Condon, David

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https://hdl.handle.net/1794/27223

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Open Access
Age Differences in Personality Structure
(Oxford University Press, 2021-12-17) Jackson, Joshua; Condon, David M.; Beck, Emorie
Most investigations in the structure of personality traits do not adequately address age, as few studies look at the structure of personality traits a-theoretically, instead presupposing a theoretical structure e.g., Big Five. As a result, the relationship among indicators within a trait (coherence) are often highlighted but relationships across traits (differentiation) are not thoroughly examined. Using a large-scale sample of 369,151 individuals ranging in age from 14 to 90, the present study examines whether personality indicators show differential relationships as a function of age. Results indicate that coherence shows few changes across the lifespan, while differentiation weakens across adulthood into old age. These finding suggest that Big Five indicators only parallel the Big Five structure among young but not older adults. Thus, using standard Big Five personality trait assessments in older adults may, at best, not reflect reality and, at worse, undermine the predictive utility of personality traits.
Open Access
Behaviors predict outcomes better than the Big Five
(2017) Elleman, Lorien G.; Condon, David M.; Revelle, William
Figure 1: Correlation matrix of traditional Big Five scales, behavioral Big Five scales (composed of items from Tables 1-5), four outcomes, and four empirical scales formed from items most highly correlated with each outcome (composed of items from Tables 6-9). Color-coded for size and sign. All correlations corrected for item overlap. Lower diagonal: raw correlations. Upper diagonal: corrected for attenuation. Diagonal: alphas.
Open Access
A Call for Cross-Fertilization Among Personality and Personnel Selection Researchers
(SAGE Publications, 2017-09-01) Lezotte, Daniel V.; Condon, David M.; Mroczek, Daniel K.
Lievens (2017) makes a case for SJTs in personnel selection, a recommendation with which we agree. In particular, we like the emphasis on branching out from current methodologies and using new techniques such as SJTs not only in I/O or personnel selection research but also in basic personality research. Despite our enthusiasm, we point out some flaws, most notably lack a time dimension to SJTs.
Open Access
Climate:Weather::Traits:State
(SAGE Publications, 2017-08-06) Revelle, William; Condon, David M.
The target article by Baumert et al. is an ambitious attempt to combine personality structure, process and development into a coherent whole. We applaud the effort and would like to suggest an analogy that might prove useful when addressing their three questions. The analogy is the physics involved in the climate sciences. Indeed we have suggested that “personality is to emotion as climate is to weather” that is, that what we call personality traits are a long term average of behaviors and emotional reactions that can seem to have different causes than the short term fluctuations known as emotional, cognitive and behavioral states (Revelle, 2007, Revelle and Wilt, 2016).
Open Access
The Convergence of Self and Informant Reports in a Large Online Sample
(University of California Press, 2021-01-04) Zola, Anne; Condon, David M.; Revelle, William
Despite their added benefits, informant-reports are largely underutilized in personality research. We demonstrate the feasibility of collecting informant-reports online, where researchers have unprecedented access to large, global populations. Using an entirely free, opt-in procedure tied to an existing personality survey, we collected 1,554 informant-reports for 921 unique targets, in conjunction with over 158,000 self-reports. Informant-reports showed a strong correspondence to self-reported traits at three levels of analysis: among the Big Five domains, the lower-level SPI-27 factors (Condon, 2018), and at the item-scale level. Among the Big Five, self-informant agreement ranged between .63 and .72, except for Openness (.42). Higher informant-ratings of Extraversion were positively associated with all Big Five self-ratings in the direction of social desirability. Across the Big Five and the 27 lower-order traits, agreement was strongest between self-reports of compassion and informant-reports of agreeableness (.74) and weakest between self-reported emotional expressiveness and informant-reported emotional stability (.02). Agreement between informants was roughly equivalent for all of the Big Five traits (.29 to .35) and attractiveness (.37), though agreement between informants for perceived intelligence was non-significant. In addition, we empirically identified the self-report items that best predict what informants say about targets, highlighting the features of self-reported personality that are most readily confirmed by informants. Finally, we discuss group level differences of participants who interacted with the informant-report system at various levels. In general, participants who sought and provided informant reports are more open and agreeable than the general sample, though targets’ personality did not affect whether or not invited informants provided ratings.
