Sleep-Related Cognitive Processes and the Incidence of Insomnia Over Time: Does Anxiety and Depression Impact the Relationship?

Depression, anxiety, and insomnia symptoms among Chinese college students: A network analysis across pandemic stages

BACKGROUND

As the stages of the COVID-19 pandemic evolved, the symptoms of depression, anxiety, and insomnia have increasingly manifested among Chinese college students. The aim of this study is to investigate the relationships between these symptoms through network analysis among Chinese college students during COVID-19.

METHOD

A three-wave cross-sectional survey was conducted at 22 colleges in Guangdong Province, involving 381,152 students during three specific time intervals: T1 (baseline, February 3 to 10, 2020), T2 (19 months after baseline, June 10 to 18, 2021), and T3 (37 months after baseline, March 15 to April 22, 2023). Depression (PHQ-9), anxiety (GAD-7), and insomnia (YSIS) were used separately. We analyzed two key network indices: "Expected influence" and "Bridge expected influence". Network stability was assessed through a case-dropping bootstrap program.

RESULT

The effective sample sizes for the three periods were as follows: T1 - 164,101 (103,645 females, 63.2 %), T2 - 86,767 (52,146 females, 60.1 %), and T3 - 130,284 (76,720 females, 58.9 %). Across these three periods, the key central symptoms were "Fatigue" (PHQ4), "Restlessness" (GAD5), "Uncontrollable worrying" (GAD2), "Worry too much" (GAD3) and "Sleep insufficiency" (YSIS6). Notably, "Fatigue" (PHQ4), "Restlessness" (GAD5) and "Irritability" (GAD6) consistently served as bridge symptoms. In the T1 and T2 period, "Motor" (PHQ8) acted as a bridge symptom but weakened in T3.

CONCLUSION

Throughout the three periods, the mental health issues among Chinese college students displayed characteristics of somatization within the depression-anxiety-insomnia comorbidity network. Over time, anxiety symptoms appeared to become more prominent. Consequently, this study highlights the importance of accurately identifying and promptly intervening in these core symptoms of mental health among college students, as these symptoms may evolve across different stages of a pandemic.

Network analysis to estimate central insomnia symptoms among daytime workers at-risk for insomnia

Although insomnia complaints are associated with mental health problems and reduced work productivity, the central insomnia symptoms in workers at-risk for insomnia remain unclear. This study aimed to identify the central insomnia symptoms among daytime workers at risk for insomnia. The participants were 881 Japanese daytime workers at-risk for insomnia with a mean age of 49.33 ± 9.92 years. At-risk for insomnia was defined as an Athens Insomnia Scale score of six or higher. The Athens Insomnia Scale was used as a screening for at-risk insomnia because it has higher sensitivity and specificity than other insomnia screening scales. The Insomnia Severity Index is recommended as a mechanism of insomnia and an outcome measure; therefore, a network analysis was conducted with the seven items of the Insomnia Severity Index. The important variables in the connections between insomnia symptoms were estimated from centrality indices, which were interpretable only for strength. The strength value results suggest that difficulty staying asleep and worry about sleep problems were the central insomnia symptoms. The connections were stronger for difficulty staying asleep and problem waking up too early, difficulty staying asleep and difficulty falling asleep, and interference with daytime functions and noticeable to others. Worry about sleep problems was strongly associated with variables other than nocturnal insomnia symptoms. Therefore, difficulty staying asleep and worry about sleep problems are important variables in daytime workers at-risk for insomnia and are key points for improvement or exacerbation of insomnia symptoms.

The course of insomnia symptoms during the acute treatment of major depressive disorder: A CAN-BIND-1 report

Despite considerable efforts to study the relationship between insomnia and depression, there is minimal research investigating whether insomnia symptoms change over time during a course of antidepressant pharmacotherapy. This study investigated the course of insomnia symptoms during the acute treatment of major depressive disorder (MDD) using a secondary analysis of data from MDD patients (N = 180) who were treated with open-label escitalopram (10-20 mg/day) for 8-weeks. Montgomery-Asberg Depression Rating Scale without sleep item (modified-MADRS) assessed depression and Self-reported Quick Inventory Depressive Scale (QIDS-SR) measured subjective sleep-onset, mid-nocturnal, and early-morning insomnia throughout 8-weeks of treatment. Pittsburgh Sleep Quality Index (PSQI) was used to assess subjective sleep quality, duration, onset latency, and efficiency throughout 8-weeks of treatment. Remission of depression was defined as modified-MADRS ≤10 at week-8. Mixed model repeated measures (MMRMs) were conducted with remission status as an independent variable and each sleep variable as a dependent variable. MMRMs demonstrated that remitters had significantly lower QIDS-SR sleep-onset and mid-nocturnal insomnia scores as well as a significantly lower PSQI sleep quality score than non-remitters throughout 8-weeks of treatment. Monitoring subjective sleep-onset and mid-nocturnal insomnia during the course of treatment with serotonergic antidepressants may be useful for predicting acute remission of depression.

