The glass half-full: How optimism can bias prognosis in serious illness

Most people think of optimism as a good thing—a positive outlook in challenging circumstances. But in reality, it’s a psychological state that can be “contagious” in a bad way. A new study, published in the journal Psycho-Oncology, details how a seriously ill patient’s optimism can impact a clinician’s survival prognosis in palliative care conversations.

Senior author Robert Gramling, M.D., D.Sc., associate professor of family medicine and the Miller Chair in Palliative Medicine at the University of Vermont’s Larner College of Medicine, and colleagues at Purdue University, the University of Rochester and University of California San Francisco, state that clinicians have a duty to estimate prognosis as accurately as possible. If survival is overestimated, Gramling and his coauthors write, “these errors in judgment can prevent patients from making timely decisions about their end-of-life care.”

For their study, the researchers enrolled 189 hospital patients with advanced cancer undergoing palliative care consultations at two geographically distant sites. A total of 41 palliative care clinicians participated in the recorded consultations.

Using established measurement tools, the group calculated the frequency and distribution of such variables as “clinician overestimation of survival time,” “patient (trait) dispositional optimism,” and “patient prognostic (state) optimism” and tracked patient survival and date of death and correlated it to clinical judgement.

The group’s findings showed a generally high level of both dispositional and prognostic optimism just before palliative care consultation, as well as a correlation between higher levels of patient optimism and clinicians’ greater likelihood of overestimating survival, even after adjusting for clinical markers of survival time.

“Our study suggests that patient-level optimism might exert an unforeseen influence over palliative care clinicians’ prognostic judgments,” write the study authors, who add that “If so, then raising clinician awareness about these effects and including de-biasing steps in prognostication skills training may lead to more accurate estimates.”

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