A proposed model for the psychometric evaluation of clinical case formulations with quantified causal diagrams.

Haynes, Stephen N.; O’Brien, William H.; Godoy, Antonio

doi:10.1037/pas0000811

Cited by 11 publications

(17 citation statements)

References 62 publications

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“…Rating perceived causal relations. The respondent was then asked to report to what degree each selected item was caused by every other selected item (corresponding to the "estimated magnitude of effect" in Haynes et al, 2020). For each item, the respondent was presented with a list of every other selected item and asked to select no more than three of these items as causes.…”

Section: The Online Pecan Questionnairementioning

confidence: 99%

Perceived Causal Problem Networks: Reliability, Central Problems, and Clinical Utility for Depression

2021

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Personalized case conceptualization is often regarded as a prerequisite for treatment success in psychotherapy for patients with comorbidity. This article presents Perceived Causal Networks, a novel method in which patients rate perceived causal relations among behavioral and emotional problems. First, 231 respondents screening positive for depression completed an online Perceived Causal Networks questionnaire. Median completion time (including repeat items to assess immediate test–retest reliability) was 22.7 minutes, and centrality measures showed excellent immediate test–retest reliability. Networks were highly idiosyncratic, but worrying and ruminating were the most central items for a third of respondents. Second, 50 psychotherapists rated the clinical utility of Perceived Causal Networks visualizations. Ninety-six percent rated the networks as clinically useful, and the information in the individual visualizations was judged to contain 47% of the information typically collected during a psychotherapy assessment phase. Future studies should individualize networks further and evaluate the validity of perceived causal relations.

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Section: The Online Pecan Questionnairementioning

confidence: 99%

Perceived Causal Problem Networks: Reliability, Central Problems, and Clinical Utility for Depression

2021

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“…The steps depicted also include elements (e.g., moderator variables and bidirectional causal relations) that are not included in the CCFCDC analyses but may be the subject of subsequent refinements. More detailed descriptions of the concepts and strategies of CCFCDs are presented (Haynes et al, 2020). Appendix B indicates the symbols used in a CCFCD, Appendix C outlines the strategies for constructing a CCFCD, and Appendix D summarizes the entire process.…”

Section: Path Analyses Of Quantified Ccfcds With Python and Ccfcdcmentioning

confidence: 99%

“…Despite their frequent promotion, there is little evidence about the reliability, validity, or treatment utility of CCFs (see review in Hurl et al, 2016). Haynes et al (2020) illustrated how the psychometric evaluation of CCFCDs could be facilitated by assigning quantitative values to the clinician's judgments of the behavior problem importance, modifiability of causal variables, and the strength of causal relations. Figure 2 includes values assigned to the clinician's judgments that are shown in Figure 1.…”

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confidence: 99%

“…Although emphasizing how the quantified CCFCDs could promote and facilitate their psychometric evaluation, Haynes et al (2020) noted "We do not advocate the use of quantified CCFCDs in routine clinical practice because it is cumbersome without computerized path analyses : : : " Consider the difficulty in estimating the relative magnitudes of effect from treatments associated with each of the five hypothesized causal variables shown in Figure 3, which is only slightly more complicated than the CCFCD shown in Figure 2. Hand calculation of the magnitudes of effect associated with the five causal variables required about 45-60 min for the authors of this article, and then with intermittent calculation errors.…”

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confidence: 99%

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

Haynes¹,

Godoy²,

Frias³

2021

Psychological Assessment

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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., Psychological Assessment, 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 (Clinical Case Formulation Causal Diagram Calculator, 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. Public Significance StatementThis article describes a computer program to help clinicians estimate the treatment focus that is most likely to help a client. The article discusses the operation of the program, gives examples, and considers its potential benefits and limitations.

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“…The case formulation also summarizes the identified problems and diagnoses as well as the motivations and features of the patient that may affect the effectiveness of treatment. The case formulation – in turn – allows the clinician to select the most effective interventions for treatment 3,4 …”

Section: Introductionmentioning

confidence: 99%

PACT: A protocol for assessment, mechanism‐based case formulation and treatment planning

Hagmayer

Witteman

Claes

2021

Evaluation Clinical Practice

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Background: Proponents of clinical case formulations argue that the causes and mechanisms contributing to and maintaining a patient's problems should be analysed and integrated into a case conceptualization, on which treatment planning ought to be based. Empirical evidence shows that an individualized treatment based on a case formulation is at least sometimes better than a standardized evidence-based treatment.Methods: We argue that it is likely to improve decisions when two conditions hold: (a) knowing about the mechanisms underlying the patient's problems makes a difference for treatment, and (b) the case formulation is based on valid knowledge about mechanisms of psychopathology.Results: We propose a protocol for assessment, case formulation and treatment planning (PACT), which incorporates transdiagnostic accounts of psychopathology. PACT describes a 5-step decision making process, which aims to help clinicians to decide when to resort to evidence-based treatments and when to construct a case formulation to individualize the treatment. Conclusion:We show how PACT works in practice by discussing treatment planning for a clinical case involving symptoms of social anxiety, depression and posttraumatic stress disorder.

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A proposed model for the psychometric evaluation of clinical case formulations with quantified causal diagrams.

Cited by 11 publications

References 62 publications

Perceived Causal Problem Networks: Reliability, Central Problems, and Clinical Utility for Depression

Perceived Causal Problem Networks: Reliability, Central Problems, and Clinical Utility for Depression

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

PACT: A protocol for assessment, mechanism‐based case formulation and treatment planning

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