Insomnia, depression, and anxiety symptoms interact and individually impact functioning: A network and relative importance analysis in the context of insomnia

STUDY OBJECTIVES

Insomnia, depression, and anxiety show high rates of comorbidity and functional impairment. Transdiagnostic symptom interactions may be implicated in this comorbidity. This network analysis sought to assess how symptoms of insomnia, depression, and anxiety may interact and individually predict impairment across several domains for individuals with insomnia.

METHODS

Baseline psychometric data from a randomised controlled trial were analysed (N = 1711). A regularized partial correlation network was estimated from the symptom data. Centrality (symptom connectivity), community structure (symptom clustering), and bridging (inter-community connectivity) were assessed. The replicability of the network model was assessed via confirmatory analyses in a holdout sample. Separately, Shapley values were estimated to determine the relative importance of each symptom in predicting functioning (i.e., psychological wellbeing, psychosocial functioning, and physical health impairment).

RESULTS

The most connected nodes were uncontrollable worrying; trouble relaxing; and depressed mood/hopelessness. Five communities were identified with trouble relaxing identified as the bridge symptom between communities. The model showed good fit in the holdout sample. Low energy and depressive affect symptoms (feelings of failure/guilt; depressed mood/hopelessness; anhedonia) were key predictors in the relative importance analysis across multiple domains of impairment.

CONCLUSION

Trouble relaxing may be of clinical and transdiagnostic significance in the context of insomnia. In terms of how symptoms relate to functioning, it was clear that, while low energy and feelings of failure/guilt were prominent predictors, a range of symptoms are associated with functional impairment. Consideration of both symptoms and functional impairment across domains may be useful in determining targets for treatment.

CLINICAL TRIAL REGISTRATION

This is a secondary analysis of an original clinical trial.

TRIAL REGISTRATION NUMBER

ISRCTN60530898. Registry URL: https://www.isrctn.com/ISRCTN60530898.

Relationship of depression and sleep quality, diseases and general characteristics

BACKGROUND

Depression is the most common type of depressive disorder. The most common sleep disorder associated with depression is insomnia. Insomnia and depression are closely related.

AIM

To investigate the relationship of designed questionnaire items and depression, and analyze the related factors with depression.

METHODS

Questionnaire included Patient Health Questionnaire-9 (PHQ-9) and Pittsburgh sleep quality index (PSQI), 12 kinds of diseases, 8 general characteristics, and 20 insomnia characteristics, totally 56 items were filled out by 411 patients enrolled.

RESULTS

All the 9 items of PHQ-9, 6 components of PSQI (except sleep duration), education, living situation, exercise, years of insomnia, western medicine treatment, Chinese medicine treatment, psychotherapy, kinds of insomnia, treatment expected to treat insomnia, psychological counseling, habit of 1 h before bed, habit of lunch break, diagnosed depression, coronary heart disease, mental illness showed significant difference between without and with depression group. By univariate analysis and multivariate analysis. The odds ratio of education, exercise, kinds of insomnia, habit of 1 h before bed, diagnosed depression, coronary heart disease (P = 0.01) showed significant difference. Their odds ratios were 0.71 (0.55, 0.93), 2.09 (1.32, 3.31), 0.76 (0.63, 0.91), 0.89 (0.81, 0.98), 0.32 (0.17, 0.60), 0.43 (0.23, 0.79).

CONCLUSION

We demonstrated that education, exercise, kinds of insomnia, habit of 1 h before bed, diagnosed depression and coronary heart disease affect the depression.

Factors associated with insomnia among frontline nurses during COVID-19: a cross-sectional survey study

BACKGROUND

Research predominantly suggests that nurses are at high risk of developing psychopathology. The empirical data show that the occurrence rate of problem-related sleep quality among clinical nurses is high. Therefore, this study was conducted to address the lack of information on the relationship between the coronavirus disease 2019 (COVID-19) pandemic and insomnia.

METHODS

A convenience sample of nurses (n = 680) completed an online survey that included the Insomnia severity index, the COVID-19-related psychological distress scale, the general health questionnaire, neuroticism, dysfunctional beliefs, attitudes about sleep scale, and difficulties in emotion regulation scale.

RESULTS

The results showed that 35.8% (n = 253) of nurses were classified as individuals with moderate to severe clinical insomnia. The results showed that the psychological distress generated by COVID-19 predicted insomnia (β = .47, SE = 0.02, P < .001, t = 13.27, 95% CI 0.31-0.46). Additionally, the association is mediated by psychopathology vulnerabilities, emotion dysregulation, dysfunctional beliefs about sleep, and neuroticism. Moreover, female nurses exhibited higher levels of insomnia (Cohen's d = .37), neuroticism (Cohen's d = 30), psychopathology vulnerability (Cohen's d = .26), and COVID-19-related psychological distress (Cohen's d = .23).

CONCLUSION

The present study's findings help to explain how pandemic consequences can be associated with insomnia. Additionally, the findings make a significant contribution to better understanding the role of neuroticism, emotion dysregulation, beliefs, and psychopathology vulnerability in the development of insomnia among nurses. The findings suggest the potential influence of cognitive behavioral therapy for insomnia (CBT-I) and transdiagnostic integrated therapies that could be incorporated into therapeutic programs designed to develop as a way of inhibiting or preventing insomnia among clinical nurses.