Using within-person change in three large panel studies to estimate personality age trajectories.

How does personality change when people get older? Numerous studies have investigated this question, overall supporting the idea of so-called personality maturation. However, heterogeneous findings have left open questions, such as whether maturation continues in old age and how large the effects are. We suggest that the heterogeneity is partly rooted in methodological issues. First, studies may have failed to recover age effects as they did not stringently separate within-person changes from confounding between-person differences. Second, items supposedly belonging to the same trait may show different individual trajectories, thus rendering results sensitive to the specific set of items used. We analyzed panel data from Australia (N = 15,268; Study 1), Germany (N = 22,833; Study 2), and the Netherlands (N = 10,163; Study 3) to investigate age trends in the Big Five on the levels of both scores and items. We applied a fixed effects approach that incorporates only within-person changes over time. Developmental trends in the Big Five scores were generally moderate to large and broadly confirmed personality maturation at younger ages. At older ages, maturation consistently continued for Neuroticism, whereas we found mixed evidence for such changes in Conscientiousness and Agreeableness. Furthermore, in each study, individual items showed age trends that diverged from the rest of the corresponding trait, and these differential patterns could be partly replicated across the three studies. Our results highlight the importance of items in the study of personality development and provide an explanation for previously unaccounted for variability in age trends. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Emotional (in)stability: Neuroticism is associated with increased variability in negative emotion after all.

The personality trait neuroticism is tightly linked to mental health, and neurotic people experience stronger negative emotions in everyday life. But, do their negative emotions also show greater fluctuation? This commonsensical notion was recently questioned by [Kalokerinos et al. Proc Natl Acad Sci USA 112, 15838-15843 (2020)], who suggested that the associations found in previous studies were spurious. Less neurotic people often report very low levels of negative emotion, which is usually measured with bounded rating scales. Therefore, they often pick the lowest possible response option, which severely constrains the amount of emotional variability that can be observed in principle. Applying a multistep statistical procedure that is supposed to correct for this dependency, [Kalokerinos et al. Proc Natl Acad Sci USA 112, 15838-15843 (2020)] no longer found an association between neuroticism and emotional variability. However, like other common approaches for controlling for undesirable effects due to bounded scales, this method is opaque with respect to the assumed mechanism of data generation and might not result in a successful correction. We thus suggest an alternative approach that a) takes into account that emotional states outside of the scale bounds can occur and b) models associations between neuroticism and both the mean and variability of emotion in a single step with the help of Bayesian censored location-scale models. Simulations supported this model over alternative approaches. We analyzed 13 longitudinal datasets (2,518 individuals and 11,170 measurements in total) and found clear evidence that more neurotic people experience greater variability in negative emotion.

No Evidence That Siblings' Gender Affects Personality Across Nine Countries.

Does growing up with a sister rather than a brother affect personality? In this article, we provide a comprehensive analysis of the effects of siblings' gender on adults' personality, using data from 85,887 people from 12 large representative surveys covering nine countries (United States, United Kingdom, The Netherlands, Germany, Switzerland, Australia, Mexico, China, and Indonesia). We investigated the personality traits of risk tolerance, trust, patience, locus of control, and the Big Five. We found no meaningful causal effects of the gender of the next younger sibling and no associations with the gender of the next older sibling. Given the high statistical power and consistent results in the overall sample and relevant subsamples, our results suggest that siblings' gender does not systematically affect personality.

Causal and Associational Language in Observational Health Research: A Systematic Evaluation.

We estimated the degree to which language used in the high-profile medical/public health/epidemiology literature implied causality using language linking exposures to outcomes and action recommendations; examined disconnects between language and recommendations; identified the most common linking phrases; and estimated how strongly linking phrases imply causality. We searched for and screened 1,170 articles from 18 high-profile journals (65 per journal) published from 2010-2019. Based on written framing and systematic guidance, 3 reviewers rated the degree of causality implied in abstracts and full text for exposure/outcome linking language and action recommendations. Reviewers rated the causal implication of exposure/outcome linking language as none (no causal implication) in 13.8%, weak in 34.2%, moderate in 33.2%, and strong in 18.7% of abstracts. The implied causality of action recommendations was higher than the implied causality of linking sentences for 44.5% or commensurate for 40.3% of articles. The most common linking word in abstracts was "associate" (45.7%). Reviewers' ratings of linking word roots were highly heterogeneous; over half of reviewers rated "association" as having at least some causal implication. This research undercuts the assumption that avoiding "causal" words leads to clarity of interpretation in medical research.

The only thing that can stop bad causal inference is good causal inference.

