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Objectives: This study investigated the relationship between numeracy skills (NS) and choice consistency in discrete choice experiments (DCEs).
Methods: A DCE was conducted to explore patients' preferences for kidney transplantation in Italy. Patients completed the DCE and answered 3-item numeracy questions. A heteroskedastic multinomial logit model was used to investigate the effect of numeracy on choice consistency.
Results: Higher NS were associated with greater choice consistency, increasing the scale to 1.63 (P < .001), 1.39 (P < .001), and 1.18 (P < .001) for patients answering 3 of 3, 2 of 3, and 1 of 3 questions correctly, respectively, compared with those with no correct answers. This corresponded to 63%, 39%, and 18% more consistent choices, respectively. Accounting for choice consistency resulted in varying willingness-to-wait (WTW) estimates for kidney transplant attributes. Patients with the lowest numeracy (0/3) were willing to wait approximately 42 months [95% CI: 29.37, 54.68] for standard infectious risk, compared with 33 months [95% CI: 28.48, 38.09] for 1 of 3, 28 months [95% CI: 25.13, 30.32] for 2 of 3, and 24 months [95% CI: 20.51, 27.25] for 3 of 3 correct answers. However, WTW differences for an additional year of graft survival and neoplastic risk were not statistically significant across numeracy levels. Supplementary analyses of 2 additional DCEs on COVID-19 vaccinations and rheumatoid arthritis, conducted online, supported these findings: higher NS were associated with more consistent choices across different disease contexts and survey formats.
Conclusions: The findings suggested that combining patients with varying NS could bias WTW estimates, highlighting the need to consider numeracy in DCE data analysis and interpretation.
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http://dx.doi.org/10.1016/j.jval.2024.07.001 | DOI Listing |
Rev Cardiovasc Med
August 2025
Department of Cardiology, University Hospitals of Leicester NHS Trust, Glenfield Hospital, LE3 9QP Leicester, UK.
Adult congenital heart disease (ACHD) constitutes a heterogeneous and expanding patient cohort with distinctive diagnostic and management challenges. Conventional detection methods are ineffective at reflecting lesion heterogeneity and the variability in risk profiles. Artificial intelligence (AI), including machine learning (ML) and deep learning (DL) models, has revolutionized the potential for improving diagnosis, risk stratification, and personalized care across the ACHD spectrum.
View Article and Find Full Text PDFCureus
August 2025
Anatomy, All India Institute of Medical Sciences, Bibinagar, Hyderabad, IND.
This systematic review investigates the influence of fenestration size and prosthesis diameter on hearing outcomes in patients undergoing primary stapedotomy for otosclerosis. A total of 11 studies were included, comprising randomized controlled trials, cohort studies, and one cross-sectional study, with follow-up durations ranging from three months to one year. Fenestration sizes most commonly ranged from 0.
View Article and Find Full Text PDFPatient
September 2025
PPD Evidera Patient-Centered Research, Thermo Fisher Scientific, Waltham, MA, USA.
Background: Migraine care is often suboptimal owing to undertreatment, variation in clinical outcomes and administration methods among existing treatments, and between- and within-individual heterogeneity in the clinical course of migraine. In response to these challenges, preference studies have been increasingly conducted to inform treatment decision-making and development. However, gaps remain in understanding how treatment preferences have been assessed across different migraine studies.
View Article and Find Full Text PDFActa Neurochir (Wien)
September 2025
Department of Neurosurgery, Istinye University, Istanbul, Turkey.
Background: Recent studies suggest that large language models (LLMs) such as ChatGPT are useful tools for medical students or residents when preparing for examinations. These studies, especially those conducted with multiple-choice questions, emphasize that the level of knowledge and response consistency of the LLMs are generally acceptable; however, further optimization is needed in areas such as case discussion, interpretation, and language proficiency. Therefore, this study aimed to evaluate the performance of six distinct LLMs for Turkish and English neurosurgery multiple-choice questions and assess their accuracy and consistency in a specialized medical context.
View Article and Find Full Text PDFRheumatol Int
September 2025
Department of Physical Medicine and Rehabilitaton, Ankara Bilkent City Hospital, Faculty of Medicine, Yıldırım Beyazıt University, Ankara, Türkiye, Turkey.
The Impact of Obesity and Overweight on Rheumatoid Arthritis Patients: Real-World Insights from a Biologic and Targeted Synthetic DMARDs Registry. The management of rheumatoid arthritis (RA) has advanced with biological and targeted synthetic disease-modifying anti-rheumatic drugs (b/tsDMARDs). However, obesity, a common comorbidity, impacts treatment and disease progression efficacy.
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