Suicidal ideation is associated with nighttime wakefulness in a community sample

Impact of an internet-based insomnia intervention on suicidal ideation and associated correlates in veterans at elevated suicide risk

Improving public health approaches to suicide prevention requires scalable evidence-based interventions that can be easily disseminated. Given empirical data supporting the association between insomnia and suicide risk, internet-delivered insomnia interventions are promising candidates to meet this need. The purpose of this study was to examine whether an unguided internet-delivered cognitive-behavioral therapy for insomnia (iCBT-I) improved insomnia severity, suicidal ideation (SI), and suicide risk correlates (depression, post-traumatic stress disorder, anxiety, hostility, belongingness, hopelessness, agitation, irritability, concentration) in a sample of veterans. Secondary data analysis of Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn veterans (n = 50) with clinically significant insomnia and elevated SI drawn from a larger randomized controlled trial (RCT) of an iCBT-I, Sleep Healthy Using the Internet (SHUTi). Two-sample t-tests or Wilcoxon rank sum tests were used to evaluate between-group differences (SHUTi vs. Insomnia Education Website control) in symptom improvement from baseline to post-intervention. SHUTi participants experienced a significant improvement in insomnia severity (P < .001; d = -1.08) and a non-significant with small (subthreshold medium) effect size reduction of SI (P = .17, d = 0.40), compared to control participants. Significant improvement in hopelessness was observed (medium effect size), with non-significant small to medium effect size reductions in most remaining suicide risk correlates. Self-administered iCBT-I was associated with improvements in insomnia severity in veterans at elevated risk for suicide. These preliminary findings suggest that SI and suicide risk correlates may improve following an iCBT-I intervention, demonstrating the need for future well-powered iCBT-I RCTs targeted for populations at elevated suicide risk.

Depression and suicidal ideation among Chinese college students during the COVID-19 pandemic: the mediating roles of chronotype and sleep quality

BACKGROUND

This study was intended to investigate the correlation between depression and suicidal ideation among Chinese college students during the COVID-19 pandemic and the potential mediating roles of chronotype and sleep quality in this relationship .

METHODS

A sample of 4,768 college students was selected from four institutions in Anhui Province, China, and the study was conducted during the COVID-19 pandemic (November to December 2020) using a stratified, cluster, multi-stage sampling method. This study used the two-item Patient Health Questionnaire (PHQ-2) to assess depressive symptoms, the Morningness-Eveningness Questionnaire 19 (MEQ-19) to determine individual sleep chronotypes (i.e., morning or evening preference), and the Pittsburgh Sleep Quality Index (PSQI) to evaluate sleep quality. Participants were asked about suicidal ideation. MPLUS 8.3 software was used to analyze the mediating effect of chronotype and sleep quality on the relationship between depression and suicidal ideation.

RESULTS

During the COVID-19 pandemic, the prevalence of suicidal ideation among Chinese college students was 5.4%. Depression was inversely correlated with chronotype (beta = - 0.346, P < 0.01) and positively correlated with sleep quality (beta = 0.846, P < 0.001), indicating that students experiencing depressive symptoms were more likely to have a later chronotype and poor sleep quality. A later chronotype (beta = - 0.019, P < 0.05) and poor sleep quality (beta = 0.066, P < 0.01) predicted suicidal ideation. Depression emerged as a direct and significant risk factor for suicidal ideation (effect value = 0.535, 95% confidence interval: 0.449 ~ 0.622). Chronotype and sleep quality were found to have potential mediating effects on the relationship between depression and suicidal ideation; however, the chain-mediating effect of chronotype and sleep quality was not statistically significant.

CONCLUSIONS

Our findings suggest that during the COVID-19 pandemic, depression can precipitate suicidal ideation through its influence on sleep chronotype and quality. These compelling findings highlight the urgency of early intervention strategies intended to mitigate suicidal thoughts, particularly among students exhibiting depressive symptoms, who experience disrupted sleep patterns and poor sleep quality.

