Case Western Reserve University, Frances Payne Bolton School of Nursing, Cleveland, OH, United States of America.
Case Western Reserve University, Frances Payne Bolton School of Nursing, Cleveland, OH, United States of America.
Appl Nurs Res. 2020 Aug;54:151301. doi: 10.1016/j.apnr.2020.151301. Epub 2020 May 15.
We aimed to (1) describe the amount of treatment burden experienced in the primary care population diagnosed with chronic conditions and (2) examine if cumulative and task-specific treatment burden were predictors of medication, exercise, and dietary adherence in patients diagnosed with chronic conditions.
We conducted a prospective, descriptive, cross-sectional study.
We enrolled 149 men and women from a single primary care clinic. Participants completed self-report surveys with data collected between September 2019 and December 2019. Our primary statistical analyses consisted of multivariate regression modeling.
The sample experience a moderate amount of treatment burden (M = 38.22; SD = 31.83). We found strong, negative correlations between both cumulative and task-specific burden in relation to medication, exercise, and dietary adherence (p < .001). Significant multivariate models (p < .001), controlling for sample demographics, demonstrated cumulative treatment burden predicted medication adherence, whereas task-specific burden predicted medication, exercise, and dietary adherence outcomes, with model effect sizes ranging from moderate (0.20) to large (0.54).
Results demonstrate higher levels of cumulative and task-specific treatment burden predict medication, exercise, and dietary adherence within a sample diagnosed with various chronic conditions. These findings indicate the potential for using treatment burden screening in the clinical setting to identify individuals at risk for poor self-management adherence. Treatment burden screening also enables the provider to determine areas of high burden affecting self-management adherence in order to design an effective treatment plan using targeted interventions, resources, or education to reduce patient burden in order to improve adherence.
（1）描述在被诊断患有慢性病的初级保健人群中所经历的治疗负担量，（2）检验累积性和任务特异性治疗负担是否可预测患有慢性病患者的药物、运动和饮食依从性。
我们进行了一项前瞻性、描述性、横断面研究。
我们从一家单一的初级保健诊所招募了 149 名男性和女性参与者。参与者完成了自我报告调查，数据收集于 2019 年 9 月至 12 月之间。我们的主要统计分析包括多元回归建模。
该样本经历了中等程度的治疗负担（M=38.22；SD=31.83）。我们发现，在药物、运动和饮食依从性方面，累积性和任务特异性负担之间存在很强的负相关（p<0.001）。多元模型具有统计学意义（p<0.001），控制了样本人口统计学特征，表明累积性治疗负担可预测药物依从性，而任务特异性负担可预测药物、运动和饮食依从性结果，模型效应大小从中等（0.20）到较大（0.54）不等。
结果表明，更高水平的累积性和任务特异性治疗负担可预测患有各种慢性病的患者的药物、运动和饮食依从性。这些发现表明，在临床环境中使用治疗负担筛查来识别自我管理依从性差的个体具有潜力。治疗负担筛查还可以使提供者确定影响自我管理依从性的高负担领域，以便设计有效的治疗计划，使用有针对性的干预措施、资源或教育来减轻患者负担，从而提高依从性。
