napping habits on individual alertness, as well as whether this effect was correlated with cortisol levels. MethodsThe study involved 80 healthy adults categorized into two groups based on self-reported napping habits: habitual nappers (n = 49) and non-habitual nappers (n = 31). Karolinska Sleepiness Scale (KSS), psychomotor vigilance task (PVT), and saliva collection were performed every 30 min within 90 min in the absence of napping during the afternoon dip. The measurements were analyzed using repeated measures ANOVA and Pearson correlation analyses. ResultsThere was an interaction between groups and time in reaction speed and lapse number of PVT and cortisol (all p < 0.05). Post hoc analysis found that habitual nappers maintained higher objective alertness and experienced more significant increases in cortisol over time (all p < 0.05). The cortisol levels at sleepiness time were negatively associated with the slowest 10 % reaction speed of PVT in non-habitual nappers (r = −0.409, p = 0.022). ConclusionUnder the premise of mitigating the impacts of acute nap deprivation on sleep homeostasis and rhythm, napping habits emerge as a potential factor influencing the ability of individuals to sustain heightened alertness.

Network analysis of smoking-related sleep characteristics in Chinese adults

The associations between multiple sleep characteristics and smoking behavior are inconsistent, and it is unclear which sleep characteristics are most crucial for tobacco prevention. This study aimed to explore the associations between smoking status/intensity and multiple sleep characteristics and to identify the potential core domain of smoking-related sleep using network analysis. Data were obtained from a survey of cancer-related risk factors among Chinese adults. Logistic regression models were used to quantify the associations between sleep characteristics and smoking status/intensity. Network analyses were employed to identify the core sleep characteristics. A total of 5,228 participants with a median age of 44 years old were included in the study. Current smoking was significantly positively associated with long nap time, difficulty falling asleep, late bedtime, getting up after 7 am, and waking up earlier than expected. There was significant positive association between current smoking and short sleep duration in young adults under 45 years old. Late bedtime and getting up after 7 am were only associated with current heavy smoking, but not current light smoking. Network analyses showed that multiple smoking-related sleep characteristics were interconnected, with difficulty falling asleep and late bedtime as central characteristics in the network. The study found that the associations between sleep characteristics and smoking varied by age and smoking intensity and highlights the potential benefits of sleep health promotion in smoking cessation, with a particular focus on difficulty falling asleep and late bedtime.

Improving the detection of sleep slow oscillations in electroencephalographic data.

We aimed to build a tool which facilitates manual labeling of sleep slow oscillations (SOs) and evaluate the performance of traditional sleep SO detection algorithms on such a manually labeled data set. We sought to develop improved methods for SO detection. SOs in polysomnographic recordings acquired during nap time from ten older adults were manually labeled using a custom built graphical user interface tool. Three automatic SO detection algorithms previously used in the literature were evaluated on this data set. Additional machine learning and deep learning algorithms were trained on the manually labeled data set. Our custom built tool significantly decreased the time needed for manual labeling, allowing us to manually inspect 96,277 potential SO events. The three automatic SO detection algorithms showed relatively low accuracy (max. 61.08%), but results were qualitatively similar, with SO density and amplitude increasing with sleep depth. The machine learning and deep learning algorithms showed higher accuracy (best: 99.20%) while maintaining a low prediction time. Accurate detection of SO events is important for investigating their role in memory consolidation. In this context, our tool and proposed methods can provide significant help in identifying these events.

Bidirectional associations between the duration and timing of nocturnal sleep and naps in adolescents differ from weekdays to weekends

Bidirectional associations between the duration and timing of nocturnal sleep and naps in adolescents differ from weekdays to weekends

Where Did Nap Time Go? Why Older Kids Do Not Nap at School

Getting enough sleep is important not only for our health but also for learning. If sleep is good for us, why do children stop napping as they get older? Why do some children stop napping around their second birthday while others nap much longer? To answer these questions, scientists reviewed studies on how sleep, the brain, and memory develop. They took information from each area to create a new theory about why and when children stop napping. The scientists suggested a specific “memory area” in the brain, known as the hippocampus, develops as children grow up. Once the hippocampus can store the day’s memories, it results in fewer “napping” signals sent to the body, causing fewer naps. Information about how and why children stop napping is important for parents and teachers so they can best support children’s sleep needs.