[Insomniac symptoms and suicidality-link and management]

BACKGROUND

A link between insomniac symptoms and suicidality has long been suspected and deserves specific attention.

OBJECTIVE

We examine the current evidence for this relationship from epidemiology and neurobiology in order to propose a targeted management.

MATERIAL AND METHOD

Clinical example and selective Medline-literature research for insomnia symptoms and suicidality.

RESULTS

Epidemiological data and statistical analysis show that symptoms of insomnia are independent risk factors for suicidality. Neurobiological factors associated with combined insomnia symptoms and suicidality are: serotonergic dysfunction and circadian rhythm disorder leading to hypofrontality with reduced problem solving capacity and impaired emotional and impulse-control. Social isolation, recurrent rumination, comorbid psychiatric disorders, access to potentially lethal drugs or weapons need urgent evaluation in patients with a combination of suicidality and symptoms of insomnia.

CONCLUSION

patients with insomnia and further risk factors for suicide need to be treated resolutely and at an early stage. Modern sleep-promoting antidepressants with low toxicity and antipsychotics must be preferred in the treatment of patients with insomniac sleep disorders and suicidality. Multimodal anti-insomnia and anti-depressive therapy adapted to the circadian rhythm can exert a favorable influence both on depressive-suicidal and insomnia symptoms and their inherent risks.

How to survive the long night? Longitudinal relationship between sleep problems and suicidal behavior among adolescents: The serial mediating roles of negative emotion, self-control, and nonsuicidal self-injury

OBJECTIVE

Sleep problems are a significant risk factor for identifying and preventing suicidal involvement among adolescents. However, there is limited evidence to assess the underlying mechanisms between them. This study investigated the longitudinal relationship between sleep problems and suicidal behavior and examined whether this relationship was moderated by negative emotions, low self-control, and nonsuicidal self-injury (NSSI).

METHODS

From December 2020 onward, we assessed 1214 Chinese secondary school adolescents (60.7% were boys, aged 13-19 years) three times, 6 months apart.

RESULTS

In the direct effects model, sleep problems were found to have a positive impact on adolescent suicidal behavior. In the indirect effects model, we observed that sleep problems were associated with an elevated risk of suicidal behavior through several pathways: one-mediator path of negative emotions, low self-control, and NSSI, respectively; two-mediator path of negative emotions via low self-control, negative emotions via NSSI, and low self-control via NSSI, and three-mediator path from negative emotions to NSSI via low self-control.

CONCLUSIONS

This longitudinal study provides evidence that sleep problems in adolescents may increase suicidal behavior by exacerbating negative emotions, weakening self-control, and promoting NSSI. The findings suggest sleep problems should be addressed in suicide prevention and intervention efforts for adolescents.

Animal models of human insomnia

Insomnia disorder (chronic sleep continuity disturbance) is a debilitating condition affecting 5%-10% of the adult population worldwide. To date, researchers have attempted to model insomnia in animals through breeding strategies that create pathologically short-sleeping individuals or with drugs and environmental contexts that directly impose sleeplessness. While these approaches have been invaluable for identifying insomnia susceptibility genes and mapping the neural networks that underpin sleep-wake regulation, they fail to capture concurrently several of the core clinical diagnostic features of insomnia disorder in humans, where sleep continuity disturbance is self-perpetuating, occurs despite adequate sleep opportunity, and is often not accompanied by significant changes in sleep duration or architecture. In the present review, we discuss these issues and then outline ways animal models can be used to develop approaches that are more ecologically valid in their recapitulation of chronic insomnia's natural aetiology and pathophysiology. Conditioning of self-generated sleep loss with these methods promises to create a better understanding of the neuroadaptations that maintain insomnia, including potentially within the infralimbic cortex, a substrate at the crossroads of threat habituation and sleep.

