Department of Human Development and Family Studies, Michigan State University, East Lansing, MI, United States of America.
Division of Psychiatry and Behavioral Medicine, Michigan State University, Grand Rapids, MI, United States of America.
PLoS One. 2022 Oct 27;17(10):e0276441. doi: 10.1371/journal.pone.0276441. eCollection 2022.
Depressive disorders are the leading contributor to medical disability, yet only 22% of depressed patients receive adequate treatment in a given year. Response to treatment varies widely among individuals with depression, and poor response to one treatment does not signal poor response to others. In fact, half of patients who do not recover from a first-line psychotherapy will recover from a second option. Attempts to personalize psychotherapy to patient characteristics have produced better outcomes than usual care, but research on personalized psychotherapy is still in its infancy. The present study explores a new method for personalizing psychotherapy for depression through simulation modeling. In this study, we developed a system dynamics simulation model of depression based on one of the major mechanisms of depression in the literature and investigated the trend of depressive symptoms under different conditions and treatments. Our simulation outputs show the importance of individualized services with appropriate timing, and reveal a new method for personalizing psychotherapy to heterogeneous individuals. Future research is needed to expand the model to include additional mechanisms of depression.
抑郁障碍是导致医疗残疾的主要原因，但在特定年份，仅有 22%的抑郁患者接受了足够的治疗。个体对治疗的反应差异很大，对一种治疗的反应不佳并不表示对其他治疗的反应不佳。事实上，一半未从一线心理治疗中康复的患者将从第二种选择中康复。针对患者特征对心理治疗进行个性化尝试已经产生了比常规护理更好的结果，但个性化心理治疗的研究仍处于起步阶段。本研究通过模拟模型探索了一种针对抑郁的心理治疗个性化的新方法。在这项研究中，我们根据文献中抑郁的主要机制之一开发了一种基于系统动力学的抑郁模拟模型，并研究了不同条件和治疗下抑郁症状的趋势。我们的模拟结果表明了个体化服务与适当时间的重要性，并揭示了一种针对异质个体的心理治疗个性化的新方法。需要进一步的研究来扩展模型，纳入更多的抑郁机制。
