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The inclusion of psychosocial variables into electronic health records provides a unique opportunity for the translation of findings from social, psychological, and behavioral domains into patient care. This commentary is a response to the recommendations of a committee convened by the Institute of Medicine to address this opportunity (Matthews, Adler, Forrest, & Stead, 2016). We concur with the committee that the inclusion of psychosocial variables in electronic health records will broadly benefit researchers, practitioners, and patients and that there is clear need for a recommended panel of psychosocial measures that is ready for implementation in clinical settings. In fact, it seems likely that these recommendations will have lasting consequences. Given this, our response highlights several concerns about the recommendations and criteria. We suggest further clarification of the audience for these recommendations, reconsideration of the overly restrictive inclusion criteria, and more extensive engagement of psychosocial researchers to achieve broader consensus. (PsycINFO Database Record, ((c) 2017 APA, all rights reserved).)

Personality traits are important predictors of health behaviors, healthcare utilization, and health outcomes. However, we know little about the role of personality traits for emergency department outcomes. The present study used data from 200 patients (effective Ns range from 84 to 191), who were being discharged from the emergency department at an urban hospital, to investigate whether the Big Five personality traits were associated with post-discharge outcomes (i.e., filling prescriptions, following up with primary care physician, making an unscheduled return to the emergency department). Using logistic regression, we found few associations among the broad Big Five domains and post-discharge outcomes. However, results showed statistically significant associations between specific Big Five items (e.g., “responsible”) and the three post-discharge outcomes. This study demonstrates the feasibility of assessing personality traits in an emergency medicine setting and highlights the utility of having information about patients’ personality tendencies for predicting post-discharge compliance. [ABSTRACT FROM AUTHOR]

Personality is not the most popular subfield of psychology. But, in one way or another, personality psychologists have played an outsized role in the ongoing “credibility revolution” in psychology. Not only have individual personality psychologists taken on visible roles in the movement, but our field’s practices and norms have now become models for other fields to emulate (or, for those who share Baumeister’s (2016, https://doi.org/10.1016/j.jesp.2016.02.003) skeptical view of the consequences of increasing rigor, a model for what to avoid). In this article we discuss some unique features of our field that may have placed us in an ideal position to be leaders in this movement. We do so from a subjective perspective, describing our impressions and opinions about possible explanations for personality psychology’s disproportionate role in the credibility revolution. We also discuss some ways in which personality psychology remains less-than-optimal, and how we can address these flaws. [ABSTRACT FROM AUTHOR]

The majority of life narrative research is performed using trained human coders. In contrast, automated linguistic analysis is oft employed in the study of verbal behaviors. These two methodological approaches are directly compared to determine the utility of automated linguistic analysis for the study of life narratives. In a study of in-person interviews (N = 158) and a second study of life stories collected online (N = 242), redemption scores are compared to the output of the Linguistic Inquiry and Word Count (Pennebaker, Francis & Booth, 2001). Additionally, patterns of language are found using exploratory principal components analysis. In both studies, redemption scores are modestly correlated with some LIWC categories and unassociated with the components. Patterns of language do not replicate across samples, indicating that the structure of language does not extend to a broader population. Redemption scores and linguistic components are independent predictors of life satisfaction up to 3 years later. These studies converge on the finding that human-coded redemption and automated linguistic analysis are complementary and nonredundant methods of analyzing life narratives, and considerations for the study of life narratives are discussed. [ABSTRACT FROM AUTHOR]