Examining sleep disturbance components as near-term predictors of suicide ideation in daily life

Suicide ideation emerges and fluctuates over short timeframes (minutes, hours, days); however, near-term predictors of such fluctuations have not been well-elucidated. Sleep disturbance is a distal suicide risk factor, but less work has examined whether daily sleep disturbance predicts near-term changes in suicide ideation. We examined subjective sleep disturbance components as predictors of passive and active suicide ideation at the within-person (i.e., day-to-day changes within individuals relative to their own mean) and between-persons (individual differences relative to the sample mean) levels. A transdiagnostic sample of 102 at-risk young adults ages 18-35 completed a 21-day ecological momentary assessment protocol, during which they reported on sleep and passive and active suicide ideation. At the within-persons level, nightmares, sleep quality, and wake after sleep onset predicted passive suicide ideation, and sleep quality and wake after sleep onset predicted active suicide ideation. At the between-persons level, nightmares, sleep onset latency, and sleep quality were associated with passive suicide ideation, and sleep onset latency was associated with active suicide ideation. In contrast, suicide ideation did not predict subsequent sleep at the within-person level. Specific sleep disturbance components are near-term predictors of intraindividual increases in suicide ideation and may hold promise for suicide prevention and intervention.

Unipolar and Bipolar Depression Detection and Classification Based on Actigraphic Registration of Motor Activity Using Machine Learning and Uniform Manifold Approximation and Projection Methods

Modern technology frequently uses wearable sensors to monitor many aspects of human behavior. Since continuous records of heart rate and activity levels are typically gathered, the data generated by these devices have a lot of promise beyond counting the number of daily steps or calories expended. Due to the patient's inability to obtain the necessary information to understand their conditions and detect illness, such as depression, objectively, methods for evaluating various mental disorders, such as the Montgomery-Asberg depression rating scale (MADRS) and observations, currently require a significant amount of effort on the part of specialists. In this study, a novel dataset was provided, comprising sensor data gathered from depressed patients. The dataset included 32 healthy controls and 23 unipolar and bipolar depressive patients with motor activity recordings. Along with the sensor data collected over several days of continuous measurement for each patient, some demographic information was also offered. The result of the experiment showed that less than 70 of the 100 epochs of the model's training were completed. The Cohen Kappa score did not even pass 0.1 in the validation set, due to an imbalance in the class distribution, whereas in the second experiment, the majority of scores peaked in about 20 epochs, but because training continued during each epoch, it took much longer for the loss to decline before it fell below 0.1. In the second experiment, the model soon reached an accuracy of 0.991, which is as expected given the outcome of the UMAP dimensionality reduction. In the last experiment, UMAP and neural networks worked together to produce the best outcomes. They used a variety of machine learning classification algorithms, including the nearest neighbors, linear kernel SVM, Gaussian process, and random forest. This paper used the UMAP unsupervised machine learning dimensionality reduction without the neural network and showed a slightly lower score (QDA). By considering the ratings of the patient's depressive symptoms that were completed by medical specialists, it is possible to better understand the relationship between depression and motor activity.

A high sense of coherence can mitigate suicidal ideation associated with insomnia

BACKGROUND

The present study aimed to investigate whether insomnia is associated with suicidal ideation (SI) among Japanese workers by conducting a multi-level analysis with sense of coherence (SOC) as a random effect.

PARTICIPANTS AND PROCEDURE

A cross-sectional survey was conducted among 19,481 workers in Tsukuba, Japan. Data from 7,175 participants aged 20-65 years were included in the analysis. The Athens Insomnia Scale (AIS) was used as the independent variable, and SI over the past year was used as the dependent variable. SOC was measured using the five-point SOC-13 scale, and socioeconomic and health factors were investigated as covariates. Participants were divided into three groups (low, medium, and high) based on their SOC scores. Multilevel logistic regression analysis was performed to calculate odds ratios (OR) and 95% confidence intervals (95% CI).

RESULTS

In the high-SOC group, only one person had SI. In a multi-level logistic analysis that excluded the high SOC group, insomnia was found to be associated with SI (OR = 2.26, 95% CI [1.75, 2.93]). Furthermore, the AIS sub-items "Final awakening earlier than desired" (OR = 1.26, 95% CI [1.05, 1.50]) and "Sense of well-being during the day" (OR = 1.63, 95% CI [1.34, 1.99]) were associated with SI. 8.95% or 11% of the variation in the presence or absence of SI was found to be explained by differences between SOC groups.