Open Access
Cross-sectional validation of the PROMIS-Preference scoring system
(Public Library of Science, 2018-07-31) Hanmer, Janel; Dewitt, Barry; Yu, Lan; Tsevat, Joel; Roberts, Mark; Revicki, Dennis; Pilkonis, Paul A.; Hess, Rachel; Hays, Ron D.; Fischhoff, Baruch; Feeny, David; Condon, David; Cella, David
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.
Open Access
Deep Lexical Hypothesis: Identifying personality structure in natural language
(Cornell University, 2022-03-04) Cutler, Andrew; Condon, David M.
Recent advances in natural language processing (NLP) have produced general models that can perform complex tasks such as summarizing long passages and translating across languages. Here, we introduce a method to extract adjective similarities from language models as done with survey-based ratings in traditional psycholexical studies but using millions of times more text in a natural setting. The correlational structure produced through this method is highly similar to that of self- and other-ratings of 435 terms reported by Saucier and Goldberg (1996a). The first three unrotated factors produced using NLP are congruent with those in survey data, with coefficients of 0.89, 0.79, and 0.79. This structure is robust to many modeling decisions: adjective set, including those with 1,710 terms (Goldberg, 1982) and 18,000 terms (Allport & Odbert, 1936); the query used to extract correlations; and language model. Notably, Neuroticism and Openness are only weakly and inconsistently recovered. This is a new source of signal that is closer to the original (semantic) vision of the Lexical Hypothesis. The method can be applied where surveys cannot: in dozens of languages simultaneously, with tens of thousands of items, on historical text, and at extremely large scale for little cost. The code is made public to facilitate reproduction and fast iteration in new directions of research.
Open Access
Descriptive, predictive and explanatory personality research: Different goals, different approaches, but a shared need to move beyond the Big Few traits
(SAGE Publications, 2020) MÕTTUS, RENÉ; Wood, Dustin; Condon, David M.; Back, Mitja D.; Baumert, Anna; Costantini, Giulio; Epskamp, Sacha; Greiff, Samuel; Johnson, Wendy; Lukaszewski, Aaron; Murray, Aja; Revelle, William; Wright, Aidan G. C.; Yarkoni, Tal; Ziegler, Matthias; Zimmermann, Johannes
We argue that it is useful to distinguish between three key goals of personality science – description, prediction and explanation – and that attaining them often requires different priorities and methodological approaches. We put forward specific recommendations such as publishing findings with minimum a priori aggregation and exploring the limits of predictive models without being constrained by parsimony and intuitiveness but instead maximising out-of-sample predictive accuracy. We argue that naturally-occurring variance in many decontextualized and multi-determined constructs that interest personality scientists may not have individual causes, at least as this term is generally understood and in ways that are human-interpretable, never mind intervenable. If so, useful explanations are narratives that summarize many pieces of descriptive findings rather than models that target individual cause-effect associations. By meticulously studying specific and contextualized behaviours, thoughts, feelings and goals, however, individual causes of variance may ultimately be identifiable, although such causal explanations will likely be far more complex, phenomenon-specific and person-specific than anticipated thus far. Progress in all three areas – description, prediction, and explanation – requires higher-dimensional models than the currently-dominant “Big Few” and supplementing subjective trait-ratings with alternative sources of information such as informant-reports and behavioural measurements. Developing a new generation of psychometric tools thus provides many immediate research opportunities.