In psychology, causal inference - both the transport from lab estimates to the real world and estimation on the basis of observational data - is often pursued in a casual manner. Underlying assumptions remain unarticulated; potential pitfalls are compiled in post-hoc lists of flaws. The field should move on to coherent frameworks of causal inference and generalizability that have been developed elsewhere.

The development of the rank-order stability of the Big Five across the life span.

Several studies have suggested that the rank-order stability of personality increases until midlife and declines later in old age. However, this inverted U-shaped pattern has not consistently emerged in previous research; in particular, a recent investigation implementing several methodological advances failed to support it. To resolve the matter, we analyzed data from two representative panel studies and investigated how certain methodological decisions affect conclusions regarding the age trajectories of stability. The data came from Australia (N = 15,465; Study 1) and Germany (N = 21,777; Study 2), and each study included four waves of personality assessment. We investigated the life span development of the rank-order stability of the Big Five for 4-, 8-, and 12-year intervals. Whereas Study 1 provided strong evidence for an inverted U-shape with rank-order stability declining past age 50, Study 2 provided more mixed results that nonetheless generally supported the inverted U-shape. This developmental trend held for single personality traits as well as for the overall pattern across traits; and it held for all three retest intervals-both descriptively and in formal tests. Additionally, we found evidence that health-related changes accounted for the decline in rank-order stability in older age. This suggests that if analyses are implicitly conditioned on health (e.g., by excluding participants with missing data on later waves), the decline in stability in old age will be underestimated or even missed. Our results provide further evidence for the inverted U-shaped age pattern in personality stability development but also extend knowledge about the underlying processes. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Replicability, Robustness, and Reproducibility in Psychological Science.

Replication-an important, uncommon, and misunderstood practice-is gaining appreciation in psychology. Achieving replicability is important for making research progress. If findings are not replicable, then prediction and theory development are stifled. If findings are replicable, then interrogation of their meaning and validity can advance knowledge. Assessing replicability can be productive for generating and testing hypotheses by actively confronting current understandings to identify weaknesses and spur innovation. For psychology, the 2010s might be characterized as a decade of active confrontation. Systematic and multi-site replication projects assessed current understandings and observed surprising failures to replicate many published findings. Replication efforts highlighted sociocultural challenges such as disincentives to conduct replications and a tendency to frame replication as a personal attack rather than a healthy scientific practice, and they raised awareness that replication contributes to self-correction. Nevertheless, innovation in doing and understanding replication and its cousins, reproducibility and robustness, has positioned psychology to improve research practices and accelerate progress.

Proximity can induce diverse friendships: A large randomized classroom experiment.

Can outside interventions foster socio-culturally diverse friendships? We executed a large field experiment that randomized the seating charts of 182 3rd through 8th grade classrooms (N = 2,966 students) for the duration of one semester. We found that being seated next to each other increased the probability of a mutual friendship from 15% to 22% on average. Furthermore, induced proximity increased the latent propensity toward friendship equally for all students, regardless of students' dyadic similarity with respect to educational achievement, gender, and ethnicity. However, the probability of a manifest friendship increased more among similar than among dissimilar students-a pattern mainly driven by gender. Our findings demonstrate that a scalable light-touch intervention can affect face-to-face networks and foster diverse friendships in groups that already know each other, but they also highlight that transgressing boundaries, especially those defined by gender, remains an uphill battle.

Putting the Self in Self-Correction: Findings From the Loss-of-Confidence Project.

Science is often perceived to be a self-correcting enterprise. In principle, the assessment of scientific claims is supposed to proceed in a cumulative fashion, with the reigning theories of the day progressively approximating truth more accurately over time. In practice, however, cumulative self-correction tends to proceed less efficiently than one might naively suppose. Far from evaluating new evidence dispassionately and infallibly, individual scientists often cling stubbornly to prior findings. Here we explore the dynamics of scientific self-correction at an individual rather than collective level. In 13 written statements, researchers from diverse branches of psychology share why and how they have lost confidence in one of their own published findings. We qualitatively characterize these disclosures and explore their implications. A cross-disciplinary survey suggests that such loss-of-confidence sentiments are surprisingly common among members of the broader scientific population yet rarely become part of the public record. We argue that removing barriers to self-correction at the individual level is imperative if the scientific community as a whole is to achieve the ideal of efficient self-correction.

Why Has Personality Psychology Played an Outsized Role in the Credibility Revolution?

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.

The Taboo Against Explicit Causal Inference in Nonexperimental Psychology.

