What Sways People's Judgment of Sleep Quality? A Quantitative Choice-Making Study With Good and Poor Sleepers

Effects of Trazodone on Sleep: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVES

Sleep problems and insomnia are common, challenging to treat, and transcend specific diagnoses. Although trazodone is a popular choice, robust meta-analytic evidence is lacking. This systematic review and meta-analysis investigates the efficacy and safety of trazodone for sleep disturbances, reflecting recent updates in insomnia diagnosis and treatment.

METHODS

We searched Medline, Embase, APA PsycINFO, the Cochrane Central Register of Controlled Trials (CENTRAL), ClinicalTrials.gov, and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) up to 1 May 2024, for Randomized Controlled Trials (RCTs) comparing trazodone with placebo and reporting sleep-related outcomes. The minimum pharmacotherapy duration was 5 days. Included were all RCTs regardless of blinding (open-label or single- or double-blind), while quasi-randomized studies were excluded. The Cochrane Risk of Bias Tool for Randomized Trials assessed bias. Analyses used a random-effects model on an intention-to-treat (ITT) basis. Risk ratio (RR) was used for dichotomous outcomes and weighted mean difference (WMD) for continuous outcomes. When different units or scales were used, Hedge's adjusted g standardized mean difference (SMD) was calculated. Subgroup and preplanned sensitivity analyses explored heterogeneity and evaluated findings' strength and consistency.

RESULTS

In total, 44 RCTs with 3935 participants were included. Trazodone did not significantly impact subjective total sleep time (TST) [WMD = 0.73 min, 95% confidence interval (CI) - 24.62; 26.07, p = 0.96] but improved sleep quality (SQ) (SMD = - 0.58, 95% CI - 0.87; - 0.28, p < 0.01) and secondary outcomes. These included the number of nocturnal awakenings (SMD = - 0.57, 95% CI - 0.85; - 0.30], p < 0.01), nocturnal time awake after sleep onset (WMD = - 13.47 min, 95% CI - 23.09; - 3.86], p < 0.01), objective TST by polysomnography (WMD = 27.98 min, 95% CI 4.02; 51.95, p = 0.02), and sleep efficiency (WMD = 3.32, 95% CI 0.53; 1.57, p = 0.02). Tolerability issues included more dropouts owing to adverse effects (RR = 2.30, 95% CI 1.45; 3.64, p < 0.01), any sleep-related adverse effects (RR = 3.67, 95% CI 1.07; 12.47, p = 0.04), more adverse effects in general (RR = 1.18, 95% CI 1.03; 1.33, p = 0.02), and more sleep-related adverse effects (RR = 4.31, 95% CI 2.29; 8.13, p < 0.01).

CONCLUSION

Trazodone extends total sleep time but does not affect perceived sleep duration. It may improve sleep quality and continuity but has minor effects on sleep latency, efficiency, and daytime impairment. Trazodone is associated with adverse effects, necessitating a careful risk-benefit assessment. Limited data restrict generalizability, underscoring the need for more research.

REGISTRATION

PROSPERO registration number,CRD42022383121.

Associations Between Repetitive Negative Thinking and Objective and Subjective Sleep Health in Cognitively Healthy Older Adults

Objective

Poor sleep and high levels of repetitive negative thinking (RNT), including future-directed (ie, worry) and past-directed (ie, brooding) negative thoughts, have been associated with markers of dementia risk. The relationship between RNT and sleep health in older adults is unknown. This study aimed to investigate this association and its specificities including multiple dimensions of objective and subjective sleep.

Methods

This study used a cross sectional quantitative design with baseline data from 127 cognitively healthy older adults (mean age 69.4 ± 3.8 years; 63% female) who took part in the Age-Well clinical trial, France. RNT (ie, worry and brooding) levels were measured using the Penn State Worry Questionnaire and the Rumination Response Scale (brooding subscale). Polysomnography was used to assess sleep objectively, and the Pittsburgh Sleep Quality Index and the St. Mary's Hospital Sleep Questionnaire were used to measure sleep subjectively. In primary analyses the associations between RNT and sleep (ie, objective sleep duration, fragmentation and efficiency and subjective sleep disturbance) were assessed via adjusted regressions.

Results

Higher levels of RNT were associated with poorer objective sleep efficiency (worry: β=-0.32, p<0.001; brooding: β=-0.26, p=0.002), but not objective sleep duration, fragmentation, or subjective sleep disturbance. Additional analyses, however, revealed differences in levels of worry between those with short, compared with typical and long objective sleep durations (p < 0.05).

Conclusion

In cognitively healthy older adults, RNT was associated with sleep characteristics that have been implicated in increased dementia risk. It will take additional research to ascertain the causal link between RNT and sleep characteristics and how they ultimately relate to the risk of developing dementia.

