Correlation Between Chronotypes and Depressive Symptoms Mediated by Sleep Quality Among Chinese College Students During the COVID-19 Pandemic

Mediating Effects of Sleep Problems and Emotional Symptoms in the Relationship Between Chronotype and Self-Harm Among Adolescents Aged 11-19 Years

Purpose

Self-harm is linked to numerous adverse health and social outcomes, including repetitive self-harm and an increased risk of suicide. This study aims to explore the influence of chronotype on self-harm among adolescents and further investigate the mediating role of sleep problems and emotional symptoms.

Participants and Methods

The study was conducted between April and June 2022, involving 13 junior and senior high schools in Tianjin. The participants were asked to complete online questionnaires assessing chronotype, sleep problems, depression, anxiety, and self-harm. The data were analyzed and processed using Spearman correlation and mediation effect analysis. Two mediation pathways were tested: Model 1 with sleep problems and depression as the mediators, and Model 2 with sleep problems and anxiety as the mediators.

Results

Participants comprised 13,374 Chinese middle school adolescents (6745 boys) aged 11-19 years. In Model 1, the independent mediation effects of sleep problems and depression were -0.216 (95% CI = [-0.263, -0.172]) and -0.101 (95% CI = [-0.121, -0.083]), accounting for 33.33% and 15.59% of the total effect, respectively. The chain mediation effect was -0.170 (95% CI = [-0.196, -0.146]), accounting for 26.23% of the total effect. In Model 2, the independent mediation effects of sleep problems and anxiety were -0.232 (95% CI = [-0.279, -0.189]) and -0.075 (95% CI = [-0.091, -0.059]), respectively accounting for 35.63% and 11.52% of the total effect. The chain mediation effect was -0.151 (95% CI = [-0.176, -0.128]), accounting for 23.20% of the total effect.

Conclusion

Chronotype is a significant predictor of self-harm, with a later chronotype associated with a higher risk. Both sleep problems and emotional symptoms independently and serially mediate the relationship between chronotype and self-harm. These findings highlight the complex pathways through which chronotype influences self-harm behavior and suggest potential targets for intervention.

Effects of physical activity on sleep quality among university students: chain mediation between rumination and depression levels

BACKGROUND

Colleges and universities are currently facing the major public health issue of poor sleep quality. Sleep quality must be taken seriously to maintain the students' emotional and physical well-being. Thus, this study sought to determine how university students' levels of physical activity related to the quality of their sleep, as well as to explore the mechanisms via which physical activity affects sleep and provide suggestions for improving it.

METHODS

A total of 883 university students from Ganzhou City, Jiangxi Province, China participated in the study. Their physical activity, sleep quality, ruminative thinking levels, and depression were assessed using various questionnaires.

RESULTS

Through the mediating effects of rumination and depression as well as the chain-mediated effects of these two factors, physical exercise changed the quality of sleep.

CONCLUSION

University students' sleep quality can be improved by increasing their physical activity and decreasing ruminative thinking and depression levels.

Changes in sleep patterns in people with a history of depression during the COVID-19 pandemic: a natural experiment

BACKGROUND

The COVID-19 pandemic, while a major stressor, increased flexibility in sleep-wake schedules.

OBJECTIVES

To investigate the impact of the pandemic on sleep patterns in people with a history of depression and identify sociodemographic, clinical or genetic predictors of those impacts.

METHODS

6453 adults from the Australian Genetics of Depression Study (45±15 years; 75% women) completed surveys before (2016-2018) and during the pandemic (2020-2021). Participants were assigned to 'short sleep' (<6 hours), 'optimal sleep' (6-8 hours) or 'long sleep' (>8 hours). We focused on those having prepandemic 'optimal sleep'.

