In plain language
For fifty years, psychotherapy research has mostly run "horse races": testing whether a named treatment package (like cognitive therapy or acceptance and commitment therapy) beats another package for a specific diagnosis (like depression). This chapter argues that this package-for-disorder approach has stalled. Differences between packages are often small, the number of packages keeps multiplying, meta-analyses suggest therapy effects may be flat or even falling, and the prevalence of mental health problems remains high.
The authors trace the problem to a misleading medical metaphor: treating the therapy package like a "pill" and the diagnosis like a "disease." In reality, therapies with the same name can work through very different mechanisms, and two people with the same diagnosis can be maintained in their suffering by completely different causal networks of thoughts, feelings, and behaviors. There is no latent "disease" of depression separate from its symptoms; instead, symptoms causally influence one another in networks that differ from person to person.
As an alternative, the chapter lays out the emerging process-based approach, organized around the extended evolutionary meta-model (EEMM). The core clinical question becomes: given this particular client, in this situation, at this stage of intervention, which biopsychosocial processes should we target, and how? The chapter reviews evidence on mediators and moderators of treatment, network approaches to case conceptualization, and candidate processes of change across affect, cognition, attention, self, motivation, overt behavior, and the biophysiological and sociocultural levels.
Key findings
- Comparative "horse race" trials of therapy packages often yield small or unclear differences, and meta-analyses suggest psychotherapy effects may be falling or staying flat while mental health problems remain highly prevalent.
- The medical "pill for a disease" metaphor fails for psychotherapy: therapies sharing a name (e.g., "CBT") can differ radically in process, and no latent disease has been found that causes the symptoms of diagnoses like depression — symptoms instead influence each other in causal networks.
- A worked example shows how three packages with identical average "efficacy" (40%) can differ dramatically in useful, unnecessary, and even harmful components — differences the package paradigm cannot detect or exploit.
- Processes of change are defined as theory-based, dynamic, progressive, contextually bound, modifiable, multilevel sequences of biopsychosocial events that lead to desired outcomes, and are distinguished from therapeutic procedures used to alter them.
- The extended evolutionary meta-model (EEMM) offers a common framework for organizing change processes across six psychological dimensions — affect, cognition, attention, self, motivation, and overt behavior — plus biophysiological and sociocultural levels.
- Mediational research has already identified candidate change processes at biological, psychological, and social levels; the chapter reviews these and calls for a paradigm focused on change within individuals rather than averages across groups.
How to cite
APA
Ciarrochi, J., Hayes, S. C., Hayes, L., Sahdra, B., Ferrari, M., Yap, K., & Hofmann, S. G. (2022). From package to process: An evidence-based approach to processes of change in psychotherapy. In Reference Module in Neuroscience and Biobehavioral Psychology. Elsevier. https://doi.org/10.1016/B978-0-12-818697-8.00085-6
BibTeX
@incollection{ciarrochi2022from,
author = {Ciarrochi, Joseph and Hayes, Steven C. and Hayes, Louise and Sahdra, Baljinder and Ferrari, Madeleine and Yap, Keong and Hofmann, Stefan G.},
title = {From package to process: An evidence-based approach to processes of change in psychotherapy},
booktitle = {Reference Module in Neuroscience and Biobehavioral Psychology},
publisher = {Elsevier},
year = {2022},
doi = {10.1016/B978-0-12-818697-8.00085-6}
}
Related work
- All publications by Joseph Ciarrochi (searchable, with free PDFs)
- Process-Based Therapy & Idionomic Analysis
Author: Joseph Ciarrochi (ORCID 0000-0003-0471-8100). Free copy hosted with permission for scholarly use. Please cite the published version via the DOI above.