Abstract
In this issue, Hofmann and Hayes (p. 37) shined a light on our field’s lack of progress in reducing the prevalence and burden of mental illness and suggested that a paradigm shift is needed to make more rapid progress. They argued that empirically supported processes of change should guide treatment planning, rather than treatment packages. This approach should allow for greater personalization of treatment and more iterative treatment planning and should increase the scalability of our intervention delivery models. In this commentary, I discuss some of the difficult questions that will arise when trying to make the shift from treatment packages to process-based therapy and highlight some steps that we can take now to facilitate the shift.
Hofmann and Hayes (2019; this issue, p. 37) challenged the field to look both backward and forward to recognize progress made, but also missed opportunities, in developing and delivering mental health services that can effectively and efficiently reduce the burden of mental illness. They present what is in many ways a simple premise: Empirically supported processes of change should guide treatment planning, rather than treatment packages. Although I might quibble with whether or not we really need a new name for this approach (they use the term process-based therapy), I agree with the basic argument and believe it can provide a valuable approach to addressing comorbidity, the need to better integrate nomothetic and idiographic approaches, and the limitations of a disorder-based diagnostic approach that fails to “carve nature at its joints.”
Moreover, as Hofmann and Hayes noted, this is not a new idea and there have been exciting strides made in this direction already. For instance, groundbreaking work over the past 15 years has focused on how to extract the common elements from evidence-based intervention packages that lead to effective mental health outcomes for children (e.g., Chorpita, Daleiden, & Weisz, 2005). Further, Hofmann and Hayes hope that “in the future, it might further be possible to train paraprofessionals in specific therapeutic procedures to target the therapeutic processes that more highly trained professionals identify as the most promising treatment targets” (p. 43). This wish for greater dissemination may be less futuristic than they suppose. There is already considerable evidence that nonspecialist providers can effectively deliver treatment strategies based on common processes of change (drawn from well-established behavioral, interpersonal, emotional, and cognitive therapy approaches) in low- and middle-income countries. A recent review of 27 trials found a moderate to strong pooled effect size in favor of the active interventions, even when the treatments were mainly delivered by peers or community health workers (Singla et al., 2017). This raises considerable hope for the potential of a process-based therapy approach to have wide reach.
The real question, then, is less should we train the next generation of providers to focus on becoming proficient in targeting key processes of change, and more how can we get there? We are swimmers sitting by the edge of the pool—the water looks inviting, but how and when do we jump in? This is a difficult question because so much is not yet known. For instance, what is the final list of change processes that would be recommended, and for which problem areas would these processes be effective and under what circumstances? And how do we know which combinations of change process strategies should be used for which client, or the optimal way to sequence the strategies? These are not easy questions to address given that the data on mechanisms and on personalization of treatments are not nearly as good as we wish (or desperately need them to be; see Teachman, Beadel, & Steinman, 2014). Thus, the fundamental question raised by Paul (1969) still remains unanswered when we shift to a process-based therapy approach: “What treatment, by whom, is most effective for this individual with that specific problem, under which set of circumstances, and how does it come about?” (p. 44).
These many unanswered questions challenge our identity as clinical scientists who want a strong base of empirical evidence to guide decision making. And yet, I would argue that it is time to take the plunge and get wet (at least in the shallow end!). We, as a field, need to do something different given how woefully ineffective we have been at reducing the burden of mental illness in a meaningful way (see Kazdin & Blase, 2011). Moreover, it will be more feasible to answer Paul’s million-dollar question with a process-based approach because the process-based approach is designed to be individualized and starts as a treatment that can be readily dismantled to determine its necessary and sufficient parts, rather than those questions often being addressed decades after traditional treatment packages have been introduced.
So, how do we “get in the pool” in an ethical and scientific way, given the unknowns? Clearly, the answer to this question will require a book, rather than a brief commentary, but a few initial steps that seem helpful include the following:
Clinical Practice Guidelines, such as those developed by the National Institute for Health and Care Excellence in the United Kingdom and recently by the American Psychological Association, provide treatment recommendations based on a systematic review of the efficacy data. New guidelines need to move away from being based on the Diagnostic and Statistical Manual of Mental Disorders (DSM–5; American Psychiatric Association, 2013) for the guideline topics and being based on treatment packages for the recommendations. Instead, more systematic reviews and associated recommendations are needed on processes of change to clarify both what is known and the large scope of what is not known. This can help prioritize the domains in which more research is most needed. Notably, I would define processes of change broadly, including both specific mechanisms (such as inhibitory learning during exposure therapy) and nonspecific factors (such as therapeutic alliance, for which we still need more experimental data but have considerable correlational data), and even processes tied to other aspects of treatment delivery, such as outside-of-session practice and application of treatment material (with homework being a common treatment strategy to achieve this change process).
Obtaining thorough and open informed consent with clients so that clients are aware of the limits of what is known about the planned approach is key. Further, this openness needs to be paired with careful progress monitoring of both change in the process of interest and change in the therapeutic outcomes (expected to follow from those change processes). By viewing treatment planning as a dynamic process that happens iteratively on the basis of client-level data, it becomes clearer how to view therapy planning in phases (Woody, Detweiler-Bedell, Teachman, & O’Hearn, 2002), rather than as a one-time decision based on which treatment package was selected.
Providers need access to good, free, easily digestible (minimal jargon) resources to facilitate training in the strategies to achieve empirically supported processes of change. The field currently has too many barriers to providers accessing the resources needed to build their toolbox and keep it up to date (e.g., resources are expensive, are often time consuming to digest, are dispersed and so are hard to locate, and lack cultural adaptation). A clearinghouse of simple resources (videos, handouts, etc.) to help providers learn and apply process-based therapy could help dissemination and implementation greatly.
We need to learn from the successes in global mental health. The impressive effects when scaling interventions with nonspecialist providers in low- and middle-income countries can teach us a lot about how to increase adoption of process-based therapy. We have a bad habit of thinking that progress moves only from disseminating Western treatment approaches to other places, but there is much we can learn from non-Western mental health success stories.
Greater investments are needed in research on personalizing treatments (beyond work on biomarkers; e.g., DeRubeis et al., 2014) to learn how to match treatments to a given individual and context, and in idiographic network models (e.g., Borsboom & Cramer, 2013) to identify the key change processes for a given person that can start a domino effect for that person and efficiently lead to other changes.
Much remains unknown about how to shift from a treatment package to a process-based therapy approach and what impact this shift will have, but the time has come to “jump in the water.” For the sake of our clients and their families, we cannot sit on the sidelines any longer.
Footnotes
Acknowledgements
I am thankful for the feedback provided by members of the Program for Anxiety, Cognition, and Treatment (PACT) lab at the University of Virginia.
Action Editor
Scott O. Lilienfeld served as action editor for this article.
Author Contributions
B. A. Teachman is the sole author of this article and is responsible for its content.
Declaration of Conflicting Interests
The author(s) declared that there were no conflicts of interest with respect to the authorship or the publication of this article.
Funding
This research was supported by National Institute of Mental Health Grant R01-MH113752 (to B. A. Teachman).
