Beutler Larry E, Someah Kathleen, Kimpara Satoko, Miller Kimberley
Palo Alto University, USA.
Int J Clin Health Psychol. 2016 Jan-Apr;16(1):99-108. doi: 10.1016/j.ijchp.2015.08.001. Epub 2015 Oct 9.
Reviews the emergence of research on fitting treatment procedures to the unique needs and proclivities of patients. Traditional research on efficacy of psychotherapy focuses on the role of interventions and theoretical brands, minimizing factors that cannot be randomly assigned. This line of research has not realized its initial and desired promise, perhaps because it fails to incorporate into the study of psychotherapy important and effective treatment variations that are associated with therapist and non-diagnostic patient factors. Contemporary efforts to "fit" treatments to patients emphasize the roles of interventions, participant factors, and contextual/relationship factors. For these complex interactions, any of which reflect factors that cannot be randomly assigned, randomized clinical trials (RCT) protocols are inappropriate as a "gold standard". Several studies are presented which illustrate not only the predictive power of incorporating both treatment mediators and moderators into the realm of psychotherapy study, but the value of a multi-method approach to research. Converging studies moreover, provide a way to incorporate matching algorithms into decisions about assigning optimal treatments.
回顾了针对患者独特需求和倾向来调整治疗程序的研究的出现。传统的心理治疗疗效研究侧重于干预措施和理论流派的作用,将无法随机分配的因素最小化。这一研究路线尚未实现其最初的预期承诺,可能是因为它未能将与治疗师和非诊断性患者因素相关的重要且有效的治疗差异纳入心理治疗研究。当代使治疗“适配”患者的努力强调了干预措施、参与者因素以及情境/关系因素的作用。对于这些复杂的相互作用,其中任何一个都反映了无法随机分配的因素,随机临床试验(RCT)方案作为“金标准”并不合适。文中呈现了几项研究,这些研究不仅说明了将治疗中介因素和调节因素纳入心理治疗研究领域的预测能力,还展示了多方法研究途径的价值。此外,多项研究汇聚起来,提供了一种将匹配算法纳入关于分配最佳治疗方案决策的方法。