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应用情感编码和动态系统数学建模来理解情感表达在整个药物滥用治疗过程中对治疗关系的作用。

Applying affect coding and dynamical systems mathematical modeling to understanding the role of emotional expression on the therapeutic relationship across an entire course of substance abuse treatment.

作者信息

Cipriano Gina, Peluso Paul R, Bright Emma, Hutarkova Blanka

机构信息

Department of Counselor Education, Florida Atlantic University, Boca Raton, FL, United States.

Department of Human Development and Family Science, Florida State University, Boca Raton, FL, United States.

出版信息

Front Hum Neurosci. 2025 Apr 23;19:1544437. doi: 10.3389/fnhum.2025.1544437. eCollection 2025.

Abstract

INTRODUCTION

Substance abuse remains a critical public health issue, with 48.7 million adults in the United States meeting the criteria for a substance use disorder (Substance Abuse Mental Health Services Administration [SAMHSA], 2023). Traditional substance abuse treatment is often considered distinct from other psychotherapeutic approaches. Practitioners have historically focused on compliance and behavior arrest rather than exploring underlying issues. Despite these efforts, relapse rates for substance abuse remain high, prompting the development of alternative treatments incorporating psychotherapeutic methods such as Motivational Interviewing and various mindfulness-based harm reduction. This paper reviews Alan Marlatt's mindfulness-based approach to substance abuse treatment, which emphasizes the therapeutic relationship's role in reducing resistance and enhancing client autonomy. The findings aim to improve therapeutic outcomes by providing a deeper understanding of these emotional interactions, ultimately contributing to more effective substance abuse interventions.

METHOD

This study utilized the APA-produced DVD series , featuring Dr. Alan Marlatt and his client, Kevin, over six therapy sessions. The sessions were coded using the Specific Affect Coding System (SPAFF) to code emotional expressions and a dynamical systems (DS) mathematical model, with parameters derived from the coded data to create unique models for each session.

RESULTS

Statistical analysis was used to compare SPAFF codes and model parameters between Alan Marlatt and his client. The therapist showed significant changes in several affect codes (e.g., Low Domineering and Sadness) as did the client (e.g., Disgust, Contempt) over six sessions. Despite these differences, the overall model parameters remained stable across the six sessions.

DISCUSSION

This study utilized SPAFF coding and DS modeling to analyze emotional expressions between Dr. Alan Marlatt and his client, over six psychotherapy sessions focused on relapse prevention. The results revealed consistent emotional expressions from Marlatt, while Kevin exhibited significant fluctuations, reflecting his struggles with addictions and relapse. Despite these variations, the overall model parameters remained stable, indicating a consistent therapeutic relationship. These findings highlight the complex emotional dynamics in substance abuse treatment and underscore the importance of a stable therapeutic presence.

CLINICAL SIGNIFICANCE/IMPACT STATEMENT: The findings from this study highlight the importance of understanding emotional dynamics in the therapeutic relationship during substance abuse treatment. The significant variations in Kevin's emotional expressions across sessions, contrasted with the stability of Marlatt's responses suggests that consistent therapeutic presences can provide a stable foundation for clients experiencing fluctuating emotional states. By employing affect coding and dynamical systems modeling, this research underscores the potential for these methods to enhance therapeutic outcomes through a deeper understanding of client-therapist interactions. These insights can inform the development of more effective, emotionally responsive treatment protocols, ultimately improving recovery rates and reducing relapse in substance abuse therapy.

摘要

引言

药物滥用仍然是一个关键的公共卫生问题,美国有4870万成年人符合药物使用障碍的标准(药物滥用和心理健康服务管理局[SAMHSA],2023年)。传统的药物滥用治疗通常被认为与其他心理治疗方法不同。从业者历来专注于依从性和行为抑制,而不是探索潜在问题。尽管做出了这些努力,药物滥用的复发率仍然很高,这促使人们开发出结合动机性访谈和各种基于正念的减少伤害等心理治疗方法的替代治疗方法。本文回顾了艾伦·马尔拉特基于正念的药物滥用治疗方法,该方法强调治疗关系在降低抵触情绪和增强客户自主性方面的作用。研究结果旨在通过更深入地理解这些情感互动来改善治疗效果,最终有助于更有效地干预药物滥用。

方法

本研究使用了美国心理学会制作的DVD系列,该系列展示了艾伦·马尔拉特博士和他的客户凯文在六个治疗疗程中的情况。使用特定情感编码系统(SPAFF)对这些疗程进行编码,以对情感表达进行编码,并使用动态系统(DS)数学模型,从编码数据中导出参数,为每个疗程创建独特的模型。

结果

使用统计分析来比较艾伦·马尔拉特和他的客户之间的SPAFF编码和模型参数。在六个疗程中,治疗师在几个情感编码方面(如低支配性和悲伤)有显著变化,客户(如厌恶、轻蔑)也是如此。尽管存在这些差异,但六个疗程的总体模型参数保持稳定。

讨论

本研究利用SPAFF编码和DS建模分析了艾伦·马尔拉特博士和他的客户在六个专注于预防复发的心理治疗疗程中的情感表达。结果显示马尔拉特的情感表达一致,而凯文则表现出显著波动,反映了他在成瘾和复发方面的挣扎。尽管存在这些差异,但总体模型参数保持稳定,表明治疗关系一致。这些发现突出了药物滥用治疗中复杂的情感动态,并强调了稳定治疗存在的重要性。

临床意义/影响声明:本研究的结果突出了在药物滥用治疗中理解治疗关系中情感动态的重要性。凯文各疗程情感表达的显著差异,与马尔拉特反应的稳定性形成对比,这表明一致的治疗存在可以为情绪状态波动的客户提供稳定的基础。通过采用情感编码和动态系统建模,本研究强调了这些方法通过更深入地理解客户与治疗师的互动来提高治疗效果的潜力。这些见解可为制定更有效、对情感有反应的治疗方案提供参考,最终提高药物滥用治疗的康复率并减少复发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd52/12055768/d95682ee2667/fnhum-19-1544437-g0001.jpg

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