Cook Paul F, Schmiege Sarah J, Starr Whitney, Carrington Jane M, Bradley-Springer Lucy
Paul F. Cook, PhD, is Associate Professor; and Sarah J. Schmiege, PhD, is Associate Professor, University of Colorado College of Nursing, Aurora. Whitney Starr, MSN, NP, is Instructor, University of Colorado School of Medicine, Aurora. Jane M. Carrington, PhD, RN, is Assistant Professor, University of Arizona College of Nursing, Tucson. Lucy Bradley-Springer, PhD, FAAN, ACRN, is Associate Professor Emeritus, University of Colorado School of Medicine, Aurora.
Nurs Res. 2017 Jul/Aug;66(4):275-285. doi: 10.1097/NNR.0000000000000216.
Many persons living with HIV (PLWH) are nonadherent to medication. Trait level measures that ask about predictors of adherence in the abstract may not adequately capture state level daily variability that more directly impacts adherence.
This preliminary study was designed to test six predictors of electronically monitored adherence at both the state and trait levels and to compare their relative effects.
Using a smartphone, 87 PLWH completed randomly cued daily surveys on thoughts, mood, stress, coping, social support, and treatment motivation. All participants also completed baseline surveys on each construct. These state and trait variables were tested as prospective predictors of next-day adherence in multilevel models, and their relative importance was quantified. The analysis sample consisted of 53 PLWH who stored their most frequent antiretroviral medication in a bottle that time-stamped openings to measure adherence.
Higher state level motivation, OR = 1.55, 95% CI [1.07, 2.24], and negative mood, OR = 1.33, 95% CI [1.07, 1.63], predicted greater adherence the following day. Importantly, these effects were only found at the state level. Trait level control beliefs predicted greater adherence, OR = 1.65, 95% CI [1.17, 2.35], but contrary to prediction, validated trait level measures of mood, stress, coping, social support, and motivation did not.
Trait and state level measures predicted adherence, but there were differences between them. Motivation for treatment and negative mood predicted adherence when measured the preceding day, but not as aggregate measures. At the trait level, only control beliefs predicted adherence. Researchers should consider state level variations in mood and motivation as possible explanations for nonadherence. Interventions could be developed to target state level variables.
许多艾滋病毒感染者（PLWH）不坚持服药。询问依从性预测因素的特质水平测量可能无法充分捕捉更直接影响依从性的状态水平每日变化情况。
本初步研究旨在测试6个在状态和特质水平上电子监测依从性的预测因素，并比较它们的相对影响。
87名艾滋病毒感染者使用智能手机完成了关于思想、情绪、压力、应对方式、社会支持和治疗动机的随机提示每日调查。所有参与者还完成了关于每个构念的基线调查。这些状态和特质变量在多水平模型中作为次日依从性的前瞻性预测因素进行测试，并对它们的相对重要性进行了量化。分析样本包括53名艾滋病毒感染者，他们将最常用的抗逆转录病毒药物储存在一个能对打开瓶盖时间进行标记以测量依从性的瓶子里。
较高的状态水平动机（OR = 1.55，95%CI [1.07, 2.24]）和消极情绪（OR = 1.33，95%CI [1.07, 1.63]）预测次日有更高依从性。重要的是，这些影响仅在状态水平上被发现。特质水平的控制信念预测更高依从性（OR = 1.65，95%CI [1.17, 2.35]），但与预测相反，经过验证的特质水平情绪、压力、应对方式、社会支持和动机测量指标并未如此。
特质和状态水平测量指标都能预测依从性，但二者存在差异。治疗动机和消极情绪在前一天测量时能预测依从性，但作为总体测量指标时则不然。在特质水平上，只有控制信念能预测依从性。研究人员应将情绪和动机的状态水平变化视为不依从的可能解释。可以开发针对状态水平变量的干预措施。