Open Access
Development of the Initial Surveys for the All of Us Research Program
(Epidemiology, 2019-07) Cronin, Robert M.; Jerome, Rebecca N.; Mapes, Brandy; Andrade, Regina; Johnston, Rebecca; Ayala, Jennifer; Schlundt, David; Bonnet, Kemberlee; Kripalani, Sunil; Goggins, Kathryn; Wallston, Kenneth A.; Couper, Mick P.; Ellitt, Michael R.; Harris, Paul; Begale, Mark; Munoz, Fatima; Lopez-Class, Maria; Cella, David; Condon, David; AuYoung, Mona; Mazor, Kathleen M.; Mikita, Steve; Manganiello, Michael; Borselli, Nicholas; Fowler, Stephanie; Rutter, Joni L.; Denny, Joshua C.; Karlson, Elizabeth W.; Ahmedani, Brian K.; O'Donnell, Chris
Background: The All of Us Research Program is building a national longitudinal cohort and collecting data from multiple information sources (e.g., biospecimens, electronic health records, and mobile/wearable technologies) to advance precision medicine. Participant-provided information, collected via surveys, will complement and augment these information sources. We report the process used to develop and refine the initial three surveys for this program. Methods: The All of Us survey development process included: (1) prioritization of domains for scientific needs, (2) examination of existing validated instruments, (3) content creation, (4) evaluation and refinement via cognitive interviews and online testing, (5) content review by key stakeholders, and (6) launch in the All of Us electronic participant portal. All content was translated into Spanish. Results: We conducted cognitive interviews in English and Spanish with 169 participants, and 573 individuals completed online testing. Feedback led to over 40 item content changes. Lessons learned included: (1) validated survey instruments performed well in diverse populations reflective of All of Us; (2) parallel evaluation of multiple languages can ensure optimal survey deployment; (3) recruitment challenges in diverse populations required multiple strategies; and (4) key stakeholders improved integration of surveys into larger Program context. Conclusions: This efficient, iterative process led to successful testing, refinement, and launch of three All of Us surveys. Reuse of All of Us surveys, available at http://researchallofus.org, may facilitate large consortia targeting diverse populations in English and Spanish to capture participant-provided information to supplement other data, such as genetic, physical measurements, or data from electronic health records.
Open Access
Do dimensional psychopathology measures relate to creative achievement or divergent thinking?
(Frontiers in Psychology, 2014-09-18) Zabelina, Darya L.; Beeman, Mark; Condon, David
Previous research provides disparate accounts of the putative association between creativity and psychopathology, including schizotypy, psychoticism, hypomania, bipolar disorder, ADHD, and autism spectrum disorders. To examine these association, healthy, non-clinical participants completed several psychopathology-spectrum measures, often postulated to associate with creativity: the Schizotypal Personality Questionnaire, the Psychoticism scale, the Personality Inventory for DSM-5, the Hypomanic Personality Scale, the Attention Deficit/Hyperactivity Disorder scale, the Beck Depression Inventory, and the Autism-Spectrum Quotient. The goal of Study 1 was to evaluate the factor structure of these dimensional psychopathology measures and, in particular, to evaluate the case for a strong general factor(s). None of the factor solutions between 1 and 10 factors provided a strong fit with the data based on the most commonly used metrics. The goal of Study 2 was to determine whether these psychopathology scales predict, independently, two measures of creativity: 1. a measure of participants' real-world creative achievements, and 2. divergent thinking, a laboratory measure of creative cognition. After controlling for academic achievement, psychoticism and hypomania reliably predicted real-world creative achievement and divergent thinking scored with the consensual assessment technique. None of the psychopathology-spectrum scales reliably predicted divergent thinking scored with the manual scoring method. Implications for the potential links between several putative creative processes and risk factors for psychopathology are discussed.
Open Access
Estimating ability for two samples
(2022-07-13) Revelle, William; Condon, David M.
Using IRT to estimate ability is easy, but how accurate are the estimate and what about multiple samples?
Open Access
Examining Validity of MTurk Workers Responses Based on Monetary Reward
(University of Oregon, 2020) Murphy, Maggie; Murphy, Margret; Condon, David; Condon, David M.
Amazon's Mechanical Turk is an online crowdsourcing marketplace (OCM) that has become widely used for data collection in scientific research, especially in the social sciences. In psychology research, a common use of the platform is to pay MTurk workers (aka "MTurkers") to complete surveys and online behavioral tasks. The MTurkers are then paid for their contribution to the survey; however, little research has considered the effect of payment on data quality (Chmielewski & Kucker, 2019). We hypothesize that the accuracy of responses are partially dependent on the amount the MTurk Workers are paid for their responses. In this study, we sought to evaluate the effect of compensation on the care that MTurkers displayed in their responses to the survey. We look to explore the validity of MTurk responses using an SPI norming survey created by Professor Condon, and delineating it by three factors: one that compensated workers at a rate equal to the U.S. federal minimum wage, one paying minimum wage plus 25%, and a third paying 25% less than minimum wage with an unannounced bonus (up to minimum wage) after the work was completed. We compare their responses based on the time spent responding to the survey, inter-item correlations, and evidence of “patterned responding” (e.g., choosing the same response option for several questions in a row). The findings from our research will be beneficial to researchers using MTurk and other OCMs for data collection.
