Using Transdiagnostic Mechanistic Targets to Advance Prevention Science

Anxiety sensitivity (AS) is a well-established transdiagnostic mechanism underlying emotional and health behavior problems. In the first meta-analysis of brief AS reduction interventions in at-risk populations, Fitzgerald and colleagues (2021) demonstrated that not only do these interventions successfully reduce AS in the short term, but they also result in long-term improvements in clinical outcomes. As such, these brief, easily scalable interventions hold significant promise for advancing prevention efforts. Building on these findings, this commentary will focus on: 1) the importance of prevention efforts to the field of clinical psychology; 2) the role of brief, technology-based interventions in prevention efforts; 3) use of the experimental medicine approach in transdiagnostic prevention efforts; and 4) key areas for future research.

THE NEED FOR PREVENTION IN CLINICAL PSYCHOLOGY

In accordance with the medical model, research and practice in clinical psychology has historically focused on the treatment of existing psychological disorders. This model of care has resulted in significant economic and individual burden. For example, healthcare spending for the treatment of psychological disorders in 2014 alone was $186 billion (SAMHSA, 2016). Under this model of care, individuals are unlikely to receive treatment until they are experiencing debilitating distress and functional impairment. Complicating the picture, such treatment may be difficult to access, cost prohibitive, and may not result in full symptom remission. Indeed, research suggests that even for evidence-based treatments, such as cognitive-behavioral therapy, remission rates are approximately 50% (Springer et al., 2018).

Therefore, a greater focus on the prevention of psychological disorders is desperately needed. A prevention rather than a treatment approach may be more cost effective in the long-run and serve to alleviate burden on the individual level. As one illustrative example, extant work has demonstrated the cost effectiveness of prevention programs for perinatal depression, child and adolescent mental health, mental illness in the workplace, suicide, and symptoms of depression and anxiety in older age (for a review, see McDaid et al., 2019). As a result of advancements in our understanding of psychological risk and protective factors over the past several decades, there are boundless opportunities for the continued development and optimization of novel secondary prevention interventions, or interventions targeted to at-risk groups. Fitzgerald and colleagues’ (2021) meta-analysis excellently summarizes research focused on secondary prevention programs targeting AS, a robust transdiagnostic cognitive-affective risk factor.

THE ROLE OF BRIEF AND TECHNOLOGY-BASED INTERVENTIONS IN PREVENTION SCIENCE

The development of scalable, cost-effective interventions is one key component of prevention efforts. Very brief (e.g., single-session) prevention programs developed by mental health experts may be the most scalable and cost-effective. Moreover, evidence from Fitzgerald et al.’s meta-analysis (2021) suggests that such interventions are efficacious not only in reducing cognitive-affective risk factors (i.e., AS), but also downstream symptoms of emotional and behavioral health issues. While intervention length was not a significant moderator from pre-treatment to short-term follow-up in this meta-analysis, there was an insufficient number of studies to assess intervention length as a moderator for long-term follow-up effects. As noted by Fitzgerald et al. (2021), more research is needed to evaluate whether very brief (i.e., single-session) prevention interventions sustain effects over time. The Multiphase Optimization Strategy (MOST), which relies on factorial designs to optimize behavioral interventions, may be excellent for testing whether subsequent booster or maintenance sessions enhance the long-term efficacy of these interventions (Collins et al., 2007).

The use of technology may also enhance the scalability, accessibility, and cost-effectiveness of prevention interventions for those who need them the most. Indeed, numerous barriers, such as cost, transportation, and childcare prevent individuals from accessing mental health prevention or treatment—particularly those from socially and economically disadvantaged groups. Moreover, historically excluded groups experience increased stress, including from discrimination and racism, placing them at greater risk for negative physical and mental health outcomes. Technology-based (e.g., self-guided, web-based) prevention programs, like some of those described in Fitzgerald et al. (2021), have the potential to address long-standing health disparities experienced by marginalized groups. While AS has been identified as an important process in Black and Latino populations (Reitzel et al., 2016; Zvolensky et al., 2015), there is limited research testing AS prevention interventions in these populations. Future research should focus on developing and testing brief, technology-based prevention interventions to reduce risk for psychopathology in minoritized groups. Relatedly, we should prioritize the involvement of diverse consumers in the development (or cultural adaptation) of such prevention interventions to enhance acceptability (e.g., via focus groups, community-based participatory research). Research will also be needed to determine the most effective methods for disseminating technology-assisted transdiagnostic prevention interventions to the public (e.g., app-based, video).

