Insomnia disorder, characterized by chronic sleep disruption, often co-occurs with maladaptive emotional memory processing. However, much remains unknown regarding the evolution of emotional memories and their neural representations over time among individuals with insomnia disorder.

We examined the electroencephalographic (EEG) activities during emotional memory encoding, post-encoding sleep, and multiple retrieval phases – including immediate post-encoding, post-sleep, and a 7-day delayed retrieval – among 34 participants with insomnia disorder and 35 healthy control participants.

Healthy controls exhibited adaptive dissipation of emotional memory: memory declined over time, accompanied by reduced subjective feelings toward negative memories. In contrast, participants with insomnia exhibited impaired dissipation: they retained both the emotional content and affective tone of the memories, with diminished time-dependent declines in memory and affect. Beyond behavioral performance, only participants with insomnia maintained stable neural representations of emotion over time, a pattern absent in healthy controls. Additionally, during the post-encoding sleep, slow-wave sleep (SWS), and rapid eye movement (REM) sleep durations predicted the adaptive dissipation of emotional memory over time, but only among healthy participants.

These findings highlight abnormalities in emotional memory processing among individuals with insomnia disorder and underscore the important function of SWS and REM sleep in facilitating adaptive emotional memory processing.

Cognitive behavioural therapy for fatigue (CBT-F) and insomnia (CBT-I) are effective therapies. Little is known on their effectiveness when severe fatigue and insomnia co-occur.

This observational study investigated whether the co-occurrence of fatigue and insomnia influences the outcomes of CBT-F and CBT-I. Furthermore, it was determined if changes in fatigue and insomnia symptoms are associated, and how often the co-occurring symptom persists after CBT.

Patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS, n = 241) received CBT-F and patients with insomnia disorder (n = 162) received CBT-I. Outcomes were fatigue severity assessed with the subscale of the Checklist Individual Strength (CIS-fat) and insomnia severity assessed with the Insomnia Severity Index (ISI). In each cohort, treatment outcomes of the subgroups with and without co-occurring symptoms were compared using ANCOVA. The association between changes in insomnia and fatigue severity were determined using Pearson’s correlation coefficient.

There were no differences in treatment outcomes between patients with and without co-occurring fatigue and insomnia (CBT-F: mean difference (95% CI) in CIS-fat-score 0.80 (−2.50–4.11), p = 0.63, d = 0.06; CBT-I: mean difference (95% CI) in ISI-score 0.26 (−1.83–2.34), p = 0.80, d = 0.05). Changes in severity of both symptoms were associated (CBT-F: r = 0.30, p < 0.001, CBT-I: r = 0.50, p < 0.001). Among patients no longer severely fatigued after CBT-F, 31% still reported insomnia; of those without clinical insomnia after CBT-I, 24% remained severely fatigued.

CBT-F and CBT-I maintain their effectiveness when severe fatigue and insomnia co-occur. Changes in severity of both symptoms after CBT are associated, but the co-occurring symptom can persist after successfully treating the target symptom.

Adenoid hypertrophy contributes to nasal obstruction and obstructive sleep disorders in children, but can be difficult to assess. This study examines whether inferior turbinate hypertrophy can predict adenoid hypertrophy severity in children with obstructive sleep disorders.

This retrospective cohort study included children (0–18 years) with a diagnosis of obstructive sleep-disordered breathing or obstructive sleep apnoea who underwent drug-induced sleep endoscopy. Analyses explored demographic, clinical and endoscopic associations with adenoid hypertrophy.

A total of 269 children were included. Separate univariate analyses showed that older age and greater inferior turbinate hypertrophy predicted greater adenoid hypertrophy (p < 0.05). However, in multivariate ordered logistic regression, only inferior turbinate hypertrophy remained significant (p < 0.01), while age did not (p = 0.11).

These findings suggest inferior turbinate hypertrophy may serve as a proxy for adenoid hypertrophy, aiding clinicians in assessment and guiding further evaluation or intervention.

Physical activity is a known protective factor against depression but physical activity competes with other time-consuming behaviors that may increase depression risk. This study investigates the association between time spent in various movement-related activities and incident major depression, with a particular focus on the effects of replacing TV-watching time with other activities. Additionally, we explored whether the impact of substituting TV-watching differs across age groups.

A population-based cohort study (Lifelines) with four-year follow-up, including 65,454 non-depressed adults (18+). Participants self-reported time spent in active commuting, leisure, sports, household, work or school physical-related activities, TV-watching, and sleep. Major depressive disorder was assessed using the Mini International Neuropsychiatric Interview. Compositional isotemporal data analysis was performed to analyze the effect of reallocating time in TV-watching with other activities adjusting for potential confounders. Interactions with age groups were also examined.

