Digital Divide in Rheumatology: Patterns of Technology and AI Adoption Across Generations of Specialists

CARLA F DIONELLO¹, ANA F PADUA², Claudia Marques³, BRUNA L PORTO⁴, LEONARDO R CAMPOS⁵, RODRIGO OLIVEIRA⁶, GUSTAVO GM BALBI⁷, RODRIGO LUPPINO-ASSAD⁶, YURE G AZEVEDO⁸, LUIZ F DIPE⁹, BRUNO BORDALLO⁵, Cleandro Pires¹⁰, Licia Maria Henrique da Mota¹⁰ and PAULA MONTINA¹⁰, ¹FEDERAL UNIVERSITY OF RIO DE JANEIRO - UFRJ, RIO DE JANEIRO, Rio de Janeiro, Brazil, ²SANTA CASA MG, BELO HORIZONTE, Minas Gerais, Brazil, ³Hospital das Clinicas - Universidade Federal de Pernambuco - UFPE, Recife, Pernambuco, Brazil, ⁴UNIVATES, SÃO LEOPOLDO, Rio Grande do Sul, Brazil, ⁵UFF, Rio de Janeiro, Rio de Janeiro, Brazil, ⁶FMRP-USP, Ribeirão Preto, Sao Paulo, Brazil, ⁷UFJF, JUIZ DE FORA, Minas Gerais, Brazil, ⁸SCR, SOBRAL, Ceara, Brazil, ⁹GRUPO AMIL, SÃO PAULO, Sao Paulo, Brazil, ¹⁰UNB, Brasilia, Distrito Federal, Brazil

Meeting: ACR Convergence 2025

Keywords: Demographics, education, medical, Health Services Research, quality of care, work

Session Information

Date: Sunday, October 26, 2025

Title: (0175–0198) Health Services Research Poster I

Session Type: Poster Session A

Session Time: 10:30AM-12:30PM

Background/Purpose: The integration of digital tools and artificial intelligence (AI) in rheumatology practice has advanced rapidly. However, disparities in adoption across generations of specialists remain underexplored. This study investigates patterns of digital technology and AI usage among Brazilian rheumatologists, stratified by years since medical graduation.

Methods: A nationwide, self-administered, anonymous questionnaire was distributed to rheumatologists affiliated with the Brazilian Society of Rheumatology. The survey included 14 binary-use items related to electronic health records (EHR), AI-assisted tasks, telemedicine, cloud-based collaboration, and scheduling tools. Respondents were categorized into four groups based on time since graduation: 3–10, 10–20, 20–30, and >30 years. Descriptive statistics, Pearson’s correlations, one-way ANOVA, chi-square tests, principal component analysis (PCA), and K-means clustering were performed.

Results: A total of 454 responses were analyzed. EHR usage demonstrated a significant negative correlation with years since graduation (r = –0.33, p < 0.001). Use of AI for text generation was also inversely correlated (r = –0.17, p < 0.01). ANOVA revealed significant variation across graduation strata in EHR usage (p < 0.0001), AI-assisted writing tools (p < 0.001), and cloud-based collaboration platforms (p < 0.01). Chi-square testing confirmed an association between experience level and AI writing tool adoption (χ² = 26.2, p < 0.0001).PCA explained 57.9% of the variance (PC1 = 34.9%, PC2 = 23.1%), and K-means clustering identified three distinct user profiles:Cluster 0 (n=49): Low digital engagement, with 83.7% having >30 years since graduation.Cluster 1 (n=96): High engagement across EHR and AI, predominantly 10–30 years since graduation (69.8%).Cluster 2 (n=179): Intermediate engagement, with mixed generational representation (35.2% >30 years).A regression model between EHR use and graduation time showed R² = 0.11 (p < 0.001), supporting a generational trend.

Conclusion: A digital divide exists in rheumatology, with more recent graduates demonstrating greater engagement with EHRs and AI tools. These findings highlight the importance of targeted training and support for senior rheumatologists to bridge gaps in digital literacy and optimize care delivery.

Disclosures: C. DIONELLO: None; A. PADUA: None; C. Marques: None; B. PORTO: None; L. CAMPOS: None; R. OLIVEIRA: None; G. BALBI: None; R. LUPPINO-ASSAD: None; Y. AZEVEDO: None; L. DIPE: None; B. BORDALLO: None; C. Pires: None; L. Henrique da Mota: None; P. MONTINA: None.

To cite this abstract in AMA style:

DIONELLO C, PADUA A, Marques C, PORTO B, CAMPOS L, OLIVEIRA R, BALBI G, LUPPINO-ASSAD R, AZEVEDO Y, DIPE L, BORDALLO B, Pires C, Henrique da Mota L, MONTINA P. Digital Divide in Rheumatology: Patterns of Technology and AI Adoption Across Generations of Specialists [abstract]. Arthritis Rheumatol. 2025; 77 (suppl 9). https://acrabstracts.org/abstract/digital-divide-in-rheumatology-patterns-of-technology-and-ai-adoption-across-generations-of-specialists/. Accessed .

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