Open AccessQuality of life of patients with rheumatic diseases during the COVID-19 pandemic: The biopsychosocial path
Author(s) -
Guillermo Guaracha-Basáñez,
Irazú Contreras-Yáñez,
Gabriela Hernández-Molina,
Viviana A. Estrada-González,
Lexli D. Pacheco-Santiago,
Salvador Saúl Valverde-Hernández,
José Roberto Galindo-Donaire,
Ingris PeláezBallestas,
Virginia PascualRamos
Publication year - 2022
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0262756
Subject(s) - biopsychosocial model , medicine , quality of life (healthcare) , comorbidity , anxiety , depression (economics) , outpatient clinic , physical therapy , feeling , psychiatry , psychology , nursing , economics , macroeconomics , social psychology
Background Previous models that assess quality-of-Life (QoL) in patients with rheumatic diseases have a strong biomedical focus. We evaluated the impact of COVID-19 related-health care interruption (HCI) on the physical, psychological, social relationships and environment QoL-dimensions, and explored factors associated with QoL when patients were reincorporated to the outpatient clinic, and after six-month follow-up. Patients and methods Study phase-1 consisted of a COVID-19 survey administered from June 24 th -October 31 st 2020, to outpatients with rheumatic diseases who had face-to-face consultation at outpatient clinic reopening. Study phase-2 consisted of 3 consecutive assessments of patient´s QoL (WHOQOL-BREF), disease activity/severity (RAPID-3), and psychological comorbidity/trauma (DASS-21 and IES-R) to patients from phase-1 randomly selected. Sociodemographic, disease and treatment-related information, and comorbidities were obtained. Multiple linear regression analysis identified factors associated with the score assigned to each WHOQOL-BREF dimension. Results Patients included (670 for phase-1 and 276 for phase-2), had primarily SLE and RA (44.2% and 34.1%, respectively), and all the dimensions of their WHOQOL-BREF were affected. There were 145 patients (52.5%) who referred HCI, and they had significantly lower dimensions scores (but the environment dimension score). Psycho-emotional factors (primarily feeling confused, depression and anxiety), sociodemographic factors (age, COVID-19 negative economic impact, years of scholarship, HCI and having a job), and biomedical factors (RAPID-3 score and corticosteroid use) were associated with baseline QoL dimensions scores. Psycho-emotional factors showed the strongest magnitude on dimensions scores. Most consistent predictor of six-month follow-up QoL dimensions scores was each corresponding baseline dimension score, while social determinants (years of scholarship and having a job), emotional factors (feeling bored), and biomedical aspects (RAPID 3) had an additional impact. Conclusions HCI impacted the majority of patient´s QoL dimensions. Psycho-emotional, sociodemographic and biomedical factors were consistently associated with QoL dimensions scores, and these consistently predicted the QoL trajectory.