Hayes and Hofmann’s paper¹ provides a new framework to conceptualize psychological therapy as a process-based clinical intervention. The authors describe the history of cognitive behavioral therapy (CBT) in three waves and formulate the process-based orientation as the step beyond theoretical orientations. They outline a shift from protocols treating syndromes to idiographic approaches using process-based clinical strategies to adapt treatment to the complexity of patients’ problems.

The main idea is to use knowledge derived from empirical findings on psychological change processes in CBT to tailor treatments to patients and include new evidence as it becomes available. Therefore, process-based therapy is presented as a conceptual framework open to new, empirically tested processes identified in international research on diverse samples and dedicated to the goal of evidence-based psychotherapy.

Overall, we welcome the development of process-based psychological therapy with­in the context of a larger trans-theoretical and integrative trend in clinical practice, train­ing, and theory building. There is no gen­eral agreement on the conceptualization of psychological therapies, and clinical services differ largely between and within countries. Furthermore, treatment models are often combined intuitively in clinical practice. The task for psychotherapy research is to improve this clinical decision-making process by grounding it in empirical data².

Hayes and Hofmann observe that, despite the many theoretical developments, the practice of psychological therapies has not seen a large improvement in success rates over the last decade. This conclusion of outcome research is receiving increasing attention and acceptance in the field². Therefore, it is no wonder that new modular and integrated concepts have emerged. The idea is to combine elements within or between different treatment orientations based on sound empirical data, with the goal of tailoring treatments to specific patient problems and needs^1-4.

Such trans-theoretical treatment concepts are complemented by recent transdiagnostic psychopathology research – for example, the Research Domain Criteria, the multivariate Hierarchical Taxonomy of Psychopathology, and network models. Psychological disorders are no longer seen as categorical entities, but as elements of a multidimensional and transdiagnostic model of psychopathology.

Beyond Hayes and Hofmann, we argue for a trans-theoretical perspective facilitated by data-informed clinical practice, research and training, and focusing particularly on patients not profiting from psychological therapies. Some recent and ongoing research trends can be delineated in this respect². These include the development of improved, standardized, freely available, and easy-to-apply mea­sures; new efforts in replication; new statistical methods (e.g., machine learning) to analyze large cross-sectional as well as intensive longitudinal datasets; improved research on processes and mechanisms of change; a better dissemination and cross-cultural adaptation of interventions, including Internet services⁵; and a better implementation of outcome monitoring and clinical navigation systems to support therapists to identify and treat patients at risk for treatment failure.

We see the chance for psychotherapy to become characterized by trans-theoretical, personalized, and evidence-based clinical practice and training. Implementing continuous multidimensional assessments in routine care and identifying negative developments early in treatment are particularly crucial. Given that the knowledge about moderators and mediators in our field is limited, any treatment application needs to be evaluated by its actual progress for the individual patient².

This development has the potential to help the field mature and to empower clinical interventions. The goal could be to move away from concepts based on average differences and broad clinical assumptions that are difficult to operationalize, and towards concrete outcomes and studies on subgroups of patients not profiting from treatment.

In recent years, concepts from precision mental health research and precision medicine have been introduced, driving these advancements forward^{6, 7}. Rather than choosing between treatment protocols, the aim of these developments is to tailor treatment to individual patients using empirical data. Evidence-based personalization in clinical practice might be improved by combining research on treatment prediction and selection with research on digital feedback and the application of decision support systems⁸.

At treatment onset, therapists are provided with prognostic information, for example based on machine learning approaches applied to large datasets in order to recommend the optimal treatment, treatment strategy, or therapist for an individual patient⁶. During treatment, therapists are made aware of patients at risk for treatment failure, dropout or self-harm by adaptive decision tools. Additionally, therapists are provided with feedback and clinical problem-solving tools to support treatment for these patients.

Currently, the implementation and prospective evaluation of such systems are rare. However, such studies and new developments are already on their way. For example, more than a decade of our department’s research activity has resulted in the devel­opment of a digital decision support and navigation system called the Trier Treatment Navigator (TTN). The system combines outcome tracking, prediction, and prescription tools, providing continuous feedback to clinicians and supporting them to apply targeted clinical strategies at the ­onset of and during treatment.

The online navigation system includes two components of patient-specific treatment recommendations: a) a pre-treatment clinical strategy recommendation and b) adaptive recommendations and support tools for patients at risk for treatment failure. The prospective evaluation on 538 patients showed an advantage in outcomes, with an effect size of about 0.3, when patients were treated with the recommended strategy during the first ten sessions. Furthermore, therapist symptom awareness, attitude, and confidence using the system were found to be significant predictors of outcome, while therapist-rated usefulness of such feedback moderated the feedback-outcome association^{2, 8}.

A similar approach, the Leeds Risk Index (LRI), was developed based on a sample of 1,347 patients and prognostically tested on 282 patients in the Improving Access to Psychological Therapies (IAPT) programme, to recommend either low or high intensity treatments⁷. Results indicated that such stratified care improves efficiency by generating comparable outcomes with less treatment sessions.

The goal of these developments is the time­ly translation of research into clinical practice. Of course, many more prospective studies are necessary. However, in the future, the field might be better able to operationalize change processes, regarding both how patients experience them and how therapists induce them. These developments could be the basis of a trans-theoretical, process-based, personalized and data-informed psychological treatment approach, which includes both an idiographic (e.g., intensive longitudinal assessments on single cases) and a nomothetic (e.g., large databases of patients and therapists) perspective. Such advancements could finally make a difference for patients previously not profiting from psychological interventions.