The incidence of major depressive disorder was 2.4%. Reallocating TV-watching time to any other physical activity or sleep reduced this risk in middle-aged adults. In older adults, only substituting TV-watching time with sports reduced the probability of becoming depressed. No significant reduction in probabilities for incident depression was found in younger adults.

Replacing TV-watching time with other activities, including sleep, may serve as a preventive strategy against depressive disorder in middle-aged adults, while only the substitution with sports seems beneficial for older adults. Future research should aim to identify other activities, particularly in younger adults, that may prevent depression.

Sleep problems are common among people with psychosis. Research suggests poor sleep is causally related to psychosis, anxiety and depression.

This review investigates the effectiveness and acceptability of cognitive–behavioural therapy (CBT) in targeting sleep problems in people with and at risk of psychosis.

Four databases were searched in line with PRISMA guidelines. Eligible studies either evaluated (a) CBT targeting sleep problems in people with or at risk of psychosis, or (b) subjective experiences of this treatment. Articles not published in peer-review journals were excluded. Treatment effectiveness was investigated for sleep, psychosis and other clinical outcomes. Acceptability was evaluated using qualitative data, drop-out rates, adverse events and relevant questionnaires. Adaptations to standard treatment protocols were described. Research quality was appraised using Cochrane Risk of Bias tools for randomised and non-randomised trials, and a checklist was developed for qualitative papers.

Of the 975 records identified, 14 were eligible. The most common CBT target was insomnia. Treatment protocols were typically adapted by omitting sleep restriction. Large effect sizes were reported for sleep outcomes; however, effects for other clinical outcomes were less clear. Qualitative data and acceptability outcomes suggest that treatment was received positively by participants.

CBT is an effective and acceptable treatment for sleep problems in people with and at risk of psychosis. However, our conclusions are limited by few good-quality studies and small samples. Further gold-standard research is required to inform evidence-based guidelines.

Sleep problems are common in psychotic disorders and are associated with worse quality of life and disease prognosis. Genome-wide association studies (GWAS) have revealed genetic influences for schizophrenia and sleep, but polygenic scores (PGSs) for sleep traits have not been evaluated systematically in patients with psychotic disorders.

This study investigated the associations between PGSs for sleep traits (insomnia, PGSINS; sleep duration, PGSSD; short sleep duration, PGSSS; long sleep duration; PGSLS), diurnal preference (eveningness, PGSME), and schizophrenia (PGSSZ) with clinical features of psychotic disorders in the Finnish SUPER study comprising 8,232 patients with psychotic disorders. The measures included self-reported sleep and well-being, cognitive assessments, clozapine use, and functional outcomes. Using FinnGen data of 356,077 individuals, we analyzed the distributions of PGSs in psychotic and bipolar disorders and the general population.

PGSINS associated with more sleep problems and worse well-being (e.g. worse health-related quality of life [β = −0.07, CI = −0.09, −0.05, p < .001]). High PGSSZ is associated with better sleep quality, worse clinical outcomes, and performance in cognitive tests (e.g. more errors in paired-associated learning [β = 0.07, CI = 0.04, 0.09, p < .001]). PGSINS was higher in affective psychotic and bipolar disorders, while PGSSD and PGSME were higher in schizophrenia as compared with individuals with no psychiatric disorders.

Genetic risks for sleep and diurnal preference vary between non-affective psychosis, affective psychosis, and the general population. The findings in this study emphasize the heterogeneity in genetic etiology of the objective features of disease severity and the more subjective measures related to well-being and self-reported measures of sleep.

Unhealthy lifestyle behaviors are prevalent among people with mental illness (MI), affecting their physical and mental health. Most research has focused on the isolated effects of lifestyle behaviors, leaving the interconnectedness between these behaviors and health outcomes unexplored. This study aimed to examine these relationships and identify the most strongly connected lifestyle behavior or health outcome within a network.

We conducted a cross-sectional study with 423 inpatients with MI, receiving care as usual. Lifestyle behaviors, physical and mental health outcomes were assessed through questionnaires and routine data. A Gaussian Graphical Model was estimated, and strength centrality was calculated to identify the most influential nodes.

Mean age was 55.5 years, 42% were female, and 41% were diagnosed with schizophrenia. Psychological and physical quality of life (QoL), nighttime sleep problems, and overall sleep quality were the most strongly connected nodes. Sleep was strongly associated with physical QoL. Furthermore, there were negative associations between healthy food intake and cholesterol ratio, and positive associations between daily doses of antipsychotics and length of hospital stay. Node strength was stable (CS(cor = 0.7) = 0.75). No clear pattern emerged among other lifestyle behaviors and health outcomes.

This study offers insights into the interrelatedness of lifestyle behaviors and health outcomes. Addressing sleep problems could enhance QoL and potentially influence other health outcomes. Psychological and physical QoL were also strongly associated, emphasizing the importance of perceived well-being in health outcomes. Future research could explore causal pathways to identify treatment targets to improve care.