Joel Ladner, Alshurafa Sawsan, Anas Nofal, Mohamed Rana, Malak Ammar, Joseph Saba, Etienne Audureau
{"title":"影响阿联酋慢性病药物依从性的因素:一项前瞻性队列研究,2021-2022","authors":"Joel Ladner, Alshurafa Sawsan, Anas Nofal, Mohamed Rana, Malak Ammar, Joseph Saba, Etienne Audureau","doi":"10.57264/cer-2025-0020","DOIUrl":null,"url":null,"abstract":"<p><p><b>Aim:</b> To assess the evolution of chronic disease medication adherence factors and identify factors predictive of long-term adherence in the UAE. <b>Materials & methods:</b> Patients ≥18 years old; newly diagnosed with one of the following diseases: ankylosing spondylitis, heart failure, multiple sclerosis, psoriasis, or asthma and prescribed long-term medication were followed ≥12 months (M12), then categorized as followed (continued treatment by prescribing physician) or lost to follow-up. Adherence was assessed using the Patient Needs Assessment Tool (PNAT), which is based on the WHO's five dimensional framework. <b>Results:</b> A total of 111 patients were included, 17 (15.3%) were lost of follow-up at M12. Time spent in consultation by medical doctor (MD) (adjusted odds ratio = 6.89, 95% CI = 2.07-12.76) and anxiety and stress level (adjusted odds ratio = 0.18, 95% CI = 0.11-0.67) were significant predictive factors associated with remaining on treatment at M12. Self organizing map methodology identified predictive factors associated with remaining on treatment at M12 as: patient satisfaction with time spent with prescribing MD, patient involvement in treatment decision, disease management ability, satisfaction with support from family/friends, low dependence on others for daily life activities, difficulties joining community activities, and acknowledgement of an influential role of cultural habits/spiritual beliefs. The highest means score differences from M0 to M12 were for difficulties joining community activities (difference [diff] M12-M0 = 1.32, p < 10<sup>-4</sup>), role of cultural habits (diff = 1.05, p < 10<sup>-4</sup>), role of spiritual beliefs (diff = 1.02, p < 10<sup>-4</sup>), patient involved in treatment decision (diff = 0.67, p = 0.007), and memory difficulties (diff = 0.62, p < 10<sup>-4</sup>). <b>Conclusion:</b> Socio-economic factors changed most significantly over 12 months. The identified factors may be used to develop strategies to improve patient satisfaction with the time they spend with the prescribing MD as well as reduce stress, each of which may improve medication adherence. Understanding patient behavior and accurately quantifying adherence are essential for improving outcomes for patients prescribed chronic disease medication in Gulf Arabic countries.</p>","PeriodicalId":15539,"journal":{"name":"Journal of comparative effectiveness research","volume":" ","pages":"e250020"},"PeriodicalIF":1.9000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Factors impacting chronic disease medication adherence in the UAE: a prospective cohort study, 2021-2022.\",\"authors\":\"Joel Ladner, Alshurafa Sawsan, Anas Nofal, Mohamed Rana, Malak Ammar, Joseph Saba, Etienne Audureau\",\"doi\":\"10.57264/cer-2025-0020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b>Aim:</b> To assess the evolution of chronic disease medication adherence factors and identify factors predictive of long-term adherence in the UAE. <b>Materials & methods:</b> Patients ≥18 years old; newly diagnosed with one of the following diseases: ankylosing spondylitis, heart failure, multiple sclerosis, psoriasis, or asthma and prescribed long-term medication were followed ≥12 months (M12), then categorized as followed (continued treatment by prescribing physician) or lost to follow-up. Adherence was assessed using the Patient Needs Assessment Tool (PNAT), which is based on the WHO's five dimensional framework. <b>Results:</b> A total of 111 patients were included, 17 (15.3%) were lost of follow-up at M12. Time spent in consultation by medical doctor (MD) (adjusted odds ratio = 6.89, 95% CI = 2.07-12.76) and anxiety and stress level (adjusted odds ratio = 0.18, 95% CI = 0.11-0.67) were significant predictive factors associated with remaining on treatment at M12. Self organizing map methodology identified predictive factors associated with remaining on treatment at M12 as: patient satisfaction with time spent with prescribing MD, patient involvement in treatment decision, disease management ability, satisfaction with support from family/friends, low dependence on others for daily life activities, difficulties joining community activities, and acknowledgement of an influential role of cultural habits/spiritual beliefs. The highest means score differences from M0 to M12 were for difficulties joining community activities (difference [diff] M12-M0 = 1.32, p < 10<sup>-4</sup>), role of cultural habits (diff = 1.05, p < 10<sup>-4</sup>), role of spiritual beliefs (diff = 1.02, p < 10<sup>-4</sup>), patient involved in treatment decision (diff = 0.67, p = 0.007), and memory difficulties (diff = 0.62, p < 10<sup>-4</sup>). <b>Conclusion:</b> Socio-economic factors changed most significantly over 12 months. The identified factors may be used to develop strategies to improve patient satisfaction with the time they spend with the prescribing MD as well as reduce stress, each of which may improve medication adherence. Understanding patient behavior and accurately quantifying adherence are essential for improving outcomes for patients prescribed chronic disease medication in Gulf Arabic countries.