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Process-based therapy : A common ground for understanding and utilizing therapeutic practices
Ciarrochi, Joseph Hernández, Cristóbal Hill, Diana Ong, Clarissa Gloster, Andrew T. Levin, Michael E. Yap, Keong Fraser, Madeleine I. Sahdra, Baljinder K. Hofmann, Stefan G.
Ciarrochi, Joseph
Hernández, Cristóbal
Hill, Diana
Ong, Clarissa
Gloster, Andrew T.
Levin, Michael E.
Yap, Keong
Fraser, Madeleine I.
Sahdra, Baljinder K.
Hofmann, Stefan G.
Abstract
This article critiques the “protocol-for-syndrome” model in mental health research, highlighting two primary concerns: the complexity of protocols that include change processes irrelevant to many individuals, and the inadequacy of Diagnostic and Statistical Manual of Mental Disorders syndromes to capture the nuances of individual well-being and suffering. Advocating a shift to a process-based therapy (PBT) approach, the article proposes a coherent integration of diverse change processes and interventions to enrich therapy practices. It introduces a slightly revised extended evolutionary metamodel (EEMM) as a comprehensive framework that provides a consistent language for discussing change processes, focusing on the key drivers of variation, selection, and retention, and categorizing these into dimensions (such as cognition, emotion, self, motivation) and levels (from biology/physiology to psychology and social relationships/culture). The article details the application of EEMM in classifying therapeutic processes, validated through both human and artificial intelligence (AI) ratings. Furthermore, we developed an AI tool built on Distilled Bidirectional Encoder Representations from Transformers (distilBERT) models for categorizing therapeutic content, proving effective and accessible for community engagement and ongoing enhancement. The article also explores network theory and new analytics as tools for therapists to customize therapy to individual client needs. In summary, PBT supports therapeutic diversity while establishing common ground among different methods and approaches. This enhances communication, cooperation, and comparison, fostering the development of tailored and effective therapy strategies. It also opens the door to the potential unification of psychotherapy.
Public Health Significance Statement
The article presents an innovative approach to mental health treatment, advocating for process-based therapy (PBT) over traditional models. PBT offers a personalized framework, aligning various therapeutic methods to an individual’s unique mental health needs. By leveraging an artificial intelligence tool for categorizing therapy content and utilizing network theory for tailored treatments, PBT aims to enhance the effectiveness of therapy and client well-being.
Keywords
process-based therapy, evidence-based processes, mediational analysis, network theory, artificial intelligence rating of processes
Date
2024
Type
Journal article
Journal
Journal of Psychotherapy Integration
Book
Volume
34
Issue
3
Page Range
265-290
Article Number
ACU Department
Institute for Positive Psychology and Education
Faculty of Education and Arts
School of Behavioural and Health Sciences
Faculty of Health Sciences
Faculty of Education and Arts
School of Behavioural and Health Sciences
Faculty of Health Sciences
Relation URI
Source URL
Event URL
Open Access Status
Published as ‘gold’ (paid) open access
License
CC BY 4.0
File Access
Open