Individual differences in the effects of the ACTION-PAC intervention: an application of personalized medicine in the prevention and treatment of obesity.

Individual differences in the effects of the ACTION-PAC intervention: an application of personalized medicine in the prevention and treatment of obesity.
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ACTION-PAC干预效果的个体差异:个性化医疗在肥胖预防和治疗中的应用。

DOI:
10.1007/s10865-021-00274-2
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发表时间:
2022
影响因子:
3.1
通讯作者:
VanHorn,MLee
VanHorn,MLee
中科院分区:
心理学3区
文献类型:
--
作者:
Kuhlemeier,Alena;Jaki,Thomas;Jimenez,ElizabethY;Kong,AlbertaS;Gill,Hope;Chang,Chi;Resnicow,Ken;Wilson,DawnK;VanHorn,MLee

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人们越来越关注使用个性化药物方法预防或治疗肥胖症,然而,很少有研究使用这些方法来确定治疗效果的个体差异。目前的研究表明,使用预测的个体治疗效果框架来测试ACTION-PAC干预效果的个体差异,该干预针对高中环境中肥胖的治疗和预防。我们展示了如何个性化医疗的方法可以用来测试显着的个体差异的干预反应,我们讨论了这些方法的潜力和局限性。在我们的例子中,25%的学生在预防性干预中,预测他们的BMI z分数降低0.39或更多,而在另一端,25%的学生预测他们的BMI z分数增加0.09或更多。在本文中,我们展示和讨论了使用个性化医疗方法的过程,并针对肥胖症进行干预,并讨论了从这种应用中吸取的教训。最终,这些方法有可能对临床医生和客户在治疗方案之间进行选择是有用的,但它们在帮助研究人员了解这些预测背后的机制方面的能力有限。
There is an increased interest in the use of personalized medicine approaches in the prevention or treatment of obesity, however, few studies have used these approaches to identify individual differences in treatment effects. The current study demonstrates the use of the predicted individual treatment effects framework to test for individual differences in the effects of the ACTION-PAC intervention, which targeted the treatment and prevention of obesity in a high school setting. We show how methods for personalized medicine can be used to test for significant individual differences in responses to an intervention and we discuss the potential and limitations of these methods. In our example, 25% of students in the preventive intervention, were predicted to have their BMI z-score reduced by 0.39 or greater, while at other end of the spectrum, 25% were predicted to have their BMI z-score increased by 0.09 or more. In this paper, we demonstrate and discuss the process of using methods for personalized medicine with interventions targeting adiposity and discuss the lessons learned from this application. Ultimately, these methods have the potential to be useful for clinicians and clients in choosing between treatment options, however they are limited in their ability to help researchers understand the mechanisms underlying these predictions.
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