FINDINGS

Pre pandemic, the majority (70%, n=4514) reported optimal sleep, decreasing to 49% (n=3189) during the pandemic. Of these, 57% maintained optimal sleep, while 16% (n=725) shifted to 'short sleep' and 27% (n=1225) to 'long sleep'. In group comparisons 'optimal-to-short sleep' group had worse prepandemic mental health and increased insomnia (p's<0.001), along with an elevated depression genetic score (p=0.002). The 'optimal-to-long sleep' group were slightly younger and had higher distress (p's<0.05), a greater propensity to being evening types (p<0.001) and an elevated depression genetic score (p=0.04). Multivariate predictors for 'optimal-to-short sleep' included reported stressful life events, psychological or somatic distress and insomnia severity (false discovery rate-corrected p values<0.004), while no significant predictors were identified for 'optimal-to-long sleep'.

CONCLUSION AND IMPLICATIONS

The COVID-19 pandemic, a natural experiment, elicited significant shifts in sleep patterns among people with a history of depression, revealing associations with diverse prepandemic demographic and clinical characteristics. Understanding these dynamics may inform the selection of interventions for people with depression facing major challenges.

Neuroimaging signatures and a deep learning modeling for early diagnosing and predicting non-pharmacological therapy success for subclinical depression comorbid sleep disorders in college students

Objective

College students with subclinical depression often experience sleep disturbances and are at high risk of developing major depressive disorder without early intervention. Clinical guidelines recommend non-pharmacotherapy as the primary option for subclinical depression with comorbid sleep disorders (sDSDs). However, the neuroimaging mechanisms and therapeutic responses associated with these treatments are poorly understood. Additionally, the lack of an early diagnosis and therapeutic effectiveness prediction model hampers the clinical promotion and acceptance of non-pharmacological interventions for subclinical depression.

Methods

This study involved pre- and post-treatment resting-state functional Magnetic Resonance Imaging (rs-fMRI) and clinical data from a multicenter, single-blind, randomized clinical trial. The trial included 114 first-episode, drug-naïve university students with subclinical depression and comorbid sleep disorders (sDSDs; Mean age=22.8±2.3 years; 73.7% female) and 93 healthy controls (HCs; Mean age=22.2±1.7 years; 63.4% female). We examined altered functional connectivity (FC) and brain network connective mode related to subregions of Default Mode Network (sub-DMN) using seed-to-voxel analysis before and after six weeks of non-pharmacological antidepressant treatment. Additionally, we developed an individualized diagnosing and therapeutic effect predicting model to realize early recognition of subclinical depression and provide objective suggestions to select non-pharmacological therapy by using the newly proposed Hierarchical Functional Brain Network (HFBN) with advanced deep learning algorithms within the transformer framework.

Results

Neuroimaging responses to non-pharmacologic treatments are characterized by alterations in functional connectivity (FC) and shifts in brain network connectivity patterns, particularly within the sub-DMN. At baseline, significantly increased FC was observed between the sub-DMN and both Executive Control Network (ECN) and Dorsal Attention Network (DAN). Following six weeks of non-pharmacologic intervention, connectivity patterns primarily shifted within the sub-DMN and ECN, with a predominant decrease in FCs. The HFBN model demonstrated superior performance over traditional deep learning models, accurately predicting therapeutic outcomes and diagnosing subclinical depression, achieving cumulative scores of 80.47% for sleep quality prediction and 84.67% for depression prediction, along with an overall diagnostic accuracy of 82.34%.

Conclusions

Two-scale neuroimaging signatures related to the sub-DMN underlying the antidepressant mechanisms of non-pharmacological treatments for subclinical depression. The HFBN model exhibited supreme capability in early diagnosing and predicting non-pharmacological treatment outcomes for subclinical depression, thereby promoting objective clinical psychological treatment decision-making.

