Ben-Porath, Yossef S.

Tarescavage, Anthony M.

English

John Carroll University

John Carroll UniversityCarroll Collected2017 Faculty Bibliography Faculty Bibliographies Community Homepage12-2017Avoiding Cognitive Biases in Clinical DecisionMaking: Commentary on “EvidenceBasedAssessment as an Integrative Model for ApplyingPsychological Science to Guide the Voyage ofTreatment”Anthony M. TarescavageJohn Carroll University, atarescavage@jcu.eduYossef S. Ben-PorathKent State UniversityFollow this and additional works at: https://collected.jcu.edu/fac_bib_2017Part of the Psychology CommonsThis Article is brought to you for free and open access by the Faculty Bibliographies Community Homepage at Carroll Collected. It has been acceptedfor inclusion in 2017 Faculty Bibliography by an authorized administrator of Carroll Collected. For more information, please contact connell@jcu.edu.Recommended CitationTarescavage, Anthony M. and Ben-Porath, Yossef S., "Avoiding Cognitive Biases in Clinical Decision Making: Commentary on“EvidenceBased Assessment as an Integrative Model for Applying Psychological Science to Guide the Voyage of Treatment”" (2017).2017 Faculty Bibliography. 97.https://collected.jcu.edu/fac_bib_2017/97·   · ··  COMMENTARY Avoiding Cognitive Biases in Clinical Deci­sion Making: Commentary on "Evidence­Based Assessment as an Integrative Model for Applying Psychological Science to Guide the Voyage of Treatment" Anthony M. Tarescavage 49, John Carroll University Yossef S. Ben-Porath, Kent State University Key words: applied assessment, assessment, cogni­tive bias, evidence-based assessment. [Clin Psycho/ Sci Prac, 2017) Youngstrom et al. (2017) have proposed and described in great depth an ambitious model of evi­dence-based assessment designed to evolve the current standards of menta.l health care. They integrate a num­ber of clinical assessment principles into their model, such as a careful review of psychometrics as well as use of measures to diagnose psychopathology, plan treat­ment, and measure patient outcomes. These, of course, are not new ideas. In fact, they are well-established and well-validated principles. As the authors point out, however, sound assessment principles are not being routinely appljed by practitioners in a comprehensive and systematic way, thereby limiting their positive impact on patient care. Why is this the case? We were persuaded by the authors that a primary factor is that practitioners are not trained in an integrated model for evaluating and comprehensively using psychological assessments. That is, even if practitioners are knowl­edgeable of sound assessment principles, there is little guidance on how to comprehensively apply these prac­tices to their settings for max11num benefit. Address correspondence to Anthony M. Tarescavage, Depart­ment of Psychological Science, John Carroll University, I John Carroll Boulevard, University Heights, OH 44118. E­mail: atarcscavage@jcu.edu. Youngstrom and colleagues' model of evidence-based assessment provides chis guidance. Youngstrom and colleagues (2017) introduce their model of evidence-based assessment by way of an anal­ogy-that a client's progress through treatment is akin in some ways to a space voyage. They use this analogy to illustrate how preparation for treatment, by way of current psychological assessment practices, is much less efficient and effective than what would be expected for space travel. The analogy is used to highlight the need for comprehensive, applied models of psychological assessment, such as evidence-based assessment. We propose that psychological treatment is also like a winter sea voyage. The clinician is the captain, and his or her passengers are the patients. The clinician's job, much like that of the captain, is co quickly and safely guide patients co their ultimate destination: suc­cessful completion of therapy. The captain and the clinician have unique education in this area. The cap­tain is trained in navigation and the inner workings of his or her ship. The clinician is trained in treatment modalities and the functions of thoughts, emotions, and behaviors. Boch the clinician and the captain are essential. However, in spite of their training, both the clinician and the captain of the winter sea voyage can be blind-sided. In this analogy, cognitive biases are icebergs. They operate outside of a clinician's conscious awareness, likt: an iceberg just under the water's surface. In spite of extensive training and experience, cognitive biases can disrupt decision making, in some cases leading co disastrous consequences. For example, in the case of clinician predictions about suicide or violence risk, the influence of cognitive biases could quite literally be the difference between life and death. In less severe instances, cognitive biases could influence incorrect diagnoses and treatment decisions, leading to delays in or failure to achieve progress in the client's journey through therapy. Lilienfeld and Lynn (2014) review biases in cljrucal decision making, including confirmation bias, overcon­fidence, and the bias blind spot. Confirmation bias is actively searching for information that confirms an initial hypothesis while also discounting evidence that is not consistent with the initial hypothesis. It can cause clinicians to avoid or distort disconfirming evidence. Overconfidence is a fonn of bias in which clinicians overestimate the accuracy of their judgments. Contrary to this belief, clinician confidence does not appear to be meaningfully related to judgment accuracy (Miller, Spengler, & Spengler, 2015). Finally, the bias blind spot is a meta-bias, in which clinicians can identify bias in others' decision making but not in their own. Turning back to our analogy and discussion of evi­dence-based assessment, just as the captain uses cools, such as radar, to avoid icebergs during winter travel, Youngstrom and colleagues' (2017) model highlights how Objective psychological testing can serve a similar function for reducing the 111fluence of cognitive biases on clinician decision making. Research on clinical ver­sus scatimcal prediction, most recently summarized by Grove, Zald, Lebow, Snitz, and Nelson (2000), indi­cates that psychological testing yields more accurate decisions than clinical judgment alone (Grove et al., 2000). We believe these findings, in part, reflect that objective test data are not inherently subject to cogni­tive biases. This is not to say chat clinicians and clinical judgment are not essential. R.ather, this literature indi­cates that psychological resting can offer substantial added value when integrated into models of clinical decision making, as Youngstrom and colleagues have proposed. A noteworthy strength of such a model is inclusion of a broad array of psychological testing before first contact with the patient, which could reduce the influ­ence of confirmation bias. In this way, initial hypothe­ses flow from objective test data rather than clinical judgment. If the testing is broad in scope, several initial hypotheses are possible. Contrast this with the tradi­tional approach, where testing is administered later in the assessment process. At this point, the clinician has already formed hypotheses using clinical judgn1ent and, when faced with disconfinning evidence from testing, may be more likely to discount or distort the objective test data chat call into question the initial hypotheses. When starting with psychological testing, the clinician anchors hypotheses co objective data but then also has the freedom co explore more specific areas of inquiry 2 in me interview co arrive at a final diagnosis and an idiographic case conceptualization. Another strength of the evidence-based model is chat psychological testing can be integrated into all phases of treatment, rather than just the intake process. Youngstrom and colleagues (2017) describe, for exam­ple, how psychotherapeutic outcome measures can be used to track client progress. These are relatively short assessments designed co be administered throughout therapy, as often as every session. Pase research indicates that patients of clinicians who use outcome measures have more success in therapy (see Tarescavage & Ben­Porath, 2014, for a review). Here, coo, we believe the ucihcy of outcome measures is, in part, due to their immunity from cognittve biases, particularly confirma­tion bias. For example, a chmcian could assume the cli­ent's symptoms are decreasing outside of the session without actively inquiring about them. R.ourine use of outcome measures puts a check on this form of bias, enabling the clinician to make changes to the treatment plan that will better reduce the client's symptoms when therapy progress has slowed. In summary, use of psychological testing before first contact with the patient and its use throughout treat­ment are two of the many ways chat evidence-based assessment can improve client care by reducing the influence of cognitive biases. We look forward co fur­ther development and implementation of the model. In the meantime, clinicians may be well served co follow the principles chat appear to have guided the tenets of evidence-based assessment-namely, that like radar for the sea captain, psychological testing is a valuable cool chat should be integrated into all phases of treatment accordingly. REFERENCES Grove, W. M., Zald, D. H., Lebow, 8. S., Snitz, 8. E., & Nelson, C. (2000). Clinical versus mechanical prediction: A meta-analysis. Psyclrological Assess111e111, 12, 19-30. https:/ /doi.org/ 10. !037/1040-3590.12. l .19 Lilienfeld, S. 0., & Lynn, S. J. (2014). Errors/biases in clinical decision making. In R.. I. Cautin & S. 0. Lilienfeld (Eds.), TI,c encyclopedia of cli11ical psyclrology (pp. 1-9). Hoboken, NJ: John Wiley & Sons. Miller, D. J., Spengler, E. S., & Spengler, P. M. (2015). A meta-analysis of confidence and judgment accuracy in clinical decision making. Joumal of Counseling Psyclrology, 62, 553-567. https://doi.org/l0.1037/cou0000105 Tarescavage, A. M., & Ben-Porath, Y. S. (2014). Psychotherapeutic outcomes measures: A cntical review for practitioners. joumal of Clinical Psyclrology, 70, 808-830. https:/ /doi.org/10. 1002/jclp.22080 Youngstrom, E. A., Van Meter, A., Frazier, T. W., Hunsley, J., Prinstein, M. J., Ong, M.-L., & Youngstrom, J. K. COMMENTARY ON YOUNGSTROM ET Al. (2017). Evidence-based assessment as an integranve model for applying psychological science to guide the voyage of treatment. Clinical Psyclrology: Science and Practice. Advance online publication. https://do1.org/l0.I I I l/cpsp.l2207. R.ece,ved September 12, 2017; accepted September 12, 2017. 

Avoiding Cognitive Biases in Clinical Decision Making: Commentary on “EvidenceBased Assessment as an Integrative Model for Applying Psychological Science to Guide the Voyage of Treatment”

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Avoiding Cognitive Biases in Clinical Decision Making: Commentary on “EvidenceBased Assessment as an Integrative Model for Applying Psychological Science to Guide the Voyage of Treatment”

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