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 Psychotherapy Over Time, 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.