In plain language
Researchers spend years building elegant models and questionnaires, yet therapists often look at them and ask a simple question: "How will this help the client sitting in front of me this week?" This handbook chapter tackles that gap head-on. It argues that the standard way of judging psychological measures — reliability and validity alone — reflects a philosophical stance ("elemental realism") that can be at odds with what practitioners actually need: tools that help people change.
Writing from a functional contextualist perspective, the authors propose that the ultimate standard for a clinical measure is its treatment utility — the degree to which using the assessment actually contributes to better treatment outcomes. Drawing on examples from both medicine (such as screening tests) and psychology, they describe research designs for testing whether an assessment practice genuinely improves care, and they show how classic psychometric theory and longitudinal research can still serve the practical goal of measuring therapeutic change and understanding processes of change.
The chapter also offers a "field guide" that organises the bewildering array of clinical process and outcome measures into a simple behavioural framework, defends well-constructed self-report measures as legitimate behavioural samples, and closes with promising new directions in contextual behavioural measurement. It is a bridge between abstract psychometrics and the concrete needs of the therapist in the room — a foundation for what later became process-based approaches to assessment.
Key findings
- Classic psychometrics rests on an "elemental realist" worldview that can conflict with functional contextualism; a good model of the mind does not automatically tell you how to change behaviour.
- Treatment utility — whether an assessment demonstrably contributes to beneficial treatment outcomes — is proposed as the sine qua non for evaluating, selecting, and using clinical measures.
- The chapter describes experimental designs (e.g., manipulated assessment designs) for directly testing whether assessment practices improve outcomes, with illustrations from medicine and psychotherapy.
- Self-report measures are defended as behavioural samples that are neither inherently superior nor inferior to observational or biological measures, and can be equally good or better predictors of behaviour.
- A practical "field guide" organises clinical process and outcome measures within a behavioural framework, including Gross's process model of emotion regulation, to help clinicians map measures to interventions.
- The chapter frames measurement around Gordon Paul's classic question — what treatment, for this individual, with that problem, under which circumstances, and how does change come about — and argues sound process measures are essential to answering it.
How to cite
APA
Ciarrochi, J., Zettle, R. D., Brockman, R., Duguid, J., Parker, P., Sahdra, B., & Kashdan, T. B. (2016). Measures that make a difference: A functional contextualistic approach to optimizing psychological measurement in clinical research and practice. In R. D. Zettle, S. C. Hayes, D. Barnes-Holmes, & A. Biglan (Eds.), The Wiley handbook of contextual behavioral science (pp. 320–347). Wiley-Blackwell. https://doi.org/10.1002/9781118489857.ch16
BibTeX
@incollection{ciarrochi2016measures,
author = {Ciarrochi, Joseph and Zettle, Robert D. and Brockman, Robert and Duguid, James and Parker, Philip and Sahdra, Baljinder and Kashdan, Todd B.},
title = {Measures That Make a Difference: A Functional Contextualistic Approach to Optimizing Psychological Measurement in Clinical Research and Practice},
booktitle = {The Wiley Handbook of Contextual Behavioral Science},
editor = {Zettle, Robert D. and Hayes, Steven C. and Barnes-Holmes, Dermot and Biglan, Anthony},
publisher = {Wiley-Blackwell},
year = {2016},
pages = {320--347},
doi = {10.1002/9781118489857.ch16}
}
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 via the DOI above.