David M. Condon

Development and Validation of the Comprehensive Health Activities Scale: A New Approach to Health Literacy Measurement

Current health literacy measures have been criticized for solely measuring reading and numeracy skills when a broader set of skills is necessary for making informed health decisions, especially when information is often conveyed verbally and through multimedia video. The authors devised 9 health tasks and a corresponding 190-item assessment to more comprehensively measure health literacy skills. A sample of 826 participants between the ages of 55 and 74 years who were recruited from an academic general internal medicine practice and three federally qualified health centers in Chicago, Illinois, completed the assessment. Items were reduced using hierarchical factor analysis and item response theory resulting in the 45-item Comprehensive Health Activities Scale. All 45 items loaded on 1 general latent trait, and the resulting scale demonstrated high reliability and strong construct validity using measures of health literacy and global cognitive functioning. The predictive validity of the Comprehensive Health Activities Scale using self-reported general, physical, and mental health status was comparable to or better than widely used measures of health literacy, depending on the outcome. Despite comprehensively measuring health literacy skills, items in the Comprehensive Health Activities Scale supported 1 primary construct. With similar psychometric properties, current measures may be adequate, depending on the purpose of the assessment.

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.

Fundamental Questions in Personality

The network perspective represents a novel contribution to personality theory by conceptualising personality traits as emerging from the mutual dependencies between fundamental and causal affective, behavioural, and cognitive components. We argue that incorporating a more nuanced biological and developmental perspective to causality and a more precise approach to affective, behavioural, cognitive and motivational components may serve to enrich the network perspective. Although the graphical approach to modelling personality is aesthetically pleasing, analytic techniques are not yet available to put network models to the (quantitative) test. Copyright

Development and Validation of the Consumer Health Activation Index

Background. Although there has been increasing interest in patient engagement, few measures are publicly available and suitable for patients with limited health literacy. Objective. We sought to develop a Consumer Health Activation Index (CHAI) for use among diverse patients. Methods. Expert opinion, a systematic literature review, focus groups, and cognitive interviews with patients were used to create and revise a potential set of items. Psychometric testing guided by item response theory was then conducted among 301 English-speaking, community-dwelling adults. This included differential item functioning analyses to evaluate item performance across participant health literacy levels. To determine construct validity, CHAI scores were compared to scales measuring similar personality constructs. Associations between the CHAI and physical and mental health established predictive validity. A second study among 9,478 adults was used to confirm CHAI associations with health outcomes. Results. Exploratory factor analyses revealed a single-factor solution with a 10-item scale. The CHAI showed good internal consistency (alpha = 0.81) and moderate test–retest reliability (ICC = 0.53). Reading grade level was found to be at the 6th grade. Moderate to strong correlations were found with similar constructs (Multidimensional Health Locus of Control, r = 0.38, P < 0.001; Conscientiousness, r = 0.41, P < 0.001). Predictive validity was demonstrated through associations with functional health status measures (depression, r = −0.28, P < 0.001; anxiety, r = −0.22, P < 0.001; and physical functioning, r = 0.22, P < 0.001). In the validation sample, the CHAI was significantly associated with self-reported physical and mental health (r = 0.31 and 0.32 respectively; both P < 0.001). Conclusions. The CHAI appears to be a valid, reliable, and easily administered tool that can be used to assess health activation among adults, including those with limited health literacy. Future studies should test the tool in actual use and explore further applications.

Web- and Phone-based Data Collection using Planned Missing Designs

The past few years have seen a revolution in the way that we are able to collect data. Using diaries (Bolger, Davis, & Rafaeli, 2003; Green, Rafaeli, Bolger, Shrout, & Reis, 2006) or smart phones (Mehl & Conner, 2012; Wilt, Funkhouser, & Revelle, 2011) to measure states within subjects across multiple time periods or the web to collect measures on thousands of subjects at a time (Gosling, Vazire, Srivastava, & John, 2004; Rentfrow, Gosling, & Potter, 2008; Revelle, Wilt, & Rosenthal, 2010; Wilt, Condon, & Revelle, 2011) has led to an exciting explosion in the amount of data collected. However, most of these studies ask the same questions of all of their participants. In this chapter we review an alternative approach where we intentionally give each participant just a small subset of the items of interest but, with the power of basic psychometrics and sampling theory, are able to analyze the data as if far more items were presented. We refer to this procedure as Synthetic Aperture Personality Assessment (SAPA) (Condon & Revelle, 2014; Revelle et al., 2010) to emphasize the use of synthetic covariance matrices. That is, we find the correlations between composite scales, not based upon scoring the raw items, but rather by synthetically finding the covariances between scales based upon basic covariance algebra applied to the pair-wise complete item covariances. We think of these techniques as analogous to the techniques used in radio astronomy where the resolving power (aperture) of a set of radio telescopes may be greatly increased by synthesizing the signals collected by each individual telescope. Indeed, by combining the signals of radio telescopes scattered around the world, the effective aperture of these long baseline radio telescopes is the size of the entire earth. Because our covariance matrices are

Levels of personality

This comment critiques Corr’s (2010) characterization of the personality traits associated with the elements of Gray’s conceptual nervous system: The behavioural inhibition system (BIS), the behavioural approach system (BAS) and the fight-flight-freeze system (FFFS). Most attention is paid to the FFFS because least is known about its manifestation in personality. Additionally, I suggest that Corr’s framework for understanding automatic and controlled processing is useful for developing theories of the biological systems underlying traits that are not directly related to BIS, BAS and FFFS. Copyright # 2010 John Wiley & Sons, Ltd.