Hayes 和 Hofmann 的论文¹提供了一个新的框架，将心理治疗概念化为基于过程的临床干预。作者用三个波次描述了认知行为疗法 (CBT) 的历史，并将基于过程的取向制定为超越理论取向的一步。他们概述了从治疗综合征的方案到使用基于过程的临床策略的具体方法的转变，以使治疗适应患者问题的复杂性。

主要思想是利用从 CBT 中心理变化过程的经验发现中得出的知识，为患者量身定制治疗方法，并在新证据可用时包括在内。因此，基于过程的治疗被呈现为一个概念框架，它对新的、经过实证检验的过程开放，这些过程在对不同样本的国际研究中确定，并致力于循证心理治疗的目标。

Overall, we welcome the development of process-based psychological therapy with­in the context of a larger trans-theoretical and integrative trend in clinical practice, train­ing, and theory building. There is no gen­eral agreement on the conceptualization of psychological therapies, and clinical services differ largely between and within countries. Furthermore, treatment models are often combined intuitively in clinical practice. The task for psychotherapy research is to improve this clinical decision-making process by grounding it in empirical data².

Hayes and Hofmann observe that, despite the many theoretical developments, the practice of psychological therapies has not seen a large improvement in success rates over the last decade. This conclusion of outcome research is receiving increasing attention and acceptance in the field². Therefore, it is no wonder that new modular and integrated concepts have emerged. The idea is to combine elements within or between different treatment orientations based on sound empirical data, with the goal of tailoring treatments to specific patient problems and needs^1-4.

Such trans-theoretical treatment concepts are complemented by recent transdiagnostic psychopathology research – for example, the Research Domain Criteria, the multivariate Hierarchical Taxonomy of Psychopathology, and network models. Psychological disorders are no longer seen as categorical entities, but as elements of a multidimensional and transdiagnostic model of psychopathology.

Beyond Hayes and Hofmann, we argue for a trans-theoretical perspective facilitated by data-informed clinical practice, research and training, and focusing particularly on patients not profiting from psychological therapies. Some recent and ongoing research trends can be delineated in this respect². These include the development of improved, standardized, freely available, and easy-to-apply mea­sures; new efforts in replication; new statistical methods (e.g., machine learning) to analyze large cross-sectional as well as intensive longitudinal datasets; improved research on processes and mechanisms of change; a better dissemination and cross-cultural adaptation of interventions, including Internet services⁵; and a better implementation of outcome monitoring and clinical navigation systems to support therapists to identify and treat patients at risk for treatment failure.

We see the chance for psychotherapy to become characterized by trans-theoretical, personalized, and evidence-based clinical practice and training. Implementing continuous multidimensional assessments in routine care and identifying negative developments early in treatment are particularly crucial. Given that the knowledge about moderators and mediators in our field is limited, any treatment application needs to be evaluated by its actual progress for the individual patient².

这一发展有可能帮助该领域成熟并增强临床干预的能力。目标可能是摆脱基于平均差异和难以操作的广泛临床假设的概念，转向对未从治疗中获益的患者亚组的具体结果和研究。

近年来，精准心理健康研究和精准医学的概念被引入，推动了这些进步^{6, 7}。这些发展的目的不是在治疗方案之间进行选择，而是使用经验数据为个体患者量身定制治疗。通过将治疗预测和选择研究与数字反馈研究和决策支持系统的应用相结合，可以改善临床实践中的循证个性化⁸。

在治疗开始时，治疗师会获得预后信息，例如基于应用于大型数据集的机器学习方法，以便为个体患者⁶推荐最佳治疗、治疗策略或治疗师。在治疗过程中，治疗师通过适应性决策工具了解有治疗失败、辍学或自我伤害风险的患者。此外，还为治疗师提供反馈和解决临床问题的工具，以支持对这些患者的治疗。

目前，此类系统的实施和前瞻性评估很少见。然而，这样的研究和新的发展已经在路上。例如，我们系十多年的研究活动导致开发了一种称为 Trier Treatment Navigator (TTN) 的数字决策支持和导航系统。该系统结合了结果跟踪、预测和处方工具，为临床医生提供持续反馈并支持他们在治疗开始和治疗期间应用有针对性的临床策略。

在线导航系统包括患者特定治疗建议的两个组成部分：a) 治疗前临床策略建议和 b) 针对有治疗失败风险的患者的自适应建议和支持工具。对 538 名患者的前瞻性评估显示，当患者在前 10 次治疗期间接受推荐的策略治疗时，结果有优势，效果大小约为 0.3。此外，发现使用该系统的治疗师症状意识、态度和信心是结果的重要预测因子，而治疗师评定的此类反馈的有用性调节了反馈-结果关联^{2, 8}。

利兹风险指数 (LRI) 是一种类似的方法，是基于 1,347 名患者的样本开发的，并在改善心理治疗 (IAPT) 计划中对 282 名患者进行了预后测试，以推荐低强度或高强度治疗⁷。结果表明，这种分层护理通过减少治疗次数产生可比较的结果来提高效率。

这些发展的目标是及时将研究转化为临床实践。当然，还需要更多前瞻性研究。然而，在未来，该领域可能能够更好地实施变革过程，包括患者如何体验它们以及治疗师如何诱导它们。这些发展可能是跨理论的、基于过程的、个性化的和以数据为依据的心理治疗方法的基础，其中包括具体的（例如，对单个病例的密集纵向评估）和规范的（例如，大型患者数据库）和治疗师）的观点。这些进步最终可能会对以前没有从心理干预中获利的患者产生影响。