Abstract
Cognitive theories of emotion posit that affective responses may be shaped by how individuals interpret emotion-eliciting situations. This study tested whether individual differences in interpretation bias (i.e., interpreting ambiguous scenarios in a more negative or positive manner) independently predict trait resilience and depression in medical interns. Interpretation bias and trait resilience scores were assessed in 47 interns prior to their first internship. Depressive symptoms were assessed twice during internship. Nearly half of the sample (42%) scored above the cut-off for mild depressive symptoms during internship, a significant rise compared to the initial assessment. Those with a more positive interpretation bias had higher trait resilience (β = 0.44, p = 0.004) and a 6-fold decreased depressive symptom risk during internship (OR = 6.41, p = 0.027). The predictive power of a positive interpretation bias for decreased depression symptoms held over and above initial depressive symptoms, demographics and trait reappraisal. Assessing positive interpretation bias may have practical utility for predicting future well-being in at risk-populations.
Highlights
Cognitive theories of emotion posit that affective responses may be shaped by how individuals interpret emotion-eliciting situations
Initial depression symptoms were significantly associated with a negative interpretation bias, β = −0.45, p = 0.004, R2 = 0.25
We investigated the predictive power of a positive interpretation bias on resilience and prospective depressive symptoms in an at-risk population, medical students commencing their first internship
Summary
Cognitive theories of emotion posit that affective responses may be shaped by how individuals interpret emotion-eliciting situations. Beck’s model of depression, for instance, highlights the tendency to interpret situations in a negatively biased manner as a key factor that may result in a negatively biased worldview and lead to depressed mood (Beck, 1976, 1987). Such a negative interpretation bias can be measured by means of responses to ambiguous scenarios (Butler and Mathews, 1983; Berna et al, 2011). A study by Rude et al (2002) assessed negative interpretation patterns using a scrambled sentences task and showed that a negative interpretation bias predicted subsequent depressive symptoms in undergraduate students
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