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Meta-Analysis
. 2025 Feb 10;28(1):e301337.
doi: 10.1136/bmjment-2024-301337.

Digital sleep phenotype and wrist actigraphy in individuals at clinical high risk for psychosis and people with schizophrenia spectrum disorders: a systematic review and meta-analysis

Affiliations
Meta-Analysis

Digital sleep phenotype and wrist actigraphy in individuals at clinical high risk for psychosis and people with schizophrenia spectrum disorders: a systematic review and meta-analysis

Rosario Aronica et al. BMJ Ment Health. .

Abstract

Aim: To identify sleep abnormalities in individuals at clinical high risk for psychosis (CHR-P) or with schizophrenia spectrum disorders (SSDs) compared with healthy controls (HCs) using wrist actigraphy, and to assess potential differences in the direction of effect with self-reported assessments of sleep.

Methods: We conducted a systematic review of observational studies, with the search last updated on 29 April 2024. Primary outcome was total sleep time (TST), with secondary outcomes including time in bed (TIB), sleep latency, sleep efficiency, wake after sleep onset, nighttime awakenings and self-reported sleep quality. Random-effects pairwise meta-analyses were used to summarise the effects of each outcome.

Results: Nineteen studies were included, with 18 contributing to the meta-analyses (202 CHR-P, 584 SSD, 582 HC). TST results were inconclusive for CHR-P (MD -4.88 min (95% CI -20.57 to 10.81)), while SSD participants showed an increase in TST compared with HC (MD 106.13 min (86.02 to 124.24)). Factors such as antipsychotic medications (pseudo-R²=88.14%), age (38.89%) and gender (26.29%) partially explained the heterogeneity between subgroups. Additionally, CHR-P individuals exhibited reduced sleep efficiency (MD -2.04% (-3.55 to 0.53)), whereas SSD participants had increased TIB (MD 121.58 min (88.16 to 155.00)) and sleep latency (MD 13.05 min (2.11 to 24.00)). The risk-of-bias assessment ranged from some concerns to high risk.

Conclusions: Our analyses identified sleep abnormalities in CHR-P and SSD compared with placebo. However, observed heterogeneity and potential biases across studies may limit the interpretability of findings. These limitations underscore the need for standardised guidelines and more precise participant stratification.

Keywords: Adult psychiatry; Data Interpretation, Statistical; Schizophrenia & psychotic disorders; Sleep.

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Conflict of interest statement

Competing interests: RA was supported by the Italian Ministry of University and Research. EGO received research and consultancy fees from Angelini Pharma. PB was partially supported by grants from the Italian Ministry of University and Research, the Italian Ministry of Health and by the CARIPLO Foundation. JT is an advisor to Precision Mental Wellness and receives research support from Otsuka. AC received research, educational and consultancy fees from the Italian Network for Paediatric Trials, CARIPLO Foundation, Lundbeck and Angelini Pharma, outside the submitted work. He is the Editor-in-Chief of BMJ Mental Health, but he was not involved in any step of the editorial management of the manuscript, including the final decision about publication. No other authors report conflicts of interest.

Figures

Figure 1
Figure 1. PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) 2020 flow diagram for systematic review.
Figure 2
Figure 2. (a) Total sleep time by diagnostic subgroups (mean difference expressed in minutes). (b) Time in bed by diagnostic subgroups (mean difference expressed in minutes).
Figure 3
Figure 3. (a) Sleep latency by diagnostic subgroups (mean difference expressed in percentage). (b) Sleep efficiency by diagnostic subgroups (mean difference expressed in minutes).
Figure 4
Figure 4. (a) Wake after sleep onset by diagnostic subgroups (mean difference expressed in minutes). (b) Nighttime awakenings by diagnostic subgroups (mean difference expressed in episodes).

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