Personality disorders (PD) and related traits are associated with and predictive of medical outcomes. One mechanism whereby this may occur is through the interaction of PD traits and distress during treatment of chronic illness, especially in cancer. The majority of head and neck cancers (HNC) are caused by alcohol and tobacco, the disordered use of which is prevalent in those with PDs. This study examined how PD traits relate to distress for individuals during and after treatment of HNC (32.8% in active treatment). A sample of 137 individuals (70.8% male; median age 66) with a diagnosis of HNC from a large southeastern cancer center completed measures of personality and psychological distress. Results of Bayesian structural equation modeling indicated that higher levels of trait negative affectivity related to greater psychological distress. Contrary to our hypotheses, Bayesian one-sample tests indicated that those with HNC may be much lower, rather than higher, in PD traits compared to a census-weighted normative community sample. Years since diagnosis (Median: 2.38 years) and treatment status were unrelated to PD trait scores, suggesting that recency of a diagnosis and active treatment may not explain the PD trait findings. Overall, PD trait scores may be lower in HNC samples and some of these traits may be predictive of distress during and after HNC treatment. Future research should use prospective longitudinal designs and examine how PD traits measured before a cancer diagnosis can affect the course of distress during and after HNC treatment. Using PD trait measures to identify those who are at greater risk of distress may allow clinics to allocate clinical resources to those individuals to address their distress and health behaviors.
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Doctor of Philosophy (Ph.D.)
College of Sciences
Psychology; Clinical Psychology
Length of Campus-only Access
Doctoral Dissertation (Open Access)
Spencer, Christopher, "Maladaptive Personality Traits and Acute Psychological Distress in Individuals with Head and Neck Cancer" (2020). Electronic Theses and Dissertations, 2020-. 296.