ArticleRheumatology (Oxford, England)2025
Rheumatoid arthritis patients' perspective on the use of prediction models in clinical decision-making.
Article in Rheumatology (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Comparative Effectiveness of a Nurse-Led Care Model vs Usual Care in Rheumatoid Arthritis: A Longitudinal Cohort Study of Clinical Outcomes and Patient Adherence.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- Perceptions of healthcare professionals in rheumatology on the use of prediction models in clinical practice.Rheumatology advances in practice · 2026Article
- Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis.Therapeutic advances in musculoskeletal disease · 2025Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesA rapidly expanding number of prediction models is being developed, aiming to improve RA diagnosis and treatment. However, few are actually implemented in clinical practice. This study explores factors influencing the acceptance of prediction models in clinical decision-making by RA patients.
methodsA qualitative study design was used with thematic analysis of semi-structured interviews. Purposive sampling was applied to capture a complete overview of the influencing factors. The interview topic list was based on pilot data.
resultsData saturation was reached after 12 interviews. Patients were generally positive about the use of prediction models in clinical decision-making. Six key themes were identified from the interviews: (i) patients have a need for information about prediction models; (ii) factors influencing trust in model-supported treatment are described; (iii) patients envision the model to have a supportive role in clinical decision-making; (iv) patients hope to personally benefit from model-supported treatment in various ways; (v) patients are willing to contribute time and effort to contribute to model input; (vi) the effects of model-supported treatment on the relationship with the caregiver are discussed.
conclusionWithin this study, RA patients were generally positive about the use of prediction models in their treatment, given some conditions were met and concerns addressed. The results of this study can be used during the development and implementation in RA care of prediction models in order to enhance patient acceptability.
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