Diagnostic Validity of the Sleep Condition Indicator to Screen for Diagnostic and Statistical Manual-5 Insomnia Disorder in Patients with Parkinson's Disease.


Journal

European neurology
ISSN: 1421-9913
Titre abrégé: Eur Neurol
Pays: Switzerland
ID NLM: 0150760

Informations de publication

Date de publication:
2021
Historique:
received: 11 11 2019
accepted: 24 04 2020
pubmed: 29 6 2021
medline: 3 2 2022
entrez: 28 6 2021
Statut: ppublish

Résumé

Insomnia is a highly common sleep disorder in patients with Parkinson's disease (PD). Yet, no screening questionnaires following the Diagnostic and Statistical Manual-5 (DSM-5) criteria have been validated in PD patients. We assessed the validity and reliability of the French version of the sleep condition indicator (SCI), in patients with PD. In a sample of 65 patients (46% women, mean age 63.8 ± 7.9 years) with PD, but without dementia, insomnia was assessed with a clinical interview and the SCI. Statistical analyses were performed to determine the reliability, construct validity, and divergent validity of the SCI. In addition, an explanatory factor analysis was performed to assess the underlying structure of the SCI. Of the 65 patients (mean duration PD 9.7 ± 6.9 years), 51% met the criteria for insomnia disorder when measured with a clinical interview. The mean SCI score was 18.05 ± 8.3. The internal consistency (α = 0.89) of the SCI was high. Using the previously defined cutoff value of ≤16, the area under the receiver operating characteristic curve was 0.86 with a sensitivity of 86% and a specificity of 87%. Exploratory factor analysis showed a 2-factor structure with a focus on sleep and daytime effects. Additionally, good construct and divergent validity were demonstrated. The SCI can be used as a valid and reliable screener for DSM-5 insomnia disorder in PD patients. Due to its short length, it is useful in both clinical practice and scientific research.

Sections du résumé

BACKGROUND
Insomnia is a highly common sleep disorder in patients with Parkinson's disease (PD). Yet, no screening questionnaires following the Diagnostic and Statistical Manual-5 (DSM-5) criteria have been validated in PD patients.
OBJECTIVES
We assessed the validity and reliability of the French version of the sleep condition indicator (SCI), in patients with PD.
METHODS
In a sample of 65 patients (46% women, mean age 63.8 ± 7.9 years) with PD, but without dementia, insomnia was assessed with a clinical interview and the SCI. Statistical analyses were performed to determine the reliability, construct validity, and divergent validity of the SCI. In addition, an explanatory factor analysis was performed to assess the underlying structure of the SCI.
RESULTS
Of the 65 patients (mean duration PD 9.7 ± 6.9 years), 51% met the criteria for insomnia disorder when measured with a clinical interview. The mean SCI score was 18.05 ± 8.3. The internal consistency (α = 0.89) of the SCI was high. Using the previously defined cutoff value of ≤16, the area under the receiver operating characteristic curve was 0.86 with a sensitivity of 86% and a specificity of 87%. Exploratory factor analysis showed a 2-factor structure with a focus on sleep and daytime effects. Additionally, good construct and divergent validity were demonstrated.
CONCLUSION
The SCI can be used as a valid and reliable screener for DSM-5 insomnia disorder in PD patients. Due to its short length, it is useful in both clinical practice and scientific research.

Identifiants

pubmed: 34182546
pii: 000508185
doi: 10.1159/000508185
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

333-339

Informations de copyright

© 2021 S. Karger AG, Basel.

Auteurs

Sophie Bayard (S)

Univ. Paul Valéry Montpellier 3, University Montpellier, Montpellier, France.

Cindy Lebrun (C)

Univ. Paul Valéry Montpellier 3, University Montpellier, Montpellier, France.

Alexia Arifi-Rossignol (A)

Service de Neurologie, Hôpital Gui de Chauliac, Montpellier, France.

Christian Geny (C)

Service de Neurologie, Hôpital Gui de Chauliac, Montpellier, France.

Marie-Christine Gély-Nargeot (MC)

Univ. Paul Valéry Montpellier 3, University Montpellier, Montpellier, France.

Annemarie I Luik (AI)

Sleep & Circadian Neuroscience Institute, Department of Epidemiology, Nuffield Department of Clinical Neurosciences, Erasmus MC University Medical Center, Rotterdam, Netherlands and University of Oxford, Oxford, United Kingdom.

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