Open Access
Frequency of use metrics for American English person descriptors: Extensions of Roivainen's internet search methodology
(PsyArXiv, 2022-05-02) McDougald, Sarah; Condon, David M.
Personality traits are often measured using person-descriptive terms, but data are limited regarding the frequency of usage for these terms in everyday language. This project reports on the relative frequency of usage for a large pool of American English terms (N = 18,240) using count estimates from search engine results and in books cataloged by Google. These estimates are based on the ngrams formed when each descriptor is combined with a common person-related noun (person, woman, man, girl, boy). Results are reported for each noun form and a frequency index in an online database that can be sorted, searched, and downloaded. We report on associations among the different noun forms and data types, and propose recommendations for the use of these data in conjunction with other resources. In particular, we encourage collaborative approaches among research teams using large language models in psycholexical research related to personality structure.
Open Access
Guest Editorial—“Green Open Access is ‘Just’ Publishing”
(University of Oregon, 2020-08) Condon, David M
A shared experience among many graduate students is the dawning realization that the vaunted privilege of having one's scholarly work accepted for publication is also a fleecing. The exact terms of this fleecing depend on a number of different factors – so many, in fact, that it can get a bit confusing – but it's quite common for researchers to pay several thousand dollars to make their work available for others to read. And these are not the expenses incurred to complete their scholarly work. It's merely the cost of having one's work posted on the website of an academic publisher!
Open Access
Imagination as a facet of Openness/Intellect: A new scale differentiating experiential simulation and conceptual innovation
(PsyArXiv, 2022-02-09) Sassenberg, Tyler A.; Condon, David M.; DeYoung, Colin G.
Previous research has investigated the nature of imagination as a construct related to multiple forms of higher-order cognition. Despite the emergence of various conceptualizations of imagination, few attempts have been made to explore the structure of imagination as a trait in the context of existing hierarchically-nested personality dimensions. We present a scale for measuring trait imagination that distinguishes between experiential simulation and conceptual innovation, aligned with the two major subfactors (aspects) of the Big Five dimension Openness/Intellect. Across two large samples, we provide evidence of a consistent factor structure distinguishing experiential, conceptual, and general descriptions of imagination, as well as validity as measures of facets of Openness and Intellect. Our findings provide a measure of major forms of imagination in line with mainstream models of the hierarchical structure of personality.
Open Access
Laying personality BARE: Behavioral frequencies strengthen personality-criterion relationships
(PsyArXiv, 2020-08-24) Elleman, Lorien G.; Condon, David M.; Revelle, William
Personality consists of stable patterns of cognitions, emotions, and behaviors, yet personality psychologists rarely study behaviors. Even when examined, behaviors typically are considered to be validation criteria for traditional personality items. In the current study (N = 332,489), we conceptualize (self-reported, yearlong) behavioral frequencies as measures of personality. We investigate whether behavioral frequencies have incremental validity over traditional personality items in correlating personality with six outcome criteria. We use BISCUIT, a statistical learning technique, to find the optimal number of items for each criterion’s model, across three pools of items: traditional personality items (k = 696), behavioral frequencies (k = 425), and a combined pool. Compared to models using only traditional personality items, models using the combined pool are more strongly correlated to four criteria. We find mixed evidence of congruence between the type of criterion and the type of personality items that are most strongly correlated with it (e.g., behavioral criteria are most strongly correlated to behavioral frequencies). Findings suggest that behavioral frequencies are measures of personality that offer a unique effect in describing personality-criterion relationships beyond traditional personality items. We provide an updated, public-domain item pool of behavioral frequencies: the BARE (Behavioral Acts, Revised and Expanded) Inventory.
