Evidence-based tailoring of treatment to patients, providers, and processes: Introduction to the special issue.

Abstract

Given the many evidence-supported psychotherapy interventions, and the fact that no single approach or therapist can successfully help all patients, in recent years, there has been a surge in studies focused on evidence-based methods of tailoring treatment to patients, providers, and processes. Although the field still has a long way to go in reliably mapping specific empirically supported avenues to personalized therapies, emerging results from this line of research underscore the potential for such optimization. In this vein, the articles in the special issue describe some of the most auspicious recent developments in the field of personalized mental health treatment. In this introduction to the special issue, we synthesize the articles and propose a list of some of the most promising personalization principles. These include (a) a diversity of aims that the approaches seek to achieve; (b) a diversity of outcomes used to evaluate the merits of these approaches; (c) the information on which the tailoring is based; (d) the tailoring approaches themselves; and (e) the research designs used to evaluate them. These pathways can inform the most current tailoring guidelines that can help clinical decision-making and inspire future translational science in this area.What is the public health significance of this article? This is an introduction to the special issue on evidence-based tailoring of treatment to patients, providers, and processes. It maps some of the most promising personalization principles to guide future research and practice.

Anxiety, history of childhood adversity, and experiencing chronic pain in adulthood: A systematic literature review and meta‐analysis

“…In addition, evidence‐based precision health care has gained more traction in recent years. Although there are multiple evidence‐supported psychotherapy (such as dialectical or cognitive behavioural therapy) and clinical intervention options, to date, no single approach, therapist, or treatment successfully helps every patient (Zilcha‐Mano et al., 2022). Despite the prevalence of ACEs, many providers remain uncomfortable treating and recognizing trauma, particularly in the paediatric setting when the opportunity for intervention and prevention is still possible.…”

Training in LGBTQ-affirmative cognitive behavioral therapy: A randomized controlled trial across LGBTQ community centers.

“…Future research that studies the application of this training to actual practice would be well-suited to incorporating established measures of CBT case conceptualization (e.g., Kuyken et al, 2016) as adapted to LGBTQ-affirmative CBT (Bucci et al, 2016; Easden & Kazantzis, 2018). This research would also allow for studying whether specific LGBTQ-affirmative CBT techniques can be appropriately matched to the client’s presenting concern rather than just being delivered at all, an important aspect of evidence-based intervention tailoring (Zilcha-Mano et al, 2022).…”

The Promises and Possibilities of Artificial Intelligence in the Delivery of Behavior Analytic Services

“…That is, a behavioral or educational intervention delivered by one practitioner or teacher might look different than the same behavioral or educational intervention implemented by another person. Based on these differences, researchers can use AI to optimize the patients that are assigned to a healthcare practitioner based on the clients' presenting symptomatology and the doctors' demonstrated skill in treating different medical conditions or implementing different interventions (e.g., Field & Caetano, 2010;Zilcha-Mano et al, 2022). Optimizing a BHP's clinical caseload is likely to maximize their abilities to help their patients and also prevent burnout (e.g., Anderson et al, 2022;Hassanzadeh et al, 2022).…”