Obstructive sleep apnea screening in young people: Psychometric validation of a shortened version of the STOP-BANG questionnaire using categorical data methods
Md Dilshad Manzar1, Unaise Abdul Hameed2, Mazen Alqahtani3, Abdulrhman Albougami1, Mohammed Salahuddin4, Prue Morgan5, Ahmed S Bahammam6, Seithikurippu R Pandi-Perumal7
1 Department of Nursing, College of Applied Medical Sciences, Majmaah University, Majmaah, 11952, Saudi Arabia
2 Department of Physiotherapy, Fatima College of Health Sciences, Al Mafraq, Abu Dhabi City, United Arab Emirates; Department of Physiotherapy, Faculty of Medicine, Nursing and Health Sciences, Monash University, Australia
3 Department of Physiotherapy, College of Applied Medical Sciences, Majmaah University, Majmaah, 11952, Saudi Arabia
4 Department of Pharmacy, College of Medicine and Health Sciences, Mizan-Tepi University (Mizan Campus), Mizan-Aman, Ethiopia
5 Department of Physiotherapy, Faculty of Medicine, Nursing and Health Sciences, Monash University, Australia
6 The University Sleep Disorders Center, College of Medicine, King Saud University, Riyadh; The Strategic Technologies Program of the National Plan for Sciences and Technology and Innovation, King Saud University, Saudi Arabia
7 Somnogen Canada Inc, College Street, Toronto, ON, Canada
Dr. Ahmed S Bahammam
Department of Medicine, University Sleep Disorders Center, College of Medicine, King Saud University, PO Box: 225503, Riyadh 11324
Source of Support: None, Conflict of Interest: None
BACKGROUND: The STOP-BANG is an easily administrable questionnaire for the screening of obstructive sleep apnea in adults, which may be adapted for use by young people. Here, we assessed the psychometric properties of the STOP-BN, a shortened version of the STOP-BANG questionnaire, using categorical data methods.
METHODS: Four hundred and three young people (age 20.71 ± 1.93 years) were selected by random sampling to participate in this cross-sectional study. Participants completed the STOP-BN, a tool for recording social and demographic characteristics, and the Epworth Sleepiness Scale (ESS), a measure of daytime sleepiness. The obtained data were analyzed using categorical data methods.
RESULTS: A two-factor model was identified for the STOP-BN, using the Kaiser's criteria (eigenvalue >1) and the screen test. However, the parallel analysis based on minimum rank, and the cumulative variance criteria (>40%) identified an one-factor model. Factor loadings ranged from 0.364 to 0.745. The identified two-factor model showed acceptable fit as the reported goodness of fit index and weighted root mean square residual were in the ideal range, and the comparative fit index was close to the ideal range. Greatest lower bound to reliability for two factors of the STOP-BN was 0.67 and 0.67, indicating an acceptable internal consistency. A weak to a nonsignificant correlation between the ESS and the STOP-BN score was demonstrated, favoring STOP-BN's divergent validity.
CONCLUSION: Categorical methods support the psychometric validity of the STOP-BN in the study population.