Open Access
Leveraging a more nuanced view of personality: Narrow characteristics predict and explain variance in life outcomes
(2022-07-07) Mõttus, René; Bates, Timothy C.; Condon, David M.; Mroczek, Daniel K.; Revelle, William
Among the main topics of individual differences research is the associations of personality traits with life outcomes. Relying on recent advances of personality conceptualizations and drawing parallels with genetics, we propose that representing these associations with individual questionnaire items (markers of personality “nuances”) can provide incremental value for predicting and explaining them—often even without further data collection. For illustration, we show that item-based models trained to predict ten outcomes out-predicted models based on Five-Factor Model (FFM) domains or facets in independent participants, with median proportions of explained variance being 9.7% (item-based models), 4.2% (domain-based models) and 5.9% (facet-based models). This was not due to item-outcome overlap. Instead, personality-outcome associations are often driven by dozens of specific characteristics, nuances. Outlining item-level correlations helps to better understand why personality is linked with particular outcomes and opens entirely new research avenues—at almost no additional cost.
Open Access
Multilevel analysis of personality: Personality of college majors
(Society of Multivariate Experimental Psychology, 2012-10) Revelle, William; Condon, David M.
Open Access
An Organizational Framework for the Psychological Individual Differences: Integrating the Affective, Cognitive, and Conative Domains
(2014-12) Condon, David M.
Recognition of the importance of individual differences dates back to humanity’s oldest surviving texts yet the scientific study of individual differences has been surprisingly limited. This paradox is presumed to result from the fact that differential psychology has struggled to graduate beyond pre-paradigmatic status as a science. In part, this has stemmed from the tendency to align idiographic approaches with the largely nomothetic methods of differential psychology under the broad label of “personality” research. The struggle has shifted – and, to some extent, abated – following acceptance of the Big Five taxonomy of personality and the more pressing concern has recently been the need to incorporate findings from additional disciplines of differential psychology. The purpose of this research was to propose an integrated assessment model – a preliminary paradigm which can be tested against extant and future models of individual differences in terms of predictive utility for a wide range of behaviors. The procedures used to develop this model are described separately by discipline (temperament, cognitive ability and vocational interests) and are supplemented by a methodological study regarding item clusters and complexity. All analyses were based on Synthetic Aperture Personality Assessment sampling procedures and large international samples (N s ranged from 24,000 to 97,000 participants representing 170 to 199 countries). The proposed temperament scales were iteratively derived from factor analyses of the items in 8 widely-used public-domain measures and can be scored at three hierarchical levels (with 3, 5 and 15 factors). The case is made that these scales are well-suited for heterarchical assessment and that the heterarchical organization of personality constructs often reflects the manner in which personality models are used in everyday settings. The cognitive ability scales represent a validated public-domain pool of items designed to assess several types of ability in unproctored online settings. The vocational interest scales are derived from two public-domain measures and reflect the traditional six-factor interests framework. Collectively, these scales form an efficient multi-dimensional, multi-disciplinary assessment model (the “SAPA Personality Inventory”) which aims to serve as a preliminary testable paradigm for differential psychology research.
Open Access
The Personality of American Nations: An Exploratory Study
(PsychOpen, 2021-01-14) Lanning, Kevin; Warfel, Evan A.; Wetherell, Geoffrey; Perez, Marina; Boyd, Ryan; Condon, David M.
Some scholars have presented models of the United States as a set of “nations” with distinct settlement histories and contemporary cultures. We examined personality differences in one such model, that of Colin Woodard, using data from over 75,000 respondents. Four nations were particularly distinct: The Deep South, Left Coast, New Netherland, and the Spanish Caribbean. Differences between nations at the level of the individual person were typically small, but were larger at the level of community, revealing how aggregation can contribute to differences in the lived experience of places in nations such as Yankeedom or Greater Appalachia. We represented effects in a three-dimensional model defined by Authoritarian conventionalism (which differentiated ‘Red’ and ‘Blue’ nations) as well as Cognitive resilience and Competitiveness (which differentiated among the Blue nations). Finally, we adjusted Woodard’s model to better fit the data, and found that nations largely maintained their boundaries, with the most drastic changes occurring on the East Coast.