Selecting treatment foci in clinical case formulations: Estimating the clinical benefits of modifying causal variables.

Clinical case formulations (CCFs) can be organized and communicated in several ways but one of the most effective is through CCF causal diagrams (CCFCDs). Haynes et al., , 2020, 32, 541 illustrated how the psychometric evaluation of CCFCDs could be facilitated by assigning quantitative values to the clinician's judgments in a CCF. Although quantification could facilitate the psychometric evaluation CCFCDs, it is less clear that it can help clinicians make decisions about the best treatment foci. This article presents an open-source computer program ( CCFCDC) for the path analyses of quantified CCFCDs, based on the free computing language Python, to assist in clinical decision making. The operation, examples, assets, and limitations of the CCFCDC are discussed in the context of measurement principles, precision, and uncertainty in clinical judgments. (PsycInfo Database Record (c) 2021 APA, all rights reserved).