Process-based functional analysis can help behavioral science step up to novel challenges: COVID - 19 as an example.

Historically speaking, the behavioral tradition advanced functional analysis as a method of applying existing principles to novel situations. In the more than half a century since that idea was advanced, functional analysis has either fallen into disuse, as in most of applied psychology, or has been used but modified to a point that is virtually inapplicable elsewhere, as in applied behavior analysis work with severe developmental disabilities. In this paper we argue that the current challenges with COVID-19 present an ideal time to reinvigorate functional analysis by combining it with the growing body of evidence on processes of change, organized under an extended evolutionary meta-model. This new form of process-based functional analysis takes advantage of the strengths of contextual behavioral science, while opening avenues of fruitful interaction with other wings of intervention and evolutionary science more generally. Using the psychological flexibility model as an example, we show how this approach solves the key problems of classical functional analysis and helps professionals deal with novel challenges such as those posed by COVID-19. Humanity is now facing an extraordinary and unexpected situation. Behavioral science needs to rise to that challenge in a way that provides both immediate practical value and greater assurance of long-term benefits for our understanding of human complexity more generally. Process-based functional analysis can be a vehicle to do just that.

The role of the individual in the coming era of process-based therapy.

For decades the development of evidence-based therapy has been based on experimental tests of protocols designed to impact psychiatric syndromes. As this paradigm weakens, a more process-based therapy approach is rising in its place, focused on how to best target and change core biopsychosocial processes in specific situations for given goals with given clients. This is an inherently more idiographic question than has normally been at issue in evidence-based therapy over the last few decades. In this article we explore methods of assessment and analysis that can integrate idiographic and nomothetic approaches in a process-based era.

Initial open trial of a computerized behavioral activation treatment for depression.

This article presents preliminary findings from use of a novel computer program that implements an evidence-based psychological intervention to treat depression based on behavioral activation (BA) therapy. The program is titled "Building a Meaningful Life Through Behavioral Activation". The findings derive from an open trial with moderate to severely depressed individuals (N = 15) in an Intention to Treat sample. Hierarchical linear modeling (HLM) analyses revealed significant change over time on Beck Depression Inventory-Second Edition (BDI-II) scores, Revised Hamilton Depression Rating Scale scores, and significant contribution to BDI-II score variance by participant age over time, change over time in negative automatic thoughts, and change over time in BA scores. Piecewise HLM analyses revealed that significant change over time was associated uniquely with active treatment and not during 3 weeks of baseline measurement. In addition to treatment-associated significant change on all dependent measures over time, effect sizes were in the moderate to large range. Limitations are small sample size, nonrandomized control, research-recruited patients instead of purely treatment-seeking patients, possible rating bias by independent assessors who had knowledge that participants had received active treatment in this open trial, and the influence of additional services received in the post acute-treatment phase by some participants could have contributed to maintenance of gains reported for that period.