A comparison of perceived barriers to optimal child sleep among families with low and high income

ObjectiveFamilies with low-income experience suboptimal sleep compared to families with higher-income. Unique drivers likely contribute to these disparities, along with factors that universally impede sleep patterns, despite income level. To inform intervention tailoring, this mixed-methods study gathered parent’s perceptions about child sleep challenges to identify similarities/differences in families with lower-income and higher-income. MethodsParents who experienced difficulties with their child (ages 2-4years) sleep were categorized as lower income (n = 15; $30,000 ± 17,845/year) or higher income (n = 15; $142,400 ± 61,373/year). Parents completed a survey and semistructured interview to explore barriers and facilitators for child sleep. Two coders independently evaluated transcripts for lower-income and higher-income groups using inductive analyses. Constant-comparison methods generated themes and characterized similarities/differences by income group. ResultsGroups were similar in themes related to diverse bedtime routines, nighttime struggles with child sleep, parent strategies to reduce night wakings, parent effort to provide a sleep-promoting environment, and presence of electronic rules. Groups differed in themes related to factors influencing routine setting (eg, lower income: external factors influencing routines; higher income: personal attributes for structure), parent appraisal of child sleep (eg, higher income: ambivalence; lower income: mostly negative appraisal), nap timing and duration (eg, lower income: longer naps), and strategy utilization and pursuit of resources (eg, higher income: more parents tried various strategies and accessed online/print resources). ConclusionsParents experienced many similar barriers to child sleep, with a few distinct differences by income group. These findings can inform future intervention components for all families, as well as customized components to address the unique needs of families across income levels.

The association between nap time, nighttime sleep and depression in Chinese older adults: A cross-sectional study.

To explore the relationship among nap time, night sleep time, and depression among the elderly and to determine the recommended sleep time to provide a scientific and reasonable basis for the prevention and control of depression in residents. Based on the 2020 China Health and Elderly Care Longitudinal Survey (CHARLS) database, the demographic data and the health and lifestyle information of the study subjects were obtained. A total of 2,959 valid samples were included, and the relationship between sleep and depression was explored by logistic regression, restricted cubic spline, and isotemporal substitution model. In the cross-sectional analysis, no statistical relationship was observed between napping time and depression in the elderly. The optimal sleep interval for the elderly at night is 6-7.5 hours, and the health benefits are the largest. A sleep duration of < 6 hours at night (OR = 2.25, 95% CI: 1.90 to 2.65) was associated with a high likelihood of depression. The probability of depression in the elderly continues to decrease with the increase of time after the nighttime sleep duration reaches 6 hours and is at the lowest level of about 7.5 hours. Moreover, the probability of depression will increase after the sleep duration exceeds 9.5 hours. In the range of 6-7.5 hours of recommended sleep duration, the likelihood of depression in the elderly will be reduced by 0.311 for every 30-minute increase in nighttime sleep time instead of noon sleep time. The duration of nighttime sleep and the probability of depression have a U-shaped relationship. The likelihood of depression was lowest in the elderly who slept for 6-8 hours at night, and the likelihood of depression could be reduced by increasing the nighttime sleep time instead of napping time within the optimal nighttime sleep range.

The effect of mandatory post-call relief on sleep and wellness in ophthalmology residents

BackgroundMultiple duty hour reforms have been implemented to optimize resident wellness through increasing opportunities for sleep recovery, but few studies have recorded objectively measured sleep or shown direct sleep and wellness benefits from such interventions. This study seeks to determine whether mandatory post-call relief policies with a partial night float system improved resident sleep, activity, and burnout among ophthalmology residents taking home call.MethodsWe conducted a two group cohort study of ophthalmology residents at the University Washington comparing post graduate year-2 (PGY-2) resident sleep, activity, and burnout between the optional post-call relief group from July 1, 2017 to June 30, 2019 to the mandatory post-call relief group from July 1, 2019 to June 30, 2021.ResultsOf twenty total residents participating in the survey portion, 18 residents participated in the sleep and activity tracking portion of the study, 9 in in the optional post-call relief cohort, and 9 in the mandatory post-call relief cohort. The mandatory post-call relief group recorded longer total sleep on call than the optional post-call relief group (p < 0.001). There was no difference in overnight sleep recorded on call (median 3.4 h), but residents recorded more time napping in the mandatory post-call relief cohort (p < 0.001). There was no significant difference between cohorts in amount of sleep while not on call. Residents in the mandatory post-call relief cohort recorded higher average daily steps, higher exercise time, and lower sedentary time than residents in the optional post-call relief cohort (p < 0.001). They also recorded lower median emotional exhaustion on the Maslach Burnout Inventory and lower stress in the Depression and Anxiety Stress Scale in the mandatory post-call relief cohort (p = 0.008).ConclusionsImplementation of mandatory post-call relief policies with a partial night-float system among PGY-2 residents was associated with more post-call naps with more overall physical activity, lower emotional exhaustion scores, and lower stress scores, despite no changes to overnight sleep on call or total sleep. Although sample size limits interpretation of data, implementation of mandatory post call relief could be considered to improve post-call sleep in programs with home call.