CONCLUSIONS

The study highlights that insomnia is associated with SI, and that high SOC may reduce SI even under insomnia. Future longitudinal studies are needed to confirm whether high SOC reduces SI due to insomnia.

Development and Initial Validation of the Assessment of Sleep Environment (ASE): Describing and Quantifying the Impact of Subjective Environmental Factors on Sleep

The purpose of this study was to develop and test the reliability and validity of a 13-item self-report Assessment of Sleep Environment (ASE). This study investigates the relationship between subjective experiences of environmental factors (light, temperature, safety, noise, comfort, humidity, and smell) and sleep-related parameters (insomnia symptoms, sleep quality, daytime sleepiness, and control over sleep). The ASE was developed using an iterative process, including literature searches for item generation, qualitative feedback, and pilot testing. It was psychometrically assessed using data from the Sleep and Healthy Activity Diet Environment and Socialization (SHADES) study (N = 1007 individuals ages 22-60). Reliability was determined with an internal consistency and factor analysis. Validity was evaluated by comparing ASE to questionnaires of insomnia severity, sleep quality, daytime sleepiness, sleep control, perceived stress, and neighborhood disorder. The ASE demonstrated high internal consistency and likely reflects a single factor. ASE score was associated with insomnia symptoms (B = 0.09, p < 0.0001), sleep quality (B = 0.07, p < 0.0001), and sleep control (B = -0.01, p < 0.0001), but not daytime sleepiness. The ASE was also associated with perceived stress (B = 0.20, p < 0.0001) and neighborhood disorder (B = -0.01, p < 0.0001). Among sleep environment factors, only smell was not associated with sleep quality; warmth and safety were negatively associated with sleepiness; and of the sleep environment factors, only light/dark, noise/quiet, and temperature (warm/cool) were not associated with insomnia symptoms. The ASE is a reliable and valid measure of sleep environment. Physical environment (light, temperature, safety, noise, comfort, humidity, and smell) was associated with insomnia symptoms and sleep quality but not sleepiness.

Suicide Risk in Military Personnel during the COVID-19 Health Emergency in a Peruvian Region: A Cross-Sectional Study

Military personnel represent a frontline group exposed to multiple stressors. These factors have increased during the COVID-19 pandemic, predisposing to the development of suicidal risk (SR). Given the few studies conducted in this population, we evaluated the prevalence of SR and its associated factors during the health emergency. A cross-sectional survey study was conducted in person among 514 participants in Lambayeque, Peru in 2021. The outcome was SR, and the exposures were depression (PHQ-9), anxiety (GAD-7), PTSD (PCL-C), and other sociodemographic variables. The prevalence of SR was 14.0% (95% CI: 11.12-17.31%) and was significantly higher in people with a family history of mental health (PR: 2.16; 95% CI: 1.13-4.15) and in those with moderate clinical insomnia (PR: 2.21; 95% CI: 1.19-4.12). Military personnel with high resilience had a lower prevalence of SR (PR: 0.54, CI: 0.31-0.95). Anxiety was associated with a higher prevalence of SR (PR: 3.27; 95% CI: 1.76-6.10). Our findings show that at least 1 out of 10 military personnel are at risk of suicide. Special attention should be paid to the associated factors to develop interventions and reverse their consequences. These results may be useful in policy implementation and general statistics of SR in the local and regional context.

