Department of Psychological and Brain Sciences, University of Louisville, Louisville, Kentucky, USA.
Int J Eat Disord. 2023 Aug;56(8):1674-1680. doi: 10.1002/eat.23982. Epub 2023 May 10.
Eating disorders (EDs) are serious mental illnesses with high mortality and relapse rates and carry significant societal and personal costs. Nevertheless, there are few evidence-based treatments available. One aspect that makes treatment difficult is the high heterogeneity in symptom presentation. This heterogeneity makes it challenging for clinicians to identify pertinent treatment targets. Personalized treatment based on idiographic models may be well-suited to address this heterogeneity, and, in turn, presumably improve treatment outcomes.
In the current randomized controlled trial, participants will be randomly assigned to either 20 sessions of enhanced cognitive behavioral therapy (CBT-E) or transdiagnostic network-informed personalized treatment for EDs (T-NIPT-ED). Assessment of ED symptoms, clinical impairment, and quality of life will occur at pre-, mid-, posttreatment, and 1-month follow-up.
We will examine the acceptability and feasibility of T-NIPT-ED compared to CBT-E. We also will test the initial clinical efficacy of T-NIPT-ED versus CBT-E on clinical outcomes (i.e., ED symptoms and quality of life). Finally, we will test if the network-identified precision targets are the mechanisms of change.
Ultimately, this research may inform the development and dissemination of evidence-based personalized treatments for EDs and serve as an exemplar for personalized treatment development across the broader field of psychiatry.
Current evidence-based treatments for eating disorders result in low rates of recovery, especially for adults with AN. Our study aims to test the feasibility, acceptability, and clinical efficacy of a data-driven, individualized approach to ED treatment, network-informed personalized treatment, compared to the current evidence-based treatment for EDs, Enhanced CBT. Findings have the potential to improve treatment outcomes for EDs by identifying and targeting core symptoms maintaining EDs.
饮食失调（ED）是一种严重的精神疾病，死亡率和复发率高，给社会和个人带来巨大的负担。然而，现有的治疗方法却很少。其中一个使治疗变得困难的因素是症状表现的高度异质性。这种异质性使得临床医生难以确定相关的治疗目标。基于个体模型的个性化治疗可能非常适合解决这种异质性，并有望改善治疗结果。
在目前的随机对照试验中，参与者将被随机分配到增强认知行为疗法（CBT-E）或跨诊断网络启发的个性化 ED 治疗（T-NIPT-ED）组中。将在治疗前、治疗中期、治疗后和 1 个月随访时评估 ED 症状、临床障碍和生活质量。
我们将比较 T-NIPT-ED 和 CBT-E 的可接受性和可行性。我们还将测试 T-NIPT-ED 与 CBT-E 对临床结果（即 ED 症状和生活质量）的初始临床疗效。最后，我们将测试网络识别的精准治疗目标是否是治疗变化的机制。
最终，这项研究可能会为 ED 的循证个性化治疗的发展和传播提供信息，并为整个精神病学领域的个性化治疗发展提供范例。
目前针对饮食失调的循证治疗方法的康复率较低，尤其是对于 AN 成人患者。我们的研究旨在测试基于数据的个体化 ED 治疗方法（网络启发的个性化治疗）与目前针对 ED 的循证治疗方法（增强 CBT）相比的可行性、可接受性和临床疗效。研究结果有可能通过确定和针对维持 ED 的核心症状来改善 ED 的治疗结果。
