Symptom content analysis of OSA questionnaires: time to identify and improve relevance of diversity of OSA symptoms?
Journal of Clinical Sleep Medicine. 2024-02-29; :
DOI: 10.5664/jcsm.11086
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Gauld C(1)(2), Baillieul S(3), Martin VP(4)(5), Richaud A(5), Lopez R(6)(7),
Pelou M(5), Abi-Saab P(5), Coelho J(5)(8), Philip P(5)(8), Pépin JL(3),
Micoulaud-Franchi JA(5)(8).
Author information:
(1)Service Psychopathologie du Développement de l’Enfant et de l’Adolescent,
Hospices Civils de Lyon & Université de Lyon 1, France.
(2)Institut des Sciences Cognitives Marc Jeannerod, UMR 5229 CNRS & Université
Claude Bernard Lyon 1, France.
(3)University Grenoble Alpes, Inserm, U1300, CHU Grenoble Alpes, Service
Universitaire de Pneumologie Physiologie, Grenoble, France.
(4)University Bordeaux, CNRS, Bordeaux INP, LaBRI, UMR 5800, Talence, France.
(5)University Bordeaux, CNRS, SANPSY, UMR 6033, Bordeaux, France.
(6)Institut des Neurosciences de Montpellier (INM), University Montpellier,
Montpellier, France.
(7)Unité des Troubles du Sommeil, Département de Neurologie, CHU Montpellier,
Montpellier, France.
(8)University Sleep Clinic, University Hospital of Bordeaux, Place Amélie
Raba-Leon, Bordeaux, France.
STUDY OBJECTIVES: Obstructive sleep apnea (OSA) is a heterogeneous condition
covering many clinical phenotypes in terms of the diversity of symptoms.
Patient-based OSA screening questionnaires used in routine practice contain
significantly varying contents that can impact the reliability and validity of
the screening. We investigated to what extent common patient-based OSA screening
questionnaires differ or overlap in their item content by conducting a rigorous,
methodical, and quantified content overlap analysis.
METHODS: We conducted an item content analysis of 11 OSA screening
questionnaires validated in adult populations and characterized their overlap
using a four-step approach: i) selection of OSA screening questionnaires; ii)
item extraction and selection; iii) extraction of symptoms from items; iv)
assessment of content overlap with the Jaccard Index (from 0: no overlap to 1:
full overlap).
RESULTS: We extracted 72 items that provided 25 distinct symptoms from 11
selected OSA questionnaires. The overlap between them was weak (mean Jaccard
Index 0.224, ranging from 0.138 to 0.329). All questionnaires contained symptoms
of the « OSA symptom » dimension (e.g., snoring or witnessed apneas). The
STOP-BANG (0.329) and the Berlin (0.280) questionnaires exhibited the highest
overlap content. Ten symptoms (40%) were investigated in only one questionnaire.
CONCLUSIONS: The heterogeneity of content and the low overlap across these
questionnaires reflect the challenges of screening OSA. The different OSA
questionnaires potentially capture varying aspects of the disorder, with the
risk of biased results in studies. Suggestions are made for better OSA screening
and refinement of clinical OSA phenotypes.
© 2024 American Academy of Sleep Medicine.
DOI: 10.5664/jcsm.11086
PMID: 38420966