Sleep quality and its relationship to mental health, physical health and health behaviours among young adults with serious mental illness enrolled in a lifestyle intervention trial

Assessing quality of life and readmission rates among women in psychiatric care: a mixed-method study

BACKGROUND

The mental health of women is significantly shaped by gender-related issues stemming from social and cultural disparities, which intensify female susceptibility and culminate in mental disorders. Despite a plethora of studies delineating the effects of gender on mental health, there exists a conspicuous deficiency in research investigating women's viewpoints regarding their own experiences of rehospitalization. Therefore, the principal aim of our investigation was to assess the relationship between rehospitalization and the Quality of Life (QoL) among women undergoing treatment at a psychiatric care institution.

METHODS

We employed a mixed-methods research framework to examine the QoL and the variables pertinent to the readmission of twenty women from a public psychiatric hospital situated in the interior region of Espírito Santo, Brazil. The quantitative aspect evaluated QoL using the scores and analytical guidelines established by the World Health Organization Quality of Life Brief Version (WHOQOL-BREF) questionnaire. The results from this phase were subjected to descriptive statistical analysis. The qualitative data were derived from semi-structured interviews aimed at exploring the factors associated with readmission; the insights obtained underwent narrative analysis. This study was approved by the ethics committee. The interviews were only carried out after the patients were medically discharged.

RESULTS

Women who are readmitted do not have their problems viewed objectively and, consequently, are not having them resolved, as the factors contributing to the mental health of these patients are complex and span across the domains of physical, psychological, social relationships, and environment. There is a notably low overall QoL (M = 47.78) in the study population, with particularly poor scores in the environment (44.49), psychological (47.71) and social relationships (48.54) domains. These findings align with participants' testimonies, which emphasize the role of unstable living conditions, financial insecurity, social isolation, and family dysfunction in their ongoing struggles with mental health.

CONCLUSIONS

The mental health outcomes of women are shaped by a multitude of factors, encompassing social support, access to resources, and individual coping strategies. Approaches to mental health care that are humanized and that address these factors are imperative for enhancing QoL and mitigating readmission rates.

Role of Sleep in Depressive Disorders and the Potential Therapeutic Role of Short-Term Sleep Deprivation and Light Therapy: A Review

Depression affects about 280 million people globally and is marked by persistent sadness and impaired daily functioning. Sleep disturbances are prevalent in major depressive disorder, affecting roughly 90% of patients, and are linked to the severity and progression of depression. This review emphasizes the critical role of sleep in depressive disorders and evaluates the alternative treatments bright light therapy and sleep deprivation. Sleep disturbances are not only symptoms but also mediators in the relationship between depression and other conditions, such as anxiety, chronic inflammation, emotional dysregulation, and cognitive decline. Effective management of depressive disorders must address these sleep issues. Bright light therapy, which uses artificial light to mimic natural sunlight, is effective for treating seasonal affective disorder and non-seasonal major depressive disorder. It is well tolerated, can be used alone or with antidepressants, and often improves both mood and sleep quality. In contrast, sleep deprivation, which involves enforced wakefulness, can provide rapid symptom relief. However, its effects are generally short-lived, and there is a risk of inducing mania in patients with bipolar disorder. In conclusion, sleep significantly impacts the severity and progression of depressive disorders. Bright light therapy and sleep deprivation offer promising alternatives to conventional treatments. The aim of this review is to underscore the importance of sleep in depression and advocate for the consideration of these alternative treatment methods to improve patient outcomes.

(Cost-)effectiveness and implementation of a combined lifestyle intervention for outpatients with severe mental illness (GOAL!): a hybrid quasi-experimental study protocol

BACKGROUND

People with severe mental illness (SMI) face not only impaired mental health, but also a greater risk of physical comorbidities and a shorter life expectancy compared to the general population. A poor lifestyle plays a substantial role in this disparity. Combined Lifestyle Interventions targeting multiple lifestyle behaviors can improve mental and physical health, and quality of life. However, there is currently no appropriate structural support for people with SMI in outpatient care in the Netherlands. The Combined Lifestyle Intervention for Outpatients with SMI (GOAL!) is developed to address this gap. This study examines the (cost-)effectiveness and implementation of GOAL!.

