Symptom content analysis of OSA questionnaires: time to identify and improve relevance of diversity of OSA symptoms?

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 4-step approach: (1) selection of OSA screening questionnaires, (2) item extraction and selection, (3) extraction of symptoms from items, and (4) 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 (eg, 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 1 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. CITATION: Gauld C, Baillieul S, Martin VP, et al. Symptom content analysis of OSA questionnaires: time to identify and improve relevance of diversity of OSA symptoms? J Clin Sleep Med. 2024;20(7):1105-1117.

Content analysis of insomnia questionnaires: A step to better evaluate the complex and multifaceted construct of insomnia disorder.

Insomnia disorder is a mental disorder that includes various types of symptoms (e.g., insomnia initiating, worries, mood disturbances) and impairments (e.g., distress related to sleep alterations). Self-report questionnaires are the most common method for assessing insomnia but no systematic quantified analysis of their content and overlap has been carried out. We used content analysis and a visualization method to better identify the different types of clinical manifestations that are investigated by nine commonly used insomnia questionnaires for adults and the Jaccard index to quantify the degree to which they overlap. Content analysis found and visualized 16 different clinical manifestations classified into five dimensions ("Insomnia symptoms", "Insomnia-related symptoms", "Daytime symptoms", "Insomnia-related impairments", "Sleep behaviors"). The average Jaccard Index was 0.409 (moderate overlap in content). There is a lack of distinction between symptoms and impairments, and the assessment of sleep duration and hyperarousal symptoms remains overlooked. This preliminary analysis makes it possible to visualize the content of each of the nine questionnaires and to select the most appropriate questionnaire based on the issue to be addressed. Suggestions are made regarding the development of future questionnaires to better distinguish symptoms and impairments, and the different phenotypes of insomnia disorder.

Systematic Item Content and Overlap Analysis of Self-Reported Multiple Sleep Disorder Screening Questionnaires in Adults.

Sleep disorders are defined on the basis of diagnostic criteria presented in medical classifications. However, no consensus has emerged on the exact list of operational symptoms that should be systematically investigated in the field of sleep medicine. We propose a systematic analysis of sleep symptoms that figure in a set of self-reported multiple sleep disorder screening questionnaires for adult populations, to identify the content overlap of symptoms that probe the presence of central sleep symptoms, and to highlight the potential level of heterogeneity among sleep disorder questionnaires. The method comprises three steps: (i) the selection of self-reported multiple sleep disorder screening questionnaires; (ii) item extraction and selection; (iii) the extraction of symptoms from items. Frequency of sleep symptoms and content overlap (Jaccard Index) are analyzed. We extracted 469 items that provide 60 different symptoms from 12 questionnaires. Insomnia, somnolence, and sleep-related breathing symptoms were found in all the questionnaires. The mean overlap among all questionnaires evaluated with the Jaccard Index is 0.44, i.e., moderate similarity. Despite limitations related to the selection of questionnaires and the symptom extraction and harmonization, this study underlines the need to standardize sleep symptom contents for sleep medicine in order to enhance the practicability, reliability, and validity of sleep disorder diagnoses.

Toward a multi-lingual diagnostic tool for the worldwide problem of sleep health: The French RU-SATED validation.

INTRODUCTION: Sleep health is "a multidimensional pattern of sleep-wakefulness, adapted to individual, social, and environmental demands, that promotes physical and mental well-being". The RU-SATED is a short practical self-reported symptom scale that is a reliable valid tool for the rapid evaluation of sleep health. This study sought to examine the psychometric validity of the French version. METHODS: We conducted an observational cross-sectional study. All professionals working in Bordeaux University Hospital were asked to answer an internet-based questionnaire assessing sleep, mental and physical health outcomes. Sleep health was measured using the French RU-SATED scale obtained by a rigorous reverse translation process. Psychometric validity included factor structure, internal structural validity, concurrent validity and external validity of the measure, with sleep, mental and physical health outcomes. RESULTS: A total of 1,562 participants were included with 80.5% of women and a mean age of 40.0 (±11.2). Sleep health was within the average range (M = 8.2, SD = 2.4) on the RU-SATED. Confirmatory factor analyses showed acceptable model fit measures. Cronbach's alpha coefficient was 0.57 and ranged from 0.46 to 0.58 when removing each item. The correlation between items with the overall corrected scores ranged from 0.19 to 0.43. The "Efficiency" item showed poor psychometric properties. Most items were highly correlated with their appropriate sleep outcome. All items showed a strong association with positive mental and physical health outcomes. DISCUSSION: The French RU-SATED scale is a reliable valid tool for measuring sleep health in adults. Nevertheless, future studies should better evaluate the reliability and validity of the "Efficiency" item. It is also important to explore how the RU-SATED can be used to evaluate the impact of sleep hygiene strategies in promoting public health in accordance with models of sleep behavior change.