Covariance patterns between sleep health domains and distributed intrinsic functional connectivity

Sleep health is both conceptually and operationally a composite concept containing multiple domains of sleep. In line with this, high dependence and interaction across different domains of sleep health encourage a transition in sleep health research from categorical to dimensional approaches that integrate neuroscience and sleep health. Here, we seek to identify the covariance patterns between multiple sleep health domains and distributed intrinsic functional connectivity by applying a multivariate approach (partial least squares). This multivariate analysis reveals a composite sleep health dimension co-varying with connectivity patterns involving the attentional and thalamic networks and which appear relevant at the neuromolecular level. These findings are further replicated and generalized to several unseen independent datasets. Critically, the identified sleep-health related connectome shows diagnostic potential for insomnia disorder. These results together delineate a potential brain connectome biomarker for sleep health with high potential for clinical translation.

Does weather anomaly still affect the emerging stock market under the unexpected event? New evidence from the COVID-19 pandemic

This paper examines the impact of COVID-19 nationwide lockdown on the relationship between weather anomaly and the Vietnam stock market - a fast-growing emerging market. The paper employs event study methodology to compute the cumulative abnormal return of stocks during the pandemic, and the Holt-Winters Exponential Smoothing model to build the formula for weather anomaly for weather variables. In addition, a t-test is performed to examine the statistical significance of weather variables, as well as the impact that the lockdown order had on stock performance. Cross-sectional analysis by Ordinary Least Squares regression is also applied for estimating the relationship between weather and stock market performance. The finding shows that prior to the COVID-19 lockdown, all of the risk and return indicators, with the exception of idiosyncratic risk, are affected by temperature. After the lockdown order was withdrawn, temperature is only correlated with cumulative real returns and cumulative abnormal returns. Meanwhile, air pressure only appears to have an influence on cumulative abnormal returns after the lockdown, yet being the only meteorological factor that could impact the stock market during the lockdown. Generally, the larger the weather anomaly, the worse the returns and the higher the risks. The paper gives recommendations for listed companies and authorities to have better performance while engaging in and regulating the stock markets. Moreover, the results can be used as a reference for the investing community to incorporate meteorological factors into their analysis.

Judgement of sleep quality of the previous night changes as the day unfolds: A prospective experience sampling study

How we form judgements of sleep quality is poorly understood. Emerging literature suggests that people infer their sleep quality based on multiple sources of accessible information, raising the possibility that sleep quality judgement may evolve as new relevant information becomes available. This study investigated whether people's rating of sleep quality of the night before changes throughout the following day, and what post-sleep factors are associated with the changes. A prospective experience sampling study of 119 healthy young adults, who completed eight short online surveys interspaced 2 hr apart from 08:00 hours to 22:00 hours. Each survey asked the participants to report total sleep time and sleep quality of the night before, and to provide ratings of current mood, physical and social activity, and pain/discomfort. A memory test was added to the final survey of the day to measure the participants' recall of their first survey responses to sleep quality, as well as total sleep time and mood. The absolute majority (91.1%) of the participants had one or more change in their sleep quality rating across the eight surveys. A similar percentage of change was found for mood rating (100%) but not total sleep time report (20.5%). Memory test in the final survey revealed that the within-person variations in sleep quality rating were not simply memory errors. Instead, positive physical activity post-sleep predicted increases in sleep quality rating. Therefore, judgement of sleep quality of the night before changes as the day unfolds, and post-sleep information can be used by people to infer their sleep quality.

How many hours do you sleep? A comparison of subjective and objective sleep duration measures in a sample of insomnia patients and good sleepers

Our objective was to assess the agreement and linear relationships amongst multiple measures of sleep duration in a sample of patients with insomnia disorder and good sleeper controls. We retrospectively analysed data from 123 patients with insomnia disorder and 123 age- and gender-matched good sleeper controls who completed a simple subjective habitual sleep duration question (Pittsburgh Sleep Quality Index), a sleep diary (5-14 days), 2 nights of polysomnography, and two corresponding morning subjective estimates of sleep duration. Descriptive statistics, linear regression analyses and Bland-Altman plots were used to describe the relationship and (dis)agreement between sleep duration measures. Relationships between polysomnography and the simple question as well as between polysomnography and sleep diary were weak to non-existent. Subjective measures and polysomnography did not agree. Sleep duration measured with the Pittsburgh Sleep Quality Index or sleep diary was about 2 hr above or up to 4 hr below polysomnography-measured sleep duration. Patients with insomnia disorder, on average, reported shorter sleep duration compared with polysomnography, while good sleeper controls, on average, reported longer sleep duration compared with polysomnography. The results suggest that subjective and objective measures apparently capture different aspects of sleep, even when nominally addressing the same value (sleep duration). They disagree in both patients with insomnia disorder and good sleeper controls, but in different directions. Studies assessing sleep duration should take into account both the investigated population and the assessment method when interpreting results. Future studies should continue to investigate possible psychological and physiological correlates of sleep (mis)perception.

Which Is More Important for Health: Sleep Quantity or Sleep Quality?