Verification of sleep scales as predictors of suicidal ideation in Japanese dayworkers: a longitudinal study

The objective of this study was to verify whether the assessment of poor sleep based on two sleep scales could predict suicidal ideation in Japanese dayworkers. A longitudinal survey was conducted among 446 Japanese dayworkers working at a company in Japan. Questionnaires were administered in 2013 (baseline) and 2014 (follow-up). To evaluate suicidal ideation, we used Question 19 of the Self-rating Depression Scale, categorizing participants who chose response options "some/a good part/most of the time" as suicidal ideation (+), and those who chose option "never or only a little of the time" as suicidal ideation (-). Two sleep scales, the Pittsburgh Sleep Quality Index (PSQI) and the 3-Dimensional Sleep Scale (3DSS), were selected as potential predictors of suicidal ideation. Only participants who were suicidal ideation (-) at baseline were included in the analysis, and suicidal ideation (+) individuals at follow-up were considered to have developed suicidal ideation during the interval between baseline and follow-up surveys. Data from 293 participants (236 men, 57 women) were analyzed. Twenty-two participants (7.5%) became suicidal ideation (+) at follow-up. Multiple logistic regression analysis showed that only sleep quality of the 3DSS subscale significantly predicted suicidal ideation, even after adjusting for depressive symptoms. That is, assessment of poor sleep did not predict suicidal ideation when based on the PSQI, but did when based on the 3DSS. Assessment of sleep quality based on the 3DSS may prove more useful in predicting worker suicidal ideation in industrial settings with limited facilities than PSQI.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-022-00404-6.

Classification of Depressive and Schizophrenic Episodes Using Night-Time Motor Activity Signal

Major depressive disorder (MDD) is the most recurrent mental illness globally, affecting approximately 5% of adults. Furthermore, according to the National Institute of Mental Health (NIMH) of the U.S., calculating an actual schizophrenia prevalence rate is challenging because of this illness’s underdiagnosis. Still, most current global metrics hover between 0.33% and 0.75%. Machine-learning scientists use data from diverse sources to analyze, classify, or predict to improve the psychiatric attention, diagnosis, and treatment of MDD, schizophrenia, and other psychiatric conditions. Motor activity data are gaining popularity in mental illness diagnosis assistance because they are a cost-effective and noninvasive method. In the knowledge discovery in databases (KDD) framework, a model to classify depressive and schizophrenic patients from healthy controls is constructed using accelerometer data. Taking advantage of the multiple sleep disorders caused by mental disorders, the main objective is to increase the model’s accuracy by employing only data from night-time activity. To compare the classification between the stages of the day and improve the accuracy of the classification, the total activity signal was cut into hourly time lapses and then grouped into subdatasets depending on the phases of the day: morning (06:00–11:59), afternoon (12:00–17:59), evening (18:00–23:59), and night (00:00–05:59). Random forest classifier (RFC) is the algorithm proposed for multiclass classification, and it uses accuracy, recall, precision, the Matthews correlation coefficient, and F1 score to measure its efficiency. The best model was night-featured data and RFC, with 98% accuracy for the classification of three classes. The effectiveness of this experiment leads to less monitoring time for patients, reducing stress and anxiety, producing more efficient models, using wearables, and increasing the amount of data.

The Mind After Midnight: Nocturnal Wakefulness, Behavioral Dysregulation, and Psychopathology

Sufficient sleep with minimal interruption during the circadian/biological night supports daytime cognition and emotional regulation. Conversely, disrupted sleep involving significant nocturnal wakefulness leads to cognitive and behavioral dysregulation. Most studies to-date have examined how fragmented or insufficient sleep affects next-day functioning, but recent work highlights changes in cognition and behavior that occur when someone is awake during the night. This review summarizes the evidence for day-night alterations in maladaptive behaviors, including suicide, violent crime, and substance use, and examines how mood, reward processing, and executive function differ during nocturnal wakefulness. Based on this evidence, we propose the Mind after Midnight hypothesis in which attentional biases, negative affect, altered reward processing, and prefrontal disinhibition interact to promote behavioral dysregulation and psychiatric disorders.

Suicidal Ideation Is Associated With Excessive Smartphone Use Among Chinese College Students

BACKGROUND

Suicidal ideation is the first step and a strong predictor of suicide. College students are at a considerably high risk of suicidal ideation, and smartphones are commonly used in this group. However, the relationship between suicidal ideation and smartphone use among Chinese college students is unclear. The current study aimed to investigate the prevalence of suicidal ideation among Chinese college students and its association with smartphone use and addiction factors.

