Evidence map›Paper›PMID 41063190›Full record

SynthesisBMC medicine2025

Global perspectives on the Sleep Condition Indicator for DSM-5 insomnia disorder: a COSMIN and STARD systematic review of psychometric and diagnostic performance.

Runtang Meng, Mengyi Huang, Christopher B Miller, Daniel Yee Tak Fong, Alice M Gregory, Amir H Pakpour, Joseph M Dzierzewski, Alasdair L Henry, Bogdan I Voinescu, Nongnong Yang and 5 more

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Runtang MengSchool of Public Health and Nursing, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, China. mengruntang@hznu.edu.cn.
Mengyi HuangThe Medical Record Statistics Department, Zhejiang Hospital, Hangzhou, Zhejiang, 310030, China.
Christopher B MillerBig Health Ltd, London, WC1H 9LT, UK.
Daniel Yee Tak FongSchool of Nursing, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, 999077, China.
Alice M GregoryDepartment of Psychology, Royal Holloway, University of London, Egham Hill, Egham, TW20 0EX, UK.
Amir H PakpourDepartment of Nursing, School of Health and Welfare, Jönköping University, 55318, Jönköping, Sweden.
Joseph M DzierzewskiNational Sleep Foundation, Washington, DC, 20036, USA.
Alasdair L HenryBig Health Ltd, London, WC1H 9LT, UK.
Bogdan I VoinescuCentre for Academic Mental Health, University of Bristol, Bristol, BS8 2BN, UK.
Nongnong YangSchool of Public Health and Nursing, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, China.
Haiyan MaSchool of Public Health and Nursing, Hangzhou Normal University, Hangzhou, Zhejiang, 311121, China.
Yi LuoSchool of Nursing, Ningbo College of Health Sciences, Ningbo, Zhejiang, 315100, China.
Esther Yuet Ying LauSleep Laboratory, Department of Psychology, The Education University of Hong Kong, Hong Kong, 999077, China.
Karen SpruytINSERM, Université Paris Cité, Paris, 75019, France.
Colin A EspieBig Health Ltd, London, WC1H 9LT, UK.

Funding

European Union under the GA 101129822 - EOSC TITANMedical Research Fund of Zhejiang Province 2023RC073National Institute for Health and Care Research (NIHR) Oxford Health Biomedical Research Centre NIHR203316National Level Project Cultivation - Seed Engineering Project (Natural Science) of Hangzhou Normal University 202522Research Initiation Fund of Hangzhou Normal University RWSK20201003
6 · The paper itself

Abstract

backgroundA robust insomnia screening and measuring tool is essential for accurately assessing and diagnosing insomnia in research and clinical settings. The Sleep Condition Indicator (SCI) is an initial screening tool designed to assess insomnia complaints according to the DSM-5 criteria. This study aims to systematically evaluate item content, psychometric performance, diagnostic performance, and overall application of the SCI through a methodological quality assessment of original validation studies. These findings offer valuable information for optimizing insomnia diagnosis, assessment, and monitoring.

methodsA comprehensive search was conducted for finding studies published from 2012 to 2024, in PubMed, EMBASE, CINAHL, and MEDLINE electronic databases, and citation searching in PubMed, SCOPUS, Web of Science, and Google Scholar. Full-text articles focusing on the translation, validation, and application of the SCI were included. The psychometric studies were assessed regarding their measurement properties and methodological quality, using the Consensus-Based Standards for the Selection of Health Measurement Instruments (COSMIN) guidelines. The diagnostic studies were assessed using the Standard for Reporting of Diagnostic Accuracy (STARD) guidelines. Finally, studies in which the SCI was used for assessment or screening purposes provided general information on the application of the scale.

resultsWe identified 285 studies with over 720,000 participants that used the SCI, and 13 language versions of the SCI were employed across at least 31 regions. The most commonly assessed measurement properties of the SCI within 19 studies were structural validity, internal consistency, criterion validity, and reliability, with findings supporting a stable two-factor structure and credible overall psychometric properties. The SCI demonstrated adequate sensitivity and specificity in 14 studies evaluating its diagnostic performance, and a cut-off value of 16 was recommended for screening insomnia. Finally, the studies showed that the SCI is widely used across clinical and non-clinical settings and provides valuable information for assessing insomnia risks.

conclusionsThe SCI includes items that align with the most current diagnostic criteria for insomnia disorder from the DSM-5. This tool demonstrates excellent psychometric performance and strong diagnostic performance. Overall, the SCI provides useful information for screening, diagnosing, and monitoring insomnia, making it a valuable tool in both research and clinical settings.

Indexed as

Diagnostic and Statistical Manual of Mental DisordersPsychometricsSleep Initiation and Maintenance DisordersHumansReproducibility of ResultsCOSMINDSM-5InsomniaScreening toolSleep Condition IndicatorSTARD

Identifiers

PMID41063190
PMCPMC12505784

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.