Differences in Disability Perception in Systemic Sclerosis: A Mirror Survey of Patients and Health Care Providers.
Quentin KirrenCamille DasteFrantz FoissacHendy AbdoulSophie AlamiMarie-Eve CarrierLinda KwakkenbosMarie-Martine Lefèvre-ColauFrançois RannouAgathe PapelardAlexandra RorenBrett D ThombsLuc MouthonChristelle NguyenPublished in: Journal of clinical medicine (2023)
Differences in disability perception between patients and care providers may impact outcomes. We aimed to explore differences in disability perception between patients and care providers in systemic sclerosis (SSc). We conducted a cross-sectional internet-based mirror survey. SSc patients participating in the online SPIN Cohort and care providers affiliated with 15 scientific societies were surveyed using the Cochin Scleroderma International Classification of Functioning, Disability and Health (ICF)-65 questionnaire, including 65 items (from 0 to 10), representing 9 domains of disability. Mean differences between patients and care providers were calculated. Care providers' characteristics associated with a mean difference ≥ 2 of 10 points were assessed in multivariate analysis. Answers were analyzed for 109 patients and 105 care providers. The mean age of patients was 55.9 (14.7) years and the disease duration was 10.1 (7.5) years. For all domains of the ICF-65, care providers' rates were higher than those of patients. The mean difference was 2.4 (1.0) of 10 points. Care providers' characteristics associated with this difference were organ-based specialty (OR = 7.0 [2.3-21.2]), younger age (OR = 2.7 [1.0-7.1]) and following patients with disease duration ≥5 years (OR = 3.0 [1.1-8.7]). We found systematic differences in disability perception between patients and care providers in SSc.
Keyphrases
- patient reported
- healthcare
- systemic sclerosis
- multiple sclerosis
- end stage renal disease
- type diabetes
- chronic kidney disease
- ejection fraction
- newly diagnosed
- public health
- machine learning
- risk assessment
- adipose tissue
- interstitial lung disease
- deep learning
- metabolic syndrome
- prognostic factors
- patient reported outcomes
- health information
- cross sectional
- molecular dynamics
- single molecule
- climate change
- health promotion