The finer details? The predictability of life outcomes from Big Five domains, facets, and nuances

This is the peer reviewed version of the following article: [Stewart, R. D., Mõttus, R., Seeboth, A., Soto, C. J., & Johnson, W. (2022). The finer details? The predictability of life outcomes from Big Five domains, facets, and nuances. Journal of personality, 90(2), 167-182. https://doi.org/10.1111/jopy.12660], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.Associations between personality traits and life outcomes are usually studied using the Big Five domains and, occasionally, their facets. But recent research suggests these associations may be driven by the items (reflecting personality nuances) chosen to measure these traits. Using a large dataset (N = 6126), we examined associations with 53 self-reported outcomes using domains, facets and items (markers for nuances), training and validating models in different sample partitions. Facets better predicted outcomes than domains (on average, 18.0% versus 16.6% of variance explained), but items provided the most accurate predictions (on average 20.9%). Removing domain and facet variance from items had no effect on their predictive validity, suggesting that outcome-related information was often in items' unique variances (i.e., nuance-specific). Item-based prediction also showed the highest discriminant validity. These observations, replicating previous findings, suggest that personality traits' valid associations with outcomes are often driven by narrow personality nuances.N/

Successful explanations start with accurate descriptions:Questionnaire items as personality markers for more accurate predictions

Personality-outcome associations, typically represented using the Big Five personality domains, are ubiquitous, but often weak and possibly driven by the constituents of these domains. We hypothesized that representing the associations using personality questionnaire items (as markers for personality nuances) could increase prediction strength. Using the National Child Development Study (N = 8,719), we predicted 40 diverse outcomes from both the Big Five domains and their 50 items. Models were trained (using penalized regression) and applied for prediction in independent sample partitions (with 100 permutations). Item-models tended to out-predict Big Five-models (explaining on average 30% more variance), regardless of outcomes’ independently-rated breadth versus behavioral specificity. Moreover, the predictive power of Big Five domains per se was at least partly inflated by the unique variance of their constituent items, especially for generally more predictable outcomes. Removing the Big Five variance from items marginally reduced their predictive power. These findings are consistent with the possibility that the associations of personality with outcomes often pertain to (potentially large numbers of) specific behavioral, cognitive, affective and motivational characteristics represented by single questionnaire items rather than to the broader (underlying) traits that these items are ostensibly indicators of. This may also have implications for personality-based interventions

Successful explanations start with accurate descriptions: Questionnaire items as personality markers for more accurate predictions

Personality-outcome associations, typically represented using the Big Five personality domains, are ubiquitous, but often weak and possibly driven by the constituents of these domains. We hypothesized that representing the associations using personality questionnaire items (as markers for personality nuances) could increase prediction strength. Using the National Child Development Study (N = 8,719), we predicted 40 diverse outcomes from both the Big Five domains and their 50 items. Models were trained (using penalized regression) and applied for prediction in independent sample partitions (with 100 permutations). Item-models tended to out-predict Big Five-models (explaining on average 30% more variance), regardless of outcomes’ independently-rated breadth versus behavioral specificity. Moreover, the predictive power of Big Five domains per se was at least partly inflated by the unique variance of their constituent items, especially for generally more predictable outcomes. Removing the Big Five variance from items marginally reduced their predictive power. These findings are consistent with the possibility that the associations of personality with outcomes often pertain to (potentially large numbers of) specific behavioral, cognitive, affective and motivational characteristics represented by single questionnaire items rather than to the broader (underlying) traits that these items are ostensibly indicators of. This may also have implications for personality-based interventions

Successful explanations start with accurate descriptions: Questionnaire items as personality markers for more accurate predictions

Personality-outcome associations, typically represented using the Big Five personality domains, are ubiquitous, but often weak and possibly driven by the constituents of these domains. We hypothesized that representing the associations using personality questionnaire items (as markers for personality nuances) could increase prediction strength. Using the National Child Development Study (N = 8,719), we predicted 40 diverse outcomes from both the Big Five domains and their 50 items. Models were trained (using penalized regression) and applied for prediction in independent sample partitions (with 100 permutations). Item-models tended to out-predict Big Five-models (explaining on average 30% more variance), regardless of outcomes’ independently-rated breadth versus behavioral specificity. Moreover, the predictive power of Big Five domains per se was at least partly inflated by the unique variance of their constituent items, especially for generally more predictable outcomes. Removing the Big Five variance from items marginally reduced their predictive power. These findings are consistent with the possibility that the associations of personality with outcomes often pertain to (potentially large numbers of) specific behavioral, cognitive, affective and motivational characteristics represented by single questionnaire items rather than to the broader (underlying) traits that these items are ostensibly indicators of. This may also have implications for personality-based interventions