A SAPA Project Update: On the Structure of phrased Self-Report Personality Items

Two large samples were collected to evaluate the structure of traits in the temperament domain. In both samples, participants were administered random subsets of public-domain personality items from a larger pool of approximately 700 items. These data broadly cover the most widely used, public-domain measures of personality (though this breadth is not likely free of theoretical bias). When combined with a third, previously-shared dataset that used the same methodological design [4], the sample includes more than 125,000 participants from more than 220 countries and regions. Re-use potential includes many types of structural, correlational, and network analyses of personality and a wide range of demographic and psychographic constructs. The data are available in both rdata and csv formats.

Who Are the Scrooges? Personality Predictors of Holiday Spending

The sharp increase in consumption over the holiday season has important economic implications, yet the psychology underlying this phenomenon has received limited attention. Here, we evaluate the role of individual differences in holiday spending patterns. Using 2 million transactions across 2,133 individuals, we investigate the relationship between the Big 5 personality traits on spending at Christmas. Zero-order correlations suggest holiday spending is associated with conscientiousness, neuroticism, and extraversion; the relationship with neuroticism persists after accounting for possible confounders including income and demographics. These results improve our understanding of how different personality traits predict how people respond to the environmental demands of the holiday season and have broader implications for how personality relates to consumer behavior.

Cross-sectional validation of the PROMIS-Preference scoring system

Objectives The PROMIS-Preference (PROPr) score is a recently developed summary score for the Patient-Reported Outcomes Measurement Information System (PROMIS). PROPr is a preference-based scoring system for seven PROMIS domains created using multiplicative multi-attribute utility theory. It serves as a generic, societal, preference-based summary scoring system of health-related quality of life. This manuscript evaluates construct validity of PROPr in two large samples from the US general population. Methods We utilized 2 online panel surveys, the PROPr Estimation Survey and the Profiles-Health Utilities Index (HUI) Survey. Both included the PROPr measure, patient demographic information, self-reported chronic conditions, and other preference-based summary scores: the EuroQol-5D (EQ-5D-5L) and HUI in the PROPr Estimation Survey and the HUI in the Profiles-HUI Survey. The HUI was scored as both the Mark 2 and the Mark 3. Known-groups validity was evaluated using age- and gender-stratified mean scores and health condition impact estimates. Condition impact estimates were created using ordinary least squares regression in which a summary score was regressed on age, gender, and a single health condition. The coefficient for the health condition is the estimated effect on the preference score of having a condition vs. not having it. Convergent validity was evaluated using Pearson correlations between PROPr and other summary scores. Results The sample consisted of 983 respondents from the PROPr Estimation Survey and 3,000 from the Profiles-HUI survey. Age- and gender-stratified mean PROPr scores were lower than EQ-5D and HUI scores, with fewer subjects having scores corresponding to perfect health on the PROPr. In the PROPr Estimation survey, all 11 condition impact estimates were statistically significant using PROPr, 8 were statistically significant by the EQ-5D, 7 were statistically significant by HUI Mark 2, and 9 were statistically significant by HUI Mark 3. In the Profiles-HUI survey, all 21 condition impact estimates were statistically significant using summary scores from all three scoring systems. In these samples, the correlations between PROPr and the other summary measures ranged from 0.67 to 0.70. Conclusions These results provide evidence of construct validity for PROPr using samples from the US general population.

Patient and healthcare provider views on a patient-reported outcomes portal

Background Over the past decade, public interest in managing health-related information for personal understanding and self-improvement has rapidly expanded. This study explored aspects of how patient-provided health information could be obtained through an electronic portal and presented to inform and engage patients while also providing information for healthcare providers. Methods We invited participants using ResearchMatch from 2 cohorts: (1) self-reported healthy volunteers (no medical conditions) and (2) individuals with a self-reported diagnosis of anxiety and/or depression. Participants used a secure web application (dashboard) to complete the PROMIS® domain survey(s) and then complete a feedback survey. A community engagement studio with 5 healthcare providers assessed perspectives on the feasibility and features of a portal to collect and display patient provided health information. We used bivariate analyses and regression analyses to determine differences between cohorts. Results A total of 480 participants completed the study (239 healthy, 241 anxiety and/or depression). While participants from the tw2o cohorts had significantly different PROMIS scores (p < .05), both cohorts welcomed the concept of a patient-centric dashboard, saw value in sharing results with their healthcare provider, and wanted to view results over time. However, factors needing consideration before widespread use included personalization for the patient and their health issues, integration with existing information (eg electronic health records), and integration into clinician workflow. Conclusions Our findings demonstrated a strong desire among healthy people, patients with chronic diseases, and healthcare providers for a self-assessment portal that can collect patient-reported outcome metrics and deliver personalized feedback.