Purpose: Alopecia Areata (AA) is a complex autoimmune condition characterized by long-term inflammatory non-scarring patches of hair loss on the face, scalp, and body. Its development involves a combination of genetic, immunological, and environmental factors, making it challenging to understand and treat. This study aims to assess the awareness, beliefs, and psychological impact of patients Patients and Methods: This cross-sectional study was conducted in Eastern and Central provinces of Saudi Arabia and utilized online questionnaires to evaluate knowledge, beliefs, and psychological effects of patients with Alopecia Areata. These questionnaires were distributed using social media platforms. Results: This study enrolled 248 patients with Alopecia Areata (AA), of whom 38.7% were aged 31-40 years and 55.2% were males. The majority were Saudis (98.4%), married (54%), and residing in the Central Region (60.1%). Nearly half (48.8%) were employed in non-medical fields, and 30.6% were vocational school graduates. Healthcare providers were the main source of AA information (52.8%), with most patients aware of AA's seriousness, curability, and quality of life impact, though many had low knowledge and experienced negative psychological effects such as shyness, anxiety, and depression. Conclusion: Despite low self-rated knowledge, most patients recognized AA as serious and requiring treatment. Psychological wellbeing was heavily impacted by AA severity, quality of life, disease duration, and treatment efficacy. Although many patients showed improved AA status and good medication compliance, adverse psychological effects persisted, highlighting the need for larger studies to better understand and address these issues.

Cutis verticis gyrata (CVG) is a rare skin condition characterized by thickened, folded scalp skin, which can occasionally coexist with neurological disorders such as epilepsy without typical known causes. It is important to be open to new explanations for this relationship. While certain characteristics are often seen in affected patients, the underlying reasons for this association remain unclear. Physicians should be aware that CVG could serve as an early indication of epilepsy or other neurological disorders. We report a case of a 15-year-old Saudi male with a history of epilepsy, who presented with progressive scalp swelling leading to the development of CVG.

Lichen planus pigmentosus is a variant of lichen planus characterized by gray-brown hyperpigmented macules and patches occurring in sun exposed areas. Vicks VapoRub is an inhalant ointment frequently used to relieve symptoms of upper respiratory tract infections. We report a case of lichen planus pigmentosus induced by Vicks VapoRub and successfully treated with topical tacrolimus 0.1% cream.

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.

BACKGROUND Artificial intelligence (AI) applications in dermatology show promising potential for diagnostic support and healthcare accessibility, yet successful implementation requires understanding public acceptance patterns. Limited research has examined attitudes toward AI specifically in dermatology within culturally diverse populations. This study assessed Saudi public attitudes toward AI in dermatology to inform implementation strategies for similar healthcare contexts. OBJECTIVE To evaluate knowledge, attitudes, and acceptance factors regarding AI applications in dermatology among Saudi adults and identify demographic and experiential predictors of AI adoption intentions. METHODS We conducted a cross-sectional online survey among Saudi adults aged 18 years and older from May 21 to June 5, 2025. The survey included 30 items divided into three sections: demographics (10 items), attitudes toward AI in dermatology (20 items on a 5-point Likert scale), and system priority ratings (6 items on a 5-point importance scale). We employed convenience and snowball sampling through social media platforms. For data analysis, we used descriptive statistics, one-way ANOVA for group comparisons, and binary logistic regression to identify predictors of high behavioral intention. We set the statistical significance at P < .05. RESULTS The study included 668 participants (61.1% female, 45.4% aged 18-24 years). Participants demonstrated high overall acceptance of AI in dermatology (mean score: 74.48 ± 10.20, Cronbach's α = 0.868). Strong preferences emerged for physician-supervised AI systems rather than autonomous implementations, with medical supervision receiving the highest endorsement (4.27 ± 0.87), followed by explainable AI decisions (4.12 ± 0.82) and physician authority during diagnostic disagreements (4.11 ± 0.86). While recognizing AI's potential benefits for healthcare access in remote areas (3.92 ± 0.94) and cost reduction (3.81 ± 0.86), participants expressed moderate enthusiasm for personal use (3.60 ± 0.97) and reservations about independent AI diagnosis (3.26 ± 0.97). System priorities emphasized privacy protection (56.4% rated as very important) and diagnostic accuracy (55.8%), followed by cultural compatibility (49.3%) and decision transparency (47.2%). Age significantly influenced acceptance (P = .009), with younger adults (18-24 years) showing the highest acceptance (75.96 ± 9.38). Technology interest demonstrated the strongest associations with both acceptance and perceived importance (P < .001). Healthcare professionals valued AI's importance more than general participants (P = .004) while maintaining similar acceptance levels. Gender, geographic region, education level, and dermatological experience showed no significant associations with acceptance patterns. CONCLUSIONS Saudi adults demonstrate predominantly positive yet nuanced attitudes toward dermatological AI, with strong preferences for collaborative physician-AI models over autonomous systems. Successful implementation requires prioritizing transparent, secure AI architectures with physician oversight, developing targeted educational initiatives across demographic groups, and ensuring cultural responsiveness in AI system design. These findings provide crucial baseline data for AI integration within Saudi Arabia's Vision 2030 healthcare objectives and offer insights relevant for culturally diverse healthcare contexts globally.

Background: Excessive sun exposure is a significant risk factor for various skin conditions, including sunburn, premature aging, and skin cancer. This study aims to assess the awareness, attitudes, and practices regarding sun exposure and sunscreen use among college students in Saudi Arabia. Methodology: A cross-sectional study was conducted with 388 college students from various disciplines. Data were collected using a structured questionnaire covering demographic information, knowledge, and practices related to sun exposure and sunscreen use. Descriptive statistics, chi-square tests, and multivariate logistic regression analysis were employed to analyze the data. Results: The study comprised 53.9% females, with the majority aged 18-23 years. Formal education on sun exposure dangers was lacking for 43.0% of participants. The most recognized consequences of excessive sun exposure were sunburn (80.6%) and skin cancer (74.4%). Intermediate knowledge of sun exposure effects was most common (40.7%). Sunscreen use was inconsistent, with 27.3% never using it during peak sunlight hours. Factors influencing sunscreen use included weather conditions and healthcare provider recommendations. Males were significantly less likely to use sunscreen. First-year students and participants without formal education on sun exposure were less likely to use sunscreen regularly. Conclusion: Despite awareness of the risks associated with excessive sun exposure, sunscreen use among college students in Saudi Arabia is inconsistent and influenced by various factors, including gender and education level. These findings highlight the need for enhanced educational initiatives to promote regular sunscreen use and other sun protection behaviors to mitigate the risk of skin conditions associated with sun exposure.