临床心理科学的主要问题及解决方法。引入多模态动态网络方法

IF 2.8 3区 心理学 Q2 PSYCHOLOGY, CLINICAL Cognitive Therapy and Research Pub Date : 2024-06-24 DOI:10.1007/s10608-024-10487-9
Marlon Westhoff, Max Berg, Andreas Reif, Winfried Rief, Stefan G. Hofmann
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引用次数: 0

摘要

背景尽管最佳疗法的推广计划令人印象深刻,但临床心理学在开发更有效的精神障碍治疗方法方面仍面临重重障碍。与其他医学学科相比,心理疗法在改善治疗效果方面进展缓慢。改进精神障碍的分类可以提高治疗的针对性,从而改善治疗效果。我们引入了一种多模态动力学网络方法,以应对临床研究面临的一些挑战。这些挑战包括缺乏全面的元理论、合并症、诊断上的巨大异质性、违反均衡性假设以及对因果过程的理解有限。方法通过应用多模态动态网络分析,我们描述了如何通过解决该领域的核心问题来推动临床研究。通过利用动态网络分析技术(如群体迭代多重模型估计、多元格兰杰因果关系)、多模态测量(即心理、精神病理学和神经生物学数据)、密集的纵向数据收集(如生态瞬间评估)和因果推断方法(如 GIMME),我们的方法可以提高对精神障碍的理解和治疗。在系统方法的框架下,我们利用图论和控制论等方法,旨在整合来自纵向、多模态测量的数据。它打破了人为的诊断界限,促进了精神病理学的跨诊断视角。通过整合纵向数据和因果推理技术,我们更有能力识别有影响力的节点、确定干预措施的优先次序以及预测治疗策略的影响。 结论:所提出的方法可以提供个性化的心理病理学模型,并提出个性化的治疗角度,从而改善心理治疗。
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Major Problems in Clinical Psychological Science and How to Address them. Introducing a Multimodal Dynamical Network Approach

Background

Despite impressive dissemination programs of best-practice therapies, clinical psychology faces obstacles in developing more efficacious treatments for mental disorders. In contrast to other medical disciplines, psychotherapy has made only slow progress in improving treatment outcomes. Improvements in the classification of mental disorders could enhance the tailoring of treatments to improve effectiveness. We introduce a multimodal dynamical network approach, to address some of the challenges faced by clinical research. These challenges include the absence of a comprehensive meta-theory, comorbidity, substantial diagnostic heterogeneity, violations of ergodicity assumptions, and a limited understanding of causal processes.

Methods

Through the application of multimodal dynamical network analysis, we describe how to advance clinical research by addressing central problems in the field. By utilizing dynamic network analysis techniques (e.g., Group Iterative Multiple Model Estimation, multivariate Granger causality), multimodal measurements (i.e., psychological, psychopathological, and neurobiological data), intensive longitudinal data collection (e.g., Ecological Momentary Assessment), and causal inference methods (e.g., GIMME), our approach could improve the comprehension and treatment of mental disorders. Under the umbrella of the systems approach and utilizing e.g., graph theory and control theory, we aim to integrate data from longitudinal, multimodal measurements.

Results

The multimodal dynamical network approach enables a comprehensive understanding of mental disorders as dynamic networks of interconnected symptoms. It dismantles artificial diagnostic boundaries, facilitating a transdiagnostic view of psychopathology. The integration of longitudinal data and causal inference techniques enhances our ability to identify influential nodes, prioritize interventions, and predict the impact of therapeutic strategies.

Conclusion

The proposed approach could improve psychological treatment by providing individualized models of psychopathology and by suggesting individual treatment angles.

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来源期刊
Cognitive Therapy and Research
Cognitive Therapy and Research PSYCHOLOGY, CLINICAL-
CiteScore
5.30
自引率
0.00%
发文量
52
期刊介绍: Cognitive Therapy and Research (COTR) focuses on the investigation of cognitive processes in human adaptation and adjustment and cognitive behavioral therapy (CBT). It is an interdisciplinary journal welcoming submissions from diverse areas of psychology, including cognitive, clinical, developmental, experimental, personality, social, learning, affective neuroscience, emotion research, therapy mechanism, and pharmacotherapy.
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