Implementing precision methods in personalizing psychological therapies: barriers and possible ways forward

This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: No data was used for the research described in the article.Highlights: • Personalizing psychological treatments means to customize treatment for individuals to enhance outcomes. • The application of precision methods to clinical psychology has led to data-driven psychological therapies. • Applying data-informed psychological therapies involves clinical, technical, statistical, and contextual aspects

Editorial Statement About JCCAP’s 2023 Special Issue on Informant Discrepancies in Youth Mental Health Assessments: Observations, Guidelines, and Future Directions Grounded in 60 Years of Research

Issue 1 of the 2011 Volume of the Journal of Clinical Child and Adolescent Psychology (JCCAP) included a Special Section about the use of multi-informant approaches to measure child and adolescent (i.e., hereafter referred to collectively as “youth”) mental health (De Los Reyes, 2011). Researchers collect reports from multiple informants or sources (e.g., parent and peer, youth and teacher) to estimate a given youth’s mental health. The 2011 JCCAP Special Section focused on the most common outcome of these approaches, namely the significant discrepancies that arise when comparing estimates from any two informant’s reports (i.e., informant discrepancies). These discrepancies appear in assessments conducted across the lifespan (Achenbach, 2020). That said, JCCAP dedicated space to understanding informant discrepancies, because they have been a focus of scholarship in youth mental health for over 60 years (e.g., Achenbach et al., 1987; De Los Reyes & Kazdin, 2005; Glennon & Weisz, 1978; Kazdin et al., 1983; Kraemer et al., 2003; Lapouse & Monk, 1958; Quay et al., 1966; Richters, 1992; Rutter et al., 1970; van der Ende et al., 2012). Thus, we have a thorough understanding of the areas of research for which they reliably appear when clinically assessing youth. For instance, intervention researchers observe informant discrepancies in estimates of intervention effects within randomized controlled trials (e.g., Casey & Berman, 1985; Weisz et al., 2017). Service providers observe informant discrepancies when working with individual clients, most notably when making decisions about treatment planning (e.g., Hawley & Weisz, 2003; Hoffman & Chu, 2015). Scholars in developmental psychopathology observe these discrepancies when seeking to understand risk and protective factors linked to youth mental health concerns (e.g., Hawker & Boulton, 2000; Hou et al., 2020; Ivanova et al., 2022). Thus, the 2011 JCCAP Special Section posed a question: Might these informant discrepancies contain data relevant to understanding youth mental health? Suppose none of the work in youth mental health is immune from these discrepancies. In that case, the answer to this question strikes at the core of what we produce―from the interventions we develop and implement, to the developmental psychopathology research that informs intervention development

A scalable, single session intervention for perceived control over anxiety during COVID-19

Anxiety is rising across the United States during the COVID-19 pandemic, and social distancing mandates preclude in-person mental healthcare. Anxiety is not necessarily pathological; however, increased worrying about COVID-19 shows links to more severe anxiety pathology. Greater perceived control over anxiety has predicted decreased anxiety pathology, including adaptive responses to uncontrollable stressors. Evidence suggests that no-therapist, single-session interventions can strengthen perceived control over emotions like anxiety; similar programs, if designed for the COVID-19 context, could hold substantial public health value. Our registered report will test whether a no-therapist, single-session online intervention adapted for the COVID-19 context can: 1) decrease generalized anxiety and increase perceived control over anxiety, versus a placebo intervention 2) without decreasing social-distancing intentions. We will test these questions using a between-subjects design in a weighted-probability U.S. sample (N=500). Findings will inform whether a highly-scalable intervention can decrease anxiety without yielding unwanted secondary effects