METHODS

In a type 1 hybrid quasi-experimental study with a mixed-method matched design, GOAL! participants (N = 50) are compared to people receiving care as usual (N = 50). The GOAL! program includes group and individual sessions, given by allied health professionals, over a period of two years. The first year starts with a 3-month intensive course on physical activity and nutrition, followed by 9 months of aftercare covering various lifestyle topics tailored to the group's needs. There is close collaboration with local stakeholders to facilitate transfer to the community setting. The second year focuses on maintaining established activities in one's daily living environment. Our primary outcome will be the change in physical activity, comparing GOAL! participants to those receiving care as usual. Secondary outcomes are changes in other lifestyle behaviors, physical health, mental well-being, and healthcare and societal costs. Additionally, achieving lifestyle-related goals, adverse effects, and barriers and facilitators to implementation are examined. Measurements are obtained at start (T0), and after 3 (T1), 12 (T2) and 24 months (T3).

DISCUSSION

This study investigates the effects of GOAL! on lifestyle behaviors, health outcomes, implementation factors and cost-effectiveness after two years, aiming to offer valuable insights into the effectiveness and implementation outcomes of lifestyle interventions for outpatients with SMI.

TRIAL REGISTRATION

ClinicalTrials.gov (Identifier: NCT05600205). Prospectively registered on October 26, 2022.

The Relationship between Lifestyle Behaviors and Mental Illness in Women in College

Women, particularly those in college, have the highest prevalence of any mental illness (MI), which negatively impacts social connection, academic performance, and health. Research into alternative treatment methods suggests that lifestyle behaviors are safer and more effective than medication at reducing MI symptoms. This study explores the relationship between lifestyle behaviors and MI in college women through an online survey. The survey included a food frequency questionnaire (Diet History Questionnaire II) and questions about lifestyle behaviors, symptoms of MI, and sociodemographic information. Diet quality was calculated using the Healthy Eating Index (HEI), and MI was assessed using the Depression, Anxiety, and Stress Scale-21. Independent sample t-tests, ANOVA, and chi-square analyses were conducted. A total of 222 women completed the survey. Overall, diet quality was poor, with a mean HEI of 62.6 ± 10.4. No significant differences or associations were found between MI groups for total HEI score, sleep, or tobacco use. However, alcohol use was significantly associated with MI (p = 0.049). Individuals with fewer concurrent unhealthy lifestyle behaviors had less severe symptoms of depression (p = 0.009) and anxiety (p < 0.001) compared to those with more unhealthy lifestyle behaviors. In this study, alcohol use was the only independent lifestyle behavior associated with symptoms of MI. We also found an association between the number of concurrent unhealthy lifestyle behaviors and depression and anxiety symptoms. Future research should explore the benefits of a healthy lifestyle on MI in a more diverse sample of women.

A genome-wide association study identifies candidate genes for sleep disturbances in depressed individuals

OBJECTIVE

This study aimed to identify candidate loci and genes related to sleep disturbances in depressed individuals and clarify the co-occurrence of sleep disturbances and depression from the genetic perspective.

METHODS

The study subjects (including 58,256 self-reported depressed individuals and 6,576 participants with PHQ-9 score ≥ 10, respectively) were collected from the UK Biobank, which were determined based on the Patient Health Questionnaire (PHQ-9) and self-reported depression status, respectively. Sleep related traits included chronotype, insomnia, snoring and daytime dozing. Genome-wide association studies (GWASs) of sleep related traits in depressed individuals were conducted by PLINK 2.0 adjusting age, sex, Townsend deprivation index and 10 principal components as covariates. The CAUSALdb database was used to explore the mental traits associated with the candidate genes identified by the GWAS.

RESULTS

GWAS detected 15 loci significantly associated with chronotype in the subjects with self-reported depression, such as rs12736689 at RNASEL (P = 1.00 × 10- 09), rs509476 at RGS16 (P = 1.58 × 10- 09) and rs1006751 at RFX4 (P = 1.54 × 10- 08). 9 candidate loci were identified in the subjects with PHQ-9 ≥ 10, of which 2 loci were associated with insomnia such as rs115379847 at EVC2 (P = 3.50 × 10- 08), and 7 loci were associated with daytime dozing, such as rs140876133 at SMYD3 (P = 3.88 × 10- 08) and rs139156969 at ROBO2 (P = 3.58 × 10- 08). Multiple identified genes, such as RNASEL, RGS16, RFX4 and ROBO2 were reported to be associated with chronotype, depression or cognition in previous studies.

CONCLUSION

Our study identified several candidate genes related to sleep disturbances in depressed individuals, which provided new clues for understanding the biological mechanism underlying the co-occurrence of depression and sleep disorders.

