Jorge Helena, Duarte Isabel C, Correia Bárbara R, Barros Luísa, Relvas Ana Paula, Castelo-Branco Miguel
PIDFIF* and Coimbra Institute for Biomedical Imaging and Translational Research, CIBIT/ICNAS, University of Coimbra, Coimbra-Lisboa, Portugal.
Coimbra Institute for Biomedical Imaging and Translational Research, CIBIT/ICNAS, University of Coimbra, Portugal.
Psychol Med. 2021 Mar 18;52(15):1-9. doi: 10.1017/S0033291721000386.
Neurobehavioral decision profiles have often been neglected in chronic diseases despite their direct impact on major public health issues such as treatment adherence. This remains a major concern in diabetes, despite intensive efforts and public awareness initiatives regarding its complications. We hypothesized that high rates of low adherence are related to risk-taking profiles associated with decision-making phenotypes. If this hypothesis is correct, it should be possible to define these endophenotypes independently based both on dynamic measures of metabolic control (HbA1C) and multidimensional behavioral profiles.
In this study, 91 participants with early-stage type 1 diabetes fulfilled a battery of self-reported real-world risk behaviors and they performed an experimental task, the Balloon Analogue Risk Task (BART).
K-means and two-step cluster analysis suggest a two-cluster solution providing information of distinct decision profiles (concerning multiple domains of risk-taking behavior) which almost perfectly match the biological partition, based on the division between stable or improving metabolic control (MC, N = 49) v. unstably high or deteriorating states (NoMC, N = 42). This surprising dichotomy of behavioral phenotypes predicted by the dynamics of HbA1C was further corroborated by standard statistical testing. Finally, the BART game enabled to identify groups differences in feedback learning and consequent behavioral choices under ambiguity, showing distinct group choice behavioral patterns.
These findings suggest that distinct biobehavioral endophenotypes can be related to the success of metabolic control. These findings also have strong implications for programs to improve patient adherence, directly addressing risk-taking profiles.
尽管神经行为决策特征对诸如治疗依从性等重大公共卫生问题有直接影响，但在慢性疾病中常常被忽视。在糖尿病领域，这仍是一个主要问题，尽管人们为其并发症付出了巨大努力并开展了公众意识提升活动。我们推测，低依从率较高与决策表型相关的冒险特征有关。如果这一假设正确，那么应该能够基于代谢控制的动态指标（糖化血红蛋白）和多维度行为特征独立定义这些内表型。
在本研究中，91名1型糖尿病早期患者完成了一系列自我报告的现实世界风险行为调查，并进行了一项实验任务——气球模拟风险任务（BART）。
K均值聚类和两步聚类分析表明，基于稳定或改善的代谢控制（MC，N = 49）与不稳定的高代谢或代谢恶化状态（NoMC，N = 42）的划分，存在一个双聚类解决方案，该方案提供了不同决策特征（涉及冒险行为的多个领域）的信息，几乎与生物学划分完美匹配。糖化血红蛋白动态预测的这种行为表型的惊人二分法通过标准统计检验得到了进一步证实。最后，BART游戏能够识别在反馈学习以及在模糊情况下随之产生的行为选择方面的组间差异，显示出不同的组选择行为模式。
这些发现表明，不同的生物行为内表型可能与代谢控制的成功与否相关。这些发现对旨在提高患者依从性、直接针对冒险特征的项目也具有重要意义。
