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People care a great deal about studying personality development during adolescence. Neuroscientists like looking at the developing brain in relation to personality development (Montag et al., 2013), while educators are interested in improving the socio-emotional skills during adolescence (Duff et al., 2004). It’s important to understand how the structure of personality changes across adolescence before we base so much on personality alone. Much of the existing research on personality development gives us an indication of normative personality structure development; however, there is less understood about the evolution of personality traits and to what extent different components of each trait remain stable across time. In the present study, we use a large-scale dataset to study the stability (or change) of personality structure during adolescence. We take a network approach to quantify and visualize personality structure; this allows us to estimate the stability of structure across several metrics (e.g., centrality and edge weights). We also use community detection methods to empirically estimate factors.

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.

The fundamental unit of data collection for self- and informant-report personality research is the item. In personality structure research, items have historically taken the form of single-word trait descriptors (e.g., “Calm”) while, in most personality assessment frameworks, they consist of phrases and sentences (e.g., “I am someone who tends to be calm”). This Registered Report will use a randomized, longitudinal design to evaluate the effects of differences in item wording on how people respond to personality measures. Specifically, we will examine the effect of four item formats—trait-descriptive adjectives presented alone (e.g., “Talkative”), with the linking verb “am” (e.g., “Am talkative”), with the additional verb “tend” (e.g., “Tend to be talkative”), and with the additional pronoun “someone” (e.g., “Am someone who tends to be talkative”)—on how people respond to an adjective-based measure of the Big Five (i.e., the Midlife Development Inventory; Lachman & Weaver, 1997). In terms of outcomes, we will consider item response distributions, participant response durations, and observed scale reliabilities, as well as the participants’ subjective experiences completing the survey. We will also test whether adding the pronoun “I” to any of these four formats influences the results. The findings from this work will have implications for ongoing research related to the assessment of personality, including the development of more detailed taxonomies of personality, the creation of more generalizable assessment models, and the harmonization of existing assessment models.

The current study seeks to answer three questions: (1) among adolescents, which individual differences (including differences in cognitive ability) are associated with BMI and the likelihood of being overweight/obese above and beyond the effect of parental SES, (2) what is the effect of parental SES on adolescent BMI and likelihood of being overweight/obese above and beyond individual differences in temperament and cognitive ability, and (3) to what extent does the relationship of individual differences to adolescent BMI and obesity depend on one's parent's SES?