Personality Predicts Mortality Risk: An Integrative Data Analysis of 15 International Longitudinal Studies.

This study examined the Big Five personality traits as predictors of mortality risk, and smoking as a mediator of that association. Replication was built into the fabric of our design: we used a Coordinated Analysis with 15 international datasets, representing 44,094 participants. We found that high neuroticism and low conscientiousness, extraversion, and agreeableness were consistent predictors of mortality across studies. Smoking had a small mediating effect for neuroticism. Country and baseline age explained variation in effects: studies with older baseline age showed a pattern of protective effects (HR<1.00) for openness, and U.S. studies showed a pattern of protective effects for extraversion. This study demonstrated coordinated analysis as a powerful approach to enhance replicability and reproducibility, especially for aging-related longitudinal research.

Health Literacy and Patient-Reported Outcomes: A Cross-Sectional Study of Underserved English- and Spanish-Speaking Patients With Type 2 Diabetes.

This study examined associations between patient characteristics, health behaviors, and health outcomes and explored the role of health literacy as a potential mediator of outcomes. English- and Spanish-speaking adults with Type 2 diabetes used a bilingual multimedia touchscreen to complete questionnaires. The behavioral model for vulnerable populations guided multivariable regression and mediation testing. Dependent variables were diabetes self-care, health status, and satisfaction with communication. Independent variables included sociodemographic and clinical characteristics, health literacy, health beliefs, and self-efficacy. Spanish speakers had lower health literacy and poorer physical, mental, and overall health compared to English speakers. Higher health literacy was associated with less social support for diet, fewer diet and medication barriers, younger age, higher diabetes knowledge, and talking with health care professionals to get diabetes information. In contrast to expectations, health literacy was not associated with diabetes self-care, health status, or satisfaction with communication, and it did not mediate the effects of other factors on these outcomes. Diabetes self-efficacy was significantly associated with health behaviors and outcomes. The association between Spanish language preference and poorer health was not mediated by this group's lower health literacy. Increasing health-related self-efficacy might be an important clinical strategy for improving outcomes in underserved patients with Type 2 diabetes.

Linking Physical and Mental Health Summary Scores from the Veterans RAND 12-Item Health Survey (VR-12) to the PROMIS(®) Global Health Scale.

BACKGROUND: Global health measures represent an attractive option for researchers and clinicians seeking a brief snapshot of a patient's overall perspective on his or her health. Because scores on different global health measures are not comparable, comparative effectiveness research (CER) is challenging. OBJECTIVE: To establish a common reporting metric so that the physical and mental health scores on the Veterans RAND 12-Item Health Survey (VR-12 (©) ) can be converted into scores on the corresponding Patient Reported Outcomes Measurement Information System (PROMIS(®)) Global Health scores. DESIGN: Following a single-sample linking design, participants from an Internet panel completed items from the PROMIS Global Health and VR-12 Health Survey. A common metric was created using analyses based on item response theory (IRT), producing score cross-walk tables for the mental and physical health components of each measure. The linking relationships were evaluated by calculating the standard deviation of differences between the observed and linked PROMIS scores and estimating confidence intervals by sample size. PARTICIPANTS: Participants (N = 2025) were 49 % male and 73 % white; mean age was 46 years. MAIN MEASURES: Mental and physical health subscales of the PROMIS Global Health and the VR-12. The mean VR-12 physical component and mental component scores were 45.2 and 46.6, respectively; the mean PROMIS physical and mental health scores were 48.3 and 48.5, respectively. KEY RESULTS: We found evidence that the combined set of VR-12 and PROMIS items were relatively unidimensional and that we could proceed with linking. Linking worked better between the physical health than mental health scores using VR-12 item responses (vs. linking based on algorithmic scores). For each of the cross-walks, users can minimize the impact of linking error with modest increases in sample sizes. CONCLUSIONS: VR-12 scores can be expressed on the PROMIS Global Health metric to facilitate the evaluation of treatment, including CER. Extending these results to other common measures of global health is encouraged.

Establishing a common metric for self-reported pain: linking BPI Pain Interference and SF-36 Bodily Pain Subscale scores to the PROMIS Pain Interference metric.

PURPOSE: The study purposes were to mathematically link scores of the Brief Pain Inventory Pain Interference Subscale and the Short Form-36 Bodily Pain Subscale (legacy pain interference measures) to the NIH Patient-Reported Outcome Measurement Information System (PROMIS(®)) Pain Interference (PROMIS-PI) metric and evaluate results. METHODS: Linking was accomplished using both equipercentile and item response theory (IRT) methods. Item parameters for legacy items were estimated on the PROMIS-PI metric to allow for pattern scoring. Crosswalk tables also were developed that associated raw scores (summed or average) on legacy measures to PROMIS-PI scores. For each linking strategy, participants' actual PROMIS-PI scores were compared to those predicted based on their legacy scores. To assess the impact of different sample sizes, we conducted random resampling with replacement across 10,000 replications with sample sizes of n = 25, 50, and 75. RESULTS: Analyses supported the assumption that all three scales were measuring similar constructs. IRT methods produced marginally better results than equipercentile linking. Accuracy of the links was substantially affected by sample size. CONCLUSIONS: The linking tools (crosswalks and item parameter estimates) developed in this study are robust methods for estimating the PROMIS-PI scores of samples based on legacy measures. We recommend using pattern scoring for users who have the necessary software and score crosswalks for those who do not.