Association between chronotype, social jetlag, sleep quality, and academic burnout among nursing students: A cross-sectional study

Academic burnout in nursing students is a serious problem worldwide that results in emotional exhaustion, cynicism and low professional efficacy. The aim of the current study was to examine the association between sleep quality and circadian rhythm indicators and academic burnout among Iranian nursing students. This cross-sectional study was conducted on 325 undergraduate nursing students studying at Qazvin University of Medical Sciences between November and February 2023. Data collection was carried out using self-report questionnaires including demographic characteristics, The Pittsburgh Sleep Quality Index (PSQI), reduced-Morningness-Eveningness Questionnaire (r-MEQ), and the Maslach Burnout Inventory-Student Survey (MBI-SS). Social jetlag (SJL) was defined as the absolute value of the difference between the midpoint of sleep on free days (MSF) and the midpoint of sleep on workdays (MSW). Data were analyzed using univariate and multivariate linear regression models. About 31.4% of participants had evening chronotype and almost half of them suffered from poor sleep quality. About 47.7% of the participants had SJL ≥ 2 h. In the multivariate linear regression model, students with evening chronotype compared to morning chronotype experienced more academic burnout in emotional exhaustion, cynicism and professional efficacy. PSQI score was only correlated with emotional exhaustion and cynicism subscales. Increased SJL was a predictor on all three subscales of academic burnout. The findings suggested that evening chronotype, poor sleep quality, and high SJL were associated with increased likelihood of academic burnout in nursing students. Assessment of circadian preference and sleep quality is beneficial for timely identification and prevention of academic burnout in nursing students.

Associations of evening-type and insomnia symptoms with depressive symptoms among youths

BACKGROUND

Evening-type and insomnia symptoms are significantly related to each other and independently associated with depressive symptoms, yet few studies have examined the potential interaction between these two conditions. Therefore, we aimed to examine the associations of evening-type and insomnia symptoms with depressive symptoms among Chinese youths, with a specific focus on the joint effects of the two conditions on depressive symptoms.

METHODS

Participants aged between 12 and 25 were invited to participate in an online survey from December 15, 2022, to May 26, 2023. Multivariate logistic regression models and additive interaction models were used to examine the independent and joint effects of chronotypes and insomnia symptoms on depressive symptoms, respectively.

RESULTS

Of the 6145 eligible youths, the prevalence of evening-type and insomnia symptoms were 24.9 % and 29.6 %, respectively. Both evening-type (adjusted OR, [AdjOR]: 3.21, 95 % CI: 2.80-3.67) and insomnia symptoms (AdjOR: 10.53, 95 % CI: 9.14-12.12) were associated with an increased risk of depressive symptoms. In addition, the additive interaction models showed that there is an enhanced risk of depression related to interaction between evening-type and insomnia symptoms (relative excess risk due to interaction, [RERI]: 11.66, 95 % CI: 7.21-16.11).

CONCLUSIONS

The present study provided additional evidence demonstrating the presence of interaction between evening-type and insomnia symptoms, which can lead to a higher risk of depressive symptoms. Our findings argue the need for addressing both sleep and circadian factors in the management of depressive symptoms in young people.

Association Between EEG Microarousal During Nocturnal Sleep and Next-Day Selective Attention in Mild Sleep-Restricted Healthy Undergraduates

Purpose

To explore whether sleep electroencephalogram (EEG) microarousals of different standard durations predict daytime mood and attention performance in healthy individuals after mild sleep restriction.

Participants and Methods

Sixteen (nine female) healthy college students were recruited to examine the correlations between nocturnal EEG microarousals of different standard durations (≥3 s, ≥5 s, ≥7 s, ≥9 s) under mild sleep restriction (1.5 h) and the following morning's subjective alertness, mood, sustained attention, and selective attention task performance.

Results

Results revealed that mild sleep restriction significantly reduced subjective alertness and positive mood, while having no significant effect on negative mood, sustained attention and selective attention performance. The number of microarousals (≥5 s) was negatively associated with positive mood at 6:30. The number of microarousals was significantly and positively correlated with the response time difference value of disengagement component of the selective attention task at around 7:30 (≥5 s and ≥7 s) and 9:00 (≥5 s). The number of microarousals (≥7 s) was significantly and positively correlated with the inaccuracy difference value of orientation component of the selective attention task at around 9:00.

Conclusion

The number of EEG microarousals during sleep in healthy adults with mild sleep restriction was significantly and negatively related to their daytime positive affect while positively associated with the deterioration of disengagement and orientation of selective attention performance, but this link is dependent on the standard duration of microarousals, test time and the type of task.