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Cited by 177

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Insomnia heterogeneity: Characteristics to consider for data-driven multivariate subtyping

Open access
Benjamins, Jeroen S., Migliorati, Filippo, Dekker, Kim, Wassing, Rick, Moens, Sarah, Blanken, Tessa F., te Lindert, Bart H.W., Sjauw Mook, Jeffrey, Van Someren, Eus J.W.·2017·Sleep Medicine Reviews

Abstract

Meta-analyses and systematic reviews have reported surprisingly few consistent insomnia-characteristics with respect to cognitions, mood, traits, history of life events and family history. One interpretation of this limited consistency is that different subtypes of insomnia exist, each with its own specific multivariate profile of characteristics. Because previously unrecognized subtypes will be differentially represented in individual studies and dilute effect sizes of subtype-dependent characteristics of importance, they are unlikely to be reported consistently in individual studies, let alone in meta-analyses. This review therefore aims to complement meta-analyses by listing previously reported psychometric characteristics of insomnia, irrespective of the degree of consistency over studies. The review clearly indicates that characteristics of insomnia may not be limited to sleep. Reports suggest that at least some individuals with insomnia may deviate from people without sleep complaints with respect to demographics, mental and physical health, childhood trauma, life events, fatigue, sleepiness, hyperarousal, hyperactivity, other sleep disorders, lifetime sleep history, chronotype, depression, anxiety, mood, quality of life, personality, happiness, worry, rumination, self-consciousness, sensitivity, dysfunctional beliefs, self-conscious emotion regulation, coping, nocturnal mentation, wake resting-state mentation, physical activity, food intake, temperature perception and hedonic evaluation. The value of this list of characteristics is that 1) internet has now made it feasible to asses them all in a large sample of people suffering from insomnia, and 2) statistical methods like latent class analysis and community detection can utilize them for a truly bottom-up data-driven search for subtypes. The supplement to this review provides a blueprint of this multivariate approach as implemented in the Sleep registry platform (www.sleepregistry.nl), that allows for bottom-up subtyping and fosters cross-cultural comparison and worldwide collaboration on insomnia subtype finding - and beyond.

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Metadata

Authors
Benjamins, J. S., Migliorati, F., Dekker, K., Wassing, R., Moens, S., Blanken, T. F., te Lindert, B. H. W., Sjauw Mook, J., & Van Someren, E. J. W.
Venue
Sleep Medicine Reviews
Publisher
Elsevier BV
Published
2017-12
Volume
36
Pages
71-81
ISSN
1087-0792 (ISSN-L)
OpenAlex
W2555058308
Cited by
177
References
49
FWCI
18.36
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Insomnia heterogeneity: Characteristics to consider for data-driven multivariate subtyping. https://app.cochat.ai/papers/10.1016/j.smrv.2016.10.005
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Benjamins, J. S., Migliorati, F., Dekker, K., Wassing, R., Moens, S., Blanken, T. F., te Lindert, B. H. W., Sjauw Mook, J., & Van Someren, E. J. W. (2017). Insomnia heterogeneity: Characteristics to consider for data-driven multivariate subtyping. Sleep Medicine Reviews. https://doi.org/10.1016/j.smrv.2016.10.005

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.