Associations Between Workplace Violence and Mental Health Among Chinese Health Technicians: A Moderated Mediation Analysis of Sleep Quality and Physical Activity

Background

Workplace violence (WPV) had always been the focus of attention in all walks of lives, especially in the health fields. Previous studies had shown it adversely affected mental health for healthcare workers. In addition, both sleep quality and physical activity were supported to have impact on mental health. However, the mechanism of sleep quality and physical activity influence the association between WPV and mental health had not been explored, so the purpose of this paper was to explore this mechanistic link among workplace violence, sleep quality, physical activity, and mental health in Chinese health technicians.

Methods

Cross-sectional study was conducted in 3 cities of China, totally 3426 valid questionnaires were collected. WPV, physical activity, and social-demographic variables were evaluated. The Pittsburgh Sleep Quality Index and the Kessler Psychological Distress Scale were used to measure sleep quality and mental health. Descriptive analysis, univariate analysis, Pearson correlation, and moderated mediation analysis were used to estimate prevalence of WPV, association between WPV and mental health, and the role of sleep quality and physical activity on association between WPV and mental health.

Results

The prevalence of WPV was 52.2% among Chinese health technicians. After controlling social-demographic and work-related variables, sleep quality partially mediated the effect of WPV on mental health (indirect effect=0.829). Physical activity moderated the relationship between WPV and sleep quality (β=0.235, p=0.013), but not find the moderating role between WPV and mental health (β=0.140, p=0.474), and between sleep quality and mental health (β=0.018, p=0.550).

Conclusion

The rate of WPV among health technicians remained at an alarming level. Sleep quality and physical activity could mitigate the adverse effect of WPV on mental health. In the future, we could improve sleep quality and encourage health technicians to engage physical activity to decrease the negative effect of WPV on mental health.

The relationship between social jetlag and subjective sleep quality: differences in young and middle-aged workers

Social jetlag is a recent problem that is associated with a wide range of issues in the context of modern life. However, differences in the effects of social jetlag on sleep quality between young and middle-aged workers remain unclear. Accordingly, we aimed to examine the different effects of social jetlag on sleep quality in young (20-39 years) and middle-aged (40-59 years) workers from one factory. We included 106 male full-time workers (average age: 35.8 ± 11.5 years) who worked at the Kobe Factory of Fuji Electric Co., Ltd. Social jetlag was evaluated using the Munich ChronoType Questionnaire Japanese Version. Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index Japanese Version. Chronotype was determined using the Morningness-Eveningness Questionnaire Japanese Version (MEQ), while the health-related quality-of-life was evaluated using a revised version of the MOS 36-Item Short-Form Survey. Furthermore, we examined factors related to sleep quality in each age group using multiple regression analysis. Subjective sleep quality in the analysis set was poor; moreover, 39.4% of the participants had social jetlag for ≥ 1 h. Compared with middle-aged workers, young workers showed significantly longer and lower social jetlag and MEQ scores, respectively. Multiple regression analysis revealed that mental health and social jet lag were significantly associated with sleep quality in young participants. Contrastingly, social jetlag was not associated with sleep quality in middle-aged workers. Our findings demonstrate the importance of considering the effects of age-based factors on sleep quality.

Sleep health among people with severe mental ill health during the COVID-19 pandemic: Results from a linked UK population cohort study

Objectives

Sleep problems are a transdiagnostic feature of nearly all psychiatric conditions, and a strong risk factor for initial and recurrent episodes. However, people with severe mental ill health (SMI) are often excluded from general population surveys, and as such the extent and associates of poor sleep in this population are less well understood. This study explores sleep health in an SMI sample during the COVID-19 pandemic, using multiple regression to identify risk factors, including daily routine, wellbeing and demographics.

Methods

An existing cohort of people with an SMI diagnosis were sampled. Participants were invited to complete a self-report survey about their health and the impacts of COVID-19 and associated public health measures. Sleep duration, efficiency, and quality were measured using items from the Pittsburgh Sleep Quality Index (PSQI).

Results

Two hundred forty-nine adults (aged 21-84 years) completed the survey. Mean sleep duration and efficiency were similar to general population estimates, at 7 h 19 min and 78%, respectively. However, 43% reported "bad" sleep quality that was associated with being younger in age as well as disturbed routine and declined wellbeing. Indeed, 37% reported a disturbed routine during the pandemic.

Conclusions

High estimates of perceived poor sleep quality in the SMI population align with previous findings. Supporting people with SMI to maintain routine regularity may work to protect sleep quality and wellbeing. Future research should more closely examine sleep health in people with SMI, using accessible and scalable measures of objective and subjective sleep, examining longitudinal trends.