METHODS

A total of 439 college students participated the survey. We collected the demographic information, physical health, psychosocial factors (depressive symptoms, social support, sleep quality), characteristics of smartphone use, and mobile phone addiction (MPA). Suicidal ideation was measured with a single question, "did you feel that life was not worth living in the past 1 year?"

RESULTS

The prevalence of suicidal ideation ("Yes" response) in the past year among Chinese college students was 7.5%. In binary logistic regression analysis, suicidal ideation was significantly correlated with less subjective social support (OR: 2.49, p = 0.049), lower utilization of social support (OR: 13.28, p = 0.012), more depressive symptoms (OR:4.96, p = 0.005), and more than 5 h of daily smartphone use (OR: 2.60, p = 0.025).

CONCLUSION

Considering the widely use of smartphones in Chinese colleges and the correlation with suicidal ideation, excessive phone use among college students should be given more attention by administrators and health workers. It is necessary to obtain more information about the intention of smartphone use, make full use of smartphones for health education, and monitor excessive use of smartphones, while improving social support and coping mechanisms for depression, to identify suicidal ideation and prevent suicidal behavior among Chinese college students.

The Dynamic Relationship Between Alpha and Beta Power and Next-Day Suicidal Ideation in Individuals With Treatment-Resistant Depression

Background

Nocturnal wakefulness has emerged as a potential predictor of short-term suicide risk. This analysis used dynamic temporal patterns in alpha and beta power and global sleep metrics to explore the possible link between next-day suicidal ideation (NDSI) and wakefulness measures in unmedicated participants with treatment-resistant depression.

Methods

Thirty-three medication-free participants with treatment-resistant depression completed overnight polysomnography. Alpha and beta spectral power as functions over time were used to represent arousal-related components of the dynamic sleep process. A functional data analytic approach (multilevel functional principal component analysis [MFPCA]) was used to preserve the oscillatory nature of the data; MFPCA PC scores were then associated with NDSI. Associations between NDSI and polysomnography-defined wakefulness after sleep onset, sleep efficiency, and total sleep time were also evaluated.

Results

NDSI had the strongest relationship with the second beta PC score (slope = 0.09 [90% credible interval, 0.03 to 0.14]), which represented an oscillating pattern that reflected disturbed sleep. The first PCs from both alpha and beta MFPCAs represented the overall magnitude of power and were most closely associated with traditional polysomnography metrics but were not related to NDSI. Results were equivocal for wakefulness after sleep onset with NDSI and did not support a relationship between NDSI and either sleep efficiency or total sleep time, highlighting the value of information contained in oscillating electroencephalogram patterns for identifying physiological links between nocturnal wakefulness and NDSI.

Conclusions

This study leveraged the dynamic nature of wakefulness-related electroencephalogram frequencies and provides a potential electrophysiological link between suicidal ideation and wakefulness during sleep in individuals with treatment-resistant depression.

Nightmare Distress as a Risk Factor for Suicide Among Adolescents with Major Depressive Disorder

PURPOSE

Nightmare is common and is also independently implicated in suicide risk among the adolescent population. Adolescents with major depressive disorder (MDD) are at an increased risk of suicide. Therefore, comorbid nightmares may amplify suicide risk among this clinical population. This study aimed to explore the effects of nightmares on suicide risk among adolescents with MDD.

PATIENTS AND METHODS

Subjects were 499 outpatients aged 12-18 in four large psychiatric hospitals clinic of China, from January 1 to October 31, 2021. Simultaneously, we matched 499 healthy controls according to gender and age. All participants underwent affective state (depressive and anxiety symptoms) and sleep variable (nightmare frequency/distress, insomnia symptoms, and daytime sleepiness) evaluation as well as MDD diagnoses and determination of suicide risk by a fully structured diagnostic clinical interview.

