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Sleep and Psychiatric Disorders: A Meta-analysis
Abstract
We reviewed the literature on sleep in psychiatric disorders and evaluated the data by meta-analysis, a statistical method designed to combine data from different studies. A total of 177 studies with data from 7151 patients and controls were reviewed. Most psychiatric groups showed significantly reduced sleep efficiency and total sleep time, accounted for by decrements in non-rapid eye movement sleep. Rapid eye movement sleep time was relatively preserved in all groups, and percentage of rapid eye movement sleep was increased in affective disorders. Reduction in rapid eye movement sleep latency was seen in affective disorders but occurred in other categories as well. Although no single sleep variable appeared to have absolute specificity for any particular psychiatric disorder, patterns of sleep disturbances associated with categories of psychiatric illnesses were observed. Overall, findings for patients with affective disorders differed most frequently and significantly from those for normal controls.
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“It should be emphasized that this evidence may afford insights for the translational research since that some dream and/or REM abnormalities represent the core symptoms of psychiatric and sleep disorders (Benca et al., 1992, 1997; Harvey, 2008; Walker and van der Helm, 2009).”
From The Functional Role of Dreaming in Emotional Processes (2019) · cites this paper as Benca et al., 1992
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“However, decades of research in the general population have shown that preventing conditions such as obesity and metabolic syndrome from ever arising is considerably more efficient than attempting to reverse their long-term consequences.134”
From The Lancet Psychiatry Commission: a blueprint for protecting physical health in people with mental illness (2019) · cites this paper as [134]
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“the analysis of sleep data showed that later sleep midpoint and offset time were associated with more severe depressive symptoms”
From Digital Biomarkers for Depression Screening With Wearable Devices: Cross-sectional Study With Machine Learning Modeling (2021) · cites this paper as [20]
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Metadata
- Authors
- Benca, R. M.
- Affiliations
- University of Chicago (US)
- Corresponding author
- Benca, Ruth M.
- Venue
- Archives of General Psychiatry
- Publisher
- American Medical Association (AMA)
- Published
- 1992-08-01
- Volume
- 49
- Issue
- 8
- Pages
- 651
- ISSN
- 0003-990X (ISSN-L)
- OpenAlex
- W2128964866
- Cited by
- 1,468
- References
- 198
- Citations by year
- 2026: 17 · 2025: 33 · 2024: 36 · 2023: 36 · 2022: 44 · 2021: 46 · 2020: 49 · 2019: 50 · 2018: 40 · 2017: 51 · 2016: 57 · 2015: 58 · 2014: 49 · 2013: 60 · 2012: 76
- FWCI
- 36.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Archives of General Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5t01mh019051-02)
- National Institute of Mental Health (MH 19051, MH 38338, MH30914)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Life Sciences › Neuroscience › Cognitive Neuroscience › Sleep and Wakefulness Research
- Health Sciences › Medicine › Physiology (medical) › Obstructive Sleep Apnea Research
- Keywords
- sleep, mental illness, sleep efficiency, total sleep time, REM sleep, REM latency, NREM sleep, mood disorders, sleep disorders, diagnostic specificity
- MeSH terms
- Adult, Age Factors, Mental Disorders, Depressive Disorder, Diagnosis, Differential, Electroencephalography, Female, Humans, Male, Middle Aged, Narcolepsy, Schizophrenia, Sleep, Sleep Wake Disorders, Sleep, REM, Meta-Analysis as Topic
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