Sara J. Weston

Personality Traits Predict the Onset of Disease

While personality traits have been linked concurrently to health status and prospectively to outcomes such as mortality, it is currently unknown whether traits predict the diagnosis of a number of specific diseases (e.g., lung disease, heart disease, and stroke) that may account for their mortality effects more generally. A sample (N = 6,904) of participants from the Health and Retirement Study, a longitudinal study of older adults, completed personality measures and reported on current health conditions. Four years later, participants were followed up to see if they developed a new disease. Initial cross-sectional analyses replicated past findings that personality traits differ across disease groups. Longitudinal logistic regression analyses predicting new disease diagnosis suggest that traits are associated with the risk of developing disease—most notably the traits of conscientiousness, neuroticism, and openness. Findings are discussed as a means to identify pathways between personality and health.

Connecting social environment variables to the onset of major specific health outcomes.

Objective: The present research examined the effects of the social environment on the onset of specific health ailments. Design: Using data from the Health and Retirement Study, we examined participants’ responses to social environment questions in 2006 as predictors of onset of different health conditions over the next four years. Main Outcome Measures: Healthy participants (n = 7514) reported on their number of social partners, interaction frequency, positive social support and negative social support with respect to both their family and friends. These variables were used to predict onset of seven conditions in 2010: high blood pressure, heart condition, lung disease, cancer, stroke, diabetes and arthritis. Results: Logistic regressions indicated that the social environment provided some predictive value for onset of most health outcomes, with more positive and less negative social support appearing to buffer against onset. Social environmental variables related to friendships appeared to play a greater role than the family indicators. However, no variable proved universally adaptive, and social indicators had little value in predicting onset of chronic conditions. Conclusion: The current findings point to the potential for the social environment to influence later health, while demonstrating the nuanced role that our social lives play with respect to health.

A Comparison of Human Narrative Coding of Redemption and Automated Linguistic Analysis for Understanding Life Stories.

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.

How do people respond to health news? The role of personality traits

When a patient receives a health diagnosis, their response (e.g. changes in behaviour, seeking support) can have significant consequences for long-term health and well-being. Characteristics of health news are known to influence these responses, but personality traits have been omitted from this line of research. The current study examines the role of personality traits in predicting response to health news. Participants (N = 298) read scenarios in which they received health news that was manipulated to vary in severity, controllability and likelihood of outcomes. Participants then rated how likely they were to engage in a number of response behaviours. We examined the main effects and interaction of situational manipulations and personality traits on ratings of these behaviours. Both situations and personality traits influenced behavioural responses to health events. In particular, conscientiousness predicted taking action and seeking social support. Neuroticism predicted both maladaptive and adaptive behavioural responses, providing support for the ‘healthy neurotic’ hypothesis. Moreover, personality traits predicted best in weak (unlikely, controllable) situations. Both personality traits and situational characteristics contribute to behavioural responses to health news.

The co-development of perceived support and the Big Five in middle and older adulthood:

The current study examined whether relationships also influence personality trait development during middle and older adulthood, focusing on the individual’s perception of support from the relationship partner. Using data from the Health and Retirement Study (n = 20,422; mean age = 65.9 years), we examined the longitudinal relationships between Big Five personality trait levels and perceived support from children, family, friends, and spouses. Results found that participants who reported more positive social support and lower negative support also tended to score higher on conscientiousness, extraversion, agreeableness, and openness to experience, but lower on neuroticism. Moreover, changes in positive support across relationship partners coincided with trait changes over time, in the form of more positive support was associated with seemingly adaptive changes on the Big Five. Findings are discussed with respect to identifying social influences on personality development in adulthood.

Personality development and health

Numerous studies that link personality traits with health status, sometimes decades in the future, providing a strong claim for personality traits to causally influence physical health. While the prevailing consensus is that personality traits influence health through intermediary processes like health behaviors, less discussed is the possibility that health status influences personality. In this chapter, we describe the existing evidence that health is associated with changes in personality and discuss the potential mechanisms that relate the two.

Reconsidering what is vital about vital signs in electronic health records: Comment on Matthews et al. (2016).

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