Sleep is one of the basic physiological processes for human survival. Both sleep quantity and sleep quality are fundamental components of sleep. This review looks at both sleep quantity and sleep quality, considering how to manage the complex but probably unavoidable physiological phenomenon of sleep. The need for sleep has marked variations between individuals, in addition to the effects of variable conditions. Studies on sleep quality started later than those on sleep quantity, beginning in 1989 when Ford and Kamerow revealed that insomnia increases the risk of psychiatric disorders. According to the nationwide research team on the quality of sleep (19FA0901), sleep quality is superior to sleep quantity as an index for assessing sleep, and that restfulness obtained through sleep is a useful index for assessing sleep quality. We should pay more attention to obtaining sleep of good quality (restfulness, no sleepiness, no need for more sleep, sufficient objective sleep depth, etc.), although there have not been enough studies on the associations between sleep quality and health or disorders in children and adolescents. Further studies using the deviation from an individual’s optimal sleep quantity may show us another aspect of the effects of sleep quantity on various life issues.

Physical Activity and Quality of Sleep in Patients with End-Stage Renal Disease on Hemodialysis: A Preliminary Report

Chronic kidney disease significantly impairs patients' daily lives and worsens their quality of life. The aim of this study was to investigate the physical activity and quality of sleep, during three days (previous day of dialysis, on the day of dialysis and after day of dialysis), in patients with end-stage renal on hemodialysis. 12 hemodialysis patients were included in our study, answered the Pittsburgh Sleep Quality Index (PSQI) questionnaire, and for each patient were used a smart bracelet for three days (day-pre- and posthemodialysis and day at hemodialysis) to record daily physical activity (steps, distance) and estimate the quality of sleep. Results showed differences between three days average of steps and distance and PSQI parameters “…engaging in social activity?” (steps, p = 0.006, distance, p = 0.006) and “…enthusiasm to get things done?” (steps, p = 0.029, distance, p = 0.030). Our study suggests interrelationship between sleep quality and physical activity.

Brain mechanisms of insomnia: new perspectives on causes and consequences

While insomnia is the second most common mental disorder, progress in our understanding of underlying neurobiological mechanisms has been limited. The present review addresses the definition and prevalence of insomnia and explores its subjective and objective characteristics across the 24-hour day. Subsequently, the review extensively addresses how the vulnerability to develop insomnia is affected by genetic variants, early life stress, major life events, and brain structure and function. Further supported by the clear mental health risks conveyed by insomnia, the integrated findings suggest that the vulnerability to develop insomnia could rather be found in brain circuits regulating emotion and arousal than in circuits involved in circadian and homeostatic sleep regulation. Finally, a testable model is presented. The model proposes that in people with a vulnerability to develop insomnia, the locus coeruleus is more sensitive to-or receives more input from-the salience network and related circuits, even during rapid eye movement sleep, when it should normally be sound asleep. This vulnerability may ignite a downward spiral of insufficient overnight adaptation to distress, resulting in accumulating hyperarousal, which, in turn, impedes restful sleep and moreover increases the risk of other mental health adversity. Sensitized brain circuits are likely to be subjectively experienced as "sleeping with one eye open". The proposed model opens up the possibility for novel intervention studies and animal studies, thus accelerating the ignition of a neuroscience of insomnia, which is direly needed for better treatment.

Identifying category representations for complex stimuli using discrete Markov chain Monte Carlo with people

With the explosion of “big data,” digital repositories of texts and images are growing rapidly. These datasets present new opportunities for psychological research, but they require new methodologies before researchers can use these datasets to yield insights into human cognition. We present a new method that allows psychological researchers to take advantage of text and image databases: a procedure for measuring human categorical representations over large datasets of items, such as arbitrary words or pictures. We call this method discrete Markov chain Monte Carlo with people (d-MCMCP). We illustrate our method by evaluating the following categories over datasets: emotions as represented by facial images, moral concepts as represented by relevant words, and seasons as represented by images drawn from large online databases. Three experiments demonstrate that d-MCMCP is powerful and flexible enough to work with complex, naturalistic stimuli drawn from large online databases.

Conceptions of sleep experience: a layman perspective

OBJECTIVE

To date, there is little information on how lay people understand and discuss sleep in the context of daily life. Efforts to conceptualize sleep quality have been largely driven by clinical considerations of sleep disorders. As such, they are not necessarily of how normal sleepers without clinical expertise conceptualize sleep quality. A phenomenological approach was taken to understand the essence of the sleep experience and the concepts held by lay people without sleep disorders. A sentence completion questionnaire was developed and administered to a quota sample of 64 respondents who were selected aiming for sufficient representation of different gender, ages, and education levels.

RESULTS

Significant sentences and meaningful units were derived inductively, resulting in a classification of nine categories. The major facets of sleep experience of lay people were 'daytime functioning', 'interruptions during the night' and 'before bed state'. This implies that the experienced sleep quality is not only depending on the progress of the night. These results can guide future research to provide suitable psychometric measures for normal sleepers, as well as the design of sleep data visualization applications in the context of health self-monitoring.