Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA.
Department of Computer Science, University of Southern California, Los Angeles, CA, 90089, USA.
Behav Res Methods. 2022 Apr;54(2):690-711. doi: 10.3758/s13428-021-01623-4. Epub 2021 Aug 3.
With the growing prevalence of psychological interventions, it is vital to have measures which rate the effectiveness of psychological care to assist in training, supervision, and quality assurance of services. Traditionally, quality assessment is addressed by human raters who evaluate recorded sessions along specific dimensions, often codified through constructs relevant to the approach and domain. This is, however, a cost-prohibitive and time-consuming method that leads to poor feasibility and limited use in real-world settings. To facilitate this process, we have developed an automated competency rating tool able to process the raw recorded audio of a session, analyzing who spoke when, what they said, and how the health professional used language to provide therapy. Focusing on a use case of a specific type of psychotherapy called "motivational interviewing", our system gives comprehensive feedback to the therapist, including information about the dynamics of the session (e.g., therapist's vs. client's talking time), low-level psychological language descriptors (e.g., type of questions asked), as well as other high-level behavioral constructs (e.g., the extent to which the therapist understands the clients' perspective). We describe our platform and its performance using a dataset of more than 5000 recordings drawn from its deployment in a real-world clinical setting used to assist training of new therapists. Widespread use of automated psychotherapy rating tools may augment experts' capabilities by providing an avenue for more effective training and skill improvement, eventually leading to more positive clinical outcomes.
随着心理干预措施的日益普及,拥有评估心理护理有效性的措施对于培训、监督和服务质量保证至关重要。传统上,质量评估是通过人类评估者完成的,他们根据特定维度评估记录的会话,这些维度通常通过与方法和领域相关的结构进行编码。然而,这是一种成本高昂且耗时的方法,导致可行性差,在现实环境中的应用有限。为了促进这一过程,我们开发了一种自动化能力评估工具,能够处理会话的原始录音,分析何时何人发言、说了什么以及卫生专业人员如何使用语言提供治疗。我们专注于一种名为“动机访谈”的特定类型心理治疗的用例,我们的系统为治疗师提供全面的反馈,包括有关会话动态的信息(例如,治疗师与客户的谈话时间)、低水平心理语言描述符(例如,提出的问题类型)以及其他高级行为结构(例如,治疗师对客户观点的理解程度)。我们使用来自实际临床环境部署的超过 5000 个录音数据集来描述我们的平台及其性能,该数据集用于辅助新治疗师的培训。广泛使用自动化心理治疗评估工具可以通过提供更有效的培训和技能提升途径来增强专家的能力,最终导致更积极的临床结果。