沙特阿拉伯慢性病患者关于使用人工智能提高药物依从性的知识、态度和看法

IF 2 3区 医学 Q2 MEDICINE, GENERAL & INTERNAL
Patient preference and adherence Pub Date : 2025-06-19 eCollection Date: 2025-01-01 DOI:10.2147/PPA.S519427
Safaa M Alsanosi, Asayel Q Aldajani, Hasnaa A Gheliwi, Manar M Alotibi, Ghadi S Bokhari, Orjuwan A Almatrafi, Abdulelah K Alqawlaq, Jakleen Z Abujamai, Mohammed Shaikhomer, Yosra Z Alhindi, Asim M Alshanberi
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引用次数: 0

摘要

背景:尽管存在数据隐私和监管等挑战,人工智能(AI)正在推动全球和沙特阿拉伯的医疗保健,提高患者护理、诊断和管理效率。本研究探讨了沙特阿拉伯麦加地区慢性患者在药物依从性方面关于AI的知识、态度和看法(KAP)。方法:对2024年7月1日至12月31日在沙特阿拉伯麦加地区的慢性疾病患者进行横断面研究。该研究包括麦加地区接受初级保健的成年慢性病患者(≥18岁)。使用描述性统计和综合评分分析KAP水平,并通过Pearson卡方检验评估人口统计学关联(结果:共有385名参与者纳入研究。大多数参与者是女性(60%),50岁或以上的群体所占比例最高(51.2%)。报告最多的慢性疾病是糖尿病(30.7%)、高血压(19.7%)和哮喘(14%)。72.7%的研究参与者的知识水平处于良好水平,45.5%的研究参与者对人工智能的作用持积极态度。50.9%的人认为“高”,但23.4%的人认为“低”。人口统计学因素,尤其是年龄,显著改善了KAP (p值分别为0.048、0.046和0.031)。58.2%的知识水平良好的参与者对人工智能在药物依从性中的作用持积极态度,而知识水平较差的参与者只有11.4% (p=0.001)。关于人工智能在药物依从性中的作用的感知水平的变化在人口统计学中是明显的,在年龄和总体知识水平上发现了统计学上显著的关联(p值分别为0.031和0.001)。结论:结果突出了人工智能在保持以人为本的方法的同时提高药物依从性和医疗效率的潜力。为了确保有效的集成,解决与隐私、信任和减少人际互动相关的问题至关重要。人工智能应该被定位为一种辅助工具,补充而不是取代人类护理,透明的治理和有针对性的教育发挥关键作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Knowledge, Attitudes, and Perceptions of Chronic Patients in Saudi Arabia Regarding the Use of Artificial Intelligence to Improve Medication Adherence.

Knowledge, Attitudes, and Perceptions of Chronic Patients in Saudi Arabia Regarding the Use of Artificial Intelligence to Improve Medication Adherence.

Background: Artificial intelligence (AI) is advancing healthcare globally and in Saudi Arabia, enhancing patient care, diagnostics, and administrative efficiency, despite challenges such as data privacy and regulation. This study explores knowledge, attitudes, and perceptions (KAP) regarding AI in medication adherence among chronic patients in Makkah region, Saudi Arabia.

Methods: A cross-sectional study was conducted among patients with chronic diseases in the Makkah region, Saudi Arabia, from 1 July to 31 December 2024. The study included adult patients with chronic diseases (≥18 years) receiving primary care in the Makkah region. KAP levels were analyzed using descriptive statistics and composite scores, with demographic associations evaluated through Pearson chi-square tests (p<0.05).

Results: A total of 385 participants were included in the study. Most participants were women (60%), and those belonging to the 50 years or older group comprised the highest percentage (51.2%). The most reported chronic conditions were diabetes (30.7%), hypertension (19.7%), and asthma (14%). Knowledge levels were at a good level among 72.7% of the study participants, and 45.5% expressed a positive attitude towards AI's role. Perception was high among 50.9% of the respondents but low among 23.4%. Demographic factors, particularly age, significantly improved KAP (p-values of 0.048, 0.046, and 0.031, respectively). A positive attitude towards AI's role in medication adherence was observed in 58.2% of the participants with good knowledge levels compared to only 11.4% of those with poor knowledge (p=0.001). Variations in perception levels regarding AI's role in medication adherence were evident across demographics, with statistically significant associations found for age and overall knowledge level (p-values of 0.031 and 0.001, respectively).

Conclusion: The results highlight AI's potential to enhance medication adherence and healthcare efficiency while maintaining a human-centred approach. To ensure effective integration, it's crucial to address concerns related to privacy, trust, and reduced human interaction. AI should be positioned as a supportive tool that complements-not replaces-human care, with transparent governance and targeted education playing key roles.

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来源期刊
Patient preference and adherence
Patient preference and adherence MEDICINE, GENERAL & INTERNAL-
CiteScore
3.60
自引率
4.50%
发文量
354
审稿时长
6-12 weeks
期刊介绍: Patient Preference and Adherence is an international, peer reviewed, open access journal that focuses on the growing importance of patient preference and adherence throughout the therapeutic continuum. The journal is characterized by the rapid reporting of reviews, original research, modeling and clinical studies across all therapeutic areas. Patient satisfaction, acceptability, quality of life, compliance, persistence and their role in developing new therapeutic modalities and compounds to optimize clinical outcomes for existing disease states are major areas of interest for the journal. As of 1st April 2019, Patient Preference and Adherence will no longer consider meta-analyses for publication.
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