Shada Khalid Alanazi

Ms. Shada Khalid Alanazi


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 July 2026 in Healthcare
Verified
Journal Article
Open access
PDF file
SAShada Khalid Alanazi
Shada Khalid Alanazi
LALama Alanazi
Lama Alanazi
ZAZahra Saleh Alsindi
Zahra Saleh Alsindi
Sarah Anwar AlmullaSarah Anwar Almulla
Sarah Anwar Almulla
NANasser A Almulhim
Nasser A Almulhim
HAheba alojail
heba alojail
Background/Objectives: Artificial intelligence (AI) holds significant potential to enhance diagnostic support and access to dermatological care; however, its adoption depends on public trust and acceptance. This study aimed to assess knowledge, attitudes, and acceptance of dermatological AI among Saudi adults, and to identify factors associated with adoption, trust, and preferred system characteristics. Methods: A nationwide cross-sectional online survey was conducted among 668 Saudi adults (≥18 years) between 21 May and 5 June 2025, using convenience and snowball sampling via social media platforms (WhatsApp, Snapchat, Twitter/X, and Telegram). The questionnaire captured demographics, attitudes toward AI (20-item Likert scale), and perceived importance of six AI system features. Data were analyzed using descriptive statistics, one-way ANOVA, and binary logistic regression. The study was approved by the Institutional Review Board of King Faisal University (Approval No. KFU-REC-2025-MAY-ETHICS3443, approval date 19 May 2025). Results: The mean overall AI attitude orientation score was 74.48 ± 10.20 (Cronbach’s α = 0.868), reflecting moderately positive but conditional attitudes toward dermatological AI. Participants strongly preferred physician-supervised AI over fully autonomous systems, with medical oversight receiving the highest agreement (mean 4.27 ± 0.87). Privacy protection and diagnostic accuracy were rated as the most important system features. Age was significantly associated with the overall AI attitude orientation score (p = 0.009), with younger participants demonstrating more favorable orientations. Interest in technology showed the strongest association with both AI attitude orientation and perceived importance (p < 0.001). No demographic variable independently predicted high intention to use AI in multivariate analysis. Conclusions: Saudi adults generally exhibit favorable yet cautious attitudes toward dermatological AI. Implementation strategies should prioritize physician oversight, transparency, data privacy, and culturally responsive design to support responsible integration into clinical practice.

23 April 2026 in JAAD Case Reports
Verified
Journal Article
Open access
NENermeen Elhofy
Nermeen Elhofy
SAShada Khalid Alanazi
Shada Khalid Alanazi
SASara Almukhaimar
Sara Almukhaimar
HAHadeel Almajid
Hadeel Almajid
AAAli Aldandan
Ali Aldandan