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Background: Osteoporosis, characterized by reduced bone mass and increased fracture risk, presents a significant public health challenge. Dual-energy X-ray Absorptiometry (DEXA) scans offer a reliable means of assessing bone mineral density (BMD) and detecting osteoporosis. The aim of this study is to assess awareness, attitude, and practice of women in the Jazan region toward DEXA scan. Methods: Data were collected through a self-administered online questionnaire. Statistical analysis was conducted using SPSS version 29.0. The total knowledge scores of participants were calculated to assess potential associations with sociodemographic data. A p-value of less than 0.05 was considered statistically significant. Results: Among 400 women, 230 (57.5%) had low knowledge scores primarily due to poor knowledge of the DEXA scan procedure. Merely 39 women had undergone a DEXA scan mainly due to medical prescription (n = 22, 56.4%). Total knowledge scores were significantly higher among women with high monthly incomes (p = 0.019) and those working in medical-related jobs (p = 0.017). Conclusions: This study underscores the need for targeted interventions to improve awareness of DEXA scans among women in Jazan City. Additionally, the findings suggest that socioeconomic factors may influence awareness levels, emphasizing the importance of tailored educational strategies to reach diverse demographics.
RESUMEN
Background The use of artificial intelligence (AI) in healthcare continues to spark interest and has been the subject of extensive discussion in recent years as well as its potential effects on future medical specialties, including radiology. In this study, we aimed to study the impact of AI on the preference of medical students at Jazan University in choosing radiology as a future specialty. Methodology An observational cross-sectional study was conducted using a pre-tested self-administered online questionnaire among medical students at Jazan University. Data were cleaned, coded, entered, and analyzed using SPSS (SPSS Inc., USA) version 25. Statistical significance was defined as a P-value of less than 0.05. We examined the respondents' preference for radiology rankings with the presence and absence of AI. Radiology's ranking as a preferred specialty with or without AI integration was statistically analyzed for associations with baseline characteristics, personal opinions, and previous exposures among those who had radiology as one of their top three options. Results Approximately 27.4% of males and 28.3% of females ranked radiology among their top three preferred choices. Almost 65.2% were exposed to radiology topics through pre-clinical lectures. The main sources of information about AI for the studied group were medical students (41%) and the Internet (27.5%). The preference of students for radiology was significantly affected when it is assessed by AI (P < 0.05). Around (16.1%) of those who chose radiology as one of their top three choices strongly agree that AI will decrease the job opportunities for radiologists. Logistic regression analysis showed that being a female is significantly associated with an increased chance to replace radiology with other specialty when it is integrated with AI (Crude odds ratio (COR) = 1.91). Conclusion Our results demonstrated that the students' choices were significantly affected by the presence of AI. Thereover, to raise medical students' knowledge and awareness of the potential positive effects of AI, it is necessary to organize an educational campaign, webinars, and conferences.