Eton David T, Yost Kathleen J
Outcomes Research Branch, Healthcare Delivery Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Rockville, MD, USA.
Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
J Multimorb Comorb. 2025 Jun 23;15:26335565251350923. doi: 10.1177/26335565251350923. eCollection 2025 Jan-Dec.
The Patient Experience with Treatment and Self-management (PETS) is a valid self-report measure of treatment burden. The objective of this analysis is to determine severity cut points for its scores.
Data from two survey studies of adults with multimorbidity were used to determine estimates of low, moderate, and high burden for twelve PETS scores. Anchor-based analyses were used to map mean PETS scores onto scores of other self-report measures, including physical and mental health, self-efficacy, and activity limitations. Low, medium, and high scores on the anchors were based on published thresholds or tertile splits of score distributions. Mean PETS scores were compared across levels of the anchor variable using analysis of variance (ANOVA) then summarized to produce burden severity cut points.
Study 1 featured survey data from 332 adults with multimorbidity (mean age = 66 years, 56% female); study 2 featured survey data from 439 adults with multimorbidity (mean age = 60 years, 62% female). Anchor measures were correlated with PETS scores at rho≥ 0.30. ANOVAs comparing PETS scores across the levels of each anchor variable were all significant (s< .001). Estimates were placed into data tables. Cut scores for discriminating treatment burden severity levels were identified as the midpoint between the mean PETS scores associated with adjacent anchor categories (e.g., low vs. medium and medium vs. high burden), rounded to the nearest whole number.
Severity thresholds can improve the interpretability of PETS scores. The preliminary estimates derived require verification in future studies.
患者治疗与自我管理体验(PETS)是一种有效的治疗负担自我报告测量方法。本分析的目的是确定其分数的严重程度切点。
来自两项针对患有多种疾病的成年人的调查研究的数据,用于确定12个PETS分数的低、中、高负担估计值。基于锚定的分析用于将PETS平均分数映射到其他自我报告测量的分数上,包括身心健康、自我效能和活动限制。锚定指标的低、中、高分基于已发表的阈值或分数分布的三分位数划分。使用方差分析(ANOVA)比较锚定变量各水平上的PETS平均分数,然后进行汇总以产生负担严重程度切点。
研究1采用了332名患有多种疾病的成年人的调查数据(平均年龄 = 66岁,56%为女性);研究2采用了439名患有多种疾病的成年人的调查数据(平均年龄 = 60岁,62%为女性)。锚定指标与PETS分数的相关性为rho≥ 0.30。比较每个锚定变量各水平上PETS分数的方差分析均具有显著性(s< .001)。估计值被列入数据表。区分治疗负担严重程度水平的切割分数被确定为与相邻锚定类别相关的PETS平均分数之间的中点(例如,低负担与中等负担以及中等负担与高负担),四舍五入到最接近的整数。
严重程度阈值可以提高PETS分数的可解释性。得出的初步估计值需要在未来的研究中进行验证。