USING THE EXPERIMENTAL MEDICINE APPROACH IN TRANSDIAGNOSTIC PREVENTION EFFORTS

The Science of Behavior Change (SOBC) experimental medicine approach may be ideal for developing and optimizing secondary prevention interventions. As described by Nielsen and colleagues (2018), traditional randomized controlled trials (RCTs) of psychological or behavioral interventions have primarily focused on assessing change in clinical outcomes (e.g., anxiety symptoms) rather than change in purported mechanistic processes. This approach is costly, slow, and leads to a lack of understanding of underlying mechanisms of these interventions. Instead, using the experimental medicine approach, researchers first evaluate whether an intervention engages a proposed mechanistic target (e.g., a transdiagnostic process such as AS). Only after the target has been shown to be successfully engaged does one then test whether changes in that target produce downstream improvements in clinical outcomes. The Fitzgerald et al. (2021) meta-analysis serves as an excellent model for use of the experimental medicine approach in developing prevention interventions for at-risk groups.

Consistent with the experimental medicine approach, future research should explore how to maximally engage transdiagnostic processes in prevention interventions. The secondary prevention interventions in the Fitzgerald et al. (2021) meta-analysis were heterogeneous and included several different intervention components (e.g., cognitive bias modification, interoceptive exposure). However, it still remains unclear which intervention components, or combination of components, most effectively reduce AS. Multiphase Optimization Strategy (MOST) designs would be ideal for determining which intervention components to retain in AS interventions to maximally engage this target. This approach could also be applied to prevention interventions focused on improving other transdiagnostic processes (e.g., distress tolerance, intolerance of uncertainty).

ADDITIONAL FUTURE DIRECTIONS IN TRANSDIAGNOSTIC PREVENTION RESEARCH

There are additional questions to consider in regards to the future of transdiagnostic prevention research for at-risk groups. First, given that individuals may display elevations across several transdiagnostic risk factors, and some of these factors are related, it may be that targeting a suite of transdiagnostic mechanisms yields larger downstream effects on clinical endpoints. As some transdiagnostic processes are highly related (e.g., AS, distress tolerance, intolerance of uncertainty), it is possible that a single strategy or intervention could successfully reduce multiple risk factors. On the other hand, prioritizing the reduction of one transdiagnostic process before another may be important for certain individuals. Future research should consider if and when to target multiple factors to achieve a more personalized approach to prevention.

In addition to ensuring that prevention interventions maximally reduce one or more transdiagnostic risk factors, another key principle in the field of prevention science is enhancing protective factors. As such, future transdiagnostic prevention research should considering targeting processes also linked to positive outcomes in at-risk groups. For example, mindfulness-based approaches may lend themselves nicely to both reducing risk and enhancing protective factors (e.g., self-compassion, positive affect) for psychological and behavioral health problems.

CONCLUSION

Taken together, increased attention on developing and optimizing scalable prevention interventions is needed. The experimental medicine approach outlined by the SOBC has the potential to improve the development of brief, technology-based prevention interventions aimed at reducing transdiagnostic processes and downstream mental and physical health problems. The quantitative synthesis provided by Fitzgerald and colleagues (2021) is an excellent template for prevention research rooted in the experimental medicine approach. Next steps for transdiagnostic prevention research include assessing intervention dose, targeting additional transdiagnostic processes, enhancing protective factors, and expanding such research to diverse groups.