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Enregistrement W4411429169 · doi:10.1016/j.ard.2025.05.842

POS0459 Patients Perspective toward Rheumatic and Musculoskeletal Diseases: Insights from a Large-Scale Survey

2025· article· en· W4411429169 sur OpenAlexaboutno aff
Khalid A. Alnaqbi, Mohammed Alaswad, Shaima Alasfour

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueMusculoskeletal Disorders and Rehabilitation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicinePerspective (graphical)Scale (ratio)Physical therapyFamily medicineCartography

Résumé

récupéré en direct d'OpenAlex

Background: Rheumatic and musculoskeletal diseases (RMDs) are prevalent among Arabic-speaking patients in the Middle East and North Africa (MENA) region. However, their perspectives on these conditions remain underexplored. This lack of understanding limits the ability to deliver effective and culturally sensitive care. Objectives: To investigate the experiences, concerns, and views of Arabic-speaking patients with RMDs in the MENA region regarding diagnosis, disease knowledge, and interactions with healthcare professionals (HCPs). Methods: A cross-sectional study was conducted utilizing an online survey titled "PRADA" (Patient peRspectives on rheumAtic Diseases in Arabic countries). The PRADA survey was developed using pilot testing with clinimetric sensibility assessment to ensure relevance and clarity, and the Open-Source Metric for Measuring Arabic Narratives (OSMAN) was used to assess readability. To our knowledge, this is the first study to utilize a readability tool for a health survey written in Arabic language. The Checklist for Reporting Internet E-Surveys (CHERRIES) was used to improve the quality of the survey's content. The survey was distributed via social media platforms to Arabic-speaking patients with self-reported RMDs across the MENA region. Collected data included demographics, disease characteristics, medication use, treatment satisfaction factors, perceived causes, and patient concerns. Data were collected anonymously from August to October 2022 and analyzed using descriptive statistics. Ethical approval was obtained from the Ministry of Health in Kuwait. Results: Of the 1050 responses received, 456 were complete and included in the analysis. Most respondents were female (81.4%), with most falling into the 25–34 age group (29.2%) and the 35–44 age group (34.0%) constituting 63.4% of the sample. The most frequently reported diseases were systemic lupus erythematosus (42.5%), rheumatoid arthritis (32.9%), and ankylosing spondylitis (10.5%). Nearly all (97%) used medications within the previous three months, primarily hydroxychloroquine (48.1%), glucocorticosteroids (37.3%), and biologics (27.6%). Key factors influencing treatment satisfaction (Table 1) included pain relief (78.3%), better laboratory test results (64.7%), improved sleep quality (51.8%), and enhancements in mood and mental health (50.2%). Other notable factors were increased physical activity, reduction or discontinuation of steroids, the side effects of treatment, the doctor's reputation and expertise, communication from the medical team, and the opinions and experiences of others regarding the treatment. Patients perceived immune system dysfunction (76.5%), psychological factors (54.8%), genetics (41.7%), and envy (21.1%) as the primary causes of their disease. Other perceived causes included magic (7.9%) and divine punishment for their sins (6.1%). The main concerns reported by patients (Table 2) were fear of disease complications (95.0%), medication side effects (85.3%), and becoming a burden to others (71.1%). Additional concerns included fear of physical disability (64%), issues related to marriage and childbearing (40%), and fear of falling while moving (31%). Two-thirds of respondents (66.7%) had not consulted a practitioner of complementary and alternative medicine, while one-third (33.3%) had. Rheumatologists (83.5%), internet search engines (71.3%), and social media accounts of rheumatologists (63.6%) were the primary sources of information for patients. Conclusion: This survey is the first and largest of its kind in the MENA region, providing important insights into patient perspectives on RMD. It emphasizes the need for a comprehensive and holistic management, enhanced education, and supportive services to improve patient's quality of life. REFERENCES: [1] Al-Ajlouni et al. The burden of musculoskeletal disorders in the Middle East and North Africa (MENA) region: a longitudinal analysis from the global burden of disease dataset 1990-2019. BMC Musculoskelet Disord. 2023;24(1):439. doi: 10.1186/s12891-023-06556-x. [2] Mousavi et al. The burden of rheumatoid arthritis in the Middle East and North Africa region, 1990-2019. Sci Rep. 2022;12(1):19297. doi: 10.1038/s41598-022-22310-0 [3] Alnaqbi et al. Development, sensibility, and reliability of the Toronto Axial Spondyloarthritis Questionnaire in inflammatory bowel disease. J Rheumatol. 2013;40(10):1726-35. doi: 10.3899/jrheum.130048. [4] El-Haj M, Rayson P. OSMAN ― A Novel Arabic Readability Metric. Portorož, Slovenia: European Language Resources Association (ELRA); 2016. p. 250-5. [5] Al-Mehmadi et al. Knowledge of Common Symptoms of Rheumatic Diseases and Causes of Delayed Diagnosis in Saudi Arabia. Patient Prefer Adherence. 2024;18:635-47. doi: 10.2147/ppa.S448999. [6] Ghaddaf et al. Public awareness about arthritic diseases in Saudi Arabia: a systematic review and meta-analysis. Int Orthop. 2023;47(12):3013-29. doi: 10.1007/s00264-023-05725-w. Acknowledgements: Patients who completed the online survey. Disclosure of Interests: None declared . © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,027
Score d'incertitude au seuil0,679

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,308
Écart entre enseignants0,295 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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Même revueAnnals of the Rheumatic DiseasesMême sujetMusculoskeletal Disorders and RehabilitationTravaux en français237 207