RESULTS

Adolescents with MDD reported a higher incidence of frequent nightmares (at least one night per week) and level of nightmare distress than healthy controls (22.0% vs 6.1%; 28.85 ± 11.92 vs 17.30 ± 5.61). Over half of the patients with suicide risk (51.6%) experienced frequent nightmares compared with approximately one-third of those at a risk for suicide (30.7%). Patients with suicide risk scored scientifically higher on sleep variables, depressive and anxiety symptoms than those without the risk. Further logistic regression analysis indicated that female gender, junior grade, recurrent depressive episode, severe nightmare distress and severe depressive symptoms were independently and significantly associated with suicide risk.

CONCLUSION

Our study provided evidence that adolescents with MDD experienced a higher prevalence of frequent nightmares and suffered more nightmare distress. Nightmare distress is an independent risk factor for suicide risk.

A network analysis of suicidal ideation, depressive symptoms, and subjective well-being in a community population

Although the relationship between subjective well-being (SWB) and suicidal ideation (SI) has been illustrated in previous research, few studies have conceptualized SWB as a comprehensive measure of life satisfaction in multiple domains, nor have they considered possible mediators such as depressive symptoms. Therefore, the present study aimed to identify dimensions of SWB correlated with SI, and to analyze associations among SWB sub-domains, depressive symptoms, and SI in a community population. A total of 1200 community adults in South Korea, aged 20-86 years, completed self-report questionnaires on demographics, depressive mood (Patient Health Questionnaire-9 [PHQ-9]), SI (item 9 of the PHQ-9), and 14 SWB sub-domains (Subjective Well-Being Inventory). Factors associated with SI, and interactions among SI, depressive mood, and SWB, were identified by logistic regression and phenotype network analyses, respectively. The five main factors influencing the regularized partial correlation network were life satisfaction, self-blame, job, hopelessness, and fatigue. Pathways were observed from work-life balance and life satisfaction to hopelessness; from self-blame and fatigue to safety and health; and from sleep disturbance, concentration difficulties, self-blame, and hopelessness to SI. Making job activities more emotionally rewarding, the potential for career progression and regular work hours could address anhedonia, hopelessness and sleep disturbance, respectively, thus enhancing SWB and reducing SI in the community population.

Chronotype and social support among student athletes: impact on depressive symptoms

Previous studies have shown individuals with evening chronotype to have a greater likelihood for depression (self-reported and clinical ratings), especially in young adults. However, the mechanisms for this relationship remain unknown. Low levels of social support may be a plausible mechanism: young adults with evening chronotypes are awake when others are sleeping, which may lead to feelings of isolation or low support. This study examined links between chronotype, depression, and social support in relationship subtypes within a group of university student athletes. Data were obtained from 189 NCAA Division-I student athletes across all sports. Chronotype was assessed with the Circadian Energy Scale and ranged from -2 (definitely morning type) to +2 (definitely evening type). Depressive symptoms were assessed with Center for Epidemiological Studies Depression scale. Social support was assessed with the Multidimensional Scale of Perceived Social Support, which included subscales for Family, Friends, and Significant Other. A subscale for Team was created using the items from the Friends subscale (changing the word "friends" to "teammates"). Regression analyses adjusted for age, sex, and minority status. More evening chronotype was associated with higher reported depressive symptoms (p = .018), lower overall perceived social support (p = .001), and lower perceived social support specifically provided by family (p < .0001), friends (p < .0001), and teammates (p = .014). However, more evening chronotype was associated with higher depressive symptoms for higher, but not lower perceived social support from significant other. Moreover, chronotype-by-support interactions on depressive symptoms were observed; the statistical relationship between chronotype and depression was evident only in those with low (but not high) social support from friends and teammates. These data suggest that having a more evening chronotype may be associated with social isolation, and decreased opportunities for interactions with friends and teammates. This may contribute to the long-standing circadian association seen with depression in college student-athletes. Interventions aimed at increasing university support networks may reduce the impact of depression in students self-identifying with later chronotypes and sleep schedules.