</p>\",\"PeriodicalId\":15539,\"journal\":{\"name\":\"Journal of comparative effectiveness research\",\"volume\":\" \",\"pages\":\"e250020\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of comparative effectiveness research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.57264/cer-2025-0020\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/5/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of comparative effectiveness research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.57264/cer-2025-0020","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/5 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
摘要
目的:评估阿联酋慢性疾病药物依从性因素的演变,并确定预测长期依从性的因素。材料与方法:患者年龄≥18岁;新诊断为以下疾病之一:强直性脊柱炎、心力衰竭、多发性硬化症、牛皮癣或哮喘,并处方长期药物随访≥12个月(M12),然后分类为随访(由处方医生继续治疗)或未随访。使用患者需求评估工具(PNAT)对依从性进行了评估,该工具基于世卫组织的五维框架。结果:共纳入111例患者,17例(15.3%)在M12时失访。就诊时间(MD)(校正优势比= 6.89,95% CI = 2.07-12.76)和焦虑和压力水平(校正优势比= 0.18,95% CI = 0.11-0.67)是与M12继续治疗相关的显著预测因素。自组织地图方法确定了与M12继续治疗相关的预测因素:患者对处方MD时间的满意度、患者对治疗决策的参与、疾病管理能力、对家人/朋友支持的满意度、日常生活活动对他人的依赖性低、参加社区活动的困难,以及承认文化习惯/精神信仰的影响作用。M0与M12的平均得分差异最大的是参加社区活动困难(差异[diff] M12-M0 = 1.32, p -4)、文化习惯的作用(差异= 1.05,p -4)、精神信仰的作用(差异= 1.02,p -4)、患者参与治疗决策(差异= 0.67,p = 0.007)和记忆困难(差异= 0.62,p -4)。结论:社会经济因素在12个月内变化最显著。确定的因素可以用来制定策略,以提高患者对他们花在处方MD的时间的满意度,并减少压力,每一个都可以提高药物依从性。了解患者行为和准确量化依从性对于改善海湾阿拉伯国家慢性病患者处方药物治疗的结果至关重要。
Factors impacting chronic disease medication adherence in the UAE: a prospective cohort study, 2021-2022.
Aim: To assess the evolution of chronic disease medication adherence factors and identify factors predictive of long-term adherence in the UAE. Materials & methods: Patients ≥18 years old; newly diagnosed with one of the following diseases: ankylosing spondylitis, heart failure, multiple sclerosis, psoriasis, or asthma and prescribed long-term medication were followed ≥12 months (M12), then categorized as followed (continued treatment by prescribing physician) or lost to follow-up. Adherence was assessed using the Patient Needs Assessment Tool (PNAT), which is based on the WHO's five dimensional framework. Results: A total of 111 patients were included, 17 (15.3%) were lost of follow-up at M12. Time spent in consultation by medical doctor (MD) (adjusted odds ratio = 6.89, 95% CI = 2.07-12.76) and anxiety and stress level (adjusted odds ratio = 0.18, 95% CI = 0.11-0.67) were significant predictive factors associated with remaining on treatment at M12. Self organizing map methodology identified predictive factors associated with remaining on treatment at M12 as: patient satisfaction with time spent with prescribing MD, patient involvement in treatment decision, disease management ability, satisfaction with support from family/friends, low dependence on others for daily life activities, difficulties joining community activities, and acknowledgement of an influential role of cultural habits/spiritual beliefs. The highest means score differences from M0 to M12 were for difficulties joining community activities (difference [diff] M12-M0 = 1.32, p < 10-4), role of cultural habits (diff = 1.05, p < 10-4), role of spiritual beliefs (diff = 1.02, p < 10-4), patient involved in treatment decision (diff = 0.67, p = 0.007), and memory difficulties (diff = 0.62, p < 10-4). Conclusion: Socio-economic factors changed most significantly over 12 months. The identified factors may be used to develop strategies to improve patient satisfaction with the time they spend with the prescribing MD as well as reduce stress, each of which may improve medication adherence. Understanding patient behavior and accurately quantifying adherence are essential for improving outcomes for patients prescribed chronic disease medication in Gulf Arabic countries.
期刊介绍:
Journal of Comparative Effectiveness Research provides a rapid-publication platform for debate, and for the presentation of new findings and research methodologies.
Through rigorous evaluation and comprehensive coverage, the Journal of Comparative Effectiveness Research provides stakeholders (including patients, clinicians, healthcare purchasers, and health policy makers) with the key data and opinions to make informed and specific decisions on clinical practice.