Causal inference is a central goal of research. However, most psychologists refrain from explicitly addressing causal research questions and avoid drawing causal inference on the basis of nonexperimental evidence. We argue that this taboo against causal inference in nonexperimental psychology impairs study design and data analysis, holds back cumulative research, leads to a disconnect between original findings and how they are interpreted in subsequent work, and limits the relevance of nonexperimental psychology for policymaking. At the same time, the taboo does not prevent researchers from interpreting findings as causal effects-the inference is simply made implicitly, and assumptions remain unarticulated. Thus, we recommend that nonexperimental psychologists begin to talk openly about causal assumptions and causal effects. Only then can researchers take advantage of recent methodological advances in causal reasoning and analysis and develop a solid understanding of the underlying causal mechanisms that can inform future research, theory, and policymakers.

Correction: Using the Dirichlet process to form clusters of people's concerns in the context of future party identification.

[This corrects the article DOI: 10.1371/journal.pone.0212944.].

Using the Dirichlet process to form clusters of people's concerns in the context of future party identification.

Connections between interindividual differences and people's behavior has been widely researched in various contexts, often by using top-down group comparisons to explain interindividual differences. In contrast, in this study, we apply a bottom-up approach in which we identify meaningful clusters in people's concerns about various areas of life (e.g., their own health, their financial situation, the environment). We apply a novel method, Dirichlet clustering, to large-scale longitudinal data from the German Socioeconomic Panel Study (SOEP) to investigate whether concerns of people living in Germany evaluated in 2010 (t0) cluster participants into robust and separable groups, and whether these groups vary regarding their party identification in 2017 (t0 + 7). Clustering results suggest a range of different groups with specific concern patterns. Some of these notably specific patterns of concerns indicate links to party identification. In particular, some patterns show an increased identification with smaller parties as the 'Bündnis 90/Die Grünen' ('Greens'), the left wing party 'Die Linke' ('The Left') or the right-wing party 'Alternative für Deutschland' ('Alternative for Germany', AfD). Considering that we identify as many as 37 clusters in total, among them at least six with clearly different party identification, it can also be concluded that the complexity of political concerns may be larger than has been assumed before.

Recommendations for Increasing the Transparency of Analysis of Preexisting Data Sets.

Secondary data analysis, or the analysis of preexisting data, provides a powerful tool for the resourceful psychological scientist. Never has this been more true than now, when technological advances enable both sharing data across labs and continents and mining large sources of preexisting data. However, secondary data analysis is easily overlooked as a key domain for developing new open-science practices or improving analytic methods for robust data analysis. In this article, we provide researchers with the knowledge necessary to incorporate secondary data analysis into their methodological toolbox. We explain that secondary data analysis can be used for either exploratory or confirmatory work, and can be either correlational or experimental, and we highlight the advantages and disadvantages of this type of research. We describe how transparency-enhancing practices can improve and alter interpretations of results from secondary data analysis and discuss approaches that can be used to improve the robustness of reported results. We close by suggesting ways in which scientific subfields and institutions could address and improve the use of secondary data analysis.

Successfully Striving for Happiness: Socially Engaged Pursuits Predict Increases in Life Satisfaction.

Happiness is considered a highly desirable attribute, but whether or not individuals can actively steer their lives toward greater well-being is an open empirical question. In this study, respondents from a representative German sample reported, in text format, ideas for how they could improve their life satisfaction. We investigated which of these ideas predicted changes in life satisfaction 1 year later. Active pursuits per se-as opposed to statements about external circumstances or fortune-were not associated with changes in life satisfaction ( n = 1,178). However, in line with our preregistered hypothesis, among individuals who described active pursuits ( n = 582), those who described social ideas (e.g., spending more time with friends and family) ended up being more satisfied, and this effect was partly mediated by increased socializing. Our results demonstrate that not all pursuits of happiness are equally successful and corroborate the great importance of social relationships for human well-being.

Individual Importance Weighting of Domain Satisfaction Ratings does Not Increase Validity.

Bottom-up models of life satisfaction are based on the assumption that individuals judge the overall quality of their lives by aggregating information across various life domains, such as health, family, and income. This aggregation supposedly involves a weighting procedure because individuals care about different parts of their lives to varying degrees. Thus, composite measures of well-being should be more accurate if domain satisfaction scores are weighted by the importance that respondents assign to the respective domains. Previous studies have arrived at mixed conclusions about whether such a procedure actually works. In the present study, importance weighting was investigated in the Panel Study of Income Dynamics (PSID; N = 5,049). Both weighted composite scores and moderated regression analyses converged in producing the conclusion that individual importance weights did not result in higher correlations with the outcome variable, a global measure of life satisfaction. By contrast, using weights that vary normatively across domains (e.g., assigning a larger weight to family satisfaction than to housing satisfaction for all respondents) significantly increased the correlation with global life satisfaction (although incremental validity was rather humble). These results converge with findings from other fields such as self-concept research, where evidence for individual importance weighting seems elusive as best.

Only so Many Hours: Correlations Between Personality and Daily Time Use in a Representative German Panel.

Time is a finite resource, strictly limited to 24 hours a day. How people spend these resources is in many ways determined by necessities and external constraints, yet research on personality-situation transactions shows that people also choose their environments to resonate with their personality. This finding implies that daily time use and individual traits should be correlated. However, few studies have linked modern methods for assessing time use to individual differences in personality traits. In this study, we investigate correlations between the Big Five traits and time spent on various daily activities in the German Socio-Economic Panel (SOEP), including 5,456 days in the lives of 1,364 individuals. Results converged towards previously reported personality-situation transactions. For example, extraversion predicted whether or not respondents reported meeting their friends, whereas openness was correlated negatively with watching TV. Effects were modest in size, ranging from r ≈ .10 to .25 Taking together, our findings corroborate the notion that our personality is robustly associated with the way we spend our lives.

In your eyes only? Discrepancies and agreement between self- and other-reports of personality from age 14 to 29.

Do others perceive the personality changes that take place between the ages of 14 and 29 in a similar fashion as the aging person him- or herself? This cross-sectional study analyzed age trajectories in self- versus other-reported Big Five personality traits and in self-other agreement in a sample of more than 10,000 individuals from the myPersonality Project. Results for self-reported personality showed maturation effects (increases in extraversion, conscientiousness, openness to experience, and emotional stability), and this pattern was generally also reflected in other-reports, albeit with discrepancies regarding timing and magnitude. Age differences found for extraversion were similar between the self- and other-reports, but the increase found in self-reported conscientiousness was delayed in other-reports, and the curvilinear increase found in self-reported openness was slightly steeper in other-reports. Only emotional stability showed a distinct mismatch with an increase in self-reports, but no significant age effect in other-reports. Both the self- and other-reports of agreeableness showed no significant age trends. The trait correlations between the self- and other-reports increased with age for emotional stability, openness, agreeableness, and conscientiousness; by contrast, agreement regarding extraversion remained stable. The profile correlations confirmed increases in self-other agreement with age. We suggest that these gains in agreement are a further manifestation of maturation. Taken together, our analyses generally show commonalities but also some divergences in age-associated mean level changes between self- and other-reports of the Big Five, as well as an age trend toward increasing self-other agreement. (PsycINFO Database Record

Probing Birth-Order Effects on Narrow Traits Using Specification-Curve Analysis.

The idea that birth-order position has a lasting impact on personality has been discussed for the past 100 years. Recent large-scale studies have indicated that birth-order effects on the Big Five personality traits are negligible. In the current study, we examined a variety of more narrow personality traits in a large representative sample ( n = 6,500-10,500 in between-family analyses; n = 900-1,200 in within-family analyses). We used specification-curve analysis to assess evidence for birth-order effects across a range of models implementing defensible yet arbitrary analytical decisions (e.g., whether to control for age effects or to exclude participants on the basis of sibling spacing). Although specification-curve analysis clearly confirmed the previously reported birth-order effect on intellect, we found no meaningful effects on life satisfaction, locus of control, interpersonal trust, reciprocity, risk taking, patience, impulsivity, or political orientation. The lack of meaningful birth-order effects on self-reports of personality was not limited to broad traits but also held for more narrowly defined characteristics.

"What else are you worried about?" - Integrating textual responses into quantitative social science research.

Open-ended questions have routinely been included in large-scale survey and panel studies, yet there is some perplexity about how to actually incorporate the answers to such questions into quantitative social science research. Tools developed recently in the domain of natural language processing offer a wide range of options for the automated analysis of such textual data, but their implementation has lagged behind. In this study, we demonstrate straightforward procedures that can be applied to process and analyze textual data for the purposes of quantitative social science research. Using more than 35,000 textual answers to the question "What else are you worried about?" from participants of the German Socio-economic Panel Study (SOEP), we (1) analyzed characteristics of respondents that determined whether they answered the open-ended question, (2) used the textual data to detect relevant topics that were reported by the respondents, and (3) linked the features of the respondents to the worries they reported in their textual data. The potential uses as well as the limitations of the automated analysis of textual data are discussed.