In plain language
Process-Based Therapy shifts the focus of psychological treatment away from diagnostic labels and toward the specific processes that keep an individual person stuck or help them thrive. The Process-Based Assessment Tool (PBAT), originally developed in English by Ciarrochi and colleagues in 2022, is an 18-item questionnaire built for exactly that purpose: it repeatedly measures positive and negative behaviors — things like using your thinking to live better, connecting with important people, or feeling stuck and unable to change — so clinicians and researchers can track what is changing for each person. This study asked whether a carefully back-translated Spanish version of the PBAT works the same way.
A representative sample of 602 Spanish adults aged 18 to 75, recruited to match national census quotas for sex, age, and location, completed the Spanish PBAT alongside measures of psychological distress (sadness, anxiety, stress, anger, lack of social support), health, vitality, and the satisfaction or frustration of the basic needs for autonomy, connection, and competence. The researchers replicated the analysis pipeline of the original validation study, including a machine learning approach (the Boruta random forest algorithm) to identify which PBAT items best predicted each outcome.
The Spanish PBAT behaved much like the English original. Positive behaviors were the strongest predictors of health, vitality, and need satisfaction, while negative behaviors were the strongest predictors of distress and need frustration. One item — sticking to strategies that worked — behaved inconsistently, possibly reflecting translation or cultural differences. Overall, the authors conclude the Spanish PBAT can be recommended for research and therapeutic use, extending process-based assessment to Spanish-speaking populations.
Key findings
- In a representative sample of 602 Spanish adults, PBAT items significantly predicted all criterion variables, replicating the original English validation study.
- Positive PBAT behaviors correlated moderately with each other (mean r = .46) and negative behaviors with each other (mean r = .39), while positive–negative correlations were weak (mean r = −.13), supporting the tool’s two-sided structure.
- Positive behaviors were moderately related to satisfaction of autonomy, connection, and competence needs (mean r = .40), and negative behaviors to frustration of those needs (mean r = .42), exactly as theory predicts.
- Positive items better predicted health and vitality (mean r = .32), whereas negative items better predicted sadness, anxiety, stress, anger, and lack of support (mean r = .41).
- In the machine learning analysis, the single best predictor of negative states was “Found no appropriate outlet for expressing feelings,” and the best predictor of positive states was “Used thinking to live better.”
- The positive retention item (“Stuck to strategies that worked”) behaved inconsistently with the original study — correlating positively with need frustration and negative variation — suggesting possible translation or cultural differences for that item.
How to cite
APA
Goicoechea, C., Wallman-Jones, A., Ciarrochi, J., Hayes, S. C., Hofmann, S. G., & Perakakis, P. (2024). Development and validation of the Spanish Process-Based Assessment Tool (PBAT) [Preprint].
BibTeX
@article{goicoechea2024development,
author = {Goicoechea, Carmen and Wallman-Jones, Amie and Ciarrochi, Joseph and Hayes, Steven C. and Hofmann, Stefan G. and Perakakis, Pandelis},
title = {Development and Validation of the Spanish Process-Based Assessment Tool (PBAT)},
journal = {Preprint},
year = {2024},
note = {Preprint}
}
Related work
- All publications by Joseph Ciarrochi (searchable, with free PDFs)
- Process-Based Therapy & Idionomic Analysis
- The Process-Based Assessment Tool (free download)
Author: Joseph Ciarrochi (ORCID 0000-0003-0471-8100). Free copy hosted